pragmatic podcasting: facilitating podcasting in developing higher education institutions

IADIS INTERNATIONAL CONFERENCE

MOBILE LEARNING 2012

iii

PROCEEDINGS OF THE IADIS INTERNATIONAL CONFERENCE

MOBILE LEARNING 2012

BERLIN, GERMANY

MARCH 11-13, 2012

Organised by IADIS

International Association for Development of the Information Society

iv

Copyright 2012

IADIS Press

All rights reserved

This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation,

broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Permission for use must always be obtained from IADIS Press. Please contact [email protected]

Edited by Inmaculada Arnedillo Sánchez and Pedro Isaías

Associate Editor: Luís Rodrigues

ISBN: 978-972-8939-66-3

v

TABLE OF CONTENTS

FOREWORD xi

PROGRAM COMMITTEE xiii

KEYNOTE LECTURE xvii

FULL PAPERS

BESOCRATIC: GRAPHICALLY ASSESSING STUDENT KNOWLEDGE Sam Bryfczynski, Roy P. Pargas, Melanie M. Cooper and Michael Kylmkowsky

3

INTRODUCING COLLABORATION AND COMPETITION INTO REAL WORLD EDUTAINMENT Keiji Miki, Hiroyuki Mitsuhara, Yusuke Noda, Kazuhisa Iwak, Yasunori Kozuki and Yoneo Yano

11

LEARNING BY LOGGING: HOW CAN WE USE LIFE-LOG PHOTOS FOR LEARNING? Hiroaki Ogata, Bin Hou, MengMeng Li and Noriko Uosaki

19

PRODUCING CONTENT SEMANTICS TO ENHANCE MOBILE LEARNERS BROWSING USABILITY Dimitrios Glaroudis, Isabella Kotini and Athanasios Manitsaris

26

A THEORETICAL GROUNDING OF LEARNING MATHEMATICS IN AUTHENTIC REAL-WORLD CONTEXTS SUPPORTED BY MOBILE TECHNOLOGY Jalal Nouri

35

WHITE CANE DEVICE: A MOBILE ASSISTANT FOR VISUALLY CHALLENGED PEOPLE Judie Attard, Matthew Montebello and Jeremy Debattista

43

DESIGN AND EVALUATION OF MOBILE LEARNING RESOURCES IN MATHEMATICS FOR PUBLIC ELEMENTARY SCHOOLS IN MEXICO V. Robledo-Rella, G. Aguilar, S. Shea, R. Pérez-Novelo, E. Ortega, J.C. Olmedo, J. Noguez, E. Tamés and P. Toiminen

51

EFFECTIVE LEARNING MATERIALS FOR MOBILE DEVICES: FOCUS ON VOCABULARY LEARNING Haruko Miyakoda, Kei-ichi Kaneko and Masatoshi Ishikaw

59

vi

SIX WAYS OF INTERACTING WITH MOBILE DEVICES IN MOBILE INQUIRY-BASED LEARNING Johan Eliasson and Ola Knutsson

67

A COMFORT ZONE FOR MOBILE LEARNING – A GROUNDED INNOVATION APPROACH Henning Breuer, Tillmann Dierichs and Stefanie Elsholz

75

MOBILE DEVICES INCREASING OPPORTUNITIES FOR INFORMAL LEARNING AND SECOND LANGUAGE ACQUISITION Carl Storz, Katherine Maillet, Carine Brienne, Laure Chotel and Catherine Dang

83

DESIGN ACTIVITIES AND CONTRIBUTIONS IN THE CREATION OF IDEAS FOR EDUCATIONAL MOBILE APPLICATIONS FOR SCHOOL-AGED CHILDREN Tuula Nousiainen, Marja Kankaanranta and Pekka Neittaanmäki

91

MOBILE SELF-EFFICACY IN A CANADIAN NURSING EDUCATION PROGRAM Richard F Kenny, Jocelyne M.C. Van Neste-Kenny, Pamela Burton and Caroline L. Park

99

APPLYING MLEARNING IN SOFTWARE ENGINEERING EDUCATION: A SURVEY OF MOBILE USAGE April Macphail, Thomas Hainey and Thomas. M. Connolly

107

TOWARDS MOBILE PERSONALIZED LEARNING MANAGEMENT SYSTEMS Natalia Müller and Diana Dikk

115

A FRAMEWORK FOR APPLYING QUANTIFIED SELF APPROACHES TO SUPPORT REFLECTIVE LEARNING Verónica Rivera-Pelayo, Valentin Zacharias, Lars Müller and Simone Braun

123

MEETING THEM WHERE THEY’RE AT’ – EXPLORING STUDENT PERSPECTIVES OF MOBILE LEARNING IN HIGHER EDUCATION Kate Reader, Sian Lindsay and Ajmal Sultany

132

PROFESSIONAL DEVELOPMENT ENHACED IN NUMERICAL METHODS COURSE BASED ON B-LEARNING: DESIGN AND FOLLOW UP Francisco Javier Delgado Cepeda

139

UNDERSTANDING, REFLECTING AND DESIGNING LEARNING SPACES OF TOMORROW Isa Jahnke, Peter Bergström, Krister Lindwall, Eva Mårell-Olsson, Andreas Olsson, Fredrik Paulsson and Peter Vinnervik

147

MOBILISING” WEB SITES AT AN OPEN UNIVERSITY: THE ATHABASCA UNIVERSITY EXPERIENCE Rory McGreal and Regina Wasti

157

JOURNALISM 2.0: EXPLORING THE IMPACT OF MOBILE AND SOCIAL MEDIA ON JOURNALISM EDUCATION Thomas Cochrane, Helen Sissons and Danni Mulrennan

165

AUTOMATIC EVALUATION SYSTEM OF DRIVING SKILL USING WEARABLE SENSORS FOR PERSONALIZED SAFE DRIVING LECTURE Masahiro Tada, Haruo Noma, Akira Utsumi, Masaya Okada and Kazumi Renge

173

OPENCAST 2 GO: MOBILE CONNECTIONS TO MULTIMEDIA LEARNING REPOSITORIES Markus Ketterl, Leonid Oldenburger and Oliver Vornberger

181

vii

BROWSER-BASED MOBILE CLICKERS: IMPLEMENTATION AND CHALLENGES Monika Andergassen, Victor Guerra, Karl Ledermüller and Gustaf Neumann

189

A QUICK PROTOTYPING FRAMEWORK FOR ADAPTIVE SERIOUS GAMES WITH 2D PHYSICS ON MOBILE TOUCH DEVICES Juan Haladjian, Damir Ismailović, Barbara Köhler and Bernd Brügge

197

REAL WORLD EDUTAINMENT BASED ON BRANCHED GAME STORY AND ITS APPLICATION TO EARTHQUAKE DISASTER PREVENTION LEARNING Yusuke Noda, Keiji Miki, Kazuhisa Iwaka, Hiroyuki Mitsuhara, Yasunori Kozuki and Yoneo Yano

205

MOBILE AND COLLABORATIVE TIMELINES FOR REFLECTION Anders Kristiansen, Andreas Storlien, Simone Mora, Birgit R. Krogstie and Monica Divitini

213

LOCALEARN - A TOOL FOR EDUCATIONAL DISCOVERY IN THE LOCAL URBAN ENVIRONMENT Liselott Brunnberg, Pelin Arslan and Federico Casalegno

222

SHORT PAPERS

MORE WITH LESS, VOCABULARY ACQUISITION THROUGH SMARTPHONE APPS Haymo Mitschian

233

ENHANCING SCIENTIFIC INQUIRY AND PRACTICING NEW LITERACIES SKILLS THROUGH ICTS AND MOBILE DEVICES Shiang-Kwei Wang, Hui-Yin Hsu and Lisa Runco

237

ROLE OF NEEDS-ANALYSIS IN MOBILE LANGUAGE LEARNING CONTENT DEVELOPMENT Yasemin Bayyurt and Nur Başak Karataş

242

MOBILE AUGMENTED REALITY APPS FOR TEACHING ETHICALLY SENSITIVE TOPICS IN MEDICINE Urs-Vito Albrecht, Bernhard Häussermann, Herbert K. Matthies and Ute von Jan

247

A SOCIAL SOFTWARE FOR MOBILE LEARNING Tássia Serrão, Sérgio Crespo C. S. Pinto, Lucas M. Braz and Gisela Clunie

253

MOBILE LEARNING SYSTEM FOR EXPERIMENTS INVOLVING ELECTRONIC CIRCUIT MAKING USING A TABLET PC Atsushi Takemura

258

A MOBILE APPLICATION WITH EMBODIED MULTIMODAL INTERACTIONS FOR UNDERSTANDING REPRESENTATIONS OF MOTION IN PHYSICS Mattias Davidsson

263

viii

YOUNG TURKISH LEARNERS’ FIRST ENCOUNTER WITH ENGLISH AS A FOREIGN LANGUAGE THROUGH MOBILE DEVICES Senem Yıldız

267

MOTIVATING LEARNING THROUGH MOBILE INTERACTION Alexiei Dingli and Dylan Seychell

271

EFFECTS OF A TEST DELIVERY SYSTEM IN A BLENDED LEARNING ENVIRONMENT: A FOCUS ON THE RELATIONSHIP BETWEEN ATTITUDE TOWARD TESTS, MOTIVATION FOR LEARNING, AND TEST SCORES Takeshi Kitazawa and Masahiro Naga

275

READINESS OF TEACHERS TO IMPLEMENT OF MOBILE LEARNING AT EURASIAN NATIONAL UNIVERSITY Daniyar Sapargaliyev

279

PRAGMATIC PODCASTING: FACILITATING PODCASTING IN DEVELOPING HEIS Raymond Mugwanya, Gary Marsden and John Traxler

285

RECOMMENDER SYSTEM FOR COMBINATION OF LEARNING ELEMENTS IN MOBILE ENVIRONMENT Fayrouz Soualah-Alila, Florence Mendes, Christophe Cruz and Christophe Nicolle

291

A NOVEL APPROACH TO THE APPLICATION OF SEMANTIC WEB TECHNOLOGIES TO STUDENT CENTRED LEARNING Ghislain Maurice Norbert Isabwe, Frank Reichert and Morgan Konnestad

296

MBCLICK - AN ELECTRONIC VOTING SYSTEM THAT RETURNS INDIVIDUAL FEEDBACK Geoff Rubner

302

HEALTH CARE EDUCATION SYSTEM FOR MOBILE DEVICES Toshiyuki Maeda, Yuki Ando, Yae Fukushige, Mayumi Yamamoto and Takayuki Asada

307

M-LEARNING 2.0: THE POTENTIAL AND CHALLENGES OF COLLABORATIVE MOBILE LEARNIG IN PARTICIPATORY CURRICULUM DEVELOPMENT Ilona Buchem, Thom Cochrane, Averill Gordon, Helen Keegan and Mar Camacho

311

MODELING OF MOBILE LEARNING Mahmoud Mohanna and Laurence Capus

315

MOBILE WEB2.0 FOR WORKPLACE INFORMAL LEARNING: CASE STUDY IN CHINA Gu Jia, Daniel Churchill and Mark King

320

A WIRELESS ARCHITECTURE FOR ASSISTIVE MOBILE LEARNING ENVIRONMENTS Catherine Marinagi and Christos Skourlas

325

AN INTERACTIVE MOBILE LEARNING SYSTEM FOR ENHANCING LEARNING IN HIGHER EDUCATION Olutayo Boyinbode, Antoine Bagula and Dick Ng’ambi

331

EXPLORING MOBILE AND CONTEXTUAL LEARNING WITH GGULIVRR Hiram Bollaert and Philippe Possemiers

335

ix

REFLECTION PAPERS

MOBILE LEARNING AND ITS APPLICATION IN JAVA PROGRAMMING LANGUAGE COURSE Jianhua Wang and Long Zhang

343

MOBILE DEVICE TRENDS AND THEIR IMPLICATIONS FOR MOBILE LEARNING AT HIGHER EDUCATION INSTITUTIONS Daniel J. Guhr and Grace A. Gair

347

NEW ACCESS TO MOBILE TECHNOLOGY AS AN EMERGING LEARNING POTENTIAL András Benedek and György Molnár

351

MOLEDIWO – MOBILE LEARNING SYSTEM FOR DISABLED PEOPLE AT WORKPLACE Benjamin Tannert, Saeed Zare and Michael Lund

355

MAKING (MORE) PEDAGOGICAL SENSE OF TWITTER WITH A NEWLY DEVELOPED TRACKING DEVICE AND PRIORITISED DISCUSSION POINTS: THE STORY OF A COLLABORATIVE TWITTER IMPROVEMENT PROJECT Thomas Menkhoff, Gabriel Yee Qi Ming and Magnus Lars Bengtsson

359

POSTERS

A PROPOSAL FOR USING VIRTUALIZATION TECHNOLOGY IN MOBILE LEARNING Carlos Oliveira

367

INTRASUBJECT RELATIONS BEING THE BASIS OF PHYSICAL CONTENTS WITH MOBILE LEARNING T. Gnitetskaya, E. Ivanova, E. Karnauhova and L. Dubovaya

370

A STUDY ON THE DEVELOPMENT OF LEARNING CONTENTS AND PLATFORM FOR ENVIRONMENTAL EDUCATION Uk Kim, Jaemoon Choi and Jiwon Yun

373

IACADEMY – AN INNOVATIVE MLEARNING APPROACH FOR LIFELONG LEARNING Astrid Jancke, Roman Götter, Sebastian Vogt and Olaf Zawacki-Richter

377

AN INVESTIGATION INTO UNIVERSITY STUDENTS’ EXPERIENCES AND PERCEPTIONS OF USING MOBILE PHONES Yukiko Maruyama

380

LINGOBEE: A MOBILE APP FOR IN-SITU LANGUAGE LEARNING Lyn Pemberton and Marcus Winter

383

AUTHOR INDEX

xi

FOREWORD

These proceedings contain the papers of the IADIS International Conference on Mobile Learning 2012, which was organised by the International Association for Development of the Information Society, in Berlin, Germany, March 11 – 13, 2012. The IADIS Mobile Learning 2012 International Conference seeks to provide a forum for the presentation and discussion of mobile learning research which illustrate developments in the field. In particular, but not exclusively, we aim to explore the theme of mobile learning under the following topics: - Pedagogical approaches, models and theories for mLearning - mLearning in and across formal and informal settings - Strategies and challenges for integrating mLearning in broader educational scenarios - User Studies in mLearning - Learner mobility and transitions afforded by mlearning - Socio-cultural context and implications of mLearning - Mobile social media and user generated content - Enabling mLearning technologies, applications and uses - Evaluation and assessment of mLearning - Research methods, ethics and implementation of mLearning - Innovative mLearning approaches - Tools, technologies and platforms for mLearning - mLearning: where to next and how? The IADIS Mobile Learning Conference 2012 received 146 submissions from more than 34 countries. Each submission has been anonymously reviewed by an average of 4 independent reviewers, to ensure that accepted submissions were of a high standard. Consequently only 28 full papers were approved which means an acceptance rate of 19%. A few more papers were accepted as short papers, reflection papers and posters. An extended version of the best papers will be published in the International Journal of Mobile and Blended Learning (ISSN: 1941-8647).

The Conference, besides the presentation of full papers, short papers, reflection papers and posters also included a keynote presentation from an internationally distinguished researcher. We would therefore like to express our gratitude to Professor Agnes Kukulska Hulme, Institute of Educational Technology, The Open University, UK, for accepting our invitation as keynote speaker.

xii

A successful conference requires the effort of many individuals. We would like to thank the members of the Program Committee for their hard work in reviewing and selecting the papers that appear in this book. We are especially grateful to the authors who submitted their papers to this conference and to the presenters who provided the substance of the meeting. We wish to thank all members of our organizing committee.

Last but not least, we hope that everybody has enjoyed Berlin and their time with colleagues from all over the world, and we invite you all to next edition of the IADIS International Mobile Learning in 2013. Inmaculada Arnedillo Sánchez, Trinity College Dublin, Ireland. Conference Program Chair Pedro Isaías, Universidade Aberta (Portuguese Open University), Portugal Conference Chair Berlin, Germany March 2012

xiii

PROGRAM COMMITTEE

PROGRAM CHAIR

Inmaculada Arnedillo Sánchez, Trinity College Dublin, Ireland

CONFERENCE CHAIR

Pedro Isaías, Universidade Aberta (Portuguese Open University), Portugal

COMMITTEE MEMBERS

Abdallah Tubaishat, Zayed University, United Arab Emirates Adamantios Koumpis, Altec Software S.A., Greece

Alessandro Caforio, UNINETTUNO University, Italy Alex Voychenko, Irtc, Ukraine

Anastasios Economides, University Of Macedonia, Greece Anastopoulou Stamatina, Systems and Products Design, University of the Aeg, Greece

Andrea Pozzali, European University of Rome, Italy Andrea Squarcia, University Of Genoa, Italy

Andreas Johannsen, Fh Brandenburg University Of Applied Sciences, Germany Andreas Schmidt, FZI Research Center For Information Technologies, Germany

Angelos Michalas, TEI of Western Macedonia, Greece Avouris Nikolaos, University of Patras, Greece

Beat Doebeli Honegger, PH Zentralschweiz Schwyz, Switzerland Beatrice Ligorio, Universita Degli Studi Di Bari, Italy

Ben Bachmair, London Mobile Learning Group, Germany Boriss F. Misnevs, Transport And Telecommunication Institute, Latvia

Bren Taylor, Service Birmingham, United Kingdom Brendan Riordan, University Of Wolverhampton, United Kingdom

Brendan Tangney, Trinity College Dublin, Ireland Carl Smith, London Metropolitan University, United Kingdom

Charalampos Karagiannidis, University of Thessaly, Greece Charles Jennings, Learning & Performance Consultant, United Kingdom

Chen Chung Liu, National Central University, Taiwan Chengjiu Yin, Kyushu University, Japan

Chiara Rossitto, Department of Computer and Systems Sciences, DSV, Sweden Chiu-kuo Liang, Chunghua University, Taiwan

Claire Bradley, London Metropolitan University, United Kingdom Clark Quinn, Quinnovation, United States

xiv

Claudia Steinberger, University Of Klagenfurt, Austria Daniel Churchill, Hong Kong University, Hong Kong Daphne Economou, University of Westminster, UK

Davide Diamantini, Universita Di Milano-bicocca, Italy Demetrios Sampson, University Of Pireaus, Greece

Eija Kaasinen, VTT, Human Technology Interaction, Finland Elia Tomadaki, Velti S.A., Greece

Elisabetta Parodi, eXact learning solutions S.p.A., Italy Emad Bataineh, Zayed University, United Arab Emirates

Emanuela Mazzone, Uned, Spain Euripides Loukis, University Of the Aegean, Greece

Fotis Liarokapis, Coventry University, United Kingdom Franz Lehner, University Of Passau, Germany Frode Guribye, University Of Bergen, Norway

Gabriella Dodero, Free University Of Bozen, Italy George Magoulas, Birbeck College, United Kingdom

Giancarlo Bo, Technology and Innovation Consulting (Freelancer), Italy Giuliana Dettori, ITD-CNR, Italy

Haiguang Fang, Capital Normal University, China Hannu-Matti Jarvinen, Tampere University Of Technology, Finland

Hans Christian Schmitz, Fraunhofer FIT, Germany Harald Kosch, University Of Passau, Germany

Hokyoung Ryu, Hanyang University, Korea Inge de Waard, Institute Of Tropical Medicine Antwerp, Belgium

Ingo Dahn, University Of Koblenz-landau, Germany Ioannis Anagnostopoulos, University Of The Aegean, Greece

Jane Sinclair, University Of Warwick, United Kingdom Jia-sheng Heh, Chung Yuan Christian University, Taiwan

Jie-chi Yang, National Central University, Taiwan Jirarat Sitthiworachart, Walailak University, Thailand

Jo Dugstad Wake, InterMedia, Uni Health, Uni Research, Norway Jocelyn Wishart, University Of Bristol, United Kingdom

John Cook, London Metropolitan University, United Kingdom John Traxler, University Of Wolverhampton, United Kingdom

Jon Dron, Athabasca University, Canada Jorge Couchet, Uned, Spain

Juan Manuel Santos-Gago, University of Vigo, Spain Judith Seipold, London Mobile Learning Group, United Kingdom

Judy Brown, Advanced Distributed Learning, United States Ju-ling Shih, National University Of Tainan, Taiwan Jun-Ming Su, National University of Tainan, Taiwan

Keith Cheverst, University Of Lancaster, United Kingdom Klaus Rummler, University of Bremen, Germany

xv

Konstantinos Tarabanis, University Of Macedonia, Greece

Lam-for Kwok, City University Of Hong Kong, Hong Kong Leonardo Giusti, MIT, US

Louise Mifsud, Oslo and Akershus University College of Applied Sc, Norway Luca Tateo, University of Sassari, Italy

Lyn Pemberton, University Of Brighton, United Kingdom Maiga Chang, Athabasca University, Canada

Malamati Louta, University of Western Macedonia, Greece Marcus Specht, Open University Of The Netherlands, Netherlands

Maria Helena Braz, Technical University Of Lisbon, Portugal Maria Uther, Brunel University, United Kingdom

Mario Vacca, La Sapienza - University Of Rome, Italy Markus Rohde, University Of Siegen, Germany

Michele Notari, University of Teacher Education Bern, Switzerland Michelle Pieri, University of Milano-Bicocca, Italy Mike Joy, University Of Warwick, United Kingdom

Mohamed Ally, Athabasca University, Canada Mona Laroussi, University Of Lille, France

Monica Divitini, Norwegian University Of Science And Technology, Norway Moushir M. El-Bishouty, City for Science and Technology, Egypt

Mudasser Wyne, National University, United States Niall Winters, University Of London, United Kingdom

Nicola Doering, Ilmenau University Of Technology, Germany Norbert Pachler, University Of London, United Kingdom

Oleksiy Voychenko, International Research And Training Center (irtc), Ukraine Patrick Danaher, University Of Southern Queensland, Australia

Paul Hayes, National College Of Ireland, Ireland Ray Yueh Min Huang, National Cheng Kung University, Taiwan

Rory Mcgreal, Athabasca University, Canada Sabine Moebs, Dublin City University, Ireland

Sanaz Fallahkhair, University Of Portsmouth, United Kingdom Sean Siqueira, Federal University of the State of Rio De Janeiro , Brazil

Stavros Demetriadis, Aristotle University Of Thessaloniki, Greece Stefanie Sieber, University of Bamberg, Germany

Stella Lee, Athabasca University, Canada Tomayess Issa, Curtin University, Perth, Australia

Vjaceslavs Sitikovs, Riga Technical University, Latvia Werner Beuschel, IBAW, Germany

xvii

KEYNOTE LECTURE

“MOBILE LANGUAGE LEARNING – THE ULTIMATE CHALLENGE”

By Professor Agnes Kukulska Hulme

Institute of Educational Technology, The Open University, UK

Abstract

Mobile learning combines the persisting challenges of effective use of technology in teaching and learning with additional requirements to understand learners’ conceptions of available time, the multiple resources at their disposal, and the diverse physical environments where digital learning can now take place. Nowhere are these magnified challenges more evident than in mobile language learning. Research with language learners reveals a range of sensibilities relating to time, activity and place, along with ingenious ways in which learners personally interweave the demands of life, work, and learning. Successful learning of a foreign language and culture is an immersive and challenging experience affecting the whole person, awakening curiosity, opening doors to new relationships and altering one’s outlook on the world. The talk will assess how far mobile language learning has come and will point to directions for future developments.

Full Papers

BESOCRATIC: GRAPHICALLY ASSESSING STUDENT KNOWLEDGE

Sam Bryfczynski1, Roy P. Pargas1, Melanie M. Cooper1 and Michael Kylmkowsky2 1Clemson University, Clemson, SC, USA 29634-0974

2University of Colorado Boulder, Boulder, CO, USA 80304

ABSTRACT

In many educational institutions today, online assessment systems are being used to evaluate student knowledge and understanding. Unfortunately, these systems often only allow teachers to ask questions in the form of multiple choice or free text responses. While these question types have value, they are either too limited to gain insight into student understanding (multiple choice responses) or too time-consuming because they need to be evaluated by the teacher (free text responses). This paper gives an overview of BeSocratic, a robust pedagogical tool that allows teachers to probe student understanding automatically using a variety of question types. These question types focus on problems with free-form answers that are structured well-enough to allow automatic evaluation. Furthermore by recording each student’s work, BeSocratic allows teachers and researchers to replay student submissions and potentially gain deeper insight into a student’s thought process through post analysis.

KEYWORDS

Tablet PC, Constructivism, Socratic Method, Assessment

1. INTRODUCTION

Among education researchers, there is a division between supporters of constructivism and those of direct instruction [24]. Most researchers in education and cognitive science believe that knowledge is ultimately constructed by students. However, there is disagreement among researchers as to the best method to promote this process. Researchers in support of constructivism believe that knowledge is generated from the interaction between experience and thought and thus students should be taught with personalized inquiry-based instruction. Direct instruction supporters believe that the best way to promote student learning is by simply telling students what to do and how to do it. And while most educators support constructivism, data in favor of constructivism is difficult to acquire [21]. This difficulty comes partly from the fact that constructivism activities and knowledge are assessed using non-constructivist methods. That is, current assessments simply ask students to retrieve facts and complete problems that the students have seen previously. It would be better if assessments could evaluate students on their ability to use learned skills in creative and novel ways which test a student’s true understanding of material.

Ideally, according to constructivism, each student would have individualized Socratic learning and assessment activities which probe the student with questions and feedback. Practical limitations make these types of assessments difficult to conduct. Personalized instruction and assessment at the levels proposed by constructivists are not feasible in large classrooms with hundreds of students.

New technologies, however, are starting to bridge this gap and allow what was previously considered to be infeasible to now possibly be practical. Today, most higher education institutions use broad learning management systems such as Blackboard, Moodle, or Instructure Canvas to aid in assessment. Additionally, specialized systems (such as Mastering software series, OWL, etc.) exist for individual disciples and courses. While these systems have shown improvements in student learning, the majority of questions they may ask fall into one of two categories: free response text-based questions or multiple-choice/matching questions. Free-response systems allow teachers to ask meaningful questions which require students to have deep understanding of the subject in order to answer correctly. More restrictive questions use simple multiple choice or matching questions. Research has suggested that multiple choice or matching questions cannot be

IADIS International Conference Mobile Learning 2012

3

used to properly assess deep knowledge on a subject [10,11,22,19]. The exercises often only involve memorization.

Which system a teacher uses depends on the amount of time the teacher has to evaluate student solutions. Evaluating student answers from free response systems requires teachers to manually check each submission; this is too time-consuming for teachers to perform on a regular basis. Instead, teachers rely on using multiple-choice or matching questions that can be quickly or automatically evaluated. The ideal system combines the best parts of both types of systems. A teacher would be able to ask questions that require students to have a deep understanding of the material and reply in an intuitive free form manner. In this ideal system, student responses would be automatically evaluated and analyzed. These are the goals of BeSocratic.

There have been other attempts at creating software with these goals in mind. While these systems may appear to allow free-form input, they are usually nothing more than multiple-choice assessments with decorative covers. Students are often clever enough to recognize patterns in the system and ultimately are able to “game” the system. For example, there are reports [12] showing that systems that generate exercises using random number generators are often worked around by students who quickly realize they can program the formula into their calculators (in the same way the teacher programmed it into the testing system).

It seems that we must change the types of questions we ask students. Instead of (randomized) multiple choice or free-response questions, we believe that visualizations may hold the key to assessment. Here, we use the term visualization the way Tufte uses it, that is, as the systematic and focused display of information in the form of tables, graphs and diagrams [25]. Many STEM (Science, Technology, Engineering, and Mathematics) disciplines use visualizations throughout their courses. Examples include drawing graphs in mathematics, free-body diagrams in physics, and energy curves in chemistry.

Teachers often need to draw graphs, diagrams and other visualizations to express ideas. It has been argued that visualization is central to student learning in science classrooms [8,9]. It seems that students need to watch scientists and mathematicians explain topics using visualizations in order for the students to gain an understanding of material and processes. Research suggests that many students can improve their problem solving ability by learning to switch between these different visual representations of material [14]. Moreover, there is evidence that when students actually create these visualizations, the activity improves their problem solving skills. Using visualizations to solve problems shows that the student is becoming an experienced problem solver [15].

Motivated by all of this research, we have developed a novel pedagogical system, BeSocratic, which focuses on evaluating visual representations to give students individualized and meaningful instruction and assessment. BeSocratic recognizes free-form student input and provides students with meaningful feedback to improve their problem solving ability. Furthermore, BeSocratic analyzes collected student data in a variety of ways allowing teachers to better manage and track progress within their classrooms. It is in this manner that BeSocratic is able to ask students meaningful questions requiring free-form input based on deep subject knowledge and provide automatic evaluation that is necessary for use in large classrooms. This paper describes BeSocratic and the results we have obtained through its use.

2. RELATED WORK

There are many intelligent tutoring systems today, systems that respond to student input with contextual feedback. A review of the use of the more advanced systems [20] shows that students make the greatest improvement when the feedback given to them is related to the mistakes they make. However, these systems are usually limited in the types of questions and feedback that can be used. These systems allow the teachers to set feedback for known missteps. Setting this feedback is typically done through a rule system where the teacher sets a number of rules and defines the feedback associated with the rules.

A popular intelligent tutoring system is the Cognitive Tutor Authoring Tools (CTAT) from Carnegie Melon University [1]. CTAT allows teachers to create questions and supply answers for the questions. With help from CTAT, the teacher generalizes the answers and the software creates a tree structure representing the answer space. The teachers then annotate the nodes and edges in the tree with hints and feedback. Lastly, CTAT provides feedback to students based on the teacher’s feedback tree.

ISBN: 978-972-8939-66-3 © 2012 IADIS

4

CogTutor is another popular application that has been used to assess students in meaningful ways. CogTutor uses methods similar to those in CTAT except that CogTutor also incorporates previous student data and machine learning to continually refine the feedback [23].

CogSketch is an application developed to recognize and respond to sketch drawings [7]. The application attempts to interpret student drawings and evaluate them against teacher created rules. While CogSketch provides a rich set of commands, the interface can make implementing an activity difficult for teachers.

Other on-line systems, such as IMMEX [13], are less rigid in that they allow students to choose their own sequence of actions. Even so, students are still restricted to mouse clicks or drag and drop actions. One feature that sets IMMEX type systems apart is the modeling of student input data. The IMMEX system collects student inputs and models them using artificial neural nets and hidden Markov modeling. Such systems can recognize changes in student strategy over time and how it responds to instruction [6].

3. BESOCRATIC

BeSocratic is a robust pedagogical assessment system designed to recognize and respond to free-form student input. BeSocratic contains a variety of question types that are free-form in nature yet well-defined enough to allow for automatic evaluation and analysis.

BeSocratic activities are composed of one or more activity steps. Each step is designed and developed using one or more modules. BeSocratic modules can be divided into two general categories: non-interactive and interactive. Non-interactive modules (which include text boxes, images, videos, and ink canvases) do not provide students with feedback. Interactive modules allow BeSocratic to pose free-form questions and are able to give automatic feedback to the student and to the teacher. Such modules include: SocraticGraphs, OrganicPad, and GraphPad. While some of the BeSocratic modules are targeted for use with a Tablet PC or touch-enabled device, it may be used with mouse and keyboards as well. The interactive modules mentioned are described in greater detail below.

Also, each module in BeSocratic inherits from a base module class. This base class provides base functions for saving and loading the module. New modules can be added to the system by simply overriding these base functions.

3.1 SocraticGraphs

SocraticGraphs is a module that allows the teacher to ask questions which require students to respond by drawing 2D graphs. SocraticGraphs analyzes raw student drawings by identifying their major components. Once the noise has been removed from the raw input, SocraticGraphs can evaluate the “clean” graphs based on rules that have been pre-specified by the teacher. Moreover, SocraticGraphs provides to the students multi-tiered feedback based on which teacher-provided rules are satisfied by the student’s solution and which are not. This functionality in SocraticGraphs is based on an underlying context-free grammar that provides teachers with a robust, flexible and expandable rule authoring tool. Examples of such rules include: the

Figure 1. A student drawing a raw stroke onto the SocraticGraph module (left), and the “clean” curve that was generated along with 3 level of feedback for the student's error (right)


5

number of maximums/minimums, area under the curve, slope, and intersections with coordinates or areas. By combining such rules, activities designed with SocraticGraphs modules may be used in a large variety of STEM disciplines including mathematics, chemistry, biology, and engineering.

Figure 1 shows an example of a student completing an activity which includes a SocraticGraph module. In this example, the student is tasked with drawing a curve for the equation: . The left side of the figure shows the student’s raw input stroke. The SocraticGraphs module converts the raw stroke into a clean curve with adjustable handles that are highlighted in orange. Once the student feels that the answer is correct, the student can click the Check button and the curve is evaluated against the teacher’s rules. Depending on the results of the evaluation, multiple levels of feedback can be given to the student. The right side of the figure displays an example of several tiers of feedback that could be given for this problem.

3.2 OrganicPad

OrganicPad is a module which focuses on drawing Lewis structures. The OrganicPad module allows users to draw Lewis structures intuitively by drawing ink strokes on the canvas. Using handwriting recognition, the strokes are converted into formatted text and form an interactive molecular structure on the canvas. By entering a solution structure for the module, OrganicPad can evaluate a student’s structure against the solution and give feedback based on the comparisons. This feedback is multi-tiered and Socratic in nature; the feedback starts with very general hints and becomes more specific if the student continues to struggle. In addition, OrganicPad can highlight the parts of the parts of the structure that are causing the errors. This is done through graph isomorphism algorithms that can compare two structures for similarities and differences.

By providing this intuitive interface to students, we were able to evaluate and analyze student work and gain insights into the students’ thought process [16,4,5,2,3]. OrganicPad was originally designed as a standalone desktop or laptop application but has now been added into the set of BeSocratic modules to be used online.

Figure 2 shows an example of a student completing a problem using an OrganicPad module. In this example problem, the student was tasked with drawing the chemical structure for ethanol. The figure shows an example where the student draws an extra bond between the oxygen and carbon atom. In this case, the OrganicPad module highlights the incorrect part of the structure and gives multi-tiered Socratic feedback.

3.3 GraphPad

A third interactive module in BeSocratic is the GraphPad module. GraphPad is designed to help computer science students learn a variety of data structures. It uses ink recognition to convert student drawings into interactive nodes and edges that may be evaluated and analyzed. Using a solution data structure provided by the teacher, GraphPad checks for differences between a student’s structure and the teacher’s solution. GraphPad gives feedback based on the results of that comparison. GraphPad recognizes nodes, undirected and directed edges, and labels for nodes and edges. This simple design allows the construction of practically any graph structure that may be found in a computer science data structures class including: lists, stacks, trees, generic graphs, and finite state automata. GraphPad was originally created for desktop and laptop computers where it showed positive results in computer science data structure classrooms [17,18]. GraphPad has been ported to

Figure 3. A GraphPad module with a binary search tree drawn

Figure 2. And OrganicPad module with a student-drawn structure (top). The structure contains an error which is

highlighted with boxes because of an error. Multiple-tiers of feedback is also shown

(bottom)

ISBN: 978-972-8939-66-3 © 2012 IADIS

6

BeSocratic where it may be used on a wider variety of devices. Figure 3 shows a student who has drawn a binary search tree using the GraphPad module.

4. BESOCRATIC TOOLS

Figure 4 shows the general flow of a BeSocratic activity’s cycle. (1) The teacher creates and develops an activity using an activity authoring tool. (2) The teacher uploads the activity to the BeSocratic database. At this point, students are able to (3) download the activity and (4) complete it. Once they are done, the students can (5) upload their results and a replayable version of their work to the database. Finally, (6) teachers may go into the database and replay and analyze the student submissions.

BeSocratic accomplishes this set of actions using three main tools: Authoring, Viewing, and Analysis. The Authoring Tool allows teachers to create BeSocratic activities and make them available for students to complete. The Viewing Tool allows students to complete an activity. The Analysis Tool allows teachers to replay student work and extract information from the replays. Together, these tools allow teachers to assess and analyze the knowledge levels of their students. The following sections describe these tools in greater detail.

A

B

C

Figure 5. The BeSocratic Activity Authoring tool

Figure 4. A diagram of BeSocratic. Activity creation, assessment and analysis can be achieved

through communication between teacher and students, as outlined in steps 1 through 6


7

Figure 7. The BeSocratic Analysis Tool. Students names are shown on the left. On the right is a paused replay of the selected student's activity

A

B

C

4.1 Authoring Tool

The Authoring Tool is designed to provide teachers with a familiar interface to create activities. Figure 5 shows an example of an activity being created with the Authoring Tool. The left sidebar (B) displays a thumbnail list for the activity’s steps. The Authoring Tool provides a variety of functions and options along the top of the screen (A). Modules are added to the current activity step by selecting the module from the list in (A) and dragging your cursor on the activity step canvas (C). Selecting a module in the activity step canvas (C) bringing up a new tab along the top (A) with more options to change for that module.

Activities can be saved to and loaded from the BeSocratic database so the teacher may access them from any computer connected to the Internet. Teachers may also set a roster and start and end dates so that students on the roster may log into BeSocratic and complete the activities within the start and end dates specified. The Authoring Tool also contains a preview function for the teacher to preview how the activity will appear to the students.

4.2 Viewing Tool

Once an activity has been created, students may download and complete the activity. A student logs into the system and is prompted with a list of available activities. The Viewing Tool (Figure 6) loads an activity selected for completion. The Viewing Tool is designed to present students with a minimalist and intuitive interface. This allows the students to focus on completing the task at hand instead of negotiating through a clumsy interface. As the student completes an activity, all of his actions are stored in a database and a snapshot of each activity step is saved.

4.3 Analysis Tool

The third tool in BeSocratic is the Analysis Tool which allows teachers to replay and analyze student submissions. In the top left side of the Analysis Tool (A) is a file browser from which teachers can select the activities they wish to analyze. With an activity selected, BeSocratic loads all of the student submissions corresponding to the activity (B). When a student’s name is selected, BeSocratic loads the student’s submission into the replay panel (C). The replay panel allows teachers to play, pause, and scan through a replay of the student’s work. This tool can provide insight into the cognitive processes of the students since the teacher can identify the points within a replay where students went astray.

Figure 6. The BeSocratic Viewing Tool. Students use this tool when completing an activity

ISBN: 978-972-8939-66-3 © 2012 IADIS

8

BeSocratic also provides a summary tool which generates reports based on multiple student replays. With this tool, teachers can get a quick overall summary of a class’ performance as a whole. We are currently working on improving the analysis capabilities of BeSocratic and describe this effort briefly in section 6.

5. RESULTS/CLASSROOM USE

BeSocratic has been in use the past year at Clemson University in South Carolina, the University of Colorado, Boulder and the University of North Carolina, Wilmington. It is being used in chemistry and molecular biology classes. Activities are also being developed for physics and mathematics courses. So far, we have collected over 45,000 student submissions over this past year.

Currently we are developing our activities in three stages. In the first stage, an activity is created to target a specific topic. This activity is tested among group members and one-on-one interviews are administered with students. The feedback received from these evaluations is used to refine the activity and handle input that was not initially accounted for. It is in this first stage that the activity undergoes the most change. In the second stage, the activity is tested in small groups of around 20 students. We use lab sessions where students are already in smaller groups to administer the activities. These tests give us additional feedback used to further refine the activity. Finally once the activity is no longer being changed through testing, it is ready to be administered to an entire class of students. Following this process, we have developed a series of activities for introductory chemistry courses at Clemson University. These activities are currently being evaluated for effectiveness over traditional instruction.

6. FUTURE WORK

We are currently testing the system in a variety of classroom environments. We will be analyzing the results to evaluate the effectiveness of BeSocratic activities over traditional instruction and assessments. We are also currently working on developing an iOS and Android BeSocratic app. We have a working prototype that is currently undergoing testing. This is possible because we have provided a web application programming interface (API) for developers to use our system to develop their own systems.

With the activity creator and viewer in place, we are now focusing our attention on creating a richer set of analysis tools. We are currently exploring using clustering algorithms to automatically identify groups of students who complete questions in similar fashions. This could help teachers quickly identify students who are making mistakes and provide extra intervention for those students. Furthermore by training BeSocratic with these clusters of students, BeSocratic could classify new student submissions into these clusters and provide early intervention if appropriate.

7. CONCLUSION

This paper has motivated and described a novel pedagogical application, BeSocratic. BeSocratic gives teachers the ability to ask students a variety of questions that require them to respond with free format visual representations. Because of the openness of the visualizations, students cannot guess their way to the correct answer. However, the visualizations contain enough structure to enable automatic evaluation and student feedback. BeSocratic provides teachers with an Analysis Tool that allows them to replay students work or export the work of an entire class. This software is freely available for use at BeSocratic.clemson.edu.


9

ACKNOWLEDGEMENT

We would like to acknowledge and thank the NSF for providing funding for this project (TUES-1043707, TUES-1122472). We would also like to acknowledge our collaborators at Clemson University, University of Colorado, Boulder, and the University of North Carolina, Wilmington.

REFERENCES

[1] Aleven, V., et al. 2006. Rapid authoring of intelligent tutors for real-world and experimental use. In Kinshuk, R. Koper, P. Kommers, P. Kirschner, D. G. Sampson, & W. Didderen (Eds.), Proceedings of the 6th IEEE International Conference on Advanced Learning Technologies (ICALT 2006), Los Alamitos, CA, pp. 847-851.

[2] Bryfczynski, S. P., et al., 2009. How Do Students Solve Chemistry Problems? Proceedings of WIPTE, Blacksburg, VA.

[3] Bryfczynski, S., et al., 2010. OrganicPad as a Research Tool: Investigating the Development of Representational Competence in Chemistry. Proceedings of the WIPTE, Blacksburg, VA.

[4] Bryfczynski, S. and Pargas, R., 2008. OrganicPad: A Tablet PC Based Chemistry Tool. Proceedings of ACMSE. Auburn, AL.

[5] Cooper, M., et al., 2009. OrganicPad: an interactive freehand drawing application for drawing Lewis structures and the development of skills in organic chemistry. Chem Education Research and Practice Journal.

[6] Cooper, M. M., et al., 2008. Journal of Chemical Education pp. 85, 866. [7] Forbus, K. et al., 2011. CogSketch: Sketch Understanding for Cognitive Science Research and for Education C.

Hölscher et al., eds. Topics in Cognitive Science, Available at: http://doi.wiley.com/10.1111/j.1756-8765.2011.01149.x.

[8] Gilbert, J. K., 2005, Visualization in Science Education, Springer, Dordrecht, The Netherlands, pp. 9-28. [9] Gilbert, J. K., 2005, Visualization in Science Education, Springer, Dordrecht, The Netherlands, pp. 346 [10] Glaser, R.,1991. Expertise and Assessment. In Wittrock, M. C. and Baker, E. L. eds.Testing and Cognition. Prentice-

Hall, Englewood Cliffs, NJ. [11] Glaser, R., 1988. Cognitive and environmental perspectives on assessing achievement. In Anonymous Assessment in

the Service of Learning ETS Invitational Conference. Princeton, NJ. [12] Gurung, R. A. R., 1992. Teaching of Psychology 30, 92. [13] Koedinger, K. R. and Corbett, A., 2006. The Cambridge Handbook of the Learning Sciences. Cambridge University

Press, pp. 61-78. [14] Kozma R. and Russell J., 2005. Visualization in Science Education, Kluwer Academic Publishers, London, pp. 121-

146. [15] Martin, L. and Schwartz, D. L., 2009, Cognition and Instruction pp. 370. [16] Pargas, R., et al., 2007, OrganicPad: A Tablet PC Based Interactivity Tool for Organic Chemistry. Proceedings of

the 1st International Workshop on Pen-Based Learning Technologies, Catania, Italy [17] Pargas, R. P. and Bryfczynski, S. 2009. What were they thinking? In Proceedings of the 14th annual ACM SIGCSE

conference on Innovation and Technology in Computer Science Education. Paris, France. ACM, New York, NY, USA, 2009, pp. 134-138.

[18] Pargas, R. P. and Bryfczynski, S. 2009. GraphPad: A Graph Creation Tool to Expose Student’s Cognitive Processes in CS2/CS4. Proceedings of SIGCSE, Chattanooga, TN.

[19] Resnick, L. B. and Resnick, D. P., 1992. Assessing the Thinking Curriculumn: New Tools for Education Reform. In Gifford, B. R. and O'Connor, M. C. eds. Changing Assessments: Alternative Views of Aptitude, Achievement and Instruction. Kluwer Academic Publishers, Boston, MA, pp 37-76.

[20] Schmid, R. F., et al., 2009, J Comput High Educ pp. 21, 95. [21] Schwartz, D. L., Lindgren R., et al. 2009 Constructivist Instruction: Success or Failure? NY, NY [22] Shepard, L., 1991. Interview on assessment issues with Lorrie Shepard. Educ. Res., 20, 2 21-23. [23] Stamper, J., Barnes, T., and Croy, M. 2010. Enhancing the Automatic Generation of Hints with Expert Seeding. In

Aleven, V., Kay, J., and Mostow., J eds. Proceeding of the 10th International Conference on Intelligent Tutoring Systems (ITS2010). vol. II, pp. 31-40. Berlin, Germany: Springer Verlag.

[24] Tobias, S. and Duffy, T. M., 2009. Constructivist Instruction: Success or Failure? NY, NY [25] Tufte, E. R., 2001. The Visual Display of Quantitative Information. Graphics Press.

ISBN: 978-972-8939-66-3 © 2012 IADIS

10

INTRODUCING COLLABORATION AND COMPETITION INTO REAL WORLD EDUTAINMENT

Keiji Miki 1, Hiroyuki Mitsuhara2, Yusuke Noda1, Kazuhisa Iwak1, Yasunori Kozuki2 and Yoneo Yano3

1Graduate School of Advanced Technology and Science, The University of Tokushima, JAPAN 2Institute of Technology and Science, The University of Tokushima, JAPAN

3Center for Administration of Information Technology, The University of Tokushima, JAPAN

ABSTRACT

Real World Edutainment (RWE) enables children to learn by viewing digital learning materials and interacting with real objects and human in the real world, based on a branched game story. Introducing collaboration and competition among learners into the RWE can increase learning motivation and effect further. This paper describes how to realize such introduction and shows an application example of the RWE to earthquake disaster prevention learning.

KEYWORDS

Edutainment, real world, collaboration, competition, disaster prevention learning, earthquake.

1. INTRODUCTION

Recently, the integration of learning and computer games has attracted attention (Kafai 2006)(Squire 2007). This integration is called edutainment (often called “serious game” in these days), which is educational software that increases learning motivation and effect by using interactive, multimedia, and game technologies. Many edutainment systems are isolated from the real world. In other words, learning is done in a pre-programmed virtual world. Therefore, learners are difficult to learn with five senses and diverse interactions. This is one of the edutainment’s weaknesses that can decrease learning motivation and effect.

To overcome the above weakness, we proposed Real World Edutainment (RWE) and developed the RWE system (Mitsuhara et al. 2010)(Noda et al. 2010). In the RWE, learners can learn from real objects (e.g., creatures, artifacts, and human) and virtual objects (e.g., digital learning materials) by using the RWE system, which fuses the real world and the virtual world with RFID, GPS, and other sensors on UMPC (Ultra Mobile PC). The RWE attaches importance to a game (learning) story and Human-Human Interaction (HHI) to increase learning motivation and effect. Digital learning materials are presented according to the game story and human actors support learners face-to-face. Thus, learning in the real world is controlled and supported.

Learning in the real world has been extensively studied (e.g., (O’Hara et al. 2007)(Ogata et al. 2008)(Wu et al. 2010)). Klopfer and Squire (2008) developed an augmented reality game that has a game story revolved in the real world and furnishes students with scientific augmentation skills. Schwabe and Göth (2005) developed a mobile game for university orientation adopting the same idea of HHI.

The RWE system adopts a stand-alone composition without access to the computer network (wireless communication). Therefore, it only deals with a game story assuming one learner (or one learner group) and never introduces collaboration and competition among learners into the learning. This is a major weakness in the RWE because collaboration and competition can be important factors in both learning and games. In the field of CSCL (Computer Supported Collaborative Learning), it has been shown that a learner often receives learning effects collaboratively from other learners. In the field of computer game design, Crawford (1984) has maintained ‘conflict’ as an important factor. In addition, nowadays, Gamification has been receiving attention. It is a design technique for incorporating game elements in various things and also attaches importance to competition.

In some educational events, we practiced the RWE and found that some learners tended to have collaboration and competition with other learners regardless of the game story that did not include the scenes


11

prompting collaboration and competition. Therefore, we recognized that collaboration and competition can be introduced into the RWE to increase learning motivation and effect further. At the same time, we started to choose a learning topic where collaboration and competition can work well in a game story.

The learning topic we chose is ‘disaster prevention’. This is because people should learn it in the real world (their living places) and would be pressed to make their decision of collaboration and/or competition to survive a disaster. Another reason is that there are many people who do not believe that they may be in disasters and do not have interest in disaster prevention.

The remainder of the paper is organized as follows. Section 2 outlines the RWE and describes the concept of introducing collaboration and competition into the RWE. Section 3 describes an application of the RWE to disaster prevention learning, showing an example of the game story focusing on earthquake. Section 4 summarizes the paper and shows the future works.

2. INTRODUCING COLLABORATION AND COMPETITION INTO RWE

We adopted story-based learning in the real world; that is, we applied a role-playing game and/or adventure game in the real world. A game story helps absorbing learners into the edutainment world (the fictional world in the real world). In addition, we adopted human actors as active characters in the game story, who will be superior to artifacts in terms of interaction (e.g., conversation) and can provide flexible instruction to learners’ characteristics (e.g., understanding) and situations (e.g., time and place).

2.1 System

The RWE system operates on UMPC in terms of mobility in the real world, and recognizes learning scenes described in a game story and presents digital learning materials. However, it does not access the computer network because of unstable wireless network areas (e.g., mountainous areas and internal spaces of shielded buildings), which can be necessary areas in a game story.

The whole system includes a game story, learning materials, an edutainment engine, learners (players), human actors (learning supporters), and locations and real objects. The system is schematically illustrated in Figure 1.

Figure 1. System overview of Real World Edutainment

2.1.1 Game Story

A game story writer(s) (e.g., teacher) selects a learning topic and writes a game story, which consists basically of ordered learning scenes and can be branched. If a learner visits at a scene in the wrong order, the scene is not recognized. If two or more scenes are prepared as the next scene, it is called ‘branched game story’. The branched story can provide multi-ending and flexible instruction. Therefore, it is expected that learners will have a sense of responsibility and self-control and consequently learning motivation and effect will be increased.

(1) Irreversible Branching This branching does not have backtrackings and loops in the story. For example, if a learner’s answer to a

ISBN: 978-972-8939-66-3 © 2012 IADIS

12

quiz is incorrect, he/she is moved to a series of scenes about a basic learning topic. (2) Reversible Branching This branching has backtrackings and loops in the story and allows a learner to alternate learning scenes.

For example, if the answer is incorrect, he/she can retry the same scene or return to a previous scene to brush up his/her understanding. In another example, if being given some locations as the next learning scene, he/she can move to all the locations.

2.1.2 Learning Scene Recognition, Learning Materials, and Learning Support

Location data (latitude, longitude, and direction) are gathered from GPS at a regular interval. A location specified by the GPS corresponds to one scene ID. In some cases, direction of a learner at the location corresponds to one scene ID. Locations are used for scene recognition in an open playing field. A learner reads an RFID tag attached to a real object using UMPC and immediately the object data recorded in the tag is gathered. When the gathered data matches a location ID or an object ID specified in the game story, the corresponding scene ID is given.

The learning materials are quiz (single-choice and multiple-choice), audio, image, and video. For example, a learner can deduce the correct answer to a quiz, watching a video given as the hint.

During the learning, a human actor plays a supporting role by providing hints to quizzes and leading the learners toward a learning goal according to the game story, while considering their characteristics and situations.

2.2 Weakness

The RWE system has a weakness due to its stand-alone composition. The weakness is that the system does not introduce collaboration and competition among learners into the RWE. When some learners (not in the same learner group) are learning in the same story at the same time, the system cannot connect them. In other words, the system cannot prompt them to collaborate and compete. When two different learners are at the same scene (approaching each other), for example, they are not prompted to exchange their knowledge and complete the scene together or faster than the other learner.

Collaboration among learners, which can provide new interaction channels and positive effects, will increase learning motivation and effect in the RWE, especially for novice learners who do not have enough prerequisite knowledge. It has become clear from several studies that introducing collaboration and competition into study increase learning motivation and effect. Garrison et al. (2003) maintained that the relationship between learners changes a motivation and participation degree, and moreover stated that improving the value of others (social presence) in collaborative learning leads to deriving discussion and increasing motivation.

Although occasionally supposed to be harmful for learning, competition is one of the important factors that can increase learning motivation and effect. Competition may induce superficial interest in a learning topic (extrinsic learning motivation) and give learners a purpose of learning. Johnmarshall et al. (1985) maintained that information feedback obtained from the results of competition influences a task performance and learning motivation.

2.3 System Extended for Collaboration and Competition

To overcome the weakness described in section 2.2, first of all, the RWE system has to be extended from the stand-alone composition to the network-based composition. Therefore, we equipped a UMPC with a wireless communication unit and set up a server on the computer network.

In the network-based composition, the server receives the learners’ data (log) from the client systems (edutainment engines) at a regular interval or every scene, and records the data in each game story. The learners’ recorded data is transmitted to the client systems when needed for the story progression.

The recorded data are used to judge which next scene learners move to, collaborative learning or competitive learning. There are two kinds of the recorded data: activity log and learning log.

(1) Activity Log � Current scene: This data item indicates his/her story progression (learning progression in the story). � Visited scenes: This data item, obtained from which scenes a learner has visited, indicates his/her


13

learning procession in the story. � Current location: This data item, obtained from GPS, indicates a learner's current location in the real

world. � First scene visitor: This data item is obtained from who the first visitor (learner) is in each scene. � Elapsed time: This data item is obtained from a timer, which counts from the beginning of the game

(learning) to the current time or from the particular scene to the current scene. � Current activity status: This data item, which has the two statuses: ‘in learning’ and ‘not in learning’, is

obtained from whether the data is successfully transmitted from the client system at a regular interval or the signal of ‘quit learning’ is transmitted.

(2) Learning Log � Answers to quizzes: This data item, obtained from which quizzes a learner answered correctly or

incorrectly, indicates his/her understanding about the subdivided learning topics corresponding to each quiz. � Percentage and number of quizzes answered correctly: This data item, obtained from how many of the

presented or prepared quizzes a learner answered correctly, indicates his/her overall understanding in a game story.

� Note: A learner can take a note as letters and drawings on the client system. For example, the learner may write his/her acquired knowledge, question, etc. The note is linked to the current scene or the current location.

� Picture: A learner can take a picture with the built-in web camera on the UMPC. For example, the learner may take pictures of the real objects he/she observed. The picture is also linked to the current scene or the current location.

2.4 Expected Learning

Introducing collaboration and competition into the RWE can increase learning motivation and effect. This is because the introduction of other learners can diversify learning in terms of the branched game story.

To introduce collaboration and competition among learners into the RWE is that the system reasonably prompts the learners to collaborate and compete according to a game story. To do it, the system uses their recorded learning activities.

2.4.1 Collaborative Learning

It is expected that collaboration will increase learning motivation by fostering camaraderie among learners and learning effect by teaching each other what they have learned. Examples of the collaborative learning (collaboration in the RWE) are shown as follows.

� In a branched game story, learners can learn through various paths. When the story is branched based on the difference of learning topics and learners can choose the next scene, their knowledge acquired in the story will be different. In such a case, the sole next scene linked from some scenes is prepared and they visit the scene certainly. Then, they can meet at the scene and exchange their acquired knowledge (Figure 2-left). If a quiz is presented at the scene and the quiz tests integrated knowledge of some learning topics, they can answer the quiz collaboratively.

� When the story is branched based on their answers to quizzes, the difference of their visited scenes may indicate the difference of their understanding. In such a case, a learning scene is prepared where a learner without enough understanding meets other learners with enough understanding (Figure 2-right). Then, the learner can be taught by the learners. Such diverse learners can get motivated to learn each other (e.g., learning from reliable companions and learning by teaching).

ISBN: 978-972-8939-66-3 © 2012 IADIS

14

Figure 2. Collaborative learning examples based on learners’ understanding (left) and acquired knowledge (right)

2.4.2 Competitive Learning

The important point in introducing competition into the RWE is how to encourage competition among learners in a game story. A simple way is that competition (its rule, goal, and winning conditions) is declared at the beginning or in the middle of the story. Another way is that the necessity of competition is implied in the story and the learners have to get aware of the competition by themselves.

There may be two kinds of competition in the RWE. One is competition against the time and another is competition in understanding. Examples of the competitive learning (competition in the RWE) are shown as follows.

� It is declared that the learner who visits the last learning scene (ending scene) first is the winner. In another example, the learner who visits the last scene in the shortest period of time is the winner. To become the winner, learners may get motivated to learn and concentrate on learning until the end. When a branching condition based on the first scene visitor is given to a scene, the first scene visitor can be moved to the limited next scene or be given the reward (Figure 3-left).

� A learner with the highest percentage of quizzes answered correctly becomes one of the winners (Figure 3-right). This competition is represented as multi-ending in a branched game story. To become the winner, learners may learn more carefully. In another example, when a learner visits the last scene, his/her percentage of quizzes answered correctly is compared with other learners’ percentages. If having the highest percentage, he/she becomes one of the winners.

Figure 3. Competitive learning examples based on the first visitor (left) and the percentage of correct answer (right)


15

3. APPLICATION TO DISASTER PREVENTION LEARNING

We selected ‘disaster prevention’ as a learning topic for the RWE. Especially we focused on ‘earthquake disaster prevention’ (EDP for short) because Japan is an earthquake country and it suffers a lot of earthquake damage. For example, Tohoku Region Pacific Coast Earthquake in March 11, 2011 was a large-scale disaster that caused a huge tsunami by which a number of towns were devastated.

3.1 Conventional EDP Learning

EDP learning has been conducted on a regular base in Japan. For instance, people acquire knowledge of EDP not only through classroom lectures, but also by participating earthquake drills outside the classroom. Learning through virtual experiences in the real world, like earthquake drills, is important in EDP learning. However, the current EDP learning tends to be monotonous. During an earthquake drill in school, for example, students just evacuate to shelters following teachers. In such monotonous EDP learning, the students get less motivated and cannot acquire enough knowledge of EDP.

To motivate people to learn EDP, pictures and statistical data of past and/or anticipated earthquakes are often used. If such pictures and statistical data are used without regard to locality (regionality), however, learning motivation is not significantly increased. In other words, learning from earthquakes in remote residences lacks impact. As a matter of course, there are many examples of EDP learning that focuses on locality and is helpful for local residents. For example, Katada and Kanai (2008) practiced the workshop where children and their parents searched for safety tsunami evacuation spots while walking around their living place and then made tsunami evacuation maps. In addition, Katada’s group (2008) developed a GIS- and simulation-based table-top system to enable residents to make their local evacuation plans. To be more precise, this system projects a local map to the tabletop and the residents can simulate a variety of evacuation plans by placing tangibles item or writing on the map with digital pens.

As another approach to increasing learning motivation about EDP, some studies adopt game-based learning. For example, “Inside the Haiti earthquake” (http://www.insidedisaster.com/experience/Main.html.) is a web-based serious game for learning the Haiti earthquake. Learners (players) play a role (survivor, journalist or aidworker) and follow the story by selecting from several options. This game presents the real videos and pictures of Haiti after the earthquake in order for many people to know tragedy and fear of devastating disaster. Through this game, the learners will get motivated to think about their own EDP. However, this game cannot be played in the real world and does not introduce competition and collaboration into learning.

3.2 Game Story Example for EDP Learning

We think that EDP learning should focus more on experiential learning within a local area in the real world. The theme of our game story was Nankai earthquake (magnitude of around 8.0), which is anticipated more than 60% of the time within 30 years and hits the mid-western part of Japan (including Tokushima).

3.2.1 Aim

It is true that there are many opportunities for people to collaborate during disaster (e.g., rescue operations). However, such collaboration is not necessarily handled in the current EDP learning. It is also true that people should evacuate to a safe spot before anyone else when an earthquake occurs. Such evacuation can be regarded as a certain kind of competition―as a matter of course, it never recommends ignoring and leaving people who need help. However, competition is not positively handled in the current EDP learning.

Although the coexistence of collaboration and competition may be difficult in EDP learning, we attempted to write a game story that handled collaboration and competition in real world. The game story aimed at giving knowledge of EDP to people, especially elementary school students.

3.2.2 Prologue and Story Outline

We wrote the branched game story including scenes of collaboration and competition. The prologue of the story is shown as follows.

ISBN: 978-972-8939-66-3 © 2012 IADIS

16

� You have encountered Nankai earthquake at the University of Tokushima when a rescue team's event has been held there! People stranded by the earthquake are seeking help. You are supposed to work together with the rescue team and rescue people safely before the tsunami attacks!

In the story, the learning flow and learning materials (e.g., video and quiz) are constructed based on EDP manual. Learners (players) act as ‘rescue workers'. Some actors play ‘injured persons' and the other actors play ‘rescue workers (supporters)’ who are enough trained and accompany the learners and provide hints. The story begins from the scene where learners hear rescue missions from rescue team director (a teacher) as if they were real rescue workers. Learning flow (storyline) is shown as follows and in Figure 4.

The first part of the story focuses on collaboration and the latter part focuses on competition. In the first part, the learners can select the next learning scene from two scenes (Scene 3 or Scene 4). In either scene, they can acquire different first aid’s knowledge. After their selected scenes, they meet at the next scene and rescue an injured person collaboratively by exchanging their acquired knowledge (Scene 5). This is collaboration in the story.

The learner who visits the last scene first is the winner and is given a special ending. In addition, the learners have to visit the last scene by the time (about 40 min.) tsunami attacks the university. These are competition against the time (Scene 6 - Scene 10).

Figure 4. A game story example including collaboration and competition for EDP learning

4. CONCLUSION

This paper described how collaboration and competition among learners were introduced into Real World Edutainment (RWE) and how the RWE was applied to earthquake disaster prevention (EDP) learning. To realize such introduction, the RWE system was extended from the stand-alone composition to the network-based composition and made more effective use of a branched game story. Our game story, which aimed at giving knowledge of EDP, prompted learners to meet at a learning scene and complete a learning task collaboratively, and moreover prompted competition against the time. For example, a learner has to reach the last scene (a safe evacuation spot) by tsunami attacks.

We are currently implementing the functions for introducing collaboration and competition into the RWE. A challenge in implementation is to detect and cope with the deadlocks in the game story. For example, it should be avoided that a learner cannot move to the next scene until other learners visit the learner’s current


17

scene. We are developing a game story authoring system where a game story writer can allocate, configure, and link learning scenes visually and designate branching conditions easily to each scene. The authoring system should have a function of deadlock detection. Furthermore, we have to improve the existing functions of the RWE system. For example, learning materials should be superimposed on real-time camera images using markerless AR (Augmented Reality) technology. The current scene recognizer can recognize a learning scene using the pictures and video captured from a web camera. However, successful scene recognition is severely limited even in the experimental environment inside a room.

The most important matter in this research is how we should achieve people’s understanding of applying the RWE to EDP learning. Some people will dislike the fusion of entertainment (game) and EDP learning. Disaster victims may refuse the fusion. We think that entertainment should be just the gateway to and the background of EDP learning. To achieve it, we have to seek an optimum balance between entertainment and EDP learning, and clarify the effect of applying the RWE to EDP learning. Therefore, our important future work is to conduct a large-scale practice based on various game stories including collaboration and competition reasonably related with the real world.

ACKNOWLEDGEMENT

This research was supported in part from the Panasonic Education Foundation, Japan.

REFERENCES

Crawford, C. 1984. The Art of Computer Game Design. http://library.vancouver.wsu.edu/sites/library.vancouver.wsu.edu/ files/ACGD.pdf

Garrison, D.R., Anderson, T. 2003. E-learning in the 21th century: A framework for research and practice. Routledge Falmar. London. UK. pp49-71.

Johnmarshall, R., Bradley, C. Olson., and Steven, G. Cole. 1985. Motivation and Performance: Two Consequences of Winning and Losing in Competition. Motivation and Emotion. Vol.9, No.3, pp.291-298.

Kafai, Y. B. 2006. Playing and Making Games for Learning― Instructionist and Constructionist. Perspective for Game Studies, Games and Culture, Vol. 1, No. 1, pp.36-40.

Katada, T. and Kanai, M. 2008. Implementation of Tsunami Disaster Education for Children and Their Parents at Elementary School. Proc. of the Solutions to Coastal Disasters Congress 2008. Oahu, Hawaii, pp.39-48.

Klopfer, E. and Squire, K.D. 2008. Environmental Detectives—the development of an augmented reality platform for environmental simulations. Educational Technology Research and Development, Vol. 59, No. 2, pp.203-228.

Kobayashi, K., Narita, A., Hirano, M., Tanaka, K.,Katada, T., and Kuwasawa, N. 2008. DIGTable: A Tabletop Simulation System for Disaster Education. Proc. of the Sixth International Conference on Pervasive Computing. Sydney, Australia, pp.57-60.

Mitsuhara, H., Kanenishi, K. and Yano, Y. 2010. Real World Edutainment Focusing on Game Story and Human-Human Interaction in the Real World. The Journal of Information and Systems in Education, Vol. 9, No. 1, pp.45-56.

Noda, Y., Mitsuhara, H., Kanenishi, K. and Yano, Y. 2010. Real World Edutainment Based on Flexible Game Story. Proc. of the 18th International Conference on Computers in Education, Putrajaya, Malaysia, pp 509-516.

Ogata, H., Hui, G.L., Yin, C., Ueda, T., Oishi, Y. and Yano, Y. 2008. LOCH: Supporting Mobile Language Learning outside Classrooms. International Journal of Mobile Learning and Organisation. Vol. 2, No. 3, pp.271-282.

O’Hara, K., Kindberg, T., Glancy, M., Baptista, L., Sukumaran, B., Kahana G. and Rowbotham, J. 2007. Collecting and Sharing Location-based Content on Mobile Phones in a Zoo Visitor Experience. Computer Supported Cooperative Work, Vol. 16, No. 1-2, pp.11–44.

Schwabe, G. and Göth, C. 2005. Mobile learning with a mobile game: design and motivational effects. Journal of Computer Assisted learning. Vol. 21, No. 3, pp.204–216.

Squire, K.D. 2007. Games, learning, and society: Building a field. Educational Technology, Vol. 4, No. 5, pp.51-54. Wu, S., Chang, A., Chang, M., Yen, Y.R, Heh, J.S. 2010. Learning Historical and Cultural Contents via Mobile Treasure

Hunting in Five-Harbor District of Tainan, Taiwan. Proc. of 6th IEEE International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education. Kaohsiung, Taiwan, pp.213-215.

ISBN: 978-972-8939-66-3 © 2012 IADIS

18

LEARNING BY LOGGING: HOW CAN WE USE LIFE-LOG PHOTOS FOR LEARNING?

Hiroaki Ogata, Bin Hou, MengMeng Li and Noriko Uosaki University of Tokushima, Japan

ABSTRACT

This paper focuses on how to capture learning experiences in our daily life for vocabulary learning. In our previous works, we developed a system named SCROLL (System for Capturing and Reminding Of Learning Log) in order to log, organize, recall and evaluate the learning log. However up to now, we just use an active mode to record logs. This means that a learner must take a capture of learned contents consciously and most of learning chances be lost unconsciously. This paper proposes a system named PACALL (Passive Capture for Learning Log) in order to have a passive capture using SenseCam to solve this problem. With the help of SenseCam, learner’s activity can be captured as a series of images. With the help of this system, a learner can find the important images by analyzing sensor data and images processing technology. Finally, the selected images will be uploaded to the current SCROLL system as ubiquitous learning logs. This research suggests that SenseCam can be used to do passive capture of learning experiences and workload of reflection can be reduced by analyzing sensor data of SenseCam.

KEYWORDS

Life log, learning log, passive capture, SenseCam, ubiquitous learning.

1. INTRODUCTION

CSUL (Computer Supported Ubiquitous Learning) or context-aware ubiquitous learning (u-Learning) is defined as a technology enhanced learning environment supported by ubiquitous computing such as mobile devices, RFID tags, and wireless sensor networks (Ogata et al, 2004). CSUL augments learning in the real world by presenting information on personal mobile devices through the Internet and surrounding environment like physical objects and sensors. Those CSUL applications are intended to be used all the time. This is one of the advantages CSUL called permanency. It means that learners never lose their work unless it is purposefully deleted and all the learning processes are recorded continuously every day. However, little attention has been paid to this aspect despite much attention being paid to other features such as accessibility, immediacy and interactivity to the Internet, physical environment and other learners.

The fundamental issues of CSUL are: (1) How to record and share learning experiences that happen at anytime and anyplace. (2) How to retrieve and reuse them in future learning. To tackle those issues, LORAMS (Linking of RFID and Movie System) (Ogata et al. 2007) was

proposed. There are two kinds of users in this system. One is a provider who records his/her experiences into videos. The other is a user who has some problems and is able to retrieve the videos. The system automatically links between physical objects and the corresponding objects in a video and allows sharing them among users. By scanning RFID tags, LORAMS shows the user the video segments that include the scanned objects. Although this system is useful in certain environments, it is not easy to be applied in practice at any place at the moment. Therefore, we started more practical research called “ubiquitous learning log (ULL)” project in order to store intentionally what we have learned as ubiquitous learning log objects (ULLOs) and consequently reuse them.

Miller and Gildea (1987) compared the way that children are taught words from dictionary definitions and a few exemplary sentences with the way vocabulary is normally learned outside the school. They noted that people generally learn words outside school. It suggests that using mobile devices is a good way for people to remember the vocabulary since people can use mobile devices anywhere and anytime. However, in the


19

previous SCROLL (System for Capturing and Reminding Of Learning Log), all the ULLOs are created by learners manually (Ogata et al. 2010a). It means that learners must record their learning experiences consciously. This is the active mode to record the learning experiences. However under this active mode, learners cannot record all of the learning experiences in the system, for example they maybe forget to take some pictures when they learned some vocabularies, and most of chance that they can learn vocabulary will be lost and forgotten.

Passive mode has the ability to solve this problem. In this mode, learner is not required to record learning experiences actively, and all the learning activity will be record by some devices automatically. Therefore, we attempt to introduce the concept of life log into this system to record learning experiences in a passive way. The notion of life log can be tracked back at least 60 year (Bush, 1945). It means to capture a person’s entire life or large portions of life. It usually uses digital devices to record life log such as wearable cameras or video recorders. For example, in the early 1980s Steve Mann captured his life using wearable computer and streaming video and even his everyday life 24 hours a day in order to see what he was looking at (Mann & Picard, 1995). The life log brings us the data of whole life of not only learning but also other activities. However, if there is any way that we can extract the learning part from it, the learning log will be more significant and more sufficient. Besides, our system captures the learning log beyond their consciousness and learners’ burden will also be reduced. Microsoft’s SenseCam (Hodges et al. 2006) is an effective way to capture the life log. It is a wearable camera equipped with a number of sensors. The SenseCam is proposed to record a series of images and capturing a log of sensor data.

In this paper, we propose a system named PACALL (PAssive CApture for Learning Log) that uses Microsoft’s SenseCam to capture the learning log pictures passively using to help learners learn vocabulary. With the help of analyzing sensor data, it extracts the meaningful images for learning from life log and helps learners upload the learning content easily. In addition, we also conducted an initial experiment to compare between active mode and passive mode and analyzed the result.

2. SCROLL: UBIQUITOUS LEARNING LOG SYSTEM

Learning Log was originally designed for children as a personalized learning resource (Ogata et al. 2010a). It was set by teachers to help their students record their thinking and learning. In this learning log, the logs were usually visually written notes of learning journals. How are we learning from past learning log? For example, we take notes, e.g., vocabularies, idioms, sentences in a language learning situation. Whereas, they will not remind us of the knowledge learned, nor the situation where the knowledge was used. We think this process can be enhanced using mobile devices. We proposed learning processes in the perspective of the learner’s activity model called LORE (Log-Organize-Recall-Evaluate).

(1) Log what the learner has learned: When the learner faces a problem in the daily life, s/he may learn some knowledge by her/himself, or ask others for a help in terms of questions. The system records what s/he learned during this process as a ULLO.

(2) Organize ULL: When the learner tries to add a ULLO, the system compares it with other ULLOs, categorizes it and shows the similar ULLOs if exist. By matching similar objects, the knowledge structure can be regulated and organized.

(3) Recall ULL: The learner may forget what s/he has learned before. Rehearsal and practice in the same context or others in idle moments can help the learner to recall past ULLOs and to shift them from short-term memory to long-term one. Therefore, the system assigns some quizzes and reminds the learner of her/his past ULLOs.

(4) Evaluate: It is important to recognize what and how the learner has learned by analyzing the past ULL, so that the learner can improve what and how to learn in future. Therefore, the system refines and adapts the organization of the ULLOs based on the learner’s evaluation and reflection.

Since 2009, we started our project and developed a system named SCROLL (System for Capturing and Reminding Of Learning Log) (Ogata et al. 2010a, 2010b) that helps learners collect their learning experiences as ubiquitous learning objects (ULLOs). Also, all of the collected ULLOs are organized, shared in this system, and the learning effect can be enhanced.

ISBN: 978-972-8939-66-3 © 2012 IADIS

20

(1) ULL registration (2) ULL (3) ULL Quiz (4) ULL navigator

Figure 1. SCROLL on Android.

SCROLL is a client-server application, which runs on different platforms including Android mobile phones, PC and general mobile phones. It contains the following components:

(1) ULL recorder: This component facilitates the way for the learners to upload their ULLOs to the server whenever and wherever they learn. Learners can take its photo, video and/or voice and ask questions about it and attach different kinds of meta-data with it, such as its meanings in different languages, comments, tags and location information. Also the learner can enter its barcode and/or RFID and select whether the new ULLO can be shared or not. Figure 1(1) is the interface of registering a new learning log that runs on Android smartphone. Figure 1(2) is an example of learning log.

(2) ULL finder: If learner registers a new ULLO, the system checks whether the same object has been already stored or not by comparing the name fields of each object using a thesaurus dictionary. Also, the learner can search ULLOs by name, location, text tag and time. Using this function, learners can understand what, where and when they learned before. In the future works, the visualization of the ULLOs will be developed.

(3) ULL reminder: This function is used to implement the Recall ULL in LORE model. This system provides a personalized and context-aware quiz to remind learners of past ULLOs. Quizzes are generated by system automatically from the ULLOs registered by all learners. The quiz function is designed not only to help the learners to practice what they have learned, but also to recommend what the other learners have learned and to remind them to re-learn their past knowledge according to their current location and their preferred time. Figure 1(3) is the interface of quiz function on Android.

(4) ULL navigator: It provides mobile augmented reality that allows the learners to navigate through the ULLOs. Like Wikitude and Sekai-Camera, it provides them with a live direct view of the physical real-world environment augmented by a real time contextual awareness of the surrounding objects. While a learner is moving with his mobile phone, the system shows an alert on the phone as soon as he enters the region of ULLOs according to the GPS data. This view is augmented, associated with a visual compass, and overlapped by the nearest objects in the four cardinal directions (Figure 1(4)). It also provides him with a list of all surrounding objects. When he selects one or more of these objects, the Google map will be retrieved, and marked with his current location and the selected object. Moreover, the system shows a path (route) for him to reach to its locations. This assists him to acquire new knowledge by discovering the existed ULLOs and to recall his own ULLOs.

3. RESEARCH DESIGN

This research is a sub-item of Ubiquitous Learning Log, and we named it as PACALL. It means a passive capture for learning log. The whole process of passive capture happens unconsciously. However it is no doubt that the simple photo capture is not the whole process of learning. It is necessary for learners to look through the captured photos and find the learning contents with the help of system. After entering the information of the image such as title and description, this learning content will be saved into SCROLL system as a ULLO. Of course, the saved ULLOs need to be recalled to help learners to remember, but this is the feature of SCROLL. That is to say, a process of passive capture includes capture, reflect and store.

� Capture: Capture a series of photos for life log in daily life. This log is assumed that it includes all what learner has seen. Besides, massive redundant contents are also included in this log. We use SenseCam in the process of capture.


21

� Reflect: After capturing life log, a learner needs to have a reflection of what he has learned. In this process, since there are so many photos, we provide a system to filter the redundant photos by analyzing sensor data or image processing technology..

� Store: When a learner finds an important learned content, the content must be stored into SCROLL. During this process, he also needs to enter the information of learned content such as title, description or tags.

In PACALL, we use SenseCam to have a passive capture of learner’s daily life. However, since this device takes photos continuously, more than 200 photos will be taken in one hour, and more than 1500 photos in one day. Therefore, we propose a method to classify these photos by sensor data.

All photos are divided into 5 levels based on importance – manual, normal, duplicate, shake and dark. (1) Manual: Manual means the photo is taken by pressing manual button consciously. When a learner

takes a photo manually, it means that this photo must be important from his point of view. Manual photos are selected by the sensor data with flag CAM and the capture reason “M” (manual capture).

(2) Normal: Normal means the photo is clear and can be used as learning log object. After excluding the duplicates, shake and dark, left photos are judged as normal.

(3) Duplicate: Duplicate means the photos are duplicated. Duplicated photos usually have same conditions. We use CLR, TMP, ACC, MAG and timestamp of photo to detect photos that are taken under the same conditions and pick out them as duplicated photos.

(4) Shake: Shake means the photo is blurred. It usually happens when the light level is low and the camera shakes. The sensor data CLR help us detect light level and ACC help us detect camera shake.

(5) Dark: Dark means the photo is taken with insufficient light and the photo is dark. It can be detected by CLR data.

4. IMPLEMENTATION

In this research, the SenseCam that we are using is produced by Vicon Revue. When the SenseCam is connected to the computer, if the software Vicon Revue Desktop is already installed, all photos will be imported into computer. The location of SenseCam repository is in the user’s document folder and the name is Vicon Revue Data. This system is programmed by Java and runs in Tomcat as a B/S system on the local machine. When using this system, Tomcat accesses the repository of SensorCam photos directly and shows them in web browser.

When the learner starts this system, s/he is required to enter the username and password as the same as SCROLL system. If this is the first time that learner logs in, system will ask learner input the location of sensor data path. This setting can be changed at any time by the setting page. The sensor data path must contain the sensor data file (data_v3.sql), and since the security issues, learner cannot choose the folder directly by file select dialog. For the Vicon Revue SenseCam, this folder is usually named “Vicon Revue Data” and located at user’s documents folder. When the SenseCam connects to the computer, all the data will be import into this folder automatically.

After that, life-log picture folders will be shown to them including the name of the folder, picture number and last updated time. Each folder contains photos for a PACALL frame. Here, the name will be used to locate the folder directly in file explorer. Sometimes, if a SenseCam has no picture and is connected to a computer, a life-log picture folder will be also created with no data. Picture number makes it clear, and save the time when the learner selects life-log picture folder.

When the learner selects a new folder, the system will analyze the file SENSOR.CSV in this folder. Because in this file, the sensor data is record as event flow, we need to analyze it and get the sensor information of each picture. At the end of this process, the information of each picture will be saved into database and the life-log picture browser page will be shown (Figure 2). On the top of this page, classifications are shown like menus including ALL, MANUAL, NORMAL, DUPLICATE, SHAKE and DARK. The numbers of pictures in each classification are shown on the side of classification. There is also a function that let users change the lines of pictures per page. It is very useful when user wants to view all of the pictures or do not want to drag the scroll bar.

ISBN: 978-972-8939-66-3 © 2012 IADIS

22

Figure 2. Interface of browsing life-log pictures

Once the learner clicks a picture, the system will show a page to view the large picture and help learner upload the picture to SCROLL. Currently, this page is very simple, and there are two buttons – “Upload it” and “Close” and one picture on it. However, in the future, we plan to expand this page and show the similar pictures from remote server on it.

Figure 3. Registration of learning log.

If leaner decides to upload this picture to the server, s/he can click the “Upload it” button. Then the picture will be uploaded to the SCROLL system directly and the page will jump to the learning log registration page (Figure 3). On the learning log registration page, learner is required to input the title of the picture. The title is usually the name of the object in this picture. Location and other options are also supported on this page. When an object is registered to the system, SCROLL system will use “organize”, “recall” and “evaluate” model to help learner remember uploaded objects and vocabularies. For example, system will remind learner this vocabulary by quizzes.

5. EVALUATION

The study group just consisted of 4 Japanese university students. The whole evaluation experiment lasted for 3 weeks consisted of 3 stages:

Stage 1: SenseCam: On this stage, students were asked to wear SenseCam every day for one week. Every evening, they need to review all the life-log pictures and choose proper pictures to upload to the SCROLL. At last, the cost time need to be record.

Repository

SCROLL

SenseCam

Learner Browser

Server


23

Stage 2: Tablet PC: In our previous works, we have compared between Tablet PC and traditional learning method like note. SCROLL with Tablet PC is more effective than traditional learning method. In this experiment, we only compare log method with SenseCam to that with Tablet PC, for log with Tablet PC is considered as active mode while log with SenseCam is considered as passive mode. On this stage, all the students were asked to record and upload the learning log objects every day with Tablet PC for one week. We used Samsung Galaxy Tab in this experiment. The operating system of this Tablet PC is android, and we have developed an android client that can upload the picture to the system conveniently.

Stage 3: SenseCam+PACALL: On this stage, PACALL system was introduced into this experiment. It is almost the same as stage 1. All the students should wear SenseCam every day for one week. Every evening, they used PACALL system to classify the life-log pictures and upload the proper pictures. The cost time need to be record. Besides, they were asked to count the wrong number of classification after uploaded all the pictures.

0

2

4

6

8

S1 S2 S3 S4

Per day

Per day

Per day

Per day

Tablet

PC

SenseC

am

0

2

4

6

S1 S2 S3 S4M

emory

Level

Memory

Level

Memory

Level

Memory

Level

Active

Passive

Figure 4. The average number of uploaded ULLOs. Figure 5. Memory level between active and passive.

The first result that we want to know is what the different is between this three learning method on the number of uploaded ULLOs. Figure 4 shows the average number of uploaded ULLOs for each subject. On this chart, the horizontal axis shows four subjects, and the vertical shows the average number of ULLOs that uploaded by subjects. We can see that SenseCam and SenseCam+PACALL have got a higher value than Tablet PC. It is sure that the base number of pictures that captured by SenseCam is larger than that by Tablet PC, but as the result, we can see that the passive mode with SenseCam can record more learning chances than active mode. Moreover, we must notice that PACALL can increase the number of uploaded pictures at most of the time (except S2). In normal circumstances pictures that captured by SenseCam would be almost the same and the number of uploaded objects would also be almost the same. However, from the feedback, we understand that the PACALL could reduce the work of reviewing life-log pictures. Learners can choose pictures and upload them conveniently. So the number of uploaded pictures by SenseCam+PACALL is larger than that by SenseCam only.

What is the different on learning effect between active mode and passive mode? This is the second result that we want to know. In order to find this result, we asked all the students to do a test paper after each stage to see whether they have remembered the uploaded objects or not. We made the test papers that contain the uploaded pictures and asked the students to write down the title of pictures and judge the memory level (from 0 to 5). If s/he remembered clearly, the memory level is 5 and if s/he absolutely cannot remember it then the memory level is 0. Figure 5 shows this result. We can see the memory level of active is a little higher than that of passive. By the feedback, we know that under the active mode, the learner takes picture consciously, so the impression is deeper than that under passive mode. Besides, the picture number of passive mode is larger than that of active mode, and it is also an impact factor. However, considering the record numbers, this result is acceptable.

We also received some suggestions and feedbacks from students. They help us to understand the usage of PACALL. Besides, these suggestion and feedbacks also help us to improve our system. We pick out some typical feedbacks, and list them as follows.

� I think PACALL is easy to use. When I use the SenseCam without PACALL, I must find the photos in the folder from browser. However when using PACALL, I just select the photo and click “upload”. The photo and time are shown in PACALL, and that is easy to understand. Besides, inappropriate photos are also excluded by this system.

ISBN: 978-972-8939-66-3 © 2012 IADIS

24

� It is better to use the Android Tablet PC in conjunction with PACALL system. � Passive mode could record the learning content even if I don’t want to learn. However, active mode

can be only used when I want to learn something. � I feel very shame when using SenseCam. � The accuracy is not so good in analyzing blurred photos. These shows that this system is easily to use and the users are satisfied with this system. Passive mode

could record the learning content even if learners do not want to learn. It means that the life-log pictures bring more chance to learn the vocabulary. However indeed the learners will feel ashamed when wearing the SenseCam in public area such as in the supermarket or on the street. And also it brings some privacy problems. This cannot be solved at present. But in the future, we believe that the SenseCam will get smaller and looks more beautiful, then maybe learners will not get so ashamed. Besides, the algorithm for classification should be improved in the future.

6. CONCLUSION

In this paper, we discussed how we can learn vocabulary from the life-log pictures. In order to do it, we used SenseCam to capture life-log passively and developed a system named PACALL to help learner to register learning log objects with vocabulary. We have designed a model of learning process in passive capture mode including capture, reflect, store. The PACALL system has been also developed in order to support reflection and reduce the workload of reviewing photos. During this research, we found that the SenseCam that originally designed for memory aid can be also used to capture learning log for passive mode to help learners to learn vocabulary. However, it usually takes too many photos, and many of them are duplicated or dark. Therefore, we must introduce other technology to help learners find out important photos. Currently, we are using sensor data to help us do it. In the future, we also use images processing technology to detect the contents of photos. Besides, current algorithm and user interface also need improvement. In addition, we plan to conduct a full evaluation experiment and invite more students to use this system in the near future.

ACKNOWLEDGEMENT

This research work was supported by Japan Science and Technology Agency, PRESTO, and the Grant-in-Aid for Scientific Research No.21650225 from the Ministry of Education, Science, Sports, and Culture in Japan.

REFERENCES

Bush, V. 1945. As we may think. the atlantic monthly 176, 1, pp. 101–108. Hodges, S., Williams, L., Berry, E., et al. 2006. SenseCam: A retrospective memory aid. Proceedings of UbiComp, 2006,

pp.177-193. Mann, S. and Picard, R.W. 1995. On being’undigital’with digital cameras: Extending dynamic range by combining

differently exposed pictures. Proc. of IS&T, pp.442-448. Miller, G.A. and Gildea, P.M. 1987. How children learn words. Scientific American 257, 3, pp.94–99. Ogata, H. and Yano, Y. 2004. Context-aware support for computer-supported ubiquitous learning, Proc. of IEEE WMTE

2004, pp.27-34. Ogata, H., Matsuka, Y., El-Bishouty, M.M., and Yano, Y. 2007. LORAMS: Linking Physical Objects and Videos for

Ubiquitous Learning. Proceeding of ICCE 2007, pp.297-304. Ogata, H., Li, M., Hou, B., Uosaki, N., Moushir, M.E.-B., and Yano, Y. 2010a. SCROLL: Supporting to Share and Reuse

Ubiquitous Learning Log in the Context of Language Learning. Proc. of mLearn 2010, pp.40-47. Ogata, H., Li, M., Hou, B., Uosaki, N., Moushir, M.E.-B., and Yano, Y. 2010b. Ubiquitous Learning Log: What if we

can log our ubiquitous learning? Proc. of ICCE 2010, pp.360-367.


25

PRODUCING CONTENT SEMANTICS TO ENHANCE MOBILE LEARNERS BROWSING USABILITY

Glaroudis Dimitrios, Kotini Isabella and Manitsaris Athanasios Department of Applied Informatics,

University of Macedonia, Thessaloniki, Greece

ABSTRACT

Mobile devices are the current trend in present days. The objective of this work is to present and evaluate a methodology for producing content semantics from the learning material. The proposed approach results in recommending relevant links to the users’ interests and improving the mobile learners’ web experience.

KEYWORDS

Mobile browsing, ontology learning, recommendation systems.

1. INTRODUCTION

The evolution of Internet and multimedia services has led to interesting applications in education. Nevertheless, because of economic realities, educators are compelled to consider new delivery strategies and approaches to developing lifelong learners. Examining the way of use and the extensive popularity of mobile devices, it is easily understood why mobile learning is gaining growing attention by researchers and scientists. Mobile learning is defined in [1] as the learning process in which the user does not find itself in predetermined locality. It can be spontaneous, personal, informal, contextual, portable, ubiquitous, and pervasive (so integrated with daily activities that are hardly noticed). Along with these attributes, mobile learning has much in common with other types of e-learning on desktop computers, but with the advantages of more immediate interaction and smaller, often wireless devices. Moreover, mobile devices cover, and predispose for further growth, the need of training community for social interaction and safeguarding of individuality [2, 3]. The exchange of data and the collaboration with other students is straightforward, therefore learners can be grouped and socialize more easily. Generally, acting as learning tools, mobile devices can enhance the learner’s communication and cooperation skills, or increase their flexibility to perform in different working or learning environments.

Besides their important benefits, mobile appliances have restraints when they are used for learning purposes. Sharples [2] formulated them as: limited memory and storage capacity, small screens, lack of continuous Internet connection, significant browsing latency, and weakness to incorporate easily current learning services for desktop PC. These restraints have high impact on mobile users' browsing behavior. Studies have indicated that mobile Internet users suffer more severely from the problem of undesired outcomes than stationary Internet users do [4]. The limited screen size forces most mobile browsers to support a line-based navigation, with a few soft keys such as OK, Clear, and Next. In their design guidelines for small screen search engine interfaces, Jones et al. [5] clearly denote that screen size has a major impact on mobile users’ web experience, success rates drop and the time to complete successful searches increases when mobile users navigate to the majority of websites. Additionally, researches [4,5,6] for both desktop and mobile users show that page-to-page navigation is very costly when browsing in general, thus authors of [2,4,7] advise web developers to reduce the amount of page-to-page navigation and to provide a quick way for users to navigate through conventional or small screen web pages.

Furthermore, learners and Internet users generally, often cope with difficulties such as distraction, lost-in-space syndrome and cognitive overhead, when trying to acquire and access learning material. By knowing how learners choose their navigation paths and the way that the learning content is organized, recommendation

ISBN: 978-972-8939-66-3 © 2012 IADIS

26

systems can be modeled and partially automate and predict learners’ steps, thus improving learning material discovery and simplifying management. Although there are different views on which features are relevant to Knowledge discovery by learners, the majority of researches [7, 8, 9] show that learners are highly goal-driven when they search information on educational sites. Thus, it is essential to improve browsing usability for learners with less effort and frustration, and, more important, by saving browsing time. Enhanced management and browsing usability could be extremely useful for mobile web visitors, who browse content from cell phones or wireless PDA.

Taking into account the above issues, this work aims to address the problem of how mobile learners can be efficiently supported by an educational platform in order to overcome browsing limitations. Working this direction, it is proposed a new methodology that aims to reduce mobile users’ effort when navigating to the educational portal, by recommending semantically related educational content to their interests and drive them to their desired knowledge. The rest of this paper is organized as follows: In Section 2 an overview of the research efforts in the area of mobile browsing and web personalization is given. The main steps of the methodology and the particular methods and techniques are presented in Section 3. The experimental results and metrics of the proposed approach are presented in Section 4, and conclusions are presented in Section 5.

2. RELATED WORK

Lately, many research efforts concentrate on mobile browsing usability. Current browsing methods for mobile devices can be classified into three main categories [10]: presentation optimization, semantic conversion, and scalable (zooming) methods. Chen and Mohapatra proposed the method of scalable browser [10] as a new way to design personal digital assistant (PDA) interfaces. However, the claim of authors that the proposed method is better over other prevailing methods, such as presentation optimization and semantic conversion, is not supported adequately with relevant experimental evidence. Buyukkokten et al. [11] present important ideas for extracting semantics from the Web text yet greatly shortening the length of text. Each text page is intended to be broken into a number of text units that can be hidden, partially displayed, fully visible, or summarized. Additional research has been conducted on content hierarchy and Hierarchical Atomic Navigation has been proposed as a new philosophy to improve Web navigation on small displays [12]. The idea is to divide an original page into zones and make the navigator page a reduced overview of the original page. Introducing an approach on the personalization-based optimization of Web interfaces for mobile devices, Hinz et al. [13] uses the ideas of structure adaptation and content adaptation to realize adaptive intelligent user interfaces.

Mobasher et al. [14] proposed content characteristics and navigation data to be integrated into a Web mining framework and used by machine recommendations uniformly for more effective personalization. Eirinaki et al [15] worked on a different approach using the same basic logic. They proposed a system that uses log files and content semantics of a website in order to enhance personalization process. They introduce C-logs, an extended form of Web usage logs that encapsulates knowledge derived from the link semantics and used as input to the Web usage mining process, resulting in a set of recommendations. Finally, many researchers in e-learning advocate the use of ontologies to produce metadata information for learning objects [16], but only a few have considered applying ontology learning techniques to education [17].

3. PROPOSED METHODOLOGY

Apart from the fact that content’s semantic conversion and personalization strategy is proposed in our approach, as happens in some of the aforementioned works, a definition of the recommendation factors and a measurement of their quality is also defined. The innovative contribution of this work lies in producing ontology concepts from the learning data and rating their relevance to the educational content. After tracking mobile users’ preferences from log records during past visits to the portal, an online system recommends a set of links to portal’s web pages with similar conceptual content. The proposed methodology is detailed described in [26, 27]. The knowledge system’s architecture is divided in four main phases: mobile user identification, educational content mining, knowledge system development and link suggestion, which are presented in Figure 1 and further discussed in the following subsections.


27

Figure 1. System architecture

3.1 Mobile User Identification

Users’ navigational/usage data is logged in the web server that supports the portal and reveals the web pages that every user visits while browsing. Although accessing the usage data can be easy, the extraction of the actual browsing path in the form of structured information is a complicated and difficult process. Initially, data filtering techniques have to be applied. The Web server log file stores all the requests and replies between servers and clients. The prime concern is to track only the so called useful data which are concerned with the actual web links of the pages that are being accessed, the IP addresses, the clients’ web browsers and the request times. Using a Java NetBeans environment that runs in the application server and the Microsoft’s open source Log Parser [18], the server log file is processed and data filtering is initially performed running suitable queries. After the initial data is filtered, the mobile user’s identification is established. In our approach, each mobile user is defined as a registered user, by user name and password, and by the mobile browser he uses. We take into account only mobile users in order to significantly improve the speed and reliability of the developed system. The second step involves the identification of mobile learners’ navigational patterns. This process is also established in the application server. Each user’s filtered data are analyzed and a session identification technique is used so as to reveal the user’s navigational pattern. A user session is considered to be a sequence of requests coming from the same user and divided by a predefined period of time (timeout). Finally, each user’s data, serving as the user’s profile, are aggregated in order to form a knowledge base. These data are stored in the database server to be used in the following phases.

3.2 Educational Content Mining

Prior to applying semantic conversion techniques, the preprocessing of the educational portal is essential for properly formatting the educational portal. Java Net Beans environment combined with open source libraries runs in the application server to parse all the site’s pages. Only the educational content of the learning portal is captured and copied in the database server, resulting in faster and easier content processing. Moreover, if further content is to be added, only the additional data will be processed. Then, knowledge mining techniques are applied. Knowledge mining uses various recovery information methods (text mining, link mining, screen data selection or removal [19] without preserving the original web page structure. As there are many open source tools for ontology creation that work more easily and efficiently with text files, text mining for knowledge extraction has been chosen. Using proper Java classes, only the text information from each web page is extracted and the final information is formatted as a text string. Eventually, every page is represented by an extracted text record, stored in the database server.

ISBN: 978-972-8939-66-3 © 2012 IADIS

28

3.3 Knowledge System Development

The development of the Knowledge system is based on semantic, conceptual analysis of the learning material. For this purpose, an ontology which defines and models the concepts of the educational portal should be developed. According to Gruber, ontology is “an explicit specification of a conceptualization” [20]. Ontology learning techniques use machine learning and natural language processing to extract concepts and build relationships from existing data. Text2Onto [21], is one of the available ontology learning tools, it is open-source and targets data-driven change discovery using an incremental ontology learning strategy from text. The tool can import documents in the usual teaching formats — PDF, HTML and plain text — and export its results in OWL, an ontology description format.

The extracted text data from the database server is set as input to Text2Onto, which performs automatic text analysis via open source language technology tools for concepts definition. Specifically, the tool uses GATE [22], which is a general architecture for knowledge mining that supports many languages. Combined with open source lexicon databases, this architecture performs linguistic and syntax analysis of the text documents. The extracted data is separated via grammatical and syntactical rules and then is annotated and tagged using XML. As a result, a semantic correlation between the content information is produced, which leads to the definition of concepts. Text2Onto can extract not only concepts, but also relations between these concepts, such as subclass-of, part-of, instance-of, equivalence, using machine learning algorithms. These relations are grouped into ontology classes resulting in the semantic enrichment of the learning content. This approach has the additional advantage that feedback information between the knowledge system and the process of concepts definition can be provided. Text2Onto stores indicators for each concept in the ontology’s model, revealing the data source from which they were extracted. When changes occur in the text of a particular web page, the system can discover these changes and redefine the concepts or create new ones, without reprocessing all the pages. Then, the ontology can easily be updated, leading to increased efficiency of the overall system. After the learning content has been semantically modeled, the knowledge system records in owl ontology file the semantic data that every page in the portal contains and their correlations. When a mobile user visits a portal’s page, the knowledge system knows which concepts are included in every page, since Text2Onto stores indicators about each extracted concept, and how these concepts are related to other ones. As a result, there are defined and specific recommendation factors in order for the knowledge system to suggest relevant links for the mobile user.

3.4 Link Suggestion to Mobile User

The pages suggested by the system may not be directly connected to those the user has visited. In this case the result is even more comprehensive and more useful for the user. Then, it is critical to present the outcome of the knowledge system, taking into account the limited screen size of mobile devices. Using the basic principles of human computer interaction, a usable mobile application has been designed, which presents the suggested links and guide the mobile learner to them with just one click.

4. EXPERIMENTAL RESULTS & DISCUSSION

In this section our experimental findings are presented, along with comments about the efficiency and applicability of our methodology. For the purposes of our experiments, teaching materials (html files, documents and presentations in pdf format) from four typical courses in a computer science department were used. The titles of the courses are: HTML Programming, PHP Programming, Speech Processing and Image Processing. For each one of the above courses, a selected set of teaching material was used in order to reduce the mining processing time. Each course is consisted of five lectures. The material of the programming courses includes many mathematical expressions, symbols, algorithmic and code examples, while the material of the other two courses contains a lot of verbal and lexical information, definitions and examples.

The goal of our experiments was to answer the following questions: What kind of input files (html, text, slides) match better to content mining processing? Does Text2Onto extract a sufficient number of concepts from the learning material? Does the course type affect the number of extracted concepts? What percentage of the extracted concepts is actually meaningful? To answer these questions, we performed two sets of


29

experiments. The goal of the first set (section 1) is firstly to examine the number of extracted concepts per corpus type (html, text, slides) for each course and secondly the way that the course type affects the number of extracted concepts. The second set of experiments (section 2) aims to verifying the results of Text2Onto against a concept relativity rating, provided by the instructors of the courses. Additionally, it is examined which confidence threshold in Text2Onto should be used in order to define a sufficient number of concepts for all course types.

4.1 Concepts Definition from Learning Material

The results of the first set of experiments are presented in Figure 1. For all courses, the number of concepts extracted from slides is significantly less than those extracted from html and pdf material. Particularly, for the Speech Processing course, 340 concepts are extracted from the html input files (HTML corpus), 255 concepts from pdf files (PDF corpus) and only 75 concepts from the ppt files (PPT corpus). These results can be explained by the fact that slides generally present material in a condensed form, avoiding verbose explanations and full sentences. In slides mainly headlines are used and text is reduced, thus Text2Onto cannot define many concepts using its grammatical & syntactical rules and its machine learning algorithms. Additionally, the number of extracted concepts from simple pdf files is lower than from html extracts. This can be traced back not only to the authors’ different writing styles but also to differing purposes: in html links the learning information is rich, more structured and usually acts as a self-contained tutorial involving thorough explanations and examples. A recommendation could then be to use html extracts, especially if a more detailed domain description is needed.

Furthermore, from Figure 2 it is derived that the number of extracted concepts for the programming courses is significantly less than the number of extracted concepts for the processing courses, for all kind of input files. As mentioned before, the programming courses contain many symbols, algorithmic and code examples, while the other two courses include lots of definitions and examples. The results of the ontology learning tool depend on the amount of structured text that the input files include. When many mathematical or symbolic expressions exist in the corpus, Text2Onto’s algorithms can not perform well and produce a small number of concepts.

0

50

100

150

200

250

300

350

400

Speech Processing Image Processing HTML Programming PHP Programming

Ext

ract

ed C

once

pts

HTML corpus

PDF corpus

PPT Corpus

Figure 2. Number of concepts per corpus type

4.2 Concepts Relativity & Confidence Threshold Proposal

In the second set of experiments, it is examined the number of extracted concepts according to their relevance rating. Generally, the number of extracted concepts by Text2Onto is high and thus the tool provides a relevance rating, called confidence threshold. When processing the educational material, Text2Onto sorts the extracted concepts by a relevance value. By increasing the threshold, concepts with low relevance are removed. In addition, when the confidence threshold is high, the concepts have strong correlation with the input corpus. Experiments have been conducted with various threshold values, ranging from 0 to 1, to discover which value seems to better serve the filtering of insignificant (very low relevance) concepts. The experiments

ISBN: 978-972-8939-66-3 © 2012 IADIS

30

in all courses indicate that as the threshold value increases, the number of concepts decreases. The developers of Text2Onto do not propose a specific threshold value for filtering irrelevant concepts [26], as this value is highly depended on the quality, the type and the number of the input files. For that reason, we added a second relativity criterion; the percentage of the extracted concepts that are meaningful. In our experiments, we asked the instructors of the courses to evaluate the extracted concepts and characterize them as relevant or irrelevant to the particular corpus. This procedure has been followed for all the courses.

Table I provides a comparative presentation of the extracted concepts, the concepts found relevant by the instructors and the instructor’s relativity percentage for the Speech Processing course, using various thresholds and the html corpus. The results are similar in the other courses as well and reveal that a satisfactory number of the extracted concepts correspond to the actual learning data. Additionally, it is derived that as the threshold value increases, the extracted and the relevant concepts decreases, but the instructor relativity percentage increases. Filtering with high threshold values seems to retain few, but important to the learning process concepts.

Table 1. Concepts relativity

Speech Processing HTML corpus Confidence Threshold Extracted Concepts Relevant Concepts % Instructor Relativity 0 340 92 27,06 0.1 92 27 29,35 0.2 49 20 40,82 0.3 35 15 42,86 0.4 23 11 47,83 0.5 11 7 63,64 0.6 6 5 83,33 0.6 5 4 80 0.8 4 4 100 0.9 2 2 100 1.0 0 0 ---

A second task in this experimental set is to propose a confidence threshold for concept definition, suitable for all course types. Previously, it is noticed that the number of extracted concepts for the programming courses is significantly low. When increasing the confidence threshold for these courses, the defined concepts would be minimized. So, in order to have enough relevant concepts, a low threshold value should be chosen. For the above reasons, it is examined which threshold value provides enough concepts and high relevance rating as well. Figure 3 presents the number of extracted concepts and the instructors’ relativity percentage per threshold values for the Signal Processing and HTML Programming courses. By examining the graphs, we can see that for both courses the Extracted concepts & % Relativity lines merge to the threshold value of 0.2. This value corresponds to a good relativity percentage (30-50 %) and a satisfactory number of extracted concepts (over 15) in both cases. Same tests have been conducted for the other two courses and similar results arise. Since the taught courses in a computer science department usually include many programming related lectures, it is proposed to use the threshold value of 0.2 for the ontology production model.

0

50

100

150

200

250

300

350

0 0.1 0.2 0.3 0.4 0.5 0.6 0.6 0.8 0.9 1.0

Confidence Threshold

Ext

ract

ed c

on

cep

ts &

% R

elat

ivit

y

Signal Processing Extracted Concepts

Signal Processing % Relativity

HTML Programming Extracted Concepts

HTML Programming % Relativity

Figure 3. Concepts & Relativity variance per threshold


31

4.3 Experimental Paradigm of System’s Recommendations

The above learning material was processed by Text2Onto using an html corpus and a confidence threshold of 0.2, resulting in an OWL file that contains the extracted concepts and their estimated relevance. The resulting ontology consists of over 200 concepts-classes, with numerous subclasses and super classes. Figure 4 provides a part of the derived ontology graph, which presents the concept recognition and its subclasses (speaker, pattern, voice, speech recognition and recognition system).

Figure 4. Ontology Graph of class recognition

The issue is to check if or how a concept is correlated with other concepts in the ontology file. This can be achieved by using a reasoner. In our experiments, we used a Pellet reasoner [28] and sparql queries [29] to check possible relations between concepts. Based on the class recognition (the corresponding ontology graph is presented in Figure 4), the execution of sparql queries results in revealing the fact that concepts speech & recognition are related (super classes of concept speech recognition), concept recognition has five concepts as subclasses (previously mentioned) and concepts system & recognition have concept recognition system as sub concept (subclass). For all the concepts in the ontology, such queries are executed and concepts correlations are derived.

As a paradigm, a mobile user logs in the educational portal using an HP iPAQ 110 Classic Handheld and an Opera mini browser for navigation purposes. The learner wishes to access the first lecture of the Speech Processing course. Without using the proposed knowledge system, the mobile user has to follow a four steps navigation path: Speech Processing→ Course Documents → Lectures → Lecture 1. Till user’s later registration in the portal, the system filters the portal’s log file and successfully identifies the mobile user and his navigation behavior in the portal’s pages. When the learner visits the portal again, the knowledge system defines the concepts included in the visited pages and the reasoner searches for relative semantic data in the pages of the portal. In the above ontology graph the concept Speech, found in the Lecture 1 link, is directly related as a subclass to concept Speech Recognition, found in the Lecture 3 link. The knowledge system in such a case recommends Lecture 3 link as a “relevant” link. The system provides the mobile user with the same web page as before (“My courses” web page), but now the page contains an additional click button, labeled “User Favorite Links” (Figure 5).

Figure 5. Mobile use: adapted web page

ISBN: 978-972-8939-66-3 © 2012 IADIS

32

System’s recommendations are provided when the mobile user clicks the “User Favorite Links” button. Then, a separate web page is displayed containing a list of suggested links. This page includes hyperlinks found relative by the knowledge system. Consequently, the learner is directed to desired learning material by selecting the appropriate link. As for the system’s efficiency, the number of browsing steps is decreased. Initially, the user had to follow a 4 steps navigation path for accessing the desired file (Lecture 1of Speech Processing) while in our approach the navigation path will be User Favorite Links→ Lecture 1 link, resulting in fewer browsing steps, enhanced usability and much less navigational effort.

5. CONCLUSION

In this paper a methodology for improving the mobile learners’ web experience is presented along with some of the experimental outcomes. Using web content semantics and user navigational information, our approach aims to provide usable browsing based on page recommendations that are consistent with preferred educational content. The innovation of this approach lies on the semantic enrichment of the learning material with ontology concepts and the measumerement of their quality. It is examined what kind of input files match better for concepts’ definition, whether a sufficient number of concepts is extracted by the proposed knowledge system, the way that the courses’ type affects the number of extracted concepts and the percentage of the extracted concepts that is actually meaningful. Furthermore, it is proposed a threshold value for concept definition, suitable for all course types. Contrary to studies mentioned in section II, the recommendation factors are clearly defined and their relativity to the learning material is studied. The proposed approach is based on open source Java classes and semantic tools and it is designed for educational portals that include mainly text information in their web pages. If text information is scarce, the semantic representation and concepts definition will suffer from confusions and the recommendation system is likely to be inaccurate.

Surely, there are several free or commercial content recommendation systems that make building and maintaining web sites faster and more convenient. Popular recommendation systems, like Drupal [23] and Plone [24], can support a wide variety of site structures, while site administrators can define properly detailed rules as to what content should be displayed to users. Especially, Drupal's taxonomy system enables developers to associate a node with one or many descriptive terms and to create a classification system for content. However, Drupal’s power (and other systems as well) comes with many complexities when used in an already developed web site. Although it can support a wide variety of site structures when used for site design from scratch, it is rather difficult to understand the structure and to configure node relationships built by other tools or different philosophy of design. In addition, Drupal’s administrative screens for configuring a site have a huge number of options- settings, making them harder to interpret [25].

Contrary to the above systems, our goal is neither to solely direct the mobile learner to the educational portal, nor to adapt the site’s structure. Our aim is to provide additional and specific information to the mobile learner, directly related to his educational interests. The mobile learner only has to visit the portal, while the toil of the site’s administrator remains insignificant. As the limited screen size forces mobile learners to a line-based navigation, the proposed solution allows navigating towards their interests with less effort, less frustration, and, more important, by saving browsing time. The results are promising, showing that the system provides semantically related links. Moreover, the proposed system seems able to be used as a semantic search engine, however with the appropriate adjustments. Still, further tests have to be conducted for evaluating user usability and overall browsing time when using the proposed architecture.

REFERENCES

O’Malley C et al, 2003. “Guidelines for Learning, Teaching and Tutoring in a Mobile Environment” MOBIlearn Project Deliverable D4.1

M. Sharples, 2000. "The Design of Personal Mobile Technologies for Lifelong Learning," Computers & Education, vol. 34, pp 177-193.

Klopfer E. et al, 2002. “Environmental Detectives: PDAs as a window into a virtual simulated world.” IEEE International Workshop on Wireless and Mobile Technologies in Education. Vaxjo, Sweden: IEEE Computer Society, 2002, pp 95-98.


33

Albers M. J, Kim L, 2000. “User Web browsing characteristics using palm handheld for Information Retrieval”, IEEE Technology & Teamwork, pp. 125-135.

Jones M et al, 1999. “Improving web interaction in small screen displays”, Proceedings of Web 8 conference, pp. 51-59, Toronto, Canada.

Dunlop M., Davidson N, 2000. "Visual information seeking on PDA top devices”, Proceedings of BCS HCI 2000, Sunderland, UK, Volume II, 2000, pp. 19-20, 2000

Nielsen, J., 2000. “Designing Web Usability: The Practice of Simplicity.” New Riders Publishing, Indianapolis, ISBN 1-56205-810-X.

Tombros A. et al, 2003. “Searchers' criteria for assessing web pages” Proc. of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 385-386. Toronto, Canada.

Barry C.L., Schamber L, 1998. “User's criteria for relevance evaluation: a cross-situational comparison", Information Processing and Management, Vol. 34 No.2-3, pp.219-36.

H.M. Chen and P. Mohapatra, 2003. “A Novel Navigation and Transmission Technique for Mobile Handheld Devices, Technical Report, CSE-2003-1, UCDAVIS.

O. Buyukkokten et al, 2001 “Text Summarization of Web Pages on Handheld Devices”, Proc. Workshop on Automatic Summarization, Pittsburgh, USA.

F.J. Gonzalez-Castano et al, 2002. “A New Transcoding Technique for PDA Browsers Based on Content Hierarchy, Proc. of the 4th International Symposium (Mobile HCI’2002), LNCS 2411, pp 69–80, Italy.

Hinz M et al, 2004. “Personalization-Based Optimization of Web Interfaces for Mobile Devices”, Proc. Mobile HCI’2004 – 6th International Symposium, pp 204–215, Glasgow, UK.

Mobasher, Bamshad et al, 2000. “Automatic personalization based on Web usage mining.” Communications of the ACM, 2000, Volume 43, Issue 8, pp 142 - 151.

Eirinaki M. et al, 2003. “SEWeP: using site semantics and a taxonomy to enhance the Web personalization process, Proc. of the ninth international conference on Knowledge discovery and data mining, (SIGKDD), ACM, pp 99-108.

E. Duval, W. Hodgins, 2003. “A LOM research agenda.” 12th International World Wide Web Conference, Budapest, Hungary.

P. Cimiano, “Ontology Learning and Population from Text -Algorithms, Evaluation and Applications”, Springer US, 2006.

Microsoft Log Parser, http://www.microsoft.com/download/en/details.aspx?displaylang=en&id=24659 Michalski R.S, Kaufman K.A., 1998. “Data Mining and Knowledge Discovery: A Review of Issues and a Multistrategy

Approach,” In Machine Learning and Data Mining: Methods and Applications, Michalski, R.S., Bratko, I. and Kubat, M. (eds.), London, John Wiley & Sons, pp. 71-112.

T. R. Gruber, 1993.”A translation approach to portable ontology specifications”, Knowledge Acquisition, 5(2):199-220. Text2Onto. http://ontoware.org/projects/text2onto/ Natural Language Processing Sheffield University, GATE Home, http://gate.ac.uk/. Drupal, http://drupal.org/ Plone CMS: Open Source Content Management, http://plone.org/ The Content Management Comparison, http://www.cmsmatrix.org Glaroudis D et al, 2010. “Providing Personalized Learning Content to Mobile Users”, IADIS International Conference

Mobile Learning 2010, Session SRP 20.3, pp 255-259, ISBN: 978-972-8924-99-7

Glaroudis D et al, 2010. “Improving browsing usability for mobile learners”, 6th IEEE International Workshop on Pervasive Learning (PerEL 2010), Session 1, 978-1-4244-5328-3/10/, Mannheim, Germany

Pellet: OWL 2 Reasoner for Java, http://clarkparsia.com/pellet SPARQL Query Language for RDF, http://www.w3.org/TR/rdf-sparql-query/

ISBN: 978-972-8939-66-3 © 2012 IADIS

34

A THEORETICAL GROUNDING OF LEARNING MATHEMATICS IN AUTHENTIC REAL-WORLD

CONTEXTS SUPPORTED BY MOBILE TECHNOLOGY

Jalal Nouri Department of Computer and Systems Sciences

Stockholm University

ABSTRACT

The problems associated with de-contextualized learning are prominently accentuated in abstract and strongly formalized educational subjects such as mathematics. As means to overcome these problems, the research domain of mathematics education has repeatedly called for situated, embodied and multimodal ways of learning. Interestingly, with the emergence of mobile learning, and through the affordances of mobile technology, opportunities are offered to extend the education of mathematics to authentic contexts for these kinds of learning practices. In this paper we give an account of theories on situated learning/cognition, multimodality, and embodied learning, and present four empirical studies on mobile mathematical learning characterized according to these theories. The paper contributes with a theoretical grounding for mobile mathematical learning.

KEYWORDS

Mobile learning, Mathematics, Situated learning, Embodied Learning, Multimodality

1. INTRODUCTION

Since the Industrial Age, and as a response to a need for mass-education, learning has to a high extent been considered to take place in traditional classroom environments of lectures and books. As a consequence of the mechanical spirit of the industrial era, learning traditions were developed describing knowledge not as something that can be constructed by learners in appropriate contexts, but rather as information that should be transferred from textbooks and teachers into the minds of learners (Figueiredo & Afonso, 2005).

As time has elapsed, many strong voices have emphasized the importance of natural contexts (Dewey, 1916; Lave & Wenger, 1991). In the beginning of the 20th century, one of the first authors warning about the de-contextualized nature of learning and challenging the assumption that the classroom is the optimal place for learning to occur was John Dewey (1916). He proposed the idea that "there is an intimate and necessary relation between the processes of actual experience and education" (p.20), advocating that meaningful learning should take place in the setting of real-world activities. Since then, several theories on learning and cognition have been introduced, such as for instance situated learning (Lave & Wenger, 1991) and situated cognition (Brown et al., 1989), which emphasize authentic problems and natural contexts as powerful learning resources for learners’ generalization process.

The problems associated with de-contextualized learning have though not disappeared and are prominently accentuated in abstract and strongly formalized educational subjects such as mathematics (Arcavi, 2002, Lehtinen & Hannula, 2006). Particularly in mathematics education, it has been highlighted that students have difficulties with transfer and often fail to learn the intended skills, which they could adequately apply in varying situations outside school (Lehtinen & Hannula, 2006; Lave & Wenger, 1991). Also, in respect to mathematics education, a vast amount of studies has shown that students perceive the subject to be too abstract and that there is still a gap to bridge between, on the one hand the mathematics learned in school and, on the other hand the mathematics required in the real world (Vershaffel et al., 1999). As means to overcome these problems, the research domain of mathematics education has repeatedly called for situated, embodied and multimodal ways of learning (Núñez et al., 1999; Nemirovsky, 2003). This paper


35

reports on the theories underlying the aforementioned ways of learning, namely situated learning and cognition, socio-semiotics, and embodied cognition. Through presenting four empirical examples, we also argue that the emergence of mobile learning, and the affordances of mobile technology, offers promising opportunities to extend the education of mathematics to authentic contexts for situated, multimodal and embodied learning. The contribution of the paper is a theoretical grounding for mobile mathematical learning.

The article is structured as follows. First the three theoretical traditions, situated learning/cognition, social-semiotics, and embodied cognition, are presented followed by their implications for mathematics education. We then give an account of the affordances of mobile technology, and end by presenting four empirical studies exploring the use of mobile technologies in the context of situated, multimodal, and embodied mathematical learning.

2. SITUATED LEARNING AND SITUATED COGNITION

While traditional schooling has been based upon the assumption that de-contextualized abstract concept can effortlessly be transferable to situations of use in the “real” world, research has repeatedly reported contradicting evidence. This is probably most evident in the domain of mathematics education, where students difficulties with transfer has been vastly documented, and where the context-bound nature of learning and cognition has been strongly emphasized (Vershaffel et al., 1999, Lehtinen & Hannula, 2006, Arcavi, 2002; Lave & Wenger, 1991). A natural implication of the studies conducted has been an increased relevance for contextualize learning, which has been most strongly advocated for by the theories of situated learning and situated cognition (Lave & Wenger, 1991, Brown et al., 1989).

Both these theories rest upon the idea that the problems of de-contextualized knowledge and the inability of students to generalize their learning, can be dealt with, with the notion of situating learning in contexts and in authentic activities (Lave & Wenger, 1991, Brown et al., 1989). What both Lave & Wenger (1991) and Brown et al. (1989) argues for is that meaningful learning will only take place if it is embedded in the physical and social context of its application. From their perspective, learning is a process of enculturation in which the opportunity to observe and to practice in situ allows the development of contextualized competencies incorporating the tools and forms of social interaction that are valued in a given cultural community. The proposed idea of Lave & Wenger (1991), which is based on anthropological case-studies of how learning takes place in informal work settings, is that learning involves a deepening participation, in a community of practice, and with a community of practitioners (e.g. scientists and mathematicians).

According to Wenger (1998) the community of practice is characterized by three elements: 1.) a mutual engagement of participants in a domain; 2.) a joint enterprise in which the participants share information, negotiate meaning, and jointly perform activities; and 3.) a shared repertoire with developed resources such as tools, words, symbols, gestures, etc. Learning from the perspective of situated learning, is thus, a matter of an increased participation in a community of practice, and a matter of, as a learner, going from a legitimate peripheral participation in a community of practice into a full participation (Lave & Wenger, 1991). In such a context, cognitive apprenticeship is viewed as the facilitating process supporting the transition from a legitimate peripheral participation into a full participation. Cognitive apprenticeship entails that the apprentices, or ‘newcomers’ in a community of practice, learn the methods and language from the masters in the community (the domain), through a combination of observation, scaffolding/coaching, and practice. This includes articulation of student strategies, shared reflection, and collaborative explorations (Collins, Brown, & Newman, 1989).

When Lave & Wenger (1991) speaks of context, they are to high extent referring to a social context that is defined in terms of participation in a social practice. In the proceeding section, focus will instead be on the role of the physical aspect of the context, and hence, on the physical affordances the context offer for learning in terms of multimodality and sensory-motor learning, viewed from the perspective of socio-semiotics and embodied cognition.

ISBN: 978-972-8939-66-3 © 2012 IADIS

36

3. SOCIAL-SEMIOTICS AND MULTIMODALITY

The term multimodality is used in different disciplines and from a variety of perspectives. In this paper we will elaborate on the notion of multimodality from two perspectives, namely from the point of view of communication and cognition. Viewed from the perspective of communication, and social-semiotics in particular, the key assumptions are, first, that learning and meaning-making is the same phenomena, and secondly, that meanings are made, distributed, interpreted, and remade, through many representational and communicational resources, i.e. with the use of semiotic resources (Kress, 2010). Examples of semiotic resources used in representation and communication, are writing, speech, image, sound, gesture, 3D objects, and so on.

These semiotic resources which are referred to as material and physical modes offer different meaning-potentials and different affordances for meaning-making (Kress, 2010). Thus, given the distinct affordances, and limitations, of different modes they can be used to do specific semiotic work. Kress (2010) argues that the modes configure the world differently, that they offer distinct ways of engaging with the world and distinctive potentials for representing the world, and can therefore be seen as ‘cultural technologies’ of transcription. Kress (2010) also emphasizes the role of the embodied experience in meaning-making, stating that “engagement with any sign, the materiality of modes – where sign and modes are understood broadly - interacts with the physiology of bodies” (p. 76), also arguing that the traditional analytical separation of mind and body should be reconsidered.

As time has lapsed, societies, and educational systems within them, have had, and still have, modal preferences which can change over time. Historically however, the written word has been the prevailing mode of most societies (Selander & Kress, 2010). In the educational systems, semiotic changes in textbooks in mathematics have only been observed recently for about seventy years, with a quite radical increase in numbers of images (Kress, 2010). Simultaneously, recent research is increasingly unveiling the semiotic learning and meaning-making potentials of other modes. For instance, Jewitt (2008) points at Kress and van Leeuwen’s (1996) work on images, van Leeuwen’s (1999) work on the materiality of the resources of sound, and Martinec’s (2000) work on movement and gesture.

4. EMBODIED COGNITION AND MULTIMODALITY

The increased interest in multimodality and social-semiotics in mathematics education research was to high extent influenced by the within the field widely recognized theory of embodied cognition (Arzarello, Robutti, & Bazzini, 2005). It’s widely argued that embodied cognition may provide a theoretical grounding for ‘realistic’ and contextualized mathematics (Nunes et al., 1999).

Embodied cognition is a movement in cognitive science that hold that human cognition is bodily-grounded, that means, embodied within a shared biological and physical context (Lakoff and Núñez, 2000). While the traditional cognitivist models of human cognition separated the biological from the cultural, and presumed an objective and external reality, the embodied cognition movement, rather declared that reality is constructed by the observer (ibid.). Sensory-motor experiences together with culturally determined forms of sense-making (termed meaning-making in the socio-semiotic tradition), are thus, the central emphasis of this new stance.

In terms of concept development, the “embodied mind paradigm” strongly challenge previous positions postulating that all concepts are symbolic and abstract, unrelated to the body, and implemented outside the brain’s sensory-motor system (Gallese & Lakoff, 2005). Instead, it is argued from the perspective of embodied cognition, with support of experimental evidence from neuroscience and other disciplines, that formal abstract concepts, and particularly mathematical concepts, are rooted in concrete sensory-motor experiences (Lakoff & Nùñez, 2000). Further, the perspective states that the multimodality of our cognitive performances should be considered, as conceptualization processes are inherently multimodal, that is, it uses many modalities together, such as sight, hearing, touch and motor actions (Gallese & Lakoff, 2005). As a consequence of the embodied cognition movement, multimodality has increasingly become a focus of attention within the research domain of mathematics education.

Multimodality viewed in terms of mathematics education has been elaborated upon both from the different but complementary perspectives of social-semiotics and embodied cognition, and in the unitary


37

frame of these (Arzarello, Robutti, & Bazzini, 2005). As a result, an increasing amount of studies, theoretical and empirical, are repeatedly stressing the role of multimodal and perceptuo/sensory–motor ways of learning as a mean to overcome the difficulties students face with traditional symbolic, abstract and monomodal mathematics education (Arzarello, Robutti, & Bazzini, 2005; Gallese & Lakoff, 2005; Nemirovsky, 2003). For instance, summarizing findings of a number of research studies on the role of multimodality and perceptuo/sensory-motor learning, Nemirovsky (2003) stated that “the understanding of a mathematical concept rather than having a definitional essence, spans diverse perceptuo-motor activities, which become more or less active depending of the context” (p.108). All this yielded findings together, pointing at the multimodal, contextual, and perceptuo-motor nature of learning mathematics, and showing that gestures, glances and visualizations of various kinds play an important role in the learning process, has given nurture to the statement that mathematics is a product of an embodied activity in the world we live (Arzarello, Robutti, & Bazzini, 2005; Lakoff & Nùñez, 2000).

5. IMPLICATIONS FOR MATHEMATICS EDUCATION

From the common perspective of the theories on situated learning and cognition, learning and transferable skills are achieved by realizing authentic learning practices that are close to real problems and contexts (Gessler, 2009). In other words, practices are considered authentic if they are similar in their dynamics and their use of the shared repertoire (i.e. tools, language, etc.) to those of professional communities of practitioners such as mathematicians or scientists. Secondly, in activities of this kind, the teacher acts as a master of a practice scaffolding the learners, and the learning activities are to high extent social and collaborative. This together constitutes a sharp contrast to traditional schooling in which students either is presented with de-contextualized concepts and problems from the teacher or the books, and in general undertakes activities that are unrelated to the kind performed by practitioners (Lave & Wenger, 1991; Collins et al., 1989).

The framework of embodied cognition on the other hand, strongly challenges traditional education which often emphasizes on transmission of content through formal language (Arzarello et al., 2005). Rather than helping students to memorize abstract definitions of mathematical ideas, Nunes et al. (1999) argue, that we should facilitate students sense-making by focusing on the experiences that provide the initial grounding for the mathematical abstractions. This, at times, can be found in concrete physical experiences, as in the case with the learning of early arithmetic, space and spatial relations, and motion (ibid).

While multimodality is an emphasized component within embodied cognition, it is even more so within the perspective of social-semiotics. In fact, the main implication for contemporary education coming from social-semiotics is a strongly emphasized role of multimodal learning and teaching, and a call for extending the means for meaning-making and communication (Selander & Kress, 2010; Jewitt, 2008). That also implicates acknowledging the possibility the classroom context does not have to be the optimal place for learning, and that other contexts may afford a richer set of semiotic resources for meaning-making.

When the current educational system, and mathematics education in particular, is viewed from a situated learning perspective, a mismatch is exposed between the educational practices of school, and the practices of the communities of practitioners of mathematics. The mismatch is, to high extent, rendered trough the employment of school practices that de-contextualize mathematics with the use of artificial problems in artificial contexts. In addition, the mismatch is, also, rendered through the different use of tools and resources, including the human body and other semiotic resources. While, for instance, practitioners of mathematics very often think, learn, and use mathematics both in embodied and multimodal ways, that is more than often not the case in the formal classroom (Kress, 2010). Thus, if we are to realize authentic learning practices, analogous to those of mathematicians and scientists, guided by the situated learning theory, there are even more reasons to consider the role of embodiment and meaning-making through more modalities than recognized within the educational system. If nothing else, there are also strong reasons to consider providing learning environments that connect to and utilize the multimodal literacy practices developed by students in their everyday life (Jewitt, 2008; Pachler et al., 2010).

ISBN: 978-972-8939-66-3 © 2012 IADIS

38

Table 1. Emphasized aspects of learning practices viewed from the perspective of situated learning/cognition, social-semiotics, and embodied cognition.

Traditional mathematics education Situated learning and cognition - Transmission of abstract de-contextualized concepts. - Learning activities that are unrelated to the kind performed by practitioners. - Context of learning is not of primer importance. - Textbook and teacher dependent. The teacher acts like a master of de-contextualized concepts. - Collaboration and multimodality less emphasized.

- Authentic collaborative learning practices close to real problems and contexts of professional practitioners. - The teacher acts as a master of a practice.

Social-semiotics - Learning and meaning-making happens through the use of many representational and communicational resources. - Meaning-making are embedded in both social and physical contexts.

Embodied cognition - Concrete physical and embodied experiences. - Perceptuo/sensory-motor: learning based on doing, touching, and seeing.

6. MOBILE LEARNING

The theories accounted for in this paper bring forward three compatible learning practices that can be characterized by the keywords situated, multimodal, and embodied (see Table 1). These practices are supported and requested within the research field of mathematics with the belief that they may be means to overcome the difficulties students face with the learning of mathematics. Interestingly, mobile technologies may be able to support the realization of meaningful situated, embodied, and multimodal mathematical learning practices in authentic contexts outside of the classroom.

What mobile learning brings to the overarching technology enhanced learning field, and what mobile technology enable through supporting mobility, is to a high extent, support for and enhancement of boundary- and context-crossing (Pachler et al., 2010). This enablement is a result of the convergence of functionalities from formerly separate digital devices into a single device, offering representational and communicational affordances, computational power, connectivity and information access, and different functionalities for content creation and data-gathering (Pachler et al., 2010, Kress, 2010) that can be utilized both to enrich and to derive benefit from in-context experiences.

With these affordances supporting observations, conversations, interactions and reflections within and across various contexts, mobile learning offer the opportunity to take learning into “the outside world. As such, mobile learning may be particularly suited for, facilitating and empowering, situated, multimodal and embodied mathematical learning practices.

When attempting to empirically confirm the potentials of mobile learning, this have to large extent been done through evaluations in the form of attitude surveys and interviews, with emphasis on either learner motivation or teacher acceptance towards the new learning innovation (Wingkvist & Ericsson, 2009; Sharples, 2009). What is even more alarming, is that examinations of practices in the mobile learning field have shown that a large portion of the pilot studies and trials have strongly been technology-driven with no explicit educational foundations (Hulme et al., 2011, Traxler & Kukulska-Hulme, 2005).

Despite this background, we acknowledge the conception that mobile learning may be able and most likely can support and enhance situated learning practices. In the following, four empirical studies are presented that, although lacking explicit pedagogical foundations, possesses characteristics of situated, multimodal and embodied ways of mathematical learning supported by mobile technologies.

6.1 MULLE

There are many authentic contexts outside of classrooms in which situated mathematical learning practices could be conducted, for instance, contexts that contain physical and concrete geometrical entities and real geometrical or spatial problems. Although these contexts were certainly available before the rise of mobile technology, they have been made more accessible through mobile technology in terms of the support provided for meaningful situated learning.

On the one hand, the affordances of mobile technology may be utilized to support mathematical problem solving in various ways. For instance, in the MULLE project (Nouri et al., 2011), affordance for gps-measurement was utilized to measure larger distances and larger areas. In that particular study, a set of


39

mobile learning activities was designed aiming at providing primary school students the opportunity to collaboratively, embodied and situated, practice the area concept in outdoors settings on authentic problems.

On the other hand, mobile technology can also be utilized to support and scaffold general learning processes, such as collaborative learning processes by opening up communication channels, and individual scaffolding needs by providing task instructions, clues and feedback (Nouri et al., 2011). Such provision of scaffolding can be particularly beneficial in dynamical contexts outside of the classroom in which teacher accessibility can become an issue.

6.2 MobileMath

Mobile technology also brings forward opportunities to support more playful ways to learn, in form of situated, embodied, and multimodal game-based learning. The project MobileMath (Wijers et al., 2008) is an excellent example of that. The design of MobileMath was grounded on research delineating the characteristics of engaging games, and on principles derived from the theory of Realistic Mathematics Education (RME).

MobileMath is a geometric game offering lower secondary education students an opportunity to deepen their experimental knowledge of geometrical concepts such as angles, parallel and perpendicular related to quadrilateral shapes. It do this through a game-based learning scenario that involves both authentic contexts and realistic problems, along with a mixed reality environment in which the students can create mathematical shapes by interacting with the real world.

As such, MobileMath constitutes an illustrative example of how mobile technology may support engaging situated, embodied, and multimodal game-based mathematical learning. The coupling of game-based learning through mixed reality environments with situated, embodied, and multimodal learning, is undeniably interesting and may offer more fascinating promises for future work.

6.3 Go Math!

Go Math! (Alexander et al., 2010) is another interesting project that took advantage of opportunities for situated learning that may arise in informal settings by utilizing mobile technology. The Go Math project, which consisted of the two mobile applications Go Play Ball and Go Road Trip, supported collaborative activity and encouraged mathematical talk and activity among family members.

Go Play Ball exploited the fact that many sport interested families uses math both in keeping scores in games they are watching and playing themselves. The application offered opportunities for families to use ratios, percentages and graphical representations to enrich their enjoyment of baseball games and to help them track their own improvement. The mobile devices were used to calculate youngsters’ statistics after each game, such as their on-base percentage, and to create graphs to track progress over time for comparison.

As such, Go Play Ball is a good example of how mobile technologies can be utilized to support everyday mathematics in game-based form, and in particular ratios, percentages, and graphical representations.

Go Road Trip on the other hand provided an infrastructure for mathematizing everyday family car activities, such as guessing the time of arrival at a destination and maintaining records of family road trip activities. The mobile application included nine different math games and was designed to promote math awareness and fun with math during long road trips. For instance, one of the games included was an estimation game that involved multiple family members in estimating time and distance problems related to the car trip. The game also included tools to record data about different routes between common destinations offering opportunities to plot the time data collected to help the families to estimate and decide the best route.

Go Road Trip constitutes another illustrative example of the situated use of mobile devices in everyday activities for solving authentic problems involving concepts such as time, distance, estimations and plotting.

6.4 mVisible

For some decades now a growing call has been demonstrated for inquiry to play an important role in science education in order to involve students in learning about science and the nature of science. mVisible was a research project where groups of primary school students used smartphones and pads outside the classroom to explore a natural phenomena guided by an inquiry-based learning approach (Eliasson et al., 2011).

ISBN: 978-972-8939-66-3 © 2012 IADIS

40

In the mVisible project the students identified and learned the characteristics of species of plants and trees, and counted the number of trees for each species to learn what kind of forest is in the current nature square. Plants and trees were tagged with QR-codes, and when scanned with a mobile phone the code gave additional information on the characteristics of each species. A pie chart was later created on the pad providing a visual representation of the distribution of the different species. The data collected outdoors was later brought for further analysis in the classroom environment.

Thus, the interdisciplinary mVisible project capitalized on situated, multimodal and embodied approaches to learning, as the species were explored in natural habitats, and perceived with the body and through different modalities. In this particular context, mathematics was utilized as an analysis tool in the scientific inquiry-process focusing on concepts such as ratios and percentages, and on the in-situ creation and analysis of graphical representations such as pie charts. In other words, mathematics was used in a real world context to enrich the experience of a concrete natural phenomenon.

7. DISCUSSION

This paper presented a theoretical grounding of mobile mathematical learning in the theories of situated, embodied, and multimodal learning, which lately, repeatedly have been emphasized within the research domain of mathematics education. In that line of reasoning, it has been suggested that the issues of mathematics education, such as declining student performance scores, transfer problems, can be alleviated trough the adoption of practices derived from these theories (Vershaffel, 1999; Lave & Wenger, 1991). Four empirical studies was also presented demonstrating that different practices of this kind, situated, multimodal and embodied, in both formal and informal settings, can be supported and realized through the use of mobile technology. We thus argue that with the advent of mobile learning, the dependency to the classroom environment and the de-contextualized mathematics does not have to continue to be a fixed given. We also argue that we can bring students outside of the classroom environment for meaningful multimodal and physical learning on authentic problems in real-world contexts.

However, in the end, the realization of the potentials of mobile learning are dependent on, and can be fairly evaluated only when, the conditions for learning are truly considered and meaningfully designed for. Unfortunately, this has not always been the case in the field of mobile learning as the attempts to empirically confirm the potentials of mobile learning, to large extent have been done through evaluations in the form of attitude surveys and interviews, with emphasis on either learner motivation or teacher acceptance towards the new learning innovation (Wingkvist & Ericsson, 2009; Sharples, 2009). Thus, even though this paper acknowledges the conception that mobile learning may be able and most likely can support and enhance situated learning practices, it also calls for a critical and humble approach. There are many critical challenges in front of us to pursue for future work.

Firstly, investigations must be done exploring how mobile learning activities can be designed informed by the aforementioned learning theories. In other words, design frameworks and methodologies are needed for this aim. Secondly, we currently lack instantiations of evaluation methodologies that evaluate learning outcomes beyond in terms of motivation and affective aspects. For instance, including analytical tools for examining how the introduction of mobile technologies transforms mathematical learning practices, or analytical tools used to evaluate students multimodal productions and meaning making processes. If we are to open up possibilities for students to create and represent gained knowledge through other modalities than previously acknowledged within the school cultures, we also need to re-evaluate “the cultures of recognition” that are associated with assessment practices (Selander & Kress, 2010). Finally, there are still an unknown number of ways to support the learning of mathematics in situated, multimodal, and embodied ways using mobile technology. Hopefully, this paper provides a theoretical grounding, and enough empirical support, that inspire others to start exploring.

REFERENCES

Alexander, A., Blair, K., Goldman, S., Jimenez, O., Nakaue, M., Pea, R., Russel, A., (2010). Go Math! How Research Anchors New Mobile Learning Environments. WMUTE (2010), pp. 57-64.


41

Arcavi, A. (2002) ‘The everyday and the academic in mathematics’, in Brenner (eds) Everyday and academic mathematics in the classroom. VA, National Council of Teachers of Mathematics, pp. 12-29.

Arzarello, F., Robutti, O., & Bazzini, L. (2005). Acting is learning: focus on the construction of mathematical concepts. Cambridge Journal of Education, 35(1), 55–67.

Brown, A. L., Collins, A., & Duguid. (1989). Situated cognition and the culture of learning. Educational Res.18 (1989), 32-42.

Collins, A., Brown, J.S., & Newman, S. (1989). Cognitive apprenticeship: Teaching the craft of reading, writing, and mathematics. In L. B. Resnick (Ed.), Knowing, learning, and instruction. Hillsdale, Erlbaum.

Dewey, J. (1916). Democracy and Education. . New York: The Free Press. Eliasson, J., Knutsson, O., Nouri, J., Ramberg, R., Cerratto-Pargman, T., (2011), Evaluating Interaction with Mobile

Devices on a Field Trip. In processeding of WMUTE 2012. Figueiredo, A. D. & Afonso, A. P. (2005). Context and Learning: A Philosophical Framework. In Figueiredo & Afonso

(eds.). Managing Learning in Virtual Settings: The Role of Context, Hershey, USA, pp. 1-22. Frohberg, D, Göth, C., & Schwabe, G. (2009). Mobile learning projects – a critical analysis of the state of the art.

Journal of Computer Assisted Learning, 25, 307–331. Gallese, V. & Lakoff, G. (2005). The brain’s concepts: The role of the sensory-motor system in conceptual knowledge.

Cognitive Neuropsychology. Gessler, M. (2009). Situated Learning and Cognitive Apprenticeship. Int. Education for the Changing World. Hulme, A., Sharples, M., Milrad, M., Arnedillo-Sánchez, I., & Vavoula, G. (2011). The Genesis and Development of

Mobile Learning in Europe. Parsons (Ed.), Combining E-Learning and M-Learning, 151-177 Jewitt, C. (2008). Multimodality and literacy in school classrooms. Research in Education, 32, 241–267. Kakihara, M., & Sørensen, C. (2002). Mobility: An Extended Perspective. 35th Hawaii Int.Conf. on System Sciences

(HICSS-35). IEEE, Big Island, Hawaii, 1756-1766. Kress, G & van Leeuwen, T. (1996). Reading Images: The Grammar of Visual Design. London: Routledge. Kress, G. (2010). Multimodality: A social semiotic approach to contemporary communication. Routledge. Lakoff, G. and R. E. Núñez, (2000). Where Mathematics Comes From. New York, NY: Basic Bookspp. Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. New York: Cambridge University

Press. Lehtinen, E. and Hannula, M. M. (2006). Attentional processes, abstraction and transfer in early mathematical

development. Verschaffel, (Eds.). Past, present and future trends. Elsevier, (pp. 39-54). Martinec, R. (2000). Types of Process in Action. Semiotica, 130, 3/4, 243-268. Nemirovsky, R. (2003). Three conjectures concerning the relationship between body activity and understanding

mathematics. In: N.A. Pateman (eds.), Proceedings of PME 27, 1, 103-135. Nouri, J., Cerratto-Pargman, T., Eliasson, J., Ramberg, R. (2011). Exploring the challenges of supporting effective

collaborative mobile learning. Jour. of Mobile and Blended Learning, 3(4) pp. 54-69, IGI Global. Núñez, R., Edwards, L. and Matos, J.F. (1999). ‘Embodied cognition as grounding for situatedness and context in

mathematics education’, Educational Studies in Mathematics. 39(1–3), 45–65. Pachler, N., Bachmair, B., & Cook, J. (2010). Mobile learning: Structures, agency, practices. Springer. Selander, S., & Kress, G. R. (2010). Design för lärande : ett multimodalt perspektiv. Stockholm: Norstedt. Sharples, M. (2009). Methods for Evaluating Mobile Learning. In G.N. Vavoula, N. Traxler, J. (2007). Defining, Discussing and Evaluating Mobile Learning: the moving finger writes and having writ.

Research in Open and Distance Learning, 8 (2). Traxler, J and Kukulska-Hulme, A. (2005). Evaluating Mobile Learning: Reflections on Current Practice. MLearn 2005,

25-28 October 2005, Cape Town, South Africa. Van Leeuwen, T. (1999) Speech, Sound, Music. London: Macmillan. Verschaffel, L , De Corte, E , Lasure, S , Van V Griet , (1999) 'Learning to Solve Mathematical Application Problems: A

Design Experiment With Fifth Graders', Mathematical Thinking and Learning, 1: 3, 195 — 229 Wenger, E., (1998). Communities of Practice: Learning, Meaning, and Identity. Cambridge: Cambridge University Press. Wijers M., Jonker V., & Kerstens K. (2008). MobileMath: the Phone, the Game and the Math. Proc. from 2nd European

Conference on Game Based Learning, 507- 516. Wingkvist, A. & Ericsson, M. (2009). Thinking ahead in mobile learning projects : A survey on risk assessment. Proc. of

the 8th Int. Conf.on Perspectives on Business Information Research, 57-66.

ISBN: 978-972-8939-66-3 © 2012 IADIS

42

WHITE CANE DEVICE: A MOBILE ASSISTANT FOR VISUALLY CHALLENGED PEOPLE

Judie Attard, Matthew Montebello and Jeremy Debattista University of Malta

Msida, Malta

ABSTRACT

The goal of this study is to exploit the portability and availability of mobile phones to provide a means of guidance to the visually impaired while travelling. This system assists a visually impaired person while travelling through the city by implementing image recognition through a mobile phone and offering information of the immediate vicinity. The ‘White Cane Device’ being proposed enables the user to capture a picture, and receives back information about the surroundings. The White Cane Device was implemented in a client-server architecture, where the client acts as a peripheral device, and the server implements the SIFT feature extraction algorithm to perform object recognition. The GPS coordinates of the images are used to optimize the latter process. A thorough evaluation of the proposed system gave exciting results and showed that White Cane Device performs reliable matching even when images contain occlusion or are taken from various perspectives. The tested system returned results within more than acceptable time spans and received positive feedback from the usability evaluations held.

KEYWORDS

Visually impaired, image recognition, mobile accessibility.

1. INTRODUCTION

Visually challenged people have over the years adapted and managed to employ tools and techniques to lead as normal a life as possible. Even with the rise of computer use and the introduction of technology in every facet of our lives they still managed to acclimatise to novel technologies and unfriendly software systems to overcome their challenges. The imaging, processing and communication capabilities of mobile phones provide the device with exciting possibilities for new uses such as image processing and computer vision technologies. Being a portable hand-held device, a camera enabled mobile phone has some unique advantages. Mobile devices have penetrated the social market for a number of years and have become an indispensable tool for every person from young children to businessman in every strata and domain of society. The communication capabilities of mobile phones with fast Internet connections and GPS localization provide the perfect setting for the purpose and functionality requested by the system presented in this paper.

In the proposed system we consider the problem of identifying the content of an image. Consider a visually impaired person travelling through a city. Similar to a foreigner in a hostile place feeling lost and requiring guidance, the use of a mobile phone to provide such assistance is ideal. The system employs the device to take a picture of the surroundings and deploys an object recognition algorithm. Object recognition involves identifying an instance of a particular object in an image by comparing features (points of interest in an image) extracted from the query image and comparing them to a database of features. Such a database is built using a set of training images. The primary aim of this project is the development of a system which enables visually challenged persons to acquire the necessary guidance and assistance by capturing an image using a mobile phone equipped with a camera, and return any objects (mainly buildings) recognized in the snapshot, such as a specific pharmacy, the local police station, or even points of interest. Additionally, the GPS capability of the phone is exploited to enhance the object recognition process. This system assumes the availability of WIFI. Figure 1 shows an overview of the system.


43

The rest of the paper is organized as follows. In Section 2 we discuss particular requirements and design specifications of the system. We explore the implementation of the prototype in Section 3. In Section 4 we discuss the system evaluation and comment the results while in Section 5 we put forward our conclusions.

Figure 1. Overview of the system

2. SPECIFICATION AND DESIGN

The development of the system required various challenges to be overcome, such as the limited processing power of the mobile phone. A client-server architecture approach was adopted for this system for several reasons. The main reason is that feature extraction algorithms require large computational power. Also, the feature database would require a large amount of space, which is not so feasible on a mobile device. A disadvantage of using the client-server architecture is the requirement of a telecommunication means such as WIFI or 3G. Using a client-server architecture means the client can act as a periphery device, used only to acquire the image and send it over to the server. This would also encourage portability, as it would be much easier to create various mobile clients for different mobile operating systems. The systems developed in (Lim, et al., 2007), (Amlacher, et al., 2009) and (Ruf, et al., 2008) all use the client-server approach for mobile based object recognition. The main components of the White Cane Device System are three, namely the client, the server and the database.

2.1 Client Component Design

The client component is a mobile-based application which allows a user to take a picture of his/her surroundings and then send it over to the server component. When the user takes an image, the geo-tagging option should be enabled. Geo-tagged images would enable the optimization of the recognition process. The reliability of the matching process decreases as the number of features in the database increases (Lowe, 2004). As shown in (Amlacher, et al., 2009), the use of location priming (GPS coordinates) can substantially increase the recognition rate of an object recognition system. By using GPS coordinates, the search space can be reduced to features extracted from images taken within a specified radius from where the query image was taken. Keeping in mind the end users of the client component, the user interface of the mobile application is designed to be very simplistic, with as few operations as possible to capture an image. Also, the application implements voice prompts to guide the user as to what is expected from him/her.

2.2 Server Component Design

The server component is made up of two processes; the training process and the query process. Before a query is performed, the training process should be run at least once to populate the database, but it could be executed for as many times as desired.

ISBN: 978-972-8939-66-3 © 2012 IADIS

44

2.2.1 Training Process

The training process enables a user to select a number of images from the local machine with the purpose of populating the feature database with features which are then used by the query process for object recognition. For each image the training process extracts the features using a feature extraction algorithm, and the GPS tags. The feature descriptor is then serialized to the feature database, along with the GPS coordinates and the name of the image from which the feature was extracted.

2.2.2 Feature Extraction

Since the scope of this paper doesn’t allow for controlled lighting, scaling and rotation, the ideal approach for the feature extractor is feature-based. Feature-based algorithms are the most promising to achieve the desired objectives since they are the most robust regarding scale, lighting and changes in perspective, and their greatest benefit is the use of local features. The local feature approach, in contrast with the global feature approach, selects only distinctive features from the image in question. The global feature approach considers the image as one entity. In (Ruf, et al., 2008) both SIFT (Lowe, 2004) and SURF (Bay, et al., 2006) feature extraction algorithms were evaluated in a fully implemented prototype mobile-based system to find the best performing algorithm. The SIFT algorithm was also implemented in (Amlacher, et al., 2009).

2.2.3 Query Process

The query process is the crux of the system. This process receives a geo-tagged image. The GPS coordinates are extracted from the image, and the feature extraction algorithm is implemented. The GPS coordinates are then used to formulate a query to retrieve particular features from the feature database. The latter features should be from images taken within a particular radius from where the query image was taken.

2.2.4 Object Recognition

This process accepts the features extracted from the query image, along with the features loaded from the feature database according to the GPS coordinates of the query image. These features are used by the matching algorithm to find if the database contains an image depicting the same object as the query image. The name of the matching image, if any, is then returned to the client component, along with any other results and/or relevant data.

3. IMPLEMENTATION

3.1 Client Component

The client component, which is the component used by the visually impaired user, was implemented on an HTC Desire mobile phone, a GPS and camera enabled touchscreen smartphone. The client component is a mobile application which was developed using the Android version 2.2 API level 8. The most important thing we kept in mind for the implementation of the user interface is the end user, that is, the visually challenged person. Such a person can only navigate a touchscreen phone by using the TalkBack function, a screen reader which speaks out as the user navigates. The screen reader reads out menus, application names, and any actions taken by the user such as a click. The client component was implemented as a simple application which when run starts up the camera and prompts the user to take a picture; requiring only two key presses from the user to get a result. The TalkBack function was also implemented in the client component to provide prompts and guidance to the user.

The application has two main functions, namely taking a picture and sending it over to the web service. First the application checks the current state of the WIFI, and turns it on if it was not enabled. Once an image is captured, the GPS coordinates are extracted from the image EXIF tags, however if no GPS coordinates are available, null values are set. The image is then compressed into PNG format and converted into a byte array. The compressed image is sent to the server via SOAP. It is important to note that due to size restrictions on the data sent through SOAP, images are always taken to be the smallest resolution supported by the phone, which is 640x480px. The server’s response contains the location of the user, which is the location of the training image nearest to the location where the query image was taken; the recognized image, which


45

represents a match between the query image and a training image; and the approximate distance between the location of the latter images.

3.2 Server Component

The server component, implemented in the C#.NET 4.0 framework, is made up of two processes; namely the training process and the query process. This component was implemented in C#. OpenCV (http://opencv.willowgarage.com/wiki/), a library of programming functions for real time computer vision, was used in the implementation of the server component. EmguCV (http://www.emgu.com/wiki/index.php/Main_Page) was used as a cross platform .NET wrapper to OpenCV. The Microsoft.SqlServer.Types (http://msdn.microsoft.com/en-us/library/microsoft.sqlserver.types.aspx) library was used when spatial data types, such as geometric and geographic data types, were needed.

3.2.1 Training Process

The training process involves the populating of the feature database, which is then used for object recognition. This process can be run more than once, obviously to add new images. However, it has to be run at least once before the system can accept and execute a query successfully. The UI for the training process enables the user to select a number of training images from the local machine, as well as truncate the database. After selecting one or more training images, the following processes are triggered.

3.2.2 GPS Extraction

The GPS coordinates are extracted from each image in turn. To enable the building of a database containing only correct data, images without GPS coordinates are discarded.

3.2.3 Feature Extraction

The SIFT algorithm was chosen for the implementation of the feature extraction process. According to the extensive evaluation led by (Juan, et al., 2009) and (Mikolajczyk, et al., 2005), even though the selection of the ideal feature extraction algorithm depends on the problem at hand, the SIFT algorithm performs best overall. In (Mikolajczyk, et al., 2005), SIFT performed best in the evaluations of scale, blur (in a textured scene), JPEG compression, illumination, and in the matching example. In (Juan, et al., 2009), SIFT performed best in the evaluations of scale, rotation and blur (with a large radius). Sift gives the best trade-off between the performance on various image transformations. This gives the best overall feature extractor for the purpose of this implementation.

The SIFT method extracts distinctive invariant features from images which are then used to match different views of some object reliably. The latter features are scale and rotation invariant, and provide robust matching even with substantial noise addition, illumination differences and affine distortion. The features are also highly distinctive. A C# version of the SIFT algorithm, ported from a C++ version was implemented in this work (Downloaded from https://sites.google.com/site/btabibian/projects/3d-reconstruction/code on 22 February 2011). This implementation is very similar to the SIFT algorithm as described above, with the only difference that the scale space is computed in parallel. This modification, which allows faster implementation of the algorithm, was done based on the work by (Lin, et al., 2009) and (Bonato, et al., 2008). The SIFT algorithm implemented in this paper accepts a greyscale image and returns a list of Feature objects for each training image.

3.2.4 Saving to Database

Up to this point, the backend of the training process has extracted the GPS coordinates from a training image, and computed a list of features from the same image. The next step is to actually save the relevant data to database. For all training images selected by the user, the feature descriptor is extracted from each Feature object. This descriptor is then serialized to database along with the GPS data. This will result in the appending to the database a number of features derived from a single image, with different descriptors and identical GPS coordinates and image name.

ISBN: 978-972-8939-66-3 © 2012 IADIS

46

3.2.5 Query Process

The query process is started by a call from the client to the webservice, which acts as an interface to the server application. The webservice accepts a byte array representing the query image, and four strings representing GPS coordinates of the image at hand. The latter strings can be null values if the query image at hand did not have GPS coordinates. When the query process is complete, the webservice returns the results to the client.

The query process starts with the re-building of the image from the byte array. The resulting bitmap image is then transformed into greyscale and passed to the SIFT algorithm. Feature extraction is then computed. The descriptor of each feature is then used to build a matrix of float values (the dataset matrix). Consider the example of 2345 features which were extracted from the query image. The matrix in this case would consist of 2345 rows, one for each feature, and 128 columns, one for each value in the feature descriptor.

The next step is to extract relevant features from the feature database. This is done by calling a method and passing the query image GPS coordinates as well as a pre-set radius value as parameters. This radius value is used to define a specific area around the location the query image was taken. The features extracted from training images taken within this area are loaded from the database. This radius value makes the object recognition process more efficient and reliable (Lowe, 2004), compared to loading the entire database, and subsequently having to compare all the features. The features are loaded from the database by calling a stored procedure, which is described later on. For query images without GPS coordinates, all the features within the database are loaded.

3.2.6 Object Recognition

The system proposed by Lowe and Muja (Muja, et al., 2009) was used for the implementation of the object recognition process. Given a dataset and the desired degree of precision, the proposed system automatically determines the best nearest neighbor algorithm and the respective parameter values. According to experiments led by (Mikolajczyk, et al., 2005), nearest neighbor distance ratio matching approaches give the best performance when matching descriptors such as the SIFT descriptor. FLANN (http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN) is a library containing the mentioned system and a collection of algorithms which were found to work best in nearest neighbor search problems in high dimensional spaces. OpenCV provides an interface to the FLANN library, which we used through EMGU.

The object recognition process starts with the building of a kd-tree index using the dataset matrix. Next, the nearest neighbors for each feature extracted from the query image are computed using the index just created. This method thus populates two matrices, the Indices matrix and the SqDist matrix. These matrices indicate the first two nearest neighbors to each feature extracted from the query image, and their respective distances from the query feature in question.

The final and crucial step left is the computation of the results. The results in the final implementation contain the following three things:

� Location of user;

� Recognized image;

� Approximated distance. The recognized image result is computed by calculating the distance ratio between the first and the

second nearest neighbor for each feature of the query image, using the Indices and SqDist matrices. This is done as explained in (Lowe, 2004); features whose distance ratio (distance of first nearest neighbor / distance of second nearest neighbor) is larger than 0.8 are discarded. This “eliminates 90% of the false matches while discarding less than 5% of the correct matches” (Lowe, 2004). This measure performs well as correct matches require having a nearest neighbor significantly closer than the closest incorrect match for reliable matching. False matches, on the other hand, will likely have a number of other false matches within similar distances due to the high dimensionality of feature space. The features which result in a ratio smaller than 0.8 are termed as matches.

With the use of hashtables and lists, the results are sorted twice; once according to the image with the highest amount of matched features, the second time according to the distance between the location of the query image and the location of the training image in question. The image which has the highest amount of matched features is the recognized image part of the results, while the image with the shortest distance value is the location of user. The distance value is of course the distance part of the results. It is important to note


47

that the recognized image and the approximated location might coincide. This occurs when the recognized image is also the training image nearest to the user’s location. Consider having two training images taken from different but near locations A and B. If a user takes a query image of B from A, then the result containing the matched image will contain B and the approximated location will contain A. If, on the other hand, the user takes an image of B, from very near B itself, both results will be B.

Upon completion of the computation of the results, the latter are returned to the client. Of course, one must note that having a query image without GPS coordinates, the distance between the query image and the training images cannot be computed. Therefore, this process is skipped, and only the recognized object within the query image is output as a result.

3.3 Database Component

The database component was implemented using Microsoft SQL Server 2008 R2. The feature database is populated by the features extracted from training images during the training process. As described earlier, both the query and the training processes interact with the database. The training process simply appends rows of data to the table. The query process, on the other hand, passes the GPS coordinates of the query image as a parameter to a stored procedure. The stored procedure is a query which enables the loading of features which were extracted from images taken within a particular radius from where the query image was taken, as explained earlier. The stored procedure calculates the distance between the query image GPS coordinates passed as a parameter and the respective GPS coordinates of the features by implementing the Haversine formula:

�� = ��2 − ��1

�� = �2 − �1

= sin� ��2 � + cos��1� ∗ cos��2� ∗ sin� ��2 �

� = 2 ∗ arcsin�min�1, �� !�

� = " ∗ �

Equation 1. The Haversine Formula. Equation from (Sinnott, 1984).

Where (lon1, lat1) and (lon2, lat2) are the coordinates (in radians) of the two points and R is the radius of the Earth (6371km - http://nssdc.gsfc.nasa.gov/planetary/factsheet/earthfact.html). The resulting distance d is in the metrics used for the Earth’s radius.

If the query image in question does not have any GPS coordinates, instead of calling the stored procedure, a simple query is executed which loads all features within the database.

4. EXPERIMENTS AND EVALUATION

A series of tests and experiments were run to determine any variations in the results when system variables are changed. Such tests also help us determine and quantify the contribution of various system features to the end result. It is important to note that this is not an evaluation of the SIFT feature extraction algorithm per se, since innumerable evaluations already exist in literature. Rather, this evaluation focuses on the implementation of the SIFT algorithm within the developed system in the context of an object recognition problem.

To enable easy experimentation a testing module was added to act as an interface to the query process described earlier, to replace the default webservice used by the client. This interface is a simple form which enables the user to select a number of query images at one go. The form also enables the user to modify the radius value. To aid the data gathering, required information obtained while computing the results are written to a text file.

Two datasets were used namely the TSG-40-HTC (http://dib.joanneum.at/cape/TSG-40/index.php?page=download) dataset and the UoM dataset (containing various images taken around the

ISBN: 978-972-8939-66-3 © 2012 IADIS

48

University of Malta and a number of other locations). Both datasets contain images taken from various perspectives, distances, illumination and weather conditions. All images are geo-tagged. A subset of the datasets was chosen as training images whilst the other images were used as query images. Recall vs 1-Precision graphs were used as evaluation metrics. For the experiments led assume that the same random sample of 20 JPEG images from the TSG-40-HTC dataset was used as test data unless otherwise specified, and that no training image was used as a query image. Also assume that the radius value is taken at 50m unless otherwise specified. One should note that this radius returns most of the training images from the TSG-40-HTC dataset. The time taken is measured from before the loading of the image, to the computation of the final result.

The various experiments shed light on the results achieved by changing properties within the SIFT algorithm. The system was tested using different values for the number of checks for the approximation of the nearest neighbor. The results confirmed that a higher number of checks results in higher precision and recall values. The timing results for the latter test were inconclusive. When query images do not have their matching training images, the training image most similar to the testing image is defined as the matching image, since the implementation of a threshold would not be effective. The exploiting of the GPS coordinates resulted in a great improvement on the time taken to compute the results; with SIFT+GPS taking nearly half the time taken by SIFT only. This optimization also enabled the user to be given more detailed results regarding his/her whereabouts. The PSIFT implementation resulted to be generally faster than the classic SIFT implementation. When tested with multiple training images, having more than one training image for a particular query image resulted in a smaller number of correct positive features, however the tests always returned the correct training image as the matching image. The use of datasets containing images taken from various perspectives also shows that White Cane Device is adequate for the proposed use, as reliable matching can be achieved even using images with quite a different perspective from the training image.

To evaluate the usefulness of the system, as well as its usability, a visually impaired user used White Cane Device within the University Campus. The user gave very good feedback regarding both evaluation criteria; he felt that such a system would be of great help to a disoriented visually impaired person, more so since it is quite fast in giving results. The user also found no difficulty at all in using the system as it is very simple to use.

5. CONCLUSIONS

Various state-of-the-art feature extraction algorithms were researched with the purpose of finding the best algorithm for this implementation. The evaluations of SIFT, SURF, PCA-SIFT and ASIFT algorithms were compared and SIFT resulted the algorithm best suited for the scope of this paper. The features extracted by SIFT are scale, rotation and blur invariant, while being robust to changes in illumination and affine transformations. Such features were ideal for our implementation since we required catering for images which were taken by visually challenged persons. The geo-tagging capability of mobile phones was exploited to enable optimization of the object recognition process.

The proposed system was modeled on a client-server environment, where the client is a mobile application enabling the user to take a picture and send it over to the server. The server, on the other hand, implements a webservice to act as an interface. This webservice accepts the picture taken by the user as well as the GPS coordinates. The server then performs object recognition on the picture and returns the results to the client.

According to the led user evaluation, White Cane Device resulted to be a very useful system capable of aiding visually impaired users by providing information about their current location. The led experiments and evaluations prove that White Cane Device is an effective solution which gives the correct matches for nearly all training images. Query images of a small resolution are correctly matched against a large database of features. The use of geo-tagged images enables the optimization of the object recognition process. Apart from considerably diminishing the time taken to compute the results, the GPS optimization also returns more correct results: less query images are matched incorrectly. Most importantly, a change in viewpoint did not result in any hindrance for the object recognition. Light occlusion was also not a concern. Apart from use by visually impaired persons, the proposed system could be useful also to persons suffering from dementia. Also, White Cane Device can be tweaked for the use in the tourist industry.


49

This study proved to be an amazing tool to assist visually challenged persons. By learning about their surroundings users can travel somewhat more independently, mostly so if help cannot be found. The application of image processing algorithms, in combination with other location-based information, provided an excellent basis to fruitfully train and employ an intelligent prototype system, thereby offering numerous future directions and additional research possibilities.

REFERENCES

Amlacher Katrin [et al.], 2009, Geo-contextual priors for attentive urban object recognition. pp. 1214-1219. Bay Herbert, Tuytelaars Tinne and Gool Luc Van, 2006, SURF: Speeded Up Robust Features . 9th European Conference

on Computer Vision.

Bonato V., Marques E. and Constantinides G. A., 2008, A Parallel Hardware Architecture for Scale and Rotation Invariant Feature Detection. Circuits and Systems for Video Technology, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 18, pp. 1703-1712.

Juan Luo and Gwon Oubong, 2009. A Comparison of SIFT, PCA-SIFT and SURF. International Journal of Image Processing (IJIP), Vol. 3, pp. 143-152.

Lim Joo-Hwee [et al.], 2007, Scene Recognition with Camera Phones for Tourist Information Access. Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007. Beijing, China, pp. 100-103.

Lin Dennis [et al.],2009. Parallelization of video processing: From programming models to applications. IEEE Signal Processing Magazine,Vol. 26, No.6, pp. 103-112.

Lowe David G., 2004. Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, Vol. 60, pp. 91-110.

Mikolajczyk Krystian and Schmid Cordelia, 2005. A performance evaluation of local descriptors. IEEE Transactions on Pattern Analysis & Machine Intelligence, Vol. 27, No. 10, pp. 1615-1630.

Muja Marius and Lowe David G., 2009, Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration. International Conference on Computer Vision Theory and Application. pp. 331-340.

Ruf Boris, Kokiopoulou Effrosyni and Detyniecki Marcin, 2008. Mobile museum guide based on fast SIFT recognition. 6th International Workshop on Adaptive Multimedia Retrieval.

Sinnott Roger W., 1984. Virtues of the Haversine. Sky Telesc.. Vol. 68, p. 159.

ISBN: 978-972-8939-66-3 © 2012 IADIS

50

DESIGN AND EVALUATION OF MOBILE LEARNING RESOURCES IN MATHEMATICS FOR PUBLIC

ELEMENTARY SCHOOLS IN MEXICO

V. Robledo-Rella1, G. Aguilar1, S. Shea1, R. Pérez-Novelo1, E. Ortega1, J.C. Olmedo1, J. Noguez1, E. Tamés1 and P. Toiminen2

1Tecnológico de Monterrey, Campus Ciudad de México, Calle del Puente 220, Ejidos de Huipulco, México, DF, 14376

2Aalto University, School of Engineering, P.O. Box 14100, 00076 Aalto, Finland

ABSTRACT

This paper presents part of a broader research project whose main objective is to increase the literacy learning outcomes in both Mathematics and Spanish for children studying in public elementary schools in Mexico City. The methodology used to design, implement and evaluate a number of mobile learning (mL) resources aimed for 5th grade in Mathematics is described. Results obtained from two elementary schools are presented. The study included six 5th grade groups with a total sample of N = 170 children, randomly divided into Experimental and Control Groups. The mL resources were uploaded to a server for storage and administration, and each child was given a unique login/password to have access to the mL resources and to interact with the system through individual mobile devices with 24/7 Internet access. The children in the Experimental Groups used the mL resources for three weeks, while the children in the Control Group worked with similar materials using traditional teaching methods. For each group, an integrated relative learning gain was calculated using a Pre-Test / Post-Test assessment tool. This tool allowed to measure the effectiveness of the mL resources with respect to increased comprehension for the topics treated, as well as the overall ability of the students for solving 5th grade math problems. In general, the Experimental Group attained an average learning gain 46% larger than the Control Group. Positive results were also achieved in the ENLACE 2011 Test from the Mexican Ministry of Education (SEP), where the students from both schools showed an average improvement of 12% compared to tests in 2010.

KEYWORDS

Mobile Learning resources, Evaluation, Learning Gains, Elementary School

1. INTRODUCTION

The use of mobile devices is changing the way we live and communicate to such an extent that we are barely able to imagine the dimensions of its impact. Most children now live in a fully digitalized world, surrounded by screens filled with attractive and interactive applications – they are the so-called net generation (Tapscott, 1998). The use of technology with educational purposes is becoming more common and important in major schools around the world, not only at college and university level (Chirino, et al. 2010; Robledo-Rella, et al. 2010, and 2011) but also for K-12 schools (Hagen, 2011).

A group of research-professors at the Tecnológico de Monterrey, Mexico City Campus, decided to lead an ambitious project aimed to improve the math learning outcomes in Mexican primary school children, using mobile devices with access to specific educational content designed for a mobile learning (mL) environment and housed on a server devoted to this end. The project was begun in January 2011 with two public primary schools in Mexico City. Both schools have been active participants in the Adopt a School Program initiated by the Tecnológico de Monterrey, Mexico City Campus. This program is designed to strengthen ties with the community and neighboring schools by offering capacity building, teaching assistance, and other small-scale interventions conducted in collaboration with the schools. The Ministry of Public Education evaluated both selected schools with high incidence of at risk children and with very low overall assessments in the national standardized testing. Given the initial results with the first two schools, the project is currently expanding to


51

include an estimated 2000 children in 10 other schools in the greater metropolitan area of Mexico City. The long-term goal of the project is to offer all the materials on a nationwide scale in order to achieve a positive impact on the OECD - Programme for International Student Assessment results, where Mexico has recently been ranked very poorly (PISA, 2011).

In order to implement the project, an international team was formed with different actors managing the different aspects and needs of the project:

a) Ympyra, a company from Finland, specialized in mobile platforms for basic learning, entered into a collaborative plan with the Tecnológico de Monterrey’s programs in mL based at the Mexico City Campus. Ympyra provided the server and built the platform onto which the core academic content was uploaded. Each child was given a login/password combination that allowed her or him to log into the Ympyra website, where all the mL resources were available. The students accessed this content through Internet enabled mobile devices. Ympyra also developed the software needed to present the academic content to the students and to administer and keep track of the individual usage and interaction with the different mL resources loaded in the system.

b) A multi-disciplinary group of research-professors from the Tecnológico de Monterrey, Mexico City Campus, worked in collaboration in the design and implementation of the project. Of fundamental importance were the following teams:

i) A project leader and project manager coordinated the logistic aspects of the project and solved practical issues involved in realizing it: Activities ranged from establishing the national and international partners in the project, to recruiting the personnel needed to work in the project, promoting and to solving legal and practical issues regarding the aforementioned primary schools, obtaining and distributing the mobile devices that were loaned free of charge to each child, and to make sure the Internet service was working properly; among many other matters.

ii) Specialists in social intervention and the uses of digital technology in education developed the conceptual and pedagogical backdrop from which the project was undertaken. The central idea behind the project is to create an environment wherein both social and educational transformations are made possible and likely for student participants.

iii) A pedagogical team provided the background, theoretical, and academic input needed to develop the mL resources for 5th grade Mathematics in accordance with the national primary level curriculum established by the Ministry of Public Education for Mexico.

iv) A team led by specialists in ethnographic research led a group of Tecnológico de Monterrey students trained in research methods to carry out a field study on the participant children population and their immediate families. Indicators in socio-economic status, ethnic origin, educational level of family members, use of technology by family members, as well as other relevant variables were gathered and analyzed, and are reported elsewhere (Ortega et al. 2012).

v) A team of research-professors with experience in the use of mL established a methodology to design, implement and evaluate the impact of the mL resources on the academic performance of the children as measured by controlled assessment tools.

c) The directors and teachers of the adopted schools were invited to participate as collaborators in, and not mere beneficiaries of the project. A team of 6 teachers, one for each of the six 5th grade primary school groups, was instrumental in the development of the resources, their use and testing, as well as scheduling and conducting the mL activities with the children.

d) Ympyra, in collaboration with Nokia Global, donated 200 mobile Internet-enabled devices to be given to all students and teachers participating in the project.

e) Through Telcel service provider, the largest cellular operator in Mexico, a unique data-only package was purchased in order to enable the mobile devices to have 24/7 Internet access during the application period of the project. One of the greatest challenges of the project was establishing reliable connectivity for such large groups of simultaneous users. In order to accommodate the demand, Telcel had to make local point antenna adjustments in order to increase the reception signal for the two aforementioned primary schools.

f) Finally, in order to facilitate the success of the project, a fast-track capacity building program was established for the directors and teachers of the primary schools involved. The main goals of this capacity building program were: i) to present the project to the teachers, ii) to build trust with the project team, iii) to allow the teachers and directors to discover for themselves the relevance and enormous potential of the

ISBN: 978-972-8939-66-3 © 2012 IADIS

52

project, and iv) to give a fast formal course so to update them regarding the current use of ICTs in education, with emphasis on mL techniques.

2. DESIGN OF MOBILE LEARNING RESOURCES

It was decided that the project should be started at the elementary level, specifically in the 5th grade. It was determined that it is 5th grade were children begin to integrate their critical academic knowledge, particularly in mathematics. Students of the 5th grade, between ages 10 to 11 have reached an appropriate developmental level from various perspectives. They are relatively more able to take on responsibility, and have the physical and mental skills needed to manage the basic features of a smart phone.

The first phase of the project started by defining the main 6 themes covered in 5th grade Mathematics according to Ministry of Public Education (Secretaría de Educación Pública; hereafter, SEP) official curricular programs. It was determined to begin with the issues that usually represent the greatest challenge for the students. The participating teachers were asked for their input on this point and, according to the assessment, 6 math topics were selected to be built as resources: Volume, Area, Perimeter, Fractions, Decimals, and Percentage, and be taught by using an mL methodology. Once it was determined which topics to use, the pedagogical team developed the initial “pedagogical resources” designed to briefly explain the main concepts and ideas for each of the selected themes. Each resource contained key elements displayed in a graphical and engaging manner so to explain to the children the definitions and main formulae to be used to solve the on-line exercises.

For each theme, another 10 mL “practice resources” were developed by a group of teachers from the Tecnológico de Monterrey, Mexico City Campus, with experience in the design, implementation and evaluation of mL resources. These “practice resources” were designed considering typical examples studied by the teachers in the classroom with the children, as well as a set of practice exercises generated with an Exam-Generator software provided by the directors of the selected primary schools. In addition, the exercises from previous ENLACE exams provided by the SEP were also considered. The ENLACE exams are uniform tests applied once a year by the SEP authorities to all public and private primary schools nationwide, and their goal is to evaluate and monitor the performance of the different schools in areas such as Mathematics, Spanish Language, History, and Geography, among others.

The “practice resources” consisted of Multiple Choice exercises with 4 options: the right answer and 3 distractors carefully designed, considering the most common mistakes made by the children. Each wrong answer provided feedback giving an encouraging message for the right answer, or pointing out the possible cause of the mistake. An additional button with “Hints” was created for each exercise containing a brief description of the solution procedure behind the exercise statement, using animated gif images, which turned out to be quite illustrative for the children. The exercise metadata included: i) name of the exercise, ii) associated theme and iii) level of difficulty, from 1 = Easy, 2 = Medium and 3 = Difficult. Each theme contained a fair distribution of exercises’ levels so as to be challenging for all children.

Ympyra also included a set of “dynamic exercises” based on simple algorithms that changed the values of the initial variables (within given limits) providing the children with different permutations of the same exercise.

3. IMPLEMENTATION AND ASSESMENT METHODOLOGY

The schedule for using the mL resources by the children in the 6 selected groups was set in collaboration with the involved teachers and directors from the two primary schools participating in the project. The mL resources were distributed for the 6 selected themes (Volume, Area, Perimeter, Fractions, Decimals, and Percentage) over the course of three weeks, and then included an additional three-week period for open use of the entire platform, to ensure that all kids used all mL theme resources within this whole time interval. The methodology for use and teaching of the mL resources was established along with the teachers and directors of the primary schools. For each theme, 5 “practice resources” were reviewed with the teacher during class hours in the classroom, while the remaining 5 “practice resources” were left as homework to be solved outside the classroom.


53

In order to evaluate the impact of the use of the mL resources on student performance, the student population was divided randomly into an Experimental Group, that had access to the mL resources within specific time intervals and a Control Group, which did not have access to the mL resources, for the corresponding time intervals.

The participating elementary schools and groups were as follow: Martín Torres Padilla School, classrooms 5A and 5B, hereafter MT5A and MT5B, and Teófilo Alvarez Borboa School, classrooms 5A, through 5D; henceforth TA5A, TA5B, TA5C, and TA5D. During a three-day time span, three groups were considered as Experimental Groups for the Volume theme, while the remaining three groups were considered as Control Groups. After these three days, the Experimental and Control Groups changed roles to study the Areas theme, repeating this methodology henceforward for the remaining 4 themes. This way, the research team was able to have three Experimental Groups and three Control Groups for all six themes considered during the implementation period. Ympyra’s platform administrator controlled the children access to the mL resources using their individual login credentials. Table 1 show the distribution of Experimental and Control Groups for the six topics considered.

The research team designed a written Pre-Test and Post-Test, being both very similar, consisting of 24 exercises each (4 exercises per theme). Both tests included items with three degrees of difficulty in order to cover a broad range of possible child performance. The Pre-Test and Post-Test exercises were similar to those contained in the “practice resources” mentioned above and to those of the ENLACE annual SEP exams. The Pre-Test was applied to the whole sample before any child had access to the mL resources in the Ympyra website. Then, the children were allowed to access the mL resources according to the Experimental and Control roles established in Table 1, for approximately three weeks. Each topic was worked for approximately three days. After the six themes’ implementation period was concluded, the Post-Test was applied to the whole student sample under similar conditions as for the Pre-Test. The two tests were applied in the morning during class hours, both had equal response sheets and the students of all 6 groups were allowed the same amount of time to solve the tests – approximately 1 hour.

Table 1. Distribution of Experimental (E) and Control (C) Groups for the six themes

Group/Theme Volume Area Perimeter Fractions Decimals Percentage MT5A E C E C E C MT5B C E C E C E TA5A E C E C E C TA5B C E C E C E TA5C E C E C E C TA5D C E C E C E

The Pre-Test was applied to the whole sample before any child had access to the mL resources in the Ympyra website. Then, the children were allowed to access the mL resources according to the Experimental and Control roles shown in Table 1, for approximately three weeks. Each topic was worked for approximately three days. After the implementation period was concluded, the Post-Test was applied to the whole student sample under similar conditions as for the Pre-Test. The two tests were applied in the morning during class hours, both had equal response sheets and the students of all 6 groups were allowed the same amount of time to solve the tests – approximately 1 hour.

4. RESULTS AND DISCUSSION

4.1 Learning Gains

The Pre-Test and Post-Test were graded as correct = 1 and incorrect = 0 scores for each of the 24 exercises in either test. The research team calculated the average Pre-Test <Pre> and average Post-Test <Post> scores for each primary group (MT5A, MT5B, TA5A, TA5B, TA5C and TA5D) and for each of the 6 topics (Volume, Area, Perimeter, Fractions, Decimals and Percentage). Following Hake (1988)’s methodology, we define an integrated relative learning gain for each group:

ISBN: 978-972-8939-66-3 © 2012 IADIS

54

100

Post PreG

Pre

−=

−

This integrated relative learning gain measures the overall group yield (Post – Pre) with respect to the maximum possible group yield (100 – Pre).

The results are summarized in Tables 2 and 3 below, where the student sample number and the average Pre-Test and Post-Test for the Experimental and Control Groups for all 6 discussed themes are shown (normalized to 100). Figure 1 shows the results in the “G vs. Pre-Test” plane where the Experimental Groups are shown with filled symbols and the Control Groups are shown with open symbols.

Table 2. Student sample number, Average Pre-Test, Average Post-Test, and Integrated Relative Learning Gain, G, for the Experimental and Control Groups, for the Volume, Area, Perimeter, Fraction, Decimals, and Percentage themes

Group N

Volume Experimental 86 26 ± 15 44 ± 19 0.25 Volume Control 84 25 ± 14 56 ± 21 0.41

Area Experimental 84 37 ± 17 45 ± 22 0.12 Area Control 86 29 ± 16 25 ± 16 -0.07

Perimeter Experimental 86 49 ± 20 57 ± 20 0.16 Perimeter Control 84 45 ± 19 62 ± 17 0.31

Fractions Experimental 84 27 ± 18 45 ± 18 0.25 Fractions Control 86 26 ± 18 29 ± 18 0.04

Decimals Experimental 86 39 ± 19 48 ± 19 0.14 Decimals Control 84 43 ± 19 47 ± 20 0.07

Percentage Experimental 84 36 ± 18 49 ± 18 0.21 Percentage Control 86 40 ± 18 42 ± 23 0.04

Table 3. Average Pre-Test, Average Post-Test, and Integrated Relative Learning Gain, G, for the Experimental and Control Groups for the six themes considered (Ntot = 170)

Group

Experimental 36 ± 18 48 ± 19 0.19 Control 35 ± 17 43 ± 19 0.13

From Tables 2 and 3 it can be seen that: a) The average Pre-Tests are about the same for all six themes, except for the Area theme, where we have a difference of 8 points. Besides the standard deviations quoted in the table, this tells us about the intrinsic experimental uncertainty within our results. However, note that the average Pre-Test for all six themes is the same for the Experimental and Control Groups, as expected (see Table 3). b) The average Post-Test for the Volume theme is larger by 12 points for the Control Group as compared with the Experimental Group. A similar trend is found for the Perimeter average Post-Test. These are unexpected results and Volume and Perimeter data are being re-analyzed so to better understand these results. However, the total average integrated learning gain for the Experimental Group is 46% larger for the Experimental Group than for the Control Group (Table 3).

Pre Pos G

Pre Pos G


55

Figure 1. Integrated relative learning gain G vs. Pre-Test for the Experimental Groups (filled symbols) and Control Groups (open symbols), for the 6 considered themes (Volume, Area, Perimeter, Fractions, Decimals, and Percentage)

4.2 ENLACE Exam Results

As mentioned above, the Ministry of Public Education of Mexico (SEP) applies once a year a nation-wide ENLACE exam for K12 children (ENLACE is the Spanish acronym of National Evaluation of Academic Performance in School Centers). At the end of the 3-week implementation period, all children were given access to all mL resources in the website. This was done to level usage of the mL resources among the children; and from an ethical point of view, to give them equal access and a fair opportunity to develop their academic knowledge and skills by using the service and resources. All the children in sample presented the ENLACE 2011 math exam after having access to the mL resources in the Ympyra website. Table 4 below, summarizes the average Pre-Test and average Post-Test sores for all six topics, the corresponding integrated relative gain, as well as the ENLACE 2010 and 2011 results for Mathematics (normalized to 100) for each of the 6 elementary school groups considered in this study (ENLACE Results, SEP).

As it can be seen from Table 4, both primary schools achieved an increment in the average Mathematics ENLACE results from 2010 to 2011. Teófilo Alvarez School had an average integrated learning gain G = 0.22 and achieved a 17% improvement in the ENLACE exam, while Martín Torres School had G = 0.17 but achieved only a 3% ENLACE exam improvement.

Table 4. Average Pre-test, Average Post-test, and Integrated Relative Learning Gain for the 6 considered themes and ENLACE 2010 and 2011 Mathematics results (normalized to 100) for the 6 elementary school groups

Group Teacher’s name

N Pre Pos G ENLACE 2010

ENLACE 2011

TA5A Gretel 25 33 ± 17 41 ± 19 0.13 63 61 TA5B Martha 28 31 ± 18 48 ± 21 0.33 59 71 TA5C Maribel 30 38 ± 18 45 ± 21 0.13 57 70 TA5D Norma 23 41 ± 18 54 ± 19 0.28 -- 76 Average TA 106 36 ± 18 47 ± 20 0.22 60 70 MT5A Alejandro 31 33 ± 18 36 ± 18 0.05 64 63 MT5B Miroslava 33 35 ± 16 50 ± 18 0.30 52 57 Average MT 64 34 ± 17 43 ± 18 0.17 58 60 Both schools 170 35 ± 17 46 ± 19 0.20 59 66

The research team also found a positive effect on the ENLACE Mathematics exams results from 2010 to 2011 regarding the percentage distribution of children in four performance ranges (Insufficient, Elemental,

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 10 20 30 40 50 60 70 80 90 100

G

<Pre-Test>

Integrated Learning Gains

Vol Exp

Vol Control

Are Exp

Are Control

Peri Exp

Peri Control

Fra Exp

Fra Control

Dec Exp

Dec Control

Perc Exp

Perc Control

ISBN: 978-972-8939-66-3 © 2012 IADIS

56

Good and Excellent). The results are summarized in Figure 2 below, where it can be seen that the percentage of “Insufficient” performance by individuals dropped considerably for both schools, while the percentage of “Good” and “Excellent” performance by individuals improved for Teófilo Alvarez School.

Figure 2. ENLACE 2010 and 2011 Mathematics percentage distribution results for Teófilo Alvarez School (left) and Martín Torres School (right) primary schools. Where, Insufficient = Students still need to acquire the knowledge and

develop the skills for this course. Elemental = Students require to strength most of the knowledge and develop skills for this course. Good = Children show an adequate level mastering the knowledge and possess the skills for this course.

Excellent = Children posses a high level mastering the knowledge and skills for the course.

5. CONCLUSIONS AND FUTURE WORK

This is a highly ambitious project and it has had very encouraging results so far. It is a project aimed to improve the learning outcomes in mathematics for Mexican children in public elementary schools. A set of mL resources were developed, storage on a server and made available for the children through the use of cloud technology. Student users had access to the mL resources via mobile devices provided by the project sponsors. The methodology developed enabled the research team to measure the impact that the use of these mL resources had on student’s learning gains and on student’s performance regarding their ability to solve math problems, appropriate to their grade based on SEP curriculum. It is found that the children in the Experimental Group got higher learning gains as compared with the Control Group. The nation-wide ENLACE 2011 exam’s results are also very encouraging since both participating primary schools improved considerably as compared to their ENLACE 2010 results. The overall methodology followed through this research project is supports the hypothesis that the sole inclusion of ICTs to support learning is not enough per se but that meaningful content and social participation processes must be included in the educational model (Kukulska-Hulme, 2010).

At present, the project is being expanded to include resources in Mathematics for 4th through 6th grades. Furthermore, the project has expanded already from 2 to 12 primary schools in the greater Metropolitan Area of Mexico City. By mid 2012, the project will expand its scope so to include also the development of Spanish language and writing skills for 4th through 6th grades.

As a future goal, we plan to extend the server interaction features to allow for delivering adaptive educational content based on the recorded student history interaction with the system, as well as to include other types of interactive mL resources (e.g. improved images and graphics, sound, video and simulations).

The obtained positive results are due in part to the novelty factor, since the children were very motivated to use the mobile device to access class content and to carry out their regular weekly assignments with the device. It is worth mentioning that although the project was initially planned to use mobile devices so to improve children math literacy, they actually expanded considerably the use given to the devices, from taking pictures and videos, downloading music, and sending SMS, to the use of Maps and to find information on the Internet, which improved considerably their other courses as well.


57

ACKNOWLEDGEMENT

We want to recognize all the teachers and directors from the two elementary schools involved in this first part of the project. Their participation and enthusiasm were essential to the development and application of this project. We recognize the support given by the Ympyra Company from Finland (including Daniel Cochran). The original Harppi-Tec research project was based on Aape Pohjavirta's conviction and initial idea to scientifically verify the effects of the next generation of mobile learning before creating widely deployed solutions for global markets. We also thank the donation of mobile devices by Nokia, the special device packages and help provided by Telcel and the seed funding given by Santander Bank to sponsor part of this project. We also acknowledge the School of Social Sciences and Humanities (including Ana Gabriela Arriaga from the Institute of Social and Sustainable Development – IDeSS), the School of Design, Engineering and Architecture, and the School of Humanities of High School Division of the Mexico City Campus to support the realization of this project.

REFERENCES

Chirino, V., Noguez, J., Neri, L., Robledo-Rella, V., & Aguilar, G., 2010 Mobile Science. Students’ Perception about the Use of Mobile Devices in Self-Managed Learning Activities and Learning Gains Related to Mobile Learning Resources. In m-Science, Sensing, Computing and Dissemination. Eds. E. Canessa & M. Zennaro, pp. 225-241.

ENLACE (Evaluación Nacional del Logro Académico en Centros Escolares), Secretaría de Educación Pública. ENLACE Results 2011, http:////www.enlace.sep.gob.mx. Consulted October 21, 2011

Hake R.R., 1988. Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. Am. J. Phys. 66, No. 1, pp. 64-74

Hagen, L. 2011, M-Ubuntu; A Case Study of Mobile Phone & Literacy Instruction in Two South African Primary Schools. IADIS International Conference on Mobile Learning. Avila, Spain, pp. 241 – 245

Kukulska-Hulme, A. 2010, Mobile Learning for Quality Education and Social Inclusion. UNESCO Institute for Information Technologies in Education. http://iite.unesco.org/publications/3214679/. (Consulted December 31, 2011)

Ortega, E., et.al (Work in Progress…) PISA (Programme for International Student Assessment), 2011. PISA Test Results. Organisation for Economic Co-

Operation and Development. http://www.pisa.oecd.org (Consulted September 2, 2011) Programme for International Student Assessment (PISA), Organisation for Economic Co-Operation and Development:

http://www.pisa.oecd.org. Consulted September 2, 2011 Robledo-Rella, V., Neri, L., Chirino, V., Noguez, J., & Aguilar, G. 2010. Design, Implementation and Evaluation of

Mobile Learning Resources. IADIS International Conference on Mobile Learning. Porto, Portugal, pp. 377 – 379 Robledo-Rella, V., Neri, L., Aguilar, G., & Noguez, J., 2011. Design and Evaluation of Mobile Learning Resources

considering Student Learning Styles. IADIS International Conference on Mobile Learning. Avila, Spain, pp. 246 – 250

Tapscott, D., 1998, Growing Up Digital: The Rise of the Net Generation, McGraw-Hill Companies

ISBN: 978-972-8939-66-3 © 2012 IADIS

58

EFFECTIVE LEARNING MATERIALS FOR MOBILE DEVICES: FOCUS ON VOCABULARY LEARNING

Haruko Miyakoda1, Kei-ichi Kaneko2 and Masatoshi Ishikawa3 1Tsuda College , 2-1-1 Tsuda-machi Kodaira-shi - Tokyo, 187-8577 Japan

2Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho Koganei-shi - Tokyo-184-8588 Japan 3Tokyo Seitoku University, 1-7-13 Jyujyoudai Kitaku - Tokyo-114-0033 Japan

ABSTRACT

It has been claimed in the literature that the effective use of visual aids and tools enhance learning (e.g. Paivio 1986). Some studies claim that the learning effect by the annotations based on movies are superior to those by still images (e.g. Al-Seyghayar 2001), while others claim that annotations based on still images are most effective (e.g. Yeh and Wang 2003). Although these studies differ as to whether movies or still images are effective, they all agree that visual data play an important role in vocabulary attainment. In this paper, we report on two experiments that tested the learning effects of four types of materials for mobile devices that were based on the following contents: 1) text only, 2) text + aural data, 3) text + visual data, 4) text + aural + visual data. In the first experiment, the material employing aural data only drew out the best results, whereas in the second experiment, the mean test scores were similar between text only and text + visual material. The results from these two experiments suggest that contrary to claims in the literature, we may not need to rely too much on visual data in vocabulary attainment. Furthermore, material based on text data only may also prove to be an effective means of learning vocabulary in a foreign language.

KEYWORDS

Aural data, e-learning, mobile devices, text data, visual data, vocabulary learning

1. INTRODUCTION

In the field of second language teaching, vocabulary has been one of the most neglected areas in the classroom. Although there are research findings indicating that lexical problems can cause serious communication breakdowns (Allen 1983), there is not enough time in the classroom to actually “teach” vocabulary.

Unlike the learning of grammar, vocabulary is largely a question of accumulating individual lexical items into long-term memory (Thornbury, 2002). This means that one of the successful ways of achieving vocabulary attainment is to spend time on repetitive memorization activities (Schmitt and McCarthy, 2005). In this sense, ubiquitous autonomous learning can be seen as an ideal method of learning vocabulary, because it allows learners to increase the time of exposure to the words to be learned and to make good use of their time outside the classrooms.

With the advent of computers, new tools for studying vocabulary have been presented. Particularly, e-Learning based on mobile devices is getting more and more popular as a way of learning a foreign language (Amemiya et al., 2007). Employing mobile devices in vocabulary learning is an ideal way of studying because the mobility and portability of these devices provide the users with a ubiquitous environment, where they can study whenever and wherever they like. In addition to the method of learning, however, it is of course important to also consider the content of the learning material that is employed. This will be the topic to be taken up in the next section.


59

2. IMAGERY VS. VERBAL CODES IN VOCABULARY BUILDING

Many papers dealing with learning material can be found in the literature, mostly supporting the effectiveness of visual data in facilitating the vocabulary learning process. For example, the dual coding theory, initially proposed by Paivio (1971, 1986, 2007), claims that using both imagery and verbal codes is more effective than using only verbal codes, because two memory codes provide a better chance of remembering an item than a single one. Some studies investigating the difference between annotations by still images and those by movies conclude that the learning effect by the annotations based on movies and texts are superior to those by still images and texts (cf. Al-Seyghayar 2001). On the other hand, other studies conclude that the annotations based on texts and still images are most effective (cf. Yeh and Wang 2003). Although these studies each have come up with different results as to whether movies or still images are effective, they all agree that visual data play an important role in vocabulary acquirement. However, as can easily be expected, even if visual data may be effective, not all lexical items can easily be expressed visually. Furthermore, even if a word could be expressed using visual data, it does not necessarily mean that everyone will come up with the same visual image for the same lexical item, so it is quite a challenging task to create visual data.

In order to find out what role visual data play in vocabulary attainment, we conducted an experiment that compared the learning effects of different material, the details of which will be given in the following section. Before going into details of the experiment, we will briefly outline the vocabulary learning online system that we employed in the experiment.

3. THE ONLINE VOCABULARY SYSTEM

The online vocabulary system that we have developed consists mainly of three subsystems: 1. a system that supports or facilitates the creating process of the learning materials for mobile devices (Personal Super Imposer), 2. a system that supports its users in downloading the entities from the database and storing them for personal use (Personal Handy Instructor, 3. a system that allows users to share and evaluate the learning entities among themselves (SIGMA). Details of each subsystem will be given below.

3.1 Personal Super Imposer

As mentioned above, Personal Super Imposer (PSI) is a subsystem that creates the vocabulary learning material for e-Learning. By feeding a movie clip, the spelling of the foreign word and its corresponding meaning in the native language, PSI automatically creates a multimedia learning entity. This process is outlined in Figure 1:

Figure 1. Personal Super Imposer

The pronunciation of the foreign word is repeated twice in each movie clip. The spelling of the foreign word is displayed from the beginning, but the corresponding meaning in the native language appears two seconds later. The length of the movie clip for each learning entity totals to five seconds. The structure of the learning entity is summarized in Figure 2:

ISBN: 978-972-8939-66-3 © 2012 IADIS

60

Figure 2. Structure of a Learning Entity

A sample of the material made by PSI is given in Figure 3.

(Japanese-English) (French-Croatian)

Figure 3. Sample of learning material

One of the advantages of creating material with PSI is that the same material can be reused or recycled so that it can be applied to virtually any language or dialect. For example, the left sample given in Figure 3 was originally created for Japanese learners of English. That is, the Japanese word appears on the first line and the corresponding meaning in English appears on the second. If we change the typed-in information from Japanese to French, English to Croatian, the system automatically transforms the entity into a French-Croatian item (right sample). In this way, users can easily share and create multilingual vocabulary material such as Japanese word learning material for Chinese speakers, French word learning material for German speakers, and so on.

3.2 Personal Handy Instructor

The second subsystem we introduce here is the Personal Handy Instructor (PHI). PHI is a system that supports its users in downloading the learning material from the database and storing them for personal use. PHI employs the five-second movie clips created by PSI mentioned above. First, the learner selects the learning material that he/she wants to use from the learning-material list managed by PHI. The selected material is copied into a ‘vocabulary book’ folder. Second, the users import the learning materials to their mobile devices such as iPods by dragging and dropping the folder onto the iTunes window. Finally, the users can download the learning material from iTunes to iPod. An outline of this process is summarized in Figure 4.

Meaning

Spelling

Movie

5 4 3 2 1 0

Pronunciation

(s)


61

Figure 4. Personal Handy Instructor

3.3 SIGMA

The third subsystem is the Special-Interested-Group Material Accumulator (SIGMA). SIGMA is a Web application that uses Apache, PHP and MySQL. It was designed to allow learners to register their own learning entities and to also download the entities created by other users. In a word, users can accumulate and distribute the learning material, and can also browse and download the entities whenever and wherever they like. Figure 5 depicts the main frame of the SIGMA system.

Figure 5. Main frame of the SIGMA

In addition to accumulating and distributing the learning material, users can evaluate each learning entity by giving scores and also giving comments. If a user just wants to browse through the evaluation scores or comments of the learning materials, no login operations are required. However, if users want to evaluate the learning material or give comments to them, they would need to become authorized users. Only authorized users can register and manage his/her own material and given evaluation scores and comments back to all material after login operation.

4. METHODOLOGY

In order to test the effectiveness of different types of vocabulary learning material, we conducted an experiment employing the online system mentioned in the previous section.

ISBN: 978-972-8939-66-3 © 2012 IADIS

62

4.1 The Procedures for Experiment 1

The main purpose of Experiment 1 is to test the efficacy of visual data in vocabulary learning. Particularly, we wanted to compare the effect of employing the following four different types of material: 1) text only (hereafter text), 2) text + aural data (hereafter aur), 3. text + visual (hereafter vis), 4. text + visual + aural (hereafter vis+aur). 59 undergraduate and graduate students attending a university in Tokyo participated in the experiment. The procedures prior to the experiment are as follows:

1. A vocabulary test was conducted on all participants in order to distinguish the lexical items that they were familiar with from the ones that were least familiar. The items that were least familiar among the participants were considered to be candidates for the experiment. The words used in the vocabulary test were selected from a drill book for the EIKEN Grade 1 Test, one of Japan’s most widely administered test in practical English proficiency.

2. Based on the result of the vocabulary test in 1, we selected the following 15 items for use in the experiment: ajar, beckon，bib，bicep，detour, disheveled，diverge，faucet，gargle，glimpse，hibernate，lament，perspire，pollen，stroll. These items were selected based on the following criteria: 1) the lexical items were all unfamiliar to the participants; 2) the corresponding visual data for the words were all available online (cf. English Walk site).

3. The learning material for the 15 words above was created using the PSI system. For the (text) and (aur) entities, no visual data is provided, and the screen would look something like the left sample given in Figure 6, where only the English word and the corresponding Japanese translation are provided as subtitles on a blank screen. The only difference between the (text) and (aur) entities is that for the (aur) material, the pronunciation of the English word is provided by sound data.

(without visual data) (with visual data)

Figure 6. Example of iPod screen materials

4. For the (vis) and the (vis + aur) entities, in addition to the original English word and its translation in Japanese, visual data corresponding to the meaning of the word is provided, as the right sample in Figure 5 indicates.

The procedures for the experiment are as follows: 1. The subjects were randomly divided into four learning groups (Group A-D), according to the type of

material they were assigned to employ (i.e. Group A, (text); Group B, (aur); Group C, (vis); and Group D, (vis+aur)).

2. The subjects were administered a test (Test 1) which included the 15 words mentioned above. In the test, the subjects were asked to write down the translation of the 15 lexical items in Japanese.

3. The subjects were given 5 minutes for learning time. They were instructed to memorize the meaning of the 15 words using mobile devices.

4. Test 2 was conducted, which was based on English to Japanese translation tasks. 5. Test 3 was conducted a week later. The task involved was the same as Test 2.

4.2 Result and Discussion for Experiment 1

The result of the experiment is summarized below in Table 1. The full score for each test was 30 points (2 points x 15 lexical items). The participants received 2 points

if they were able to answer the meaning of the lexical item correctly, 1 point if the meaning was partially right (e.g. “to be hot” for “perspire”), and 0 point if they were not able to come up with the correct answer.


63

Table 1. Result of Experiment 1

Test 1 A B C D Total Average 0.73 0.47 1.00 0.13 0.58 Standard Deviation 1.87 1.13 2.32 0.52 1.59 Variance 3.50 1.27 5.38 0.27 2.52 Test 2 Average 21.20 22.47 20.00 20.20 20.98 Standard Deviation 5.88 6.30 4.62 6.71 5.88 Variance 34.60 39.70 21.38 45.03 34.57 Test 3 Average 11.33 13.40 11.73 11.14 11.96 Standard Deviation 7.45 6.63 7.94 5.60 6.73 Variance 55.52 43.97 63.02 31.36 45.29

When we focus on Test 1, we find that the results among the four groups vary slightly, with Group C having the highest average score of 1.00 out of 30.00, and Group D having the lowest score of 0.13. The average for all 59 subjects came out as 0.58. Since the 15 words employed in the experiment were all supposed to be least familiar to the subjects, the low average score for Test 1 was what we had expected. When we shift our attention to Test 2, which was administered to the participants right after the 5 minute learning process, we find that Group B, which employed the (aur) material, had the highest average score of 22.47 out of 30.00, followed by 21.20 for Group A (text), 20.20 for Group D (vis+aur), and 20.00 for Group C (vis). For Test 3, which was administered to the participants one week after the learning process, here again, Group B had the highest average score of 13.40 out of 30.00, followed by Group C (11.73), Group A (11.33) and then Group D (11.14). In both Tests 2 and 3, the group that came out with the highest average score was Group B, which had used the translation and the sound data to memorize the meaning of the words.

In addition to these findings, we calculated the retention rate of the words’ meanings between Tests 2 and 3. The retention rate was obtained by comparing each participant’s test score for Test 2 with that of Test 3. The overall results are as follows: Group A (text) 52.70%; Group B (aur) 57.90%; Group C (vis) 52.53%; Group D (aur + vis) 57.25%. Here again, Group B scored the highest, followed by Group A, Group C, and then Group D.

In all cases, the material employing aural data only drew out the best results. Interestingly, in addition, the data employing translation only scored better or did as well as either the (vis) or the (aur + vis) data. This implies that contrary to claims found in the literature, visual data may not be playing as crucial a role as one might expect. As mentioned above, previous studies related to vocabulary acquirement generally emphasize the importance of employing visual data for effective learning. However, since the results obtained in this experiment were not statistically significant, we conducted a follow-up experiment.

4.3 Experiment 2

The basic procedures for Experiment 2 (i.e., the follow-up experiment) were the same as for Experiment 1. 40 university students participated in this experiment. They were randomly divided into four groups. Just as for Experiment 1, the four groups were divided according to the type of material employed in the learning process. That is, text only (Group A), text + aural (Group B), text + visual (Group C), and text + visual + aural (Group D). The results of the mean scores for these two sets are given below:

Table 2. Mean Scores of Follow-up Experiment

pre-test 1 A B C D Total 1.1 2.1 1.1 1.7 1.5 post-test 1 24.2 18.7 24.3 19.8 21.7 pre-test 2 13.7 8.6 13.8 9.9 11.5 post-test 2 29.3 26.8 29.7 28.4 28.5

ISBN: 978-972-8939-66-3 © 2012 IADIS

64

The pre-test 1 results for Group A and C were exactly the same (1.1), indicating that the starting point was exactly the same for the group that was provided translation only and the one that had both translation and visual data. The mean scores for post-test 1 conducted right after the learning session were also very similar for these two groups. The mean score for Group A in post-test 1 was 24.2, and 24.3 for Group C. The difference observed between the two is only 0.1.

As for the remaining two groups, the mean scores for Group B and D in pre-test 1 were slightly higher than those of either Group A or C, yet, the mean scores for post-test 1 in the former were lower than the latter. This tendency for Group A and C to outscore the remaining two groups persists throughout. In pre-test 2, which was conducted a week later from the learning session, Group C scored the highest (13.8), followed by Group A (13.7), but the difference again was merely 0.1. In the end, all four groups were able to attain fairly good scores, but here again, Group C had the highest mean score followed by Group A, then C, then B, but the difference between Group A and C was slight (0.4). If we exclude the pre-test 1 scores, the result summarized in Table 2 depicts the fact that the learning effect varied greatly as to whether the material used aural data or not. Unlike the result obtained for Experiment 1, however, aural data did not work in favor of enhancing the learning effect. On the contrary, the mean scores for Group B (aur) and Group D (vis + aur), the two groups that employed aural data in the learning material, constantly were lower than the remaining two groups that did not employ aural data.

Table 3 shows the experimental results of the memory retention rates of the four types of learning materials. The memory retention rate here refers to the difference observed between the results for post-test 1 and pre-test 2, conducted one week apart.

Table 3. Learning material and memory retention rates

Factor 1 (visual) without With Factor 2 (aural) without with without with Data 1 0.333 0.267 0.567 0.133 Data 2 0.233 0.308 0.833 0.357 Data 3 0.233 0.333 0.267 0.607 Data 4 0.545 0.267 0.429 0.517 Data 5 0.367 0.067 0.367 0.375 Data 6 0.444 0.071 0.267 0.300 Data 7 0.367 0.133 0.130 0.300 Data 8 0.533 0.133 0.321 0.214 Data 9 0.733 0.364 0.233 0.000 Data 10 0.600 0.462 0.633 0.100 Number of Data 10 10 10 10 Average 0.439 0.240 0.405 0.290 SD 0.155 0.127 0.203 0.177

We conducted ANOVA based on the result of the memory retention rates, and found the F number for Factor 2 (aural) to be 7.81, as shown in Table 4.

Table 4. Result of ANOVA

Factors Square sums DOF Mean squares F numbers Factor 1 6.17E-04 1 6.17E-04 1.97E-02 Factor 2 2.45E-01 1 2.45E-01 7.81E+00 Interaction 1.78E-02 1 1.78E-02 5.67E-01 Residual 1.13E+00 36 3.13E-02 Total 1.39E+00 39

If we put forward the null hypothesis that “there is no difference between the memory retention rates of learning material with sound and without,” the result obtained makes it is possible to refute this with a significance level of 0.01. That is, from the average memory retention rates, we can conclude that the learning material without sound is superior to the one with sound. On the other hand, no significant difference could be observed for Factor 1 (visual). Furthermore, there was no significant difference in the interaction of these two factors either.

In Experiment 1, the aural data brought about the best result, but in Experiment 2, the two groups using aural data (whether with or without visual data) did not do as well as the groups that did not use aural data. Although the two experiments differed in this point, Experiment 2 parallels Experiment 1 in that visual data


65

did not particularly have a positive effect on the participants’ learning. The findings obtained from both experiments go counter to the general claim in the literature that visual data enhance vocabulary learning. Furthermore, the group that employed the translation only material actually did quite as well as the group that employed visual data in addition to the translation.

5. CONCLUSION

Although a number of studies in the literature claim the effectiveness of employing visual data in vocabulary learning, the results of the two experiments in this study lead us to conclude that imagery plus verbal coding does not show superiority, at least for Japanese students learning English. This has important implications for language learning. It is very time-consuming to create visual data for use in the classroom. Finding the right visual data that corresponds to the word is a bit of a burden, and even with the aid of technology, it still requires much time and effort in the creation process. A further problem arises in the case of abstract words; since visual images are hard to create for these words to begin with. Therefore, even though material employing movies and visual images may seem useful for vocabulary learning, we must not forget that it has its limitations. It is hardly practical for advanced learners, who, especially must cope with abstract terminology most of the time. The result of our experiment indicates that we may not need to rely on visual data, and that employing either aural data only or text data only may be effective ways in vocabulary attainment.

One of the reasons why a difference was observed here may have something to do with the orthography of the first language (Schmitt & McCarthy 2005). That is, the findings that support the dual coding theory, for example, are generally confined to alphabetic languages. Japanese, being a non-alphabetic language, may involve different cognitive strategies, and this may have affected the results of the experiments. In order to better understand the relationship between imagery and verbal codes, studies on logographic languages including Japanese and Chinese need to be conducted further.

ACKNOWLEDGEMENT

The authors are grateful to Takeshi Goto, Marie Matsumoto for their contribution to this study.

REFERENCES

Allen, V. F. 1983. Techniques in Teaching Vocabulary. Oxford University Press. Oxford and New York. Al-Seyghayar, K. 2001. The Effect of Multimedia Annotation Modes in L2 Acquisition: a Comparative. Language

Learning and Technology 5, pp.202-232. Amemiya, S. et al. 2007. Long-term Memory of Foreign Word-learning by Short Movies for iPods. Proc. Of the 7th IEEE

International Conference on Advanced Learning Technologies, pp. 561-563. Hasegawa, K. et al. 2007. Promoting Autonomous Learning: a Multilinguistic Word Learning System Based on iPod.

Proc. of the 2007 International Conference on ESL/EFL, pp.70-83. Paivio, A. 1971. Imagery and Verbal Processes. Holt, Rinehart, & Winston, New York. Paivio, A. 1986. Mental Representations: a Dual Coding Approach. Oxford University Press, New York. Paivio, A. 2007.Mind and its Evolution: a Dual Coding Theoretical Approach. Erlbaum, Mahwah,NJ. Schmitt, N. and McCarthy, M. 2005. Vocabulary:Description, Acquisition, and Pedagogy. Cambridge University Press,

Cambridge. Thornbury, S. 2002. How to Teach Vocabulary. Longman, London. Yeh, Y. and Wang, C. 2003. Effects of Multimedia Vocabulary Annotations and Learning Styles on Vocabulary Learning.

CALICO Journal Vol. 21, No. 1, pp.131-144.

ISBN: 978-972-8939-66-3 © 2012 IADIS

66

SIX WAYS OF INTERACTING WITH MOBILE DEVICES IN MOBILE INQUIRY-BASED LEARNING

Johan Eliasson and Ola Knutsson Stockholm University

Department of Computer and Systems Sciences SE-16440 Stockholm, Sweden

ABSTRACT

We design a mobile learning activity with the aim of supporting inquiry-based learning and analyze it to understand how students interact with mobile devices. For analysis we use a model of contextual human-technology interaction, which is an expansion of an older model by Buxton (1995). Our research question is: How can student interaction in a mobile learning activity be described in the model of contextual human-technology interaction? We approach this question by analyzing an eight minute long video clip of a group of three students using mobile devices for calculating the distribution of trees in a forest area. We categorize the results in six different ways of interacting with technology according to the model. The analysis shows how the model of contextual human-technology interaction can be used for describing placement of technology in mobile learning activities when students are mobile in and between contexts relevant for their learning goals.

KEYWORDS

Human-Computer Interaction, Conceptual Model, Mobile Learning, Field Trip

1. INTRODUCTION

In primary education in Sweden field trips serve as a complement to formal education in the classroom. Such field trips have long been of interest to the mobile learning research community, because mobile technology may play an important role in guiding and scaffolding students when interacting in and with the outdoor environment. However, the mobile phones that are there to support the learning activity, may instead distract from the outdoor environment relevant to the learning goals.

In a previous paper (Eliasson et al., forthcoming) we designed a field trip supported by mobile devices. Inquiry-based learning was adopted as the pedagogical framework for the learning tasks of identifying species of plants, calculating distribution of trees and explaining the forest type. In this previous paper we suggested a model of contextual human-technology interaction (Figure 1). The model is an expansion of a model by Buxton (1995), where we have added the two bottom squares to account for human-context interaction. The hypothesis is that the added squares will make the model more suitable for analyzing human-technology interaction in mobile learning activities, where students are mobile in and between contexts relevant for their learning goals.

To test this hypothesis we analyze an eight-minute long video clip from the same field trip, but on a more detailed level. The clip shows a group of three students using a pie chart on a mobile device with a larger display to calculate the distribution of trees in a forest area. The reason for doing this second analysis is to provide a description of each of the six types of interaction and give examples of each type of interaction from the field trip. To give an account of the whole activity in the analysis we adopt the theoretical perspective of Activity-Based Communication Analysis (Allwood, 2007) as framing. The analysis is bottom-up where we start from the video data, framed by the theoretical perspective, and end in the model of contextual human-technology interaction.

The research question for this paper is: How can student interaction in a mobile learning activity be described in the model of contextual human-technology interaction?


67

The contribution of this paper is applying the model of contextual human-technology interaction to identify how mobile technology can be placed in a mobile learning activity.

The structure of the paper is as follows. In the Design section we describe the mobile learning activity in seven tasks, with going into detail on how students were intended to interact with the mobile devices in each task. In the Method section we present the theoretical framework, the model of contextual human-technology interaction and the techniques and tools used for data collection and analysis. In the Results section we map video data into one of the six categories of the conceptual model.

2. BACKGROUND

In the research field of human-computer interaction, there have been a number of projects studying the problem of interacting with mobile devices while on the move. These studies commonly build on two assumptions. The first assumption is that the problem lies in how to match cognitive capacities (like cognitive load and short term memory) to what capacities are required to interact with the mobile device. The second assumption is that the solution is to be found in the design of the user interface of the device, through ‘minimal attention’ interfaces or making use of other modalities not just relying on vision (Pascoe et al., 2000, Oulasvirta et al., 2005, Lumsden and Brewster, 2003).

Referring to a review of 102 research projects in mobile learning (Frohberg et al., 2009), Göth (2009) argues that among the 38 projects where the learning activities are set in the physical context, technology is too dominating in 28 of them (70%). In these projects the devices require continuous attention and interaction from the students, leading them to focus more on the devices than intended. This review of related research work suggests that mobile devices as distraction rather than support is a problem that is noted by other researchers. However, with one exception the solutions suggested are not elaborated. In the only exception, Göth, Frohberg, & Schwabe (2006), the evaluation of the follow-up study (Göth and Schwabe, 2010) resulted in only marginal improvements.

These findings are intriguing, especially because we believe one of the most promising arguments for introducing mobile devices to learning is to provide students with opportunities to learn outside the classroom, with direct access to contents and contexts relevant to their learning goals. At the same time the challenge is to let technology support access to, rather than distract from, contents and contexts relevant to the learning goals. Furthermore, we think that pedagogical frameworks such as inquiry-based learning (Bruner, 1961, Dewey, 1910) might have an important role to play in introducing mobile devices with the objective to bring students closer to tangible and authentic phenomena outside the classroom.

3. DESIGN

The field trip reported on in this paper is part of a project called mVisible, aimed at making abstract relations in natural sciences visible by using mobile devices. Plants and trees are tagged with QR-codes, and when scanned with a mobile phone the code gives additional information on the characteristics of each species. A pie chart on a larger device can then be used to see how different species are distributed.

The mVisible project is at Stockholm University, Sweden, in collaboration with a local school. It is intended for fifth grade students working in groups of three. Prototyping and field trials were done in spring 2011 and the main study was done in May/June the same year.

3.1 Design Process

The design process of mVisible has been informed by four areas of research: 1. previous mobile learning research (as presented above), 2. pedagogy and didactics (inquiry-based learning), 3. participatory design with the school children (future workshop and prototype testing), and 4. mobile learning interaction design guidelines (Eliasson et al., 2011) related to Buxton’s model of human-technology interaction (Buxton, 1995, Eliasson and Ramberg, forthcoming). In other words, every step of the human-technology-context interaction

ISBN: 978-972-8939-66-3 © 2012 IADIS

68

design loop, here presented as seven tasks (see below), has been considered from what we know is problematic in mobile learning design, together with the project’s perspectives on pedagogy and didactics.

In the following we will focus on the model of contextual human-technology interaction, and how we use it as a tool for analyzing video data from the mVisible project in order to answer our research question: How can student interaction in a mobile learning activity be described in the model of contextual human-technology interaction?

3.2 Model of Contextual Human-Technology Interaction

One of the earliest conceptualizations of human-technology interaction in the human-computer interaction (HCI) research field is a two by two model called the Taxonomy of telematics (Buxton, 1995). This is a model of what is in the foreground of human consciousness, the human-human interaction or the human-computer interaction, or if any one of them are in the background. Buxton (1995) suggested designers to make it possible for users to make transitions between all four ways of interacting with technology. Buxton’s argument was that too much emphasis in HCI was on placing technology in the foreground, requiring intentional human interaction with the technology by using a graphical user interface.

When evaluating interaction with mobile devices in our previous paper (Eliasson et al., forthcoming) we identified a problem in using the Buxton model for describing interaction with the physical context as supported by mobile devices. The problem was that some instances of individual interaction with context were not captured by the category “human-computer interaction with technology in the background”. This problem raised the need for a model that could be used to describe human-context interaction.

In our previous paper we suggested an expansion of the original model to better account for human-context interaction. This adds two new possibilities, where the physical context is either in the foreground or in the background of human consciousness. Figure 1 shows the model with the two added squares for human-context interaction.

Figure 1. Model of contextual human-technology interaction

3.3 Mobile Learning Activity

The mobile learning activity starts with a group of students arriving at one of four different areas in the forest behind the school. The area is 10x10 meters and has been prepared with white tape markings on each side of it. Each student has a mobile device, a smartphone, and there is one common device, a pad with a larger display, belonging to each area.

The activity was designed as a sequence of seven tasks, where each task feeds into the next task. The seven tasks were designed to play out as follows; All three students in the group use their mobile devices to scan the QR code for the 10x10 m area they arrive at. The code initializes the mobile devices to show a list of what species are available in the current area. On the common device, the students read the task instruction to


69

identify each species. The students use their mobile devices individually to scan QR codes attached to each species to identify them and take photos of what is characteristic for each species. For the next task, the three students reconvene at the common device, where they use a pie chart to calculate the distribution of trees in the area. Also on the common device, they get the task to define what type of forest they are in based on the distribution of trees in the area. They are then asked to video film while they explain to each other why this forest type is growing at this particular place.

The last part of the activity is a preparation for a follow-up analysis indoors. Therefore they are asked to fill out a paper-based form summarizing their findings. They note which species they found, what characterizes each species, the distribution of trees, what forest type the distribution point to and what conditions are required for this forest type to grow.

The analysis in this paper is based on the fourth task of calculating the distribution of trees. However, each task has to be performed for the next task to be consistent.

3.4 Interacting with Devices

The two types of devices used in the mobile learning activity, the individual smartphones and the common pad, were intended to be used in a certain way for each one of the seven tasks. From an inquiry-based learning perspective both devices were used to structure the activity in the seven tasks. The mobile device was also used to give students in-situ descriptions of species and the pie chart on the common device was used to investigate the distribution of trees.

In the fourth task the students were intended to interact with the common device to calculate the distribution of trees and to define the type of forest they were currently studying.

3.5 Interacting with People

In the mobile learning activity the students could interact directly with the two students in the same group or with a teacher and a technical help by calling them on the common device. The option to use the common device to call for help was available to the students throughout the whole mobile learning activity. The students were asked not to interact with the researcher manning the close-up camera and the researcher was asked not to answer questions from the group.

In the fourth task one student could interact with the common device at a time. Still the group were to calculate the distribution of trees and define the forest type together, meaning that the students needed to interact within the group to construct the required answers.

3.6 Interacting with Context

The students were intended to interact directly with the species and investigate their characteristics in task number three and four. This investigation was one step towards the open-ended exploration of phenomena in inquiry-based learning.

In the fourth task they were to count the number of trees of each species in the 10x10 m area, to be able to calculate the distribution of trees.

4. METHOD

Activity-based communication analysis (ACA) (Allwood, 2007) was used as a theoretical framework for analysis. We use the MUMIN multimodal coding scheme (Allwood et al., 2007) as a basis for transcription and annotation.

4.1 Participants

Seven groups of three students, 21 in total, took part in the study. The students were from the same fifth grade class, participating in the study as part of their mathematics and natural sciences curriculum. The

ISBN: 978-972-8939-66-3 © 2012 IADIS

70

groups were formed by their mathematics teacher in collaboration with their natural sciences teacher. Apart from which students were known to be able to work together and which students were not, the teachers used high heterogeneity as the basis for group formations. Six out of seven groups had both female and male students and the differences in background knowledge on the subject was as large as possible in all seven groups. Figure 2 shows the group for which the analysis is done.

Figure 2. Still from the video showing the group, the common device (right) and one mobile device (middle)

4.2 Data Collection and Analysis

We analyze an 8 minutes and 23 seconds long video clip of one group using a pie chart in task 4 to calculate the distribution of trees. The primary data used for analysis is from a handheld video camera. A stationary wide-angle camera covering each 10x10 meter square was used as a complement when one or more participants were outside the frame of the handheld close-up camera. Only video was used for the transcription and annotation.

The video of each group was first segmented into the seven tasks described in the mVisible mobile learning activity section.

The criteria for choosing a video segment for analysis were that interactions of all three students were visible on the video. Task four was chosen for analysis because this was the only task where the students were intended to interact with people, context and devices. This means that we would expect to see interaction in all three types in the model: Human-Human Interaction, Human-Computer Interaction and Human Context Interaction.

In the analysis, the transcripts for each segment were mapped back to the type of interaction (devices, people or context) designed for in each task, in order to see to what extent the students were interacting with the mobile devices in the ways intended in the design of the mobile learning activity.

Interaction of each student in the group was categorized into the six categories of the model of contextual human-technology interaction. All interaction in the clip was successfully categorized into the model.

5. RESULTS

The clip shows the three participants P1, P2 and P3 interacting with the common device, with their mobile devices, with each other, with a teacher, T1, via speakerphone and with the trees and plants around them.

In the first half of the clip the three students are interacting with the common device and their individual devices in creating the pie chart. In the second half they are rather interacting with the teacher T1 via speakerphone. In the examples below, she is used for both sexes.


71

5.1 Interactions Identified in the Clip

In the clip the students use in total 26 gestures, gaze and head movements. They use two iconic gestures and 17 indexical gestures. Student P2 is gesturing slightly more (9) than student P1 and P3 (5 + 5). P1 and P2 uses gaze indexically twice. P1 uses her head indexically once and P2 twice. These gestures, gazes and head movements are used as evidence for certain interactions in the examples below. Indexical gestures, gazes and head movements can be seen as evidence of interaction with people, devices or context as the gestures are co-occurring with speech. Speech can then be used to interpret what is going on.

Below, we provide one or more examples for each one of the six types of interaction in the model of contextual human-technology interaction (Figure 3). In the cases where we do not find evidence of a certain type of interaction in indexical gestures, gazes and head movements, we provide a discussion.

Mobile phone call: The group decides to call for help in identifying the Goat Willow tree. They call T1 using the speakerphone:

[speakerphone is ringing] T1: T1 here. P1: Hello. T1: Who’s speaking? P1: P1. T1 answers the phone. P1 uses the speakerphone to communicate with T1. This is an example where

technology is in the foreground of human-human interaction (see Figure 3) as communication is mediated by the phone.

Face-to-face collaboration: Student P2 talks to P1 and P3 and describes the characteristic of pine trees. P3 answers back.

[P1 interacts with the pie chart (to input the number of pine trees)] P2: It is those pine tree. With these huge. Look here P1, it is these very

tall trunks lots of needles up there, you know. P3: Right. P2 talks to the other group members who are standing next to her. She does not use technology, but still

what she says is structured by technology in the form of a task structure that she is aware of. Framed like this face-to-face communication is and example human-human interaction with technology in the background.

Mobile device interaction: At the start of the clip, the three students are to unlock the next instruction on the common device. To do this you need to use one code from each of the three individual devices. This code was called a “mobile code” and it became available on the individual device when all but one species had been identified (when the QR codes for these species had been scanned).

[P1 interacts with the common device] P1: What am I supposed to click? Student P1 moves to the common device and starts interacting with it. Mobile device interaction ends

with P1 asking the other two students how to unlock the common device. In the model this change in focus can be described as a transition from human-computer interaction with technology in the foreground to human-human interaction with technology in the foreground (from the middle left square to the upper left square).

Individually interacting with the device is an example where technology is in the foreground of human-computer interaction, while pointing to contents on the screen and interacting with other students is an example where technology is in the foreground of human-human interaction.

QR-code based task structure: P2 takes a break from the current activity to confirm that they are working on the correct task.

[P2 looks at the common device] P2: Alright we’re there The seven tasks provide a structure that occasionally puts technology in the foreground, for example

when going from one task to the next or commenting on the current activity, and occasionally lets students interact with technology in the background, for example when it is used as a frame for the current activity.

Take photo of species: P2 walks away from the other two students to a QR-code on a tree and scans it. [P2 scans a QR-code on a fir tree] P2: Fir P2 identifies the fir tree by scanning it. She then gets the name of the tree and some information of what

characterizes it. The individual devices can be used to scan QR-codes. In doing this they are mediating the

ISBN: 978-972-8939-66-3 © 2012 IADIS

72

human-context interaction and in addition to confirming that the correct species is identified, they also give additional information on the characteristics of each species when a QR-code is scanned. This is an example of human-context interaction with technology in the foreground. Another use where technology is in the foreground of human-context interaction is when the students are taking photos of what is characteristic for each species.

Search for species: P1 interacts with the pie chart on the common device, which provides a structure for the activity. She tells the other students which species needs to be counted next. P2 counts the pine trees.

[P2 points to the pine trees and starts counting them] P2: One, two, three, four... When P2 starts counting she also points indexically towards the pine trees. Pointing towards the pine tree

can be seen as interacting with context. Technology is in the background as it structures the activity.

Figure 3. Model of contextual human-technology interaction with examples taken from the mVisible project

6. DISCUSSION

Given that the students are to interact with each other, with devices and with learning contexts in a certain way in order to reach certain learning goals, the model can be used as a tool for designing mobile devices and activities to support this interaction. The two squares on the bottom of the model may then be used in designing for mobile learning activities where students are mobile in and between contexts relevant for their learning goals.

The model is an improvement from the original model of only four squares in that it makes it easier to map video data of students interacting with context to the model. It is an improvement because all interaction in the eight minute long video clip could be described by using the model. But the model might still need improvements. The two new squares bring new choices, which makes it more difficult to map activity into one single square. Most difficult to discriminate is between the squares where technology is in the background. In our data there are instances where the students use their individual devices in searching for species while they communicate with the other students. In this case it can be argued that the data should be mapped to any of the three squares where technology is in the background; human-human interaction, human-computer interaction and human-context interaction. This potential problem with the design of the model could be solved to some extent by using a three-dimensional model instead. The reason we do not choose to redesign the model into three or even four dimensions is that we want it to be as simple as possible. A model with more dimensions might be easier to use for someone who knows it by heart, but as a tool for design and analysis without prior training a two dimensional model should be more attractive.

The analysis also offers an overview of six types of interactions with mobile devices in a mobile learning activity. This overview can then be used for further analysis and re-design of specific parts of the activity, for example to have tasks aimed at collaboration, interaction with devices or individual investigation of an


73

outdoor environment. The analysis also indicates that it is possible to use the model to compare the outcome of different tasks.

The model can be used as a tool for designing for six ways of interacting with mobile devices. These six ways of interacting with mobile devices can then be used in designing for mobility, especially the two ways of interacting with context. These six ways of interacting with mobile devices can also be used in designing for learning based on interaction with other students, devices or contexts.

7. CONCLUSION AND FUTURE WORK

The model of contextual human-technology interaction can help us both in designing and in analyzing mobile learning activities where students are mobile in and between contexts relevant for their learning goals. In analyzing mobile learning activities, the model helps us understand the role of mobile devices. In designing such mobile learning activities, the model helps us understand how to place mobile devices to support students in reaching learning goals based on interaction with other students, devices or context.

In future work we want to evaluate the model of contextual human-technology interaction further, based on video data from different mobile learning activities, to allow for comparisons. We also want to go back to mobile learning activity to re-design it in line with the evaluation.

REFERENCES

Allwood, J. 2007. Activity Based Studies of Linguistic Interaction. Gothenburg Papers in Theoretical Linguistics, 93. Allwood, J., Cerrato, L., Jokinen, K., Navarretta, C. & Paggio, P. 2007. The MUMIN coding scheme for the annotation

of feedback, turn management and sequencing phenomena. Language Resources and Evaluation, 41, 273-287. Bruner, J. S. 1961. The act of discovery. Harvard Educational Review, 31, 21-32. Buxton, B. 1995. Integrating the periphery and context: A new model of telematics. Graphics Interface. Dewey, J. 1910. Science as subject-matter and as method. Science, 31, 121-127. Eliasson, J., Cerratto Pargman, T., Nouri, J., Spikol, D. & Ramberg, R. 2011. Mobile Devices as Support Rather than

Distraction for Mobile Learners: Evaluating Guidelines for Design. International Journal of Mobile and Blended Learning, 3, 1-15.

Eliasson, J., Knutsson, O., Nouri, J., Karlsson, O., Ramberg, R. & Cerratto Pargman, T. forthcoming. Evaluating Interaction with Mobile Devices on a Field Trip. 7th IEEE International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education. Takamatsu, Japan.

Eliasson, J. & Ramberg, R. forthcoming. Design Guidelines for Location- Based and Contextual Learning Supported by Mobile Devices. International Journal of Handheld Computing Research.

Frohberg, D., Göth, C. & Schwabe, G. 2009. Mobile Learning projects - a critical analysis of the state of the art: Original article. Journal of Computer Assisted Learning, 25, 307-331.

Göth, C. 2009. Mobile Exploration: Lernen Im Physischen Kontext, Zürich University, Switzerland, Doctoral Thesis. Göth, C., Frohberg, D. & Schwabe, G. 2006. The focus problem in mobile learning. Fourth IEEE International

Workshop on Wireless, Mobile and Ubiquitous Technology in Education, WMUTE 2006.

Göth, C. & Schwabe, G. 2010. Navigation support for mobile learning. HICSS '10 Proceedings of the 2010 43rd Hawaii International Conference on System Sciences.

Lumsden, J. & Brewster, S. 2003. A paradigm shift: Alternative interaction techniques for use with mobile & wearable devices. Proceedings of the 2003 Conference of the Centre for Advanced Studies on Collaborative Research, 197-210.

Oulasvirta, A., Tamminen, S., Roto, V. & Kuorelahti, J. Year. Interaction in 4-second bursts: The fragmented nature of attentional resources in mobile HCI. In, 2005. 919-928.

Pascoe, J., Ryan, N. & Morse, D. 2000. Using while moving: HCI issues in fieldwork environments. ACM Transactions on Computer-Human Interaction, 7, 417-437.

ISBN: 978-972-8939-66-3 © 2012 IADIS

74

A COMFORT ZONE FOR MOBILE LEARNING – A GROUNDED INNOVATION APPROACH

Henning Breuer, Tillmann Dierichs and Stefanie Elsholz University of Applied Sciences Potsdam,

Pappelallee 8-9, 14469 Potsdam, Germany

ABSTRACT

Mobile learning activities of commuters have widely been neglected. The paper reports on the adaption of a grounded innovation approach involving a futures workshop for interaction design and ideation based on ethnographic insights in the field of mobile learning. Current obstacles and utopian futures of mobiles learning lay the grounds for envisioning new systems to support mobile learning for public transport. A system to enhance comfort zones for mobile learners is being specified and illustrated. It proposes a gesture-based handling of tablet computers in order create an adaptable and comfortable personal learning environment with individually adaptable and familiar modules. An iDesk prototype preserving a personal comfort zone for mobile learners is presented. The system intends to support formal and informal learning in mobile times.

KEYWORDS

Mobile learning, portable devices, ethnography, futures workshop, grounded innovation, learner-centered design.

1. INTRODUCTION

Mobile times! Within a fast moving society we are always on the run. A substantial part of our lifetime we spend in traffic. Innovation literature reports, what is the "job done" by milkshakes in the morning (Christensen et al. 2007): To kill time of driving commuters – a low form of entertainment for a hand and a mouth during a dull drive to the workplace. But even in public transport where the hands are not handicapped by a steering wheel one may observe a rich variety of useless distractions from those mobile moments.

Still, since the invention of the book contributed to the history of portable media several formats of tools and interaction techniques enable mobile learning. In particular students whose job is to learn with limited resources populate public transport with learning activities, but rarely they find ideal conditions. Thinking of suitable, learner-centered media and environmental conditions, not only instructional methods, but also individual learning goals, strategies, preferences and contents have to be taken into account.

This paper begins with a discussion of such impacting factors known from the literature and introduces the conceptual ancestors of our methodological approach to develop new concepts for mobile learning. Within a class on strategic user research several methods of observation, data analysis and idea generation have been applied in order to understand and differentiate mobile learning activities and media usage in public transport. During the observations we looked into learning motives, educational contents, and recurring problems of commuting students. The empirical data from observations provided the basis for the systematic generation of ideas how to address these problems within a futures workshop. The empirical and the development approach and their results are described. One main opportunity to design mobile learner-centered systems was identified around the attempt of mobile learners to sustain a comfort zone and familiar environment for learning in public spaces. Based on the empirically collected requirements and ideas from the future workshop we elaborate upon a concept for a mobile system sustaining such a scaffolding learner-centered environment. We describe the system design for an iDesk prototype and illustrate its use through a fictional usage scenario. Final conclusions sum up the project and its results and reflect upon lessons learnt with impact beyond the scope of this project.


75

2. RELATED WORKS

Mobile learning involving portable devices has been described as “learning across contexts” (Walker 2006), but the notion of context remains disputed in the related works. Portable devices have been discussed as a valuable means to support the context-dependent construction of knowledge (e.g. Jippling, Dieter, Krikker, & Sandro, 2001). Especially their ability to collect data, to work collaboratively and location awareness features are suited to create uniquely new learning opportunities (Patten, Sanchez, & Tangney, 2006). Learning may be understood as expansion into a context where meaning-making practices and objective opportunities for development relate. Systems may provide opportunities for learners to expand their abilities for engagement in a given environment (Breuer and Matsumoto 2008). Still, in many cases learners just want to utilize commuting times for learning purposes. Following this assumption this work continues a series of works intended to explore and design formal and informal learning environments (e.g. Breuer& Matsumoto 2011). The research and prototype we describe resulted from a university class on advanced user research.

3. RESEARCH DESIGN FOR GROUNDED INNOVATION

Grounded innovation generates empirical data from multiple perspectives on a roughly defined design space and takes its analysis as a basis for the proposition of qualified opportunities for innovation (Breuer & Steinhoff 2010). In this case we looked for new ideas and concepts how to support self-initiated learning activities of commuters. Ethnographic observation and a diary study provide the empirical problems we addressed within a future workshop on mobile learning. One of the resulting idea clusters addressed the difficulties of commuting students to sustain a familiar comfort zone for their learning – the iDesk prototype was then specified to conform with the requirements derived from the empirical studies.

3.1 Participatory Observation and Diary Study

In order to understand the requirements of mobile, especially commuting learners we set up and conducted a user diary study and day-in-a-live visits. Focusing on the observation such ethnographic methods are suited to identify problems and opportunities beyond the ones that are accessible through interviews and to the participants consciousness. The participants of this study were 19 female and 27 male students between 24 and 36 years old studying interface design, industrial design, history, literature, social studies and medicine. Regularly commuting 30 to 90 minutes between their homes in Berlin and universities in Potsdam they all share a common interest in utilizing commuting times for learning purposes.

The first task and step in the document "day in the live study" we interviewed the participants on demographic data and about their mobile learning activities. We wanted to find out which utilities they use, which method they prefer to learn when they are on the move, their learning places or their preferred learning time. In order to understand their learning context we asked about their actual learning topics and goals, and purpose (e.g. an exam or an applied design task during the semester). After the interview we began with the observation. Observers from the class accompanied the participants for several hours trying to find out insights about mobile learning routines and behavior. The task of the observers is to document their observations and thoughts. The forms of documentation include photographs and illustrations attached to the written protocols, notes and interviews. An observation guide put focus on media preferences and ways to organize mobile learning including not taking and use of utilities to support mobile learning through pencils, post-its or digital devices. Questions we tried to clarify through the participatory observation were: Where do students learn? How they practice mobile learning? When they are learning? And in which constellation they learn? Beside the general observations observers make memos or notes of ideas, for example: "Simon memorizes lot of thoughts through shortcuts”. After the observation we conduct a second interview to explore individual learning preferences and habits further based partially on our observations through questions such as: If you have to research, how do you proceed? Why do you choose this particular way? Why are you learning while on the move? We also asked the participants to draw their personal learning network including the kinds, contents, frequency and strengths of connections. Participants also rated their learning media after importance yielding the book as the most important.

ISBN: 978-972-8939-66-3 © 2012 IADIS

76

Finally the learners were asked about their personal schedule, e.g. how much time they have to learn for an exam. We also ask about the time the learners use to learn on the move or they private desktop.

In addition to the day in a live study we gave out user diaries to get insights into mid term developments that cannot be observed live by a dedicated observer. In a user diary participants document notes or observations from instructed self-observation. In our case the aim of the user diary was to find out how people organize their learning day when they are on the move. Participants write down for one week how they learn when they are not at home. We also wanted to know something about their different and preferred learning places and the problems and disruptions within each context. The study should also reveal what they carry with them, what they learn and which kind of topics. First the participants were also interviewed about their learning behavior, especially the learning on the move. For example: How you plan your learning activities? During the documentation the participants answer a set of questions at the end of every day. They document their times and place of learning and their preferred utilities, media, and methods for each. At the end of a day participants construct a learning curve in a given diagram summing up places, time of learning, sleeping phases, concentration phases and learning success. They rate their capacity of learning and their concentration, and in how far they reached their learning goal or less than what they intended.

3.2 Data Analysis and Aggregation

After the observations and receiving back the user diaries data analysis and aggregation started oriented on principles of adductive thinking as developed in Grounded Theory (Glaser & Strauss 1967). Following an approach of “Grounded Innovation” (Breuer & Steinhoff 2010) and "Divergent Innovation” (Breuer, Hewing, Steinhoff 2009) we structure the design space of mobile learning in order to create innovative concepts. First we inspect all data and note first impressions and insights to get a first idea of mobile learning. After first inspection we could categorizes our notes and phrase first codes from that. These codes are the basis for our first hypotheses about mobile learning. Through repeated viewing of our data we refine our knowledge and insights of learners. Open coding results in memos and a list of codes. Finally the codes are sorted. Four categorizes resulted: motivation/purpose, situation/places, material and problems. At the end we formulate a thesis including proposals for design concepts and descriptions.

The motives to mobile learning are different. Some students are learning to save time and to use their time effectively: "What I can learn on the move, I do not need to learn at home." Another motive for learning is boringness and the wish to bridge the time gab. Other participants mentioned feeling alone at long learning hours at home and therefore attending the library (besides from more flexible access to books). Most learners actively pursued or constructed their own motivating learning environment.

Students study almost everywhere; places include the library, cafés, parks, and fitness-studios, learning groups, bureau or public transports. The times to learn in the public transports are short, between 10 to 40 minutes. Apart from library, where learners typically spend hours to study complex topics, students learn less complex themes when they are on the move. They use the time to repeat the suspect matter or to read less complex themes. They repeat previously learned content, learn vocabulary, read or take notes and deal with SMS or calls. Preferred media are books, files or flash cards or notes and post its. Mobile phones, audio player and laptops were rarely used.

The observation and the user diary reveal that learner have some problems during mobile learning. Due to the available media and the environmental sound all learners complained about frequent disruptions. The most used media on the move are books. But they use books because of missing alternatives. Laptops are often too heavy and too unhandy for using on the move. Students also are often missing fast, reliable and affordable internet connection for further research. Books on the other hand lack further research possibilities. Another constraint for learners due to weight is that they have to decide which book they take to read on the move. Therefore they can use only a little part of their preferred learning material. Disturbing environmental noise in the public transports includes other people speaking on the mobile phone and operational noise of the means of transport. In the library the unsettled atmosphere and typing of other learners on their laptops was perceived as disturbing. The learners were disrupted when they are on the move during the public transport through the announcement or changing the trains. Often they are in a hurry and put their material in their bags very hasty. “After some turns of tearing the print articles out of the backpack and putting them back in a hurry they mutate into a paper ball with poor readability.” Other disturbances are noise by other people or music by headphones. Several participants felt uncomfortable about the closeness to


77

other people and the general unsettled and foreign situation, by contrast to their homely environment. That's why they try to isolate them from the noise, for example with headphones that help them to create their own (virtual) audio environment. In general we could observe that the learners experience mobile learning as a disruption from their learning at home. That's why they try to organize a fluent passage between their home desktop to mobile learning. Some cultivated their own symbols or systems to work on the move: "If I read a text, I use small symbols. At home, I see through the icons how I have to continue learning. For example, I use QG, that means look at Google, QL look at Leo and QA, look at the ACM portal." Other students use own symbols to sign text passages of interest. A further kind of organization was to categorize their learning material and plan what they learn on the move to use the time gap.

The coding of the data and its categorization into emerging categories allowed developing first concepts and the following core categories: The learner will be affect by different outer influences during their mobile learning. They didn't have the optimal learning environment like the one they created at home. They try to simulate their home environment. One core aspect we then conceptualized as a need for a personal “comfort zone”, to make their situation on the move pleasant as possible and to support the learner. Further more, the learner have to use analog media instead of the digital media most of them would have preferred. Available digital media do not suffice to support learners due to weight and limited internet connection. Participants required a means that supports them on the move, containing aspects of analog media and additional aspects of digital media to support the workflow between mobile and home learning at their home desktop. A seamless transition and passage between both situations appears most promising.

A digital learning device like a tablet PC can support the learners at their studies. A wireless internet connection is needed for additional research and constant availability of learning materials, the possibility to take and exchange notes and processing, and the availability of interactive learning materials. Such a compact device is a combination of the benefit of analogue media and an e-learning platform: handiness, contextual study and research on the move and processing of subject matter.

3.3 Ideation Design and Futures Workshop

Ideation Design applies divergent and convergent thinking (Edelmann 2003). Principles of detour (Breuer, Hewing, Steinhoff 2009) involve the idea that “function follows form” (Goldenberg, 2003) and apply external points of reference in order to enable multiple shifts in perspective. Within futures workshops we detour through a utopian stage without limits in order to come up with desirable solutions to problems or opportunities in reality. A futures workshop can be interpreted as catalysis for reducing the discontent with a current situation and for showing positive development possibilities for the future (Jungk & Müllert 1987). Normally, a futures workshop lasts several days and is subdivided into three sequential process phases: the critique phase, the utopian phase and the realization phase.

In the first phase of our future workshop, participants collect problems as well as resentments and make comments on dissatisfactory situations within a specific subject area. Since most of the participating students commute daily between Berlin and Potsdam, the strengths and weaknesses of mobile learning were a topic of common interest. The illustration of problem fields by formulating negative news headlines is an appropriate way to make the significance of a problem and its implications for the future evident. By individual evaluation, relevant problem complexes are being selected for the next phase. The topic of this particular futures workshop was “Mobile Learning in Public Transport”. In the utopian phase, it is assumed that any limitations of real life are not valid and that, in principle, everything is possible. Hereby, participants portray an exaggerated picture of the future driven by desire. The problems of the critique phase are being reformulated so that they result in a positive statement, e.g. positive future news headlines. Possible solutions are being identified. The neutralization of any limitations stimulates unusual and unconventional ideas and solution concepts. The third, realization phase, re-establishes the connection with the world as we know it. The ideas and solution concepts of the utopian phase are being critically examined. The participants analyze how single aspects of the utopian vision can be realized in reality. Especially, the needs on which the utopian visions provide starting points for the realization with today’s and upcoming means, e.g. technologies.

Our futures workshop was prepared based on the ethnographic insights and learning barriers from the observation and diary studies. After the introduction the participants were shown a short film as a warm up. In the following phase of critics the goals and regulations were explained to the participants in order to make them conscious of their role in the process and the task. The participants could now begin to collect problems

ISBN: 978-972-8939-66-3 © 2012 IADIS

78

and critical points of mobile learning by acclamation, each of which was noted to ensure that everyone got a precise overview of the problems of the subject. All collected critical points were subsequently arranged into four categories in order to make the most important problems more conscious. The participants were now divided into four teams – each team was assigned with one of these categories they should specialize in and work with in the following utopian phase. After an introduction into the utopian phase (goals, tasks, regulation), four tools were explained more closely (brainstorming paradox, adaptation, buzz word analysis and method 635) that could help to develop ideas in an unconventional way. Each team developed a utopian vision with the creative technique. They could consult a teaching moderator for questions and support. After this phase each team should evaluate its own utopias. Each participant had three points to rate an idea. The three utopias that got the best evaluation were presented to the other teams. The phase of realization began by outlining the goals of the phase. Each participant had four votes to give for the best solution of the utopias presented above. The results were evaluated. Each group had the task to realize one solution that would be possible to bring into being with the technical possibilities of today. Each team presented in the end its solution or the exact description of its concept. All four ideas were acted out trough an informance to the group and discussed in the end of the workshop.

We selected this best idea grounded in the empirically driven innovation approach as a basis for system design. It provides a solution to the problems of students with distractions and disruptions during their mobile learning activities, and strengthens their weak attempts to sustain a familiar and comfortable learning environment in public space by means of sophisticated software for light weight tablet computers: a personal library or iDesk design. The iDesk ought to offer the possibility to depict the complete learning environment virtually in a handy and easy-to-use format. It provides access to a personalized learning environment, which adapts to the home environment. Among them are graphical illustrations of typical domestic learning venues or their metaphors, like one’s own desk, bookshelf, files and other objects ready for interaction on the tablet.

4. DESIGNING A LEARNER-CENTERED I-DESK SYSTEM

The basic idea for the system design is to preserve aspects of formal and home learning environments within mobile settings and intends to support self-directed learning activities during commuting times. The concept utilizes tablet computers with camera and gyro sensor in order to create a personal or shared space for learning. An iDesk device is a tablet-PC like the iPad by Apple enhanced through learner-centered software. An improved but optional device design, however, would provide for two touch screens that can be folded like a book. This does not only have the advantage that the display is protected when storing it in a bag and saving space. The biggest advantage of this design is to ensure natural working like with a book or notepad, which can be opened and is thus adapted to the typical learning media of pupils or students. Furthermore, the two screens can be used in different ways, for example to use diverse contents clearly and separately from one another. The device also contains a stylus by which handwritten notes can be made and text passages marked, for example in a book or other things can be done with it. It supports familiar ways of working and learning with analogous media and methods.

After starting the device, a segment of the learning environment is depicted at first, for example the picture of one’s own desk with all filed media, like books, notepads, learning cards, and such – everything which is also typically on the home desk within reach. By moving the device in different directions, it shows parts of the home learning environment, similar to a picture frame revealing only a part of the room. Holding the “iDesk” horizontally it shows the surface of the table with different interactive objects. Moving it to the side changes the visible segment, for example to the bookshelf where all previously filed books are depicted and ready to be read. They cannot only be relocated, filed, read or edited within the shelf but also between shelf and desk as direct work space. The operation with the finger or the stylus should work as expected. Scrolling through books or notes is possible by swiping a finger. With the stylus handwritten notes can be created or menu items handled, which can be relocated by moving an application to the other (area of the) screen. By means of this simple principle, the familiar learning environment ought to be imitated in a small, handy format. It is enriched with mobile features like wireless Internet access, telephone function, savings possibilities, data collation, calendar management, notes, email, and such, also allowing a seamless transition between analogous learning and educational multimedia.


79

Figure 1. Different sketches of the interface. View on the table, some files and an opened book, ready to read.

4.1 Experience Prototype

The current system, as described in the following, builds the requirements of the participants in the empirical study. We found that students predominantly learn analogously in an individual learning environment (mostly at home). Learning on the go, predominantly on trains, buses, in the café, gym or library would be a great advantage for many for reasons of time saving and motivation. But mobile learning is limited through several factors: On the one hand, books and notes on the go are simply too unhandy or heavy and even the possibilities for a quick research on the Internet are not given. Problems of space for learning media on the go and the insufficient offer of educational computers or suitable devices make additionally sure that mobile learning only takes place to a limited extent.

The iDesk described closer in the previous chapter, could fill these gaps and allow for what the investigated test persons were missing. The added value of such a device is to allow mobile learning in a learning environment, which is based on the home environment and can be adapted fully to one’s own needs. It is suitable for the different learning contents and times (more intensive learning even with other learners over a longer period of time as well as for shorter times, e.g. a 10-minute bus ride). It offers the possibility to create one’s own comfort zone in isolation from disturbing ambient noises.

4.2 Hardware

The iDesk must adhere to different requirements to the hardware like weight. Investigating and comparing the average weight of books, mobile phones, tablet-PCs and net books, a weight of not more than 500 grams seems to be optimal, because thus the device can still be held in one hand for a while without feeling tired. At least 10 hours duration for permanent operation should be possible, on stand-by-operation this value should be many times higher. It should be easy to switch the iDesk on or off or put it in stand-by since quick changes of location and a quick activation of the device are essential. Besides WLAN or the possibility to go online per UMTS to be able to research on the go and send emails, the integration of a video camera is planned to enable collaborative video telephony via Internet. The possibility to get in touch with other learners per video telephony via Skype from the home PC, is a basic requirement for the iDesk to make collaborative learning and the exchange with other learners possible on the go. Additional interfaces like Bluetooth for a wireless connection of several devices, a USB-connection as well as an SD-card slot are important to be able to load and install data from other media.

4.3 Interaction Design

Requirements for design, which the software must meet, are just as complex because they must make the analogous data like books tangible on other media, enrich them with interactive possibilities without limiting the user in any form if they want to adjust the software individually in addition.

Basic activities to be carried out with the iDesk are: Reading, writing, marking, taking notes, information retrieval on the Internet, writing email, creating files, comparing data, administering, searching and copying. Individual adaptability of the software supports users in recreating their personal home learning environment and familiar interaction patterns. One possibility to depict this collection of demands in one single device is through controlling by gestures. For instance, holding the tablet horizontally, the surface of the desk with all

ISBN: 978-972-8939-66-3 © 2012 IADIS

80

its documents is shown; more parts show up when the tablet is moved to one side. Keeping the iDesk vertically, a bookshelf and additional contents can be shown depending on how and in what segment the device is moved further on. Detailed working on documents, reading books, an such can be done by the help of the stylus or by counteracting with one or several fingers.

Two screens would offer additional possibilities to arrange one’s documents on the device. Two documents can be displayed next to one another or an opened page takes up both screens for a better picture

by turning the device vertically. To prevent unwanted changes of the display detail when holding the device (for example for a quick change of the seating position on the bus), the display detail can be fixed by pressing a key. This option is also necessary when working on documents in a certain position. In order to synchronize documents of all kinds as well as the learning environment, e.g. one’s study desk with the iDesk, the method of visual search is employed (a more simple initial version may apply barcodes). Documents or even entire shelves can be scanned. These data are filed away, identified and transformed in form of photos on the iDesk so that they can be worked with further on. A usage scenario illustrates how to work in such an environment.

Figure 2. Scanning documents

4.4 Usage Scenario

Jessica is 23 years old and in their 6th semester of social pedagogy and English. She has to learn for an exam. First she is learning at home, after she goes to a fitness studio by bus. Later, she attends a meeting with fellow students to learn for the exam. At home Jessica is learning vocabulary and English grammar by a workbook where she fills out fill-in-the-blank-text. In addition she reads English literature. In the book she is editing important words with a pen. Before leaving the house she packs her stuff together and synchronize her stuff with iDesk. On the move she wants to repeat their vocabulary. She needs one book for the meeting with her fellow students. Cautionary she takes also her fill-in-the-blank-text away, when she have unexpected waiting time. On the move she has a 25-minutes trip with the bus to fitness-studio. During the trip she opens her iDesk and starts her vocabulary trainer through a smear gesture. The first vocabulary card is shown. Through smearing she turns the card and gets the answer. Before she reaches the stop, she has a look to her tasks for the day. She pushes the trainer away and zooms into her notes with two fingers. With the help of a strike out gesture she closes the vocabulary task. At the fitness studio she uses iDesk like a book. While running she reads and highlights important words through smear gestures. With a circle gesture around words she gets a menu with related tasks like copy or paste. Afterwards she studies vocabulary and listens to the pronunciation visa audio. On the way to her fellow students she searches and browses with iDesk for books on the Internet. At the library she meets her fellow students for learning together for their exam. For that they lay their iDesks together to one big screen to learn collaboratively on one document. One of the students is writing, another is handling with the document and another is editing words from the books can be copied to the document. Afterwards each one studies individually and takes notes with handwriting technology.

Figure 3. From left to right: Learning at home, Bus ride working with the iDesk and meeting in the library


81

5. CONCLUSIONS

The research and development methodology and the project results demonstrate a showcase of grounded innovation (Breuer & Steinhoff 2010), which was based on empirical observations, interviews and diary studies. Starting from an empirically based understanding of learner-centered requirements commuting students and the design space provided by mobile devices we identified, qualified and specified opportunities for innovation

Analysis of the empirical data yielded the maintenance of personal comfort zones for mobile learners as a new and valuable opportunity for learner-centered interaction design. Beyond the basic idea and concept the empirical research and findings especially from the utopian phase of the workshop contributed a rich variety of insights and user requirements to the specification of the prototype that is currently under development. A personal library and iDesk system were designed based on this insight and ideas generated within a futures workshop. The prototype that was developed accordingly applies gesture-based handling of tablet computers in order create an adaptable and comfortable personal learning environment with individually adaptable and familiar modules.

Since the printed book and later portable computers created a market for mobile learning means technological capabilities develop rapidly. The challenge persists to design and employ them in meaningful ways for users and learners.

REFERENCES

Breuer, H. & Matsumoto, M., 2011. Ubiquitous Learning Environments: Notions of Context, Application Scenarios and Reflective Stories. In T. Bastiaens & M. Ebner (Eds.), Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2011 (pp. 2366-2374). Chesapeake, VA: AACE.

Breuer, H., & Steinhoff, F., 2010. Grounded Innovation – A Research Approach for the Fuzzy Front End of Innovation Management. Proceedings of BAI International Conference on Business and Innovation, Vol. 7 (ISSN 1729-9322). Kitakyushu, Japan.

Breuer, H., Hewing, M., & Steinhoff, F., 2009. Divergent innovation: Fostering and managing the fuzzy front end of innovation. PICMET 2009 Conference Technology Management in the Age of Fundamental Change, Portland, USA. Available from http://www.picmet.org

Breuer, H., & Matsumoto, M., 2008. Mobile Learning across Expanding Contexts. The 8th IEEE International Conference on Advanced Learning Technologies (ICALT), Spain.

Breuer, H., Baloian, N., Matsumoto, M. & Sousa, C., 2007. Interaction Design Patterns for Classroom Environments. HCI International Conference. Beijing, China. Lecture Notes in Computer Science. New York: Springer.

Christensen, C.M., Anthony, S.D., Berstell, G. and Nitterhouse, D., 2007. Finding the Right Job For Your Product. MIT Sloan Management Review.

Edelmann, W., 2000. Lernpsychologie / Psychology of Learning. Weinheim: Beltz Psychologie Verlags Union. Glaser, B.G. & Strauss, A.L. 1967. The Discovery of Grounded Theory. Strategies for Qualitative Research. Chicago:

Aldine Publishing Company. Goldenberg, J., Horowitz, R., Levav, A. and Mazursky, D., 2003. Finding your innovation sweet spot. In: Harvard

Business Review. Jungk, R. and Müllert, N., 1987. Future workshops: How to Create Desirable Futures. London. England, Institute for

Social Inventions, 1987. Jippling, M., Dieter, S., Krikker, J., & Sandro, S., 2001. Using handheld computers in the classroom: Laboratories and

collaboration with handheld machines. Proceedings of the 2001 SIGCSE, Technical Bulletin, 33 (1), pp.169-173. Patten, B., Sanchez, I. A., & Tangney, B., 2006. Designing collaborative, constructionist and contextual applications for

handheld devices. Computers & Education, 46, pp. 294–308. Steinhoff, F., & Breuer, H., 2009. Customer-centric open R&D and innovation in the telecommunication industry.

Proceedings of the 16th International Product Development Management Conference on Managing Dualities in the Innovation Journey. Twente, Netherlands.

Walker, K., 2006. Introduction: Mapping the Landscape of Mobile Learning. In M. Sharples (Ed.), Big Issues in Mobile Learning. Report of a workshop by the Kaleidoscope Network of Excellence Mobile Learning Initiative. Learning Sciences Research Institute. University of Nottingham.

ISBN: 978-972-8939-66-3 © 2012 IADIS

82

MOBILE DEVICES INCREASING OPPORTUNITIES FOR INFORMAL LEARNING AND SECOND LANGUAGE

ACQUISITION

Carl Storz1, Katherine Maillet1, Carine Brienne1, Laure Chotel1 and Catherine Dang2 1Institut Telecom, Telecom Ecole de Management, 9, rue Charles Fourier, 91011 – EVRY, France

2http://www.4nmedia.com

ABSTRACT

This paper provides the results from a study conducted in 2010-2011 on 638 French-speaking university students in order to identify how informal learning with English language media enhances English language acquisition and to identify the role that mobile technology plays in providing access to such media. By associating the respondents’ answers to the survey questions with their English language test scores we have been able to demonstrate that there is a positive correlation between a student’s level of English and the amount of time he/she spends learning English informally by consuming media and participating in social networks. The study indicated that only 13% of the time a student spends consuming English language media is spent using a mobile device. The students who participated in the survey give learning the lowest ranking amongst uses they have for mobile phones.

KEYWORDS

MALL, SLA, formal, non-formal and informal learning, TEL

1. INTRODUCTION

Much literature on Mobile Assisted Language Learning (MALL) discusses the potential of the mobile phone, especially pre-smartphone mobile terminals for mobile language learning rather than how actual use or how mobile access to resources have enhanced learning. The study presented in this paper was conducted within the framework of a research and development project called LIMED (Linguistic Meta-Educational Engine for Audiovisual Content) (www.limed.org) which aims to automatically generate listening comprehension quizzes to support English language learning with authentic video content accessible from a PC or a smartphone to exploit the potential of mobile technologies for language learning. The LIMED service targets young adults, students, and professionals working in France. This paper provides the results of a quantitative study designed to identify major trends in the individual English language learning paths in various learning contexts: formal, non-formal, informal, mobile and non-mobile amongst of a group of 638 French-speaking university students. Our research was intended to identify the importance of media in their personal learning paths, more particularly in mobile and informal learning contexts. Our overriding research question is: How does the consumption of media made available with mobile devices enhance second language acquisition? Our preliminary analysis would tend to indicate that the amount of time students spend learning English informally with English-language media and social networks can be positively correlated to the students’ performance on standardized tests of English like the Test of English as International Communication (TOEIC) or the Oxford Placement Test (OPT). While at the time of our study the most widely used form of access to media is via a non-mobile Internet device, this may change in the future as mobile devices are increasingly media-friendly and accessible in price. The frequency of mobile Internet access to media may surpass the frequency of non-mobile Internet access to media in the same way Internet access to media has surpassed non-networked access to media for the students who answered our questionnaire.

This paper is broken down into five parts. Part 2 deals with the conceptual framework and learning theories relevant for learning with mobile devices such as: mobile learning and MALL, formal, non-formal and informal learning. Part 3 presents the research methodology implemented for our study followed by a


83

presentation and discussion of the important results in part 4. Part 5 concludes the paper and offers future perspectives.

2. BACKGROUND

In this part we first introduce the motivation for conducting our study and the characteristics of the learner group under study. We assume that the Internet multiplies learning opportunities by providing access to comprehensible input (Krashen, 1985), thus enhancing second language acquisition (SLA). We highlight key concepts which relate to how technology enhances opportunities to learn with comprehensible input, namely: mobility, mobile learning, mobile assisted language learning, and the concepts of formal, non-formal and informal learning.

2.1 Motivation for Conducting the Study and Context

Our study was conducted on a group of 638 students aged 19 – 23 enrolled in Master’s degree programs in engineering and management in France. Prior to entry, the majority of students have followed a fairly standardized primary and secondary program of study as prescribed by the French Ministry of Education1 which requires all students to study two foreign languages. Entrance exams to Master’s programs in engineering and management include written and oral exams in foreign languages. Whereas their formal learning paths are fairly homogeneous for the majority of students, there is a great deal of disparity in their English language proficiency when they enter the Masters’ programs as measured by the Oxford Placement Test. Interviews with students would tend to indicate that there is a great deal of heterogeneity amongst their practices in non-formal and informal learning of English which could explain the disparity in their mastery. During the 80s and 90s the most commonly cited non-formal and informal English language learning opportunities were immersion, study programs, and internships abroad. Since the beginning of the 21st century an ever increasing number of students cite the importance of the “Internet” in providing learning opportunities, facilitating access to the foreign press, films, and television series. This observation motivated the investigation that we report on in this paper. Our aim is to measure and compare the time spent in formal, non-formal, and informal learning, consumption of various media types, behavior in accessing the media and the correlation with English language acquisition.

2.2 Mobile Learning and Mobile Assisted Language Learning

The meaning of the term mobility (See Traxler in Bachmair 2010, pp. 103-113) as used in mobile learning (ML) or mobile assisted language learning (MALL) has evolved over time. Mobility often refers to the mobile device, technology, systems or access via a portable, handheld, personal electronic device often connected to a network, i.e. Internet, thus enabling anytime, anywhere access to data, ICT tools and Web 2.0 applications (Chaka, 2009; Redecker and Punie, 2010). Mobility also refers to time and place (Kukulska-Hume, 2008), especially the imposed set or prescribed conditions of formal learning environments compared to freer conditions of informal environments. Sharples et al. (2007, p.225) define m-learning as the processes of coming to know through conversations across multiple contexts amongst people and personal interactive technologies.

MALL is often associated with computer assisted learning (CALL) although currently there is no specific learning theory which is characteristic of any one or differentiates these learning environments from basic learning. Each one offers features which may impact (Traxler, 2007) the learning process and ultimately the outcome as Kukulska-Hulme and Shield (2008, p.273) point out: MALL differs from computer-assisted language learning in its use of personal, portable devices that enable new ways of learning, emphasizing continuity or spontaneity of access and interaction across different contexts of use. Taylor (2006, p. 26) adds the overall context of contemporary society which he characterizes as a mobile age. As for learning theory,

1 Ministère Education nationale jeunesse vie associative. Baccalauréat générale: définitions des épreuves jusqu'à la session 2012 (http://eduscol.education.fr/cid46201/definitions-des-epreuves.html)

ISBN: 978-972-8939-66-3 © 2012 IADIS

84

any one or a number of them could provide the theoretical framework of ML resources depending on the: learners, their learning culture, objectives, content, time, place (See Naismith et al. 2004).

The language learning community has not yet massively taken up mobile technologies although there have been many small-scale experiments which aim to develop one or two specific skills such as vocabulary, listening comprehension, reading comprehension, or speaking and listening. Many applications are now available on AppStore but no research has shown learners’ actual use and learning outcomes (Godwin-Jones, 2011).

2.3 Formal, Non-Formal and Informal Learning

Much literature (Coombs 1968; Hrimech 1996; Shurugensky 2000; Livingstone 2000, 2001) classifies learning into three main categories with various characteristics. Generally speaking formal learning is the most socially recognized form entrusted to official institutions (schools or a school system) with structured learning objectives, a prescribed timeframe and various support. It is intentional on the learners’ part and leads to certification (European Commission 2010). Non-formal learning is offered by many types of organizations not officially recognized as learning institutions and does not lead to certification. It may also have structured objectives, be intentional on the learner’s part and have a predefined time framework. Informal learning corresponds to everyday life, i.e. activities whose main objective is not education (See Brougère and Ullmann 2009, esp. Ch. X on media). It is not structured, non intentional and does not lead to certification. In practice, borders between different forms are rather fuzzy, especially when mobility enters the picture as Kukulska-Hulme (2009) points out: “Irrespective of whether teachers decide to adopt new technologies in formal education, learners are found to be already using them to support aspects of their learning”. Some research indicates that mobile devices increase learners taking responsibility for their learning, defining needs and directing their learning (Kukulska-Hulme & Shield, 2008, Kukulska-Hulme, 2009), including life-long learning as well as possibilities of personalization of learning and learning resources.

3. METHODOLOGY – QUANTITATIVE SURVEY

The objective of our study is to identify the role that informal learning, more especially informal learning with the media, plays in second language acquisition and how mobile devices contribute to learning English. Opportunities to learn English informally abound in Europe where English is widely spoken as an international language and access to English language resources is made widely available by traditional and online media: television, radio, Internet, etc. Another goal was to identify the role that mobile devices play in facilitating learners’ access to English language media.

Our research is based on a quantitative study for which we used a questionnaire to collect data. The survey was designed to: (1) quantify the amount of time each student has spent throughout their lifetime learning English: formally, non-formally, and informally; (2) quantify the amount of time spent annually accessing English language media and the type of media most often accessed; (3) quantify the most frequently used forms of access to media: non-networked (print and electronic), non-mobile Internet, mobile Internet; (4) correlate the individual learning paths to the students’ level of English as identified by standardized tests; (5) evaluate how well equipped the students are with mobile devices and (6) evaluate the students’ perceptions about mobile devices as a tool for learning.

The quantitative survey was conducted during the 2010-2011 academic year and the beginning of the 2011-2012 academic year amongst the entire student body of 1,771 students enrolled in Master’s degree programs. The survey included 13 questions and was distributed in paper-based format during English classes and made available online. Questions covered English language learning experiences from formal training in elementary school through to university; non-formal training such as language classes outside the traditional school system, summer study abroad, home stays; informal learning in immersion in the form of work experiences, leisure activities, vacation; informal learning with media and new technologies. Most questions were closed; open-ended ones concerned the amount of time spent on different activities or examples of resources used. (See questionnaire at www.limed.org).


85

638 questionnaires were validated for analysis, the majority of which were collected in paper-based format during English classes. Questionnaires were correlated with students’ level of English: results from Test of English for International Communication (TOEIC) and Oxford Placement Test (OPT). We were able to correlate 263 questionnaires with TOEIC scores (Tannenbaum and Wylie, 2008) and 338 questionnaires with OPT scores (Allan, 2004) to the Common European Framework of References for Languages (CEFR)2. The TOEIC exam does not evaluate level C2. We do not have test results for 37 questionnaires; however we calculated these into the results concerning trends in use of technology to consume media (Figures 3 and 4). The majority of respondents were speakers of French, aged between 19 and 23 and are required to study English for their degree. Most of the students surveyed have spent approximately 10 years studying English in school from elementary school through higher education. The breakdown of respondents according to their level of English proficiency in terms of the CEFR based on TOEIC or OPT scores can be seen in Table 1:

Table 1. Distribution of students who participated in the survey according to their level of English

CEFR Level Number of students % A 30 5% B1 124 19% B2 237 37% C 210 33%

Students without standardized test score 37 6% TOTAL 638 100%

In order to best interpret the results of the quantitative survey, interviews are being conducted with sample sets of students representing the different English language levels.


The tables and charts in this section provide the preliminary results from our quantitative study. They illustrate the significant amount of time that students spend learning English informally either in immersion or with the media as compared to the amount of time spent learning English formally in school and the positive correlation with English language acquisition. Our findings would tend to indicate that access to English language media has a greater impact on English language acquisition than immersion. At the current time the participants in this study most often access media via non-mobile Internet devices rather than mobile devices.

4.1 Comparison of Hours Cumulated in Formal, Non-Formal, and Informal (Immersion) English Language Learning

Figure 1 compares the total number of hours spent by our respondents in formal, non-formal, and informal (immersion) learning contexts. Students provided information about their English language classes during their elementary, secondary, and tertiary schooling and the number of hours was calculated according to the official figures provided by the French Ministry of Education. We asked students to express the amount of time they spent in immersion as a number of weeks for which we counted 35 hours for each week in immersion.

Globally students have cumulated an average of 1045 hours learning English in a formal setting; the average total number of hours varies from 897 for B1s to 1204 for Cs. Curiously B1s cumulate fewer hours in formal learning than As (950 hours) yet they perform better on standardized tests.

The fact that B1s score higher on standardized tests than As could be explained by the time they spend learning English informally in immersion. At the time the questionnaire was conducted, the respondents had cumulated an average of 303 hours in immersion. On average As spent 88 hours in immersion while B1s spent almost twice as much time in immersion, 151 hours. Thus, Cs and B2s spent more time than the global average in immersion (12% and 11% respectively) while and B1s and As spent less than the average number of hours in immersion (50% and 71% respectively).

2 http://www.coe.int/t/dg4/linguistic/cadre_en.asp

ISBN: 978-972-8939-66-3 © 2012 IADIS

86

0 200 400 600 800 1000 1200 1400

A

B1

B2

C

CE

FR

Lev

el

Cumulated Number of Hours

Formel

Informel (Immersion)

Non-formel

Figure 1. Comparison of hours cumulated in formal, non-formal and informal learning: elementary school through university

4.2 Comparison of Hours Cumulated in Formal and Informal Learning (English Language Media and Social Networks)

Students were asked to identify the types of English language media they regularly consume and the average amount of time they work with the media. All the time estimates are expressed in number of hours per year. The results in Figure 2 would tend to indicate that there is a strong, positive correlation between the number of hours a student spends consuming English language media and his/her level of English. Annually students spend on average 95 hours in formal English language learning: Cs spend 102 hours per year, B2s 90 hours, B1s 88 hours, As 92 hours, reflecting the global number of hours each group has cumulated throughout their studies as seen previously in 4.1. Figure 2 illustrates the annual time students spend in formal learning, consumption of media and working with social networks. Compared to the figures for formal learning students spend a significantly greater amount of time each year consuming English media than in formal learning: AsX6; B1sX9; B2s and Cs X 10. Additionally, students with a better mastery of English (B1s, B2s and Cs) spend more time working in English language social networks than they do in formal learning: B1s 40% more time, B2s 50% more time, and Cs spend twice as much time, while As spend 20% less time working with social media than in formal learning. Thus, our study shows a positive correlation between the time students spend learning English informally with media and social networks and their level of English, measured by standardized tests.

0

200

400

600

800

1000

1200

1400

A B1 B2 C

CEFR Level

Ave

rag

e n

um

ber

of

ho

urs

per

yea

r

Informel (Réseaux Sociaux)

Informel (Medias)

Formel

Figure 2. Comparison of annual number of hours spent in formal and informal learning (media and social networks)


87

4.3 Personalization and access to English Language Media

Students were asked to identify the types of English language media they worked with most often and to indicate how they access the media. We identified three types of access to media: non-networked which includes paper-based and electronic media; non-mobile Internet access and mobile Internet access.

Concerning media consumption, most types of media in English are used to support informal, either out of the classroom or unintentional/incidental learning, but strong preferences for some English-language media emerge: 88% of the students listen to music, 83% watch films, and 82% watch television series, while only about 35% of the students read books and news or play video games. Figure 3 shows that students who listen to music spend an average of 414 hours per year, those who watch TV series an average of 148 hours per year, and those who watch films about 102 hours per year.

0 50 100 150 200 250 300 350 400 450

Number of hours spent each year working with media

News and documentaries

Specialised documentation

Learning resources

Reference resources

Press

Video games

Books

Films

TV series

Songs

Digital resources, mobileaccess (Personal portabledevices)

Digital resources, non-mobileinternet access

Non-networked resources(paper, CD, DVD, TV, etc.)

Figure 3. Types of English language media most often accessed by students and form of access: stand-alone, non-mobile Internet and mobile Internet

The results in Figure 3 indicate that all media types are still being accessed via non-networked supports (print and electronic), in fact this form of access represents 30% of the time students spend working with English-language media. 70% of the hours students spend accessing media is electronic and networked, 57% is non-mobile Internet and 13% is mobile. Thus the time spent accessing English-language media via “traditional” non-networked supports is still greater than mobile access. Books are an exception in the general preference among students for networked media. They are most often accessed in their traditional paper-based form, representing 59% of the time the students spend reading, although they are available in electronic format.

Students were asked to indicate the type of computing and mobile devices they owned. 89% of the students surveyed own a mobile phone, 68% have mobile phones with Internet access, and 4.2% of the students have a mobile tablet. We observe that although 51 to 55% of the students surveyed are adequately equipped to access the Internet with mobile devices, mobile Internet access only represents 13% of the time students spend accessing English media resources with mobile devices.

Students were asked to provide the titles of the media they listen to, watch, or read most often. The results reveal a wide variety of interest. 427 respondents gave examples of their favourite TV series. 987 titles of TV shows were cited representing 113 different titles. 403 students provided 752 film titles among which 267 different titles were cited. The wide variety of titles cited by students indicates the way in which they personalize their own informal learning.

4.4 Use of Mobile Devices for Learning

Students were asked to rank their use of mobile devices from 1 to 9 with 9 being the highest value for the most important use of the mobile device. Students most often use the currently established functions of mobile phones for communicating with others: telephone, SMS, MMS. Using mobile phones for information search/retrieval like GPS, e-books and Wikipedia are in second position. Among the nine uses of mobile devices that students could rank Learning got the lowest ranking. Although information retrieval from

ISBN: 978-972-8939-66-3 © 2012 IADIS

88

references like Wikipedia is frequently used by the students, they do not yet perceive the mobile device as a tool for learning.

0 1 2 3 4 5 6 7 8 9 10

Other

Learning

Games

Self-organisation (calendar, banking, job, etc.)

Recording (audio, video, photos , etc.)

Retrieving information (Wikipedia, e-books , podcasts , etc.)

Retrieving information about local surroundings (GPS, etc.)

Social networking (Facebook, Twitter, Blog, etc.)

Communicate with others (telephone, SMS, MMS, email , etc.)

Figure 4. Most frequent uses of mobile devices, ranked in order of importance

Mobility may offer advantages and opportunities for learning but it has not been massively taken up by the language learning community (Stockwell 2010; Chotel et al 2011) and learning (in the sense of formal courses or rather than informal learning such as accessing information, or learning how to use applications, etc.) is not one of the most frequent, daily uses of mobile technologies (Bachmair 2007; Stockwell 2008).

5. CONCLUSION

This paper presents the results of a quantitative study conducted amongst a group of 638 French-speaking university students which demonstrates that there is a strong, positive correlation between a student’s level of English and the amount of time he/she spends accessing English language media and working in social networks. The abundance of English language media provides a vast array of (comprehensible) input, allowing learners to personalize their informal English language acquisition. 70% of the hours students spend accessing media are spent accessing electronic media via the Internet. 57% of access to media is via is non-mobile Internet and 13% is mobile. Students do not yet perceive the mobile phone as a tool for learning. Currently we are following up the questionnaires with face-to-face semi-directed interviews to better understand answers to the questionnaire used in the quantitative study and how their experiences and learning paths have contributed to English language acquisition and the role that mobile devices contribute to language learning.

ACKNOWLEDGEMENT

This research was conducted within the framework of the LIMED project funded by the European Commission’s FEDER program and the Ile de France Region (www.limed.org).

REFERENCES

Allen, D. 2004. Oxford Placement Test 1 Test Pack. Oxford University Press, Oxford, New York. Bachmair, B., 2007. M-Learning and media use in everyday life. In: N. Pachler 2007. Mobile learning: towards a

research agenda, WLE Centre, IoE. London, England, pp. 105-153. Bachmair, B., 2010. Medienbildung in neuen Kulturräumen. VS-Verlag für Sozialwissenschaft, Wiesbaden, Germany. Brougère, G. and Ulmann, A.-L., 2009. Apprendre de la vie quotidienne. PUF, Paris.


89

Chaka, C., 2009. From Classical Mobile Learning to Mobile Web 2.0 Learning. In: R. Guy, 2009. The Evolution of Mobile Teaching and Learning. Information Science Press, Santa Rosa, USA, pp. 79-102.

Chotel, L. et al, 2011. Cas pratique d’apprentissage de l’anglais sur mobile et/ou PC : équipements technologique et pratiques d’étudiants et d’enseignants. Ludovia, Ax-Les-Thermes, France.

Coombs, P.H., 1968. La crise mondiale de l’éducation : analyse de systèmes. Paris, PUF; republished in 1989 Bruxelles, DeBoeck-Wesmael.

European Commission, 2010. Définitions de l’apprentissage formel, non formel, informel. http://ec.europa.eu/education/lifelong-learning-policy/doc52_fr.htm

Godwin Jones, R., 2011. Emerging Technologies: Mobile Apps for Language Learning. In Language Learning & Technology. Vol. 15, No. 1, pp. 2-11. http://llt.msu.edu/issues/june2011/emerging.pdf

Guy, R. ed., 2009. The Evolution of Mobile Teaching and Leaning. Information Science Press, Santa Rosa, USA. Hrimech, M., 1996. L'apprentissage informel : voie royale de l'autoformation. Les sciences de l'éducation pour l'ère

nouvelle, n. 39, Vol. 1-2, pp. 217-239. Krashen, S. D., 1985. The Input Hypothesis. Longman, London, England. Kukulska-Hulme, A., 2006. Mobile language learning now and in the future. In: P. Swenson, ed., Från vision till

praktik: Språkutbilding och Informationsteknik. Swedish Net University (Nätuniversitete), Sweden, pp. 295-310. http://oro.open.ac.uk/9542/1/kukulska-hulme.pdf

Kukulska-Hulme, A., and Shield, L., 2008. An Overview of Mobile Assisted Language Learning: can mobile devices support collaborative practice in speaking and listening? In Recall, Vol. 20, No. 3, pp. 271-289. http://oro.open.ac.uk/11617/1/S0958344008000335a.pdf

Kukulska-Hulme, A., 2009. Will mobile learning change language learning? In ReCALL, Vol. 21, No. 2, pp. 157–165. http://oro.open.ac.uk/16987/2/AKH_ReCALL_Will_mobile_learning_change_language_learning.pdf

Livingstone, D.W., 2000. Exploring the iceberg of adult learning: findings of the first Canadian survey of informal learning practices. NALL working paper #10-2000. http://webspace.oise.utoronto.ca/~living13/icebergs/index.html

Livingstone, D.W., 2001. Adults’ Informal Learning: Definitions, Findings, Gaps and Future Research. WALL Working Paper No.21, 2001. Centre for the Study of Education and Work. Department of Sociology and Equity Studies in Education, Toronto, Canada. https://tspace.library.utoronto.ca/retrieve/4484/21adultsinformallearning.pdf

Naismeth, L. P. et al, 2004. Literature Review in Mobile Technologies and Learning. Futurelab, Bristol. England. http://www.futurelab.org.uk/sites/default/files/Mobile_Technologies_and_Learning_review.pdf

Pachler, N., ed., 2007. Mobile learning: towards a research agenda. WLE Centre, IoE, London, England. Redecker C. and Punie, Y., 2010. Learning 2.0 Promoting Innovation in formal Education and Training in Europe. In EC-

TEL'10 Proceedings of the 5th European conference on Technology enhanced learning conference on Sustaining TEL: from innovation to learning and practice, pp. 308-325.

Redecker C. et al, 2010. Learning 2.0 – The Impact of Social Media on Learning in Europe (JRC Technical Notes). Office for Official Publications of the European Communities, Luxemburg, Luxemburg. http://ftp.jrc.es/EURdoc/JRC56958.pdf

Rudd, T., et al, 2006. Towards New Learning Networks. Futurelab, Bristol, England. http://www2.futurelab.org.uk/resources/documents/opening_education/Learning_Networks_report.pdf

Sharples, M., et al. 2007. Big Issues in mobile learning. LSRI, University of Nottingham, England. http://mlearning.noe-kaleidoscope.org/repository/BigIssues.pdf

Schugurensky, D., 2000. The Forms of Informal Learning: Towards a Conceptualization of the Field. NALL Working paper. www.nall.ca/res/19forms_of_informal.htm

Stockwell, G., 2008. Investigating learner preparedness for and usage patterns of mobile learning. In ReCall, Vol. 20, No. 3, pp. 253-270.

Stockwell, G., 2010. Using Mobile Phones for Vocabulary Activities: Examining the Effect of the Platform. In Language Learning & Technology, Vol. 14, No. 2, pp. 95-110.

Tannenbaum, R J. and, Wylie, E.C., 2008. Linking English-Language Test Scores Onto the Common European Framework of references: An Application of Standard-Setting Methodology. ETS, Princeton, USA.

Taylor, J., 2006. What are the appropriate methods for evaluating learning in mobile environments? Evaluating Mobile Learning In M. Sharples, ed., Big Issues in Mobile Learning. Kaleidoscope Network of Excellence, Mobile Learning Initiative, Nottingham, England, pp.26-29. http://mlearning.noe-kaleidoscope.org/repository/BigIssues.pdf

Traxler, J., 2007. Defining, Discussing, and Evaluating Mobile Learning: The moving finger writes and having writ… In International Review of Research in Open and Distance Learning. Vol. 8, No. 2, pp. 1-12. http://www.irrodl.org/index.php/irrodl/article/view/346/875

ISBN: 978-972-8939-66-3 © 2012 IADIS

90

DESIGN ACTIVITIES AND CONTRIBUTIONS IN THE CREATION OF IDEAS FOR EDUCATIONAL MOBILE

APPLICATIONS FOR SCHOOL-AGED CHILDREN

Tuula Nousiainen1, Marja Kankaanranta1 and Pekka Neittaanmäki2

University of Jyväskylä, - P.O. Box 35, FIN-40014 Finland 1Agora Center

2Department of Mathematical Information Technology

ABSTRACT

This paper examines the involvement of users in the development of educational mobile applications intended for school-aged children and young people. We present the user workshops carried out in two different projects: 1) a game-like mobile tool to support children’s zoo visits and 2) a self-monitoring tool to support students’ management of their everyday life routines. We examine these workshops and their outcomes based on a framework for design activities with children: we evaluate the types of design contributions of the workshops (context/content) and examine the issues related to their organization (management/engagement). The approach allowed the participants to choose their preferred form of expression when producing their design ideas, which yielded a versatile selection of different types of outcomes. On the dimension of design contributions, the outcomes produced a fairly balanced set of context- and content-related ideas. In terms of design activities, the importance of meaningful preliminary activities to set the context and give adequate starting points was highlighted; however, they could have emphasized aspects of mobility even more.

KEYWORDS

Mobile learning, user involvement, idea creation, design activities

1. INTRODUCTION

The participation of users is generally considered an important aspect in the design of technology, and active user involvement is recommended in order to achieve outcomes that satisfy the users and benefit the development process in other ways. User involvement and its effects have been explored in different ways. Involvement in a design process has been found to affect user satisfaction via improved system quality, but involvement per se can also have a direct positive value for users (Kujala 2008). Lynch and Gregor (2004) suggest that the important factor affecting system outcomes is not participation as such but its influence – which consists of the depth and the type of participation. In their review of studies on user involvement, Harris and Weistroffer (2009) identify the following points as the factors playing the key roles in successful user involvement: the degree, amount, and activities of user involvement; the complexity of the system being developed; management style; and the involvement of users with or without functional expertise. The meta-analysis of He and King (2008) suggests that the type of successful user participation depends on its ultimate goal: if the main goal is system acceptance, then the participation process should be designed so that it fosters psychological involvement in the users, while in cases where productivity improvements are being strived for, the participation should focus more on ensuring that it gives the developers the knowledge they need.

When it comes to user involvement in projects conducted with children, Mazzone et al. (2010) suggest a framework for analyzing the feasibility of design activities on two dimensions: whether the activities contribute to the outcome and whether they succeed in involving children in the design process. The framework, firstly, takes into account whether the primary contributions of a specific design activity are related to the context or the content of the design solution and, secondly, how aspects related to children’s engagement in the activity and researchers’ management in the organization of the activity manifest in the activities. As to how children are affected by design participation, Guha et al. (2010) point out that this aspect


91

has not been extensively explored yet. They suggest that design processes be studied using qualitative methods to gain a thorough understanding of the issue.

In this paper, we will discuss the design activities conducted with children in the design of two mobile applications. We describe the design workshops and the approaches used in them, and analyze the workshops based on the aforementioned framework by Mazzone et al. (2010), as we were interested in finding out what types of issues the use of this framework would reveal about the design activities. In accordance with the framework, we evaluate the types of design contributions (context/content) of the activities and examine the issues related to their organization (management/engagement). The two applications are 1) a zoo-themed game-like mobile tool for elementary school children and 2) a self-monitoring tool which aims to support lower secondary school students’ management of their everyday life routines, including sleep patterns, mood, eating habits, and school work.

The use of mobile tools in different contexts that entail a field trip to a museum, zoo, or another out-of-school setting has been shown to have positive results from different points of view. Sandberg et al. (2011) examined the effects on language learning when the use of a game-like mobile learning application (focusing on animal related content) was combined with a field trip to a zoo. They found that a mobile tool can motivate students to use it also in their free time and thereby bring added value to formal education by making use of informal learning contexts. Another encouraging result related to the use of mobile tools during field trips is their potential to enhance and facilitate topic-related interaction and communication between students (Cahill et al. 2011). A wide variety of different self-monitoring tools have been developed in the recent years to help people observe and keep track of different aspects of their lifestyles. Such applications have proven useful and beneficial for users, enabling them to identify and change their problem-maintaining behavioural patterns (e.g. Mattila et al. 2008). Children who are entering lower secondary school (i.e., in the Finnish context, starting 7th grade at the age of 13) are facing a major stage of transition both in terms of human development (cf. Erikson 1968) and school system. Such transitions set new kinds of challenges for the children in the management of their daily lives – which may manifest as irregular sleeping or eating patterns, trouble with focusing on schoolwork, etc. Therefore a mobile self-monitoring tool might be helpful in learning new ways of organizing the demands of everyday life and learning to be autonomous.

2. CONDUCTING THE STUDY

The design projects discussed in this paper are a part of a broader project which aims at developing mobile application concepts for the purposes of learning and well-being, aimed at diverse user groups. The key idea in the project is to use approaches that emphasize active user involvement throughout the development process. The focus of this paper is on analyzing the design workshops (their activities and outcomes) carried out in the two aforementioned case projects: the game-like mobile tool to support primary school classes’ zoo visits (later referred to as “zoo application”) and the self-monitoring tool to support secondary-school aged students’ management of their everyday life routines (later referred to as “self-monitoring application”). In the zoo application project, a third-grade class (age 9-10) from a local elementary school participated in the early design stage. In the project aiming to develop the self-monitoring application, two classes from a local lower secondary school (7th-graders, age 13-14) participated in the design process.

The principal research approaches applied in this study are case study research and development research (Yin 1994; Richey et al. 2004; van den Akker 1999). As regards development research, the primary context where it is usually employed is the research of educational interventions, addressing either the intervention itself, the process of developing it, or both (Richey et al. 2004; van den Akker 1999). In this paper, we will focus on the latter aspect, from the perspective of methods used to involve users in the process.

Both case study and development research require that the data collected and analyzed be extensive and versatile in order to document the process in detail and provide a rich description of the case being studied (e.g. van den Akker 1999; Yin 1994). The data used in this study consist of various types of design session outcomes and researchers’ field journals documenting the design sessions. The data are analyzed using the framework of Mazzone et al. (2010) as a general structure providing the main themes to be identified: from the design session outcomes, we will extract ideas falling into the categories of context-related and content-related ideas, while the field journals will provide data for identifying issues to describe the management of the design activities and the participants’ engagement in the activities.

ISBN: 978-972-8939-66-3 © 2012 IADIS

92

3. DESIGN ACTIVITIES IN THE CASE PROJECTS

In each of the projects, a workshop session was organized for the participants to generate ideas for the respective mobile applications. The themes and starting points for the workshops were established with the aid of certain preliminary activities carried out at the beginning of each project.

3.1 Preliminary Activities: Setting the Basis for The Workshops

The goal of the preliminary activities related to the zoo application – which was to consist of small games situated at different points of interest along the zoo route – was to lead the children to consider the context and the physical setting of the application. Prior to the workshop, the children went on a field trip to the zoo. The visit was part of their scheduled school activities while also giving us an opportunity to give the children some advance assignments. The children were given three questions to consider during the visit: 1) which animals they would like the games to address, 2) which were the most interesting and fun places in the zoo, and 3) which places were the least interesting. The main goal was to define which spots along the zoo route should be prioritized as target locations for games – either to assure that the games would be related to topics interesting to the children or, on the other hand, to bring something extra into less interesting locations.

For recording their ideas during the visit, the children were given copies of the zoo map, where they were instructed to mark their favourite and least favourite locations with smiley-face symbols. The principal reason for a simple smiley-face annotation was the desire to keep the annotation tasks as quick as possible so as not to take up too much time during the visit or distract their attention from the animals. Smiley-face based evaluation with children has been used before with good experiences. In technology projects, “smiley-o-meters” have been used as evaluation scales, helping children express their opinions on different aspects of fun in the applications being evaluated (Read et al. 2002; Read & MacFarlane 2006). In environmental design, pictures of happy or sad faces, or alternatively different colour tags, have been used by children to illustrate places with positive or negative connotations in their residential areas (Clark 2005; Kiili 2006).

After the zoo visit, the children’s annotations were discussed in class. With the teacher leading the activity, the children’s respective annotations were gathered into one shared zoo map displaying the collective ideas of the whole class. The collective map was discussed together, the children explaining the reasons for including certain animals or locations in it. Based on this, the class started discussing initial game ideas; in particular, what types of games would fit each location marked on the map. These ideas were gathered into mind maps in order for them to be used as starting points for the workshop session.

Regarding the self-monitoring tool, the aim was to determine the principal content themes around which the idea generation would concentrate. Initial needs were gathered with a questionnaire that inquired the students about different aspects of their well-being, school work, free time activities, social relations, and everyday life management in general. The aim was, firstly, to establish a baseline for studying the potential effects of the self-monitoring application to be developed, and secondly, to find out the most significant areas of the students’ everyday lives that would need to be addressed by such an application.

The most significant problem areas identified by the students included issues such as tiredness and sleep patterns, problems with paying attention in class and focusing on tasks, time management related to e.g. homework and upcoming exams, general restlessness or irritability, as well as some physical problems such as headache and neck pain. After corroborating these views with those of a team representing different groups of school staff (teachers, nurses, special educators, and psychologists), these issues served as the key themes and general starting points for the workshop phase.

3.2 Workshops: Generating Ideas for the Applications

Based on the outcomes of the preliminary activities described above, student workshop sessions were organized in both of the projects. The basic premise was the same in both workshops. The workshops had a certain set of starting points and themes around which the children brainstormed in groups. The modes of expression and the presentation forms of the outcomes of the brainstorming were not strictly pre-defined, however. Instead, the groups were given a chance to choose the type of outcome they wanted to produce.

Previous research has pointed out that it is important to allow children to be able to use multiple channels of expression in communicating their design ideas (e.g. Mazzone et al. 2010; Nousiainen 2008). Although


93

drawing, for example, is often considered to be something that is natural for children and generally enjoyed by them, it is not necessarily ideal for everyone, as some children may feel apprehensive about expressing their ideas by drawing if they feel that they are not very good at it (Nousiainen 2008). Storyboards and other formats resembling comic strips are structurally very familiar to children while also allowing the representation of temporal and spatial elements, and therefore a useful technique in presenting children’s ideas (Hall et al. 2004; Hart 1997). Similarly, different types of collages (Hart 1997; Verhaegh et al. 2006), idea maps (Nousiainen et al. 2008) as well as techniques based on drama or storytelling (e.g. Dindler et al. 2005) each lend their particular attributes to the variety of presentation forms. Diversity in design outcomes has been discovered to be useful for the developers as well. Having a wide range of outcomes of varying types and of different levels of abstraction is beneficial because it allows the developers to better use the products as sources of inspiration and draw ideas from them (Nousiainen 2008).

In the workshop for the zoo application, the children brainstormed elements of mini games to be included in the application. At the beginning of the session, the preliminary ideas from the previous session were quickly reviewed together as a starting point. The children set out to work in small groups, and they were told that they could produce their outcome in any format they preferred, such as a drawing, a textual description, or any other presentation form. Some of the children created drawings of their game idea, some made idea maps explaining different elements of their game, and some presented the idea in a written form. At the end of the session, each group presented their outcome to the rest of the class.

The aim of the workshops in the self-monitoring application project was to collect the students’ ideas on how to support their everyday life management with mobile technology. Two classes participated in the activity; a similar workshop was arranged with each of them. The workshop consisted of two parts, the first addressing school work related aspects of the application and the latter exploring a broader array of issues, including sleep, food, mood, and exercise. In this paper, we will focus on the first part of the workshop. A similar approach as the zoo application workshop was used, i.e. the students were free to determine the format of their brainstorming outcomes. The students worked in small groups, and they were given a list of keywords to help them get started with the idea creation. The keywords included items like exams, homework, lessons, and time management. The students were encouraged to use their imagination in presenting their ideas and to choose any format they liked for their workshop outcome. The types of the final outcomes included posters with bulleted lists of ideas, comic strips, and drawings. At the end of the workshop, the groups presented their ideas to the others.

4. RESULTS OF THE ANALYSIS OF THE DESIGN WORKSHOPS

This section presents the main findings from the analysis of the design workshops. We will first discuss the types of the outcomes produced by the children and then proceed to examine the design activities and outcomes, using the framework of Mazzone et al. (2010) as the core structure for the analysis.

4.1 Types of Outcomes

The third-graders’ workshop for the zoo application produced eight design outcomes altogether, and the seventh-graders’ workshops for the self-monitoring application yielded eleven final products. The types of the outcomes are summarized in Table 1 (one product could consist of more than one form of expression).

Table 1. Design outcomes from the workshops in each project

Form of expression Workshop

Zoo application (n=8) Self-monitoring application (n=11) Idea map 4 - Drawing, as an only presentation form 4 1 Textual scenario 1 - List 1 8 Drawing, as an illustration to a list - 5 Comic strip - 2

ISBN: 978-972-8939-66-3 © 2012 IADIS

94

There were differences in the preferred forms of expression between the two projects. In the zoo application workshop, idea maps and drawings were the most frequent presentation forms, while the ideas for the self-monitoring application were principally presented as categorized lists of items. Drawings were somewhat commonly present also in the outcomes of the latter workshops, but they were more in the role of illustrations or decorations rather than present ideas on their own. Comic strip format was used in two of the outcomes of the self-monitoring application workshops. Figure 1 presents examples of the design outcomes (a comic strip, an idea map, and a drawing).

Figure 1. Some examples of workshop session outcomes related to the self-monitoring application (left) and the zoo application (middle and right)

The different preferences are likely to reflect, on one hand, the age of the participants and, on the other hand, the type of the application being developed. While drawing is an everyday activity in different contexts in primary school, secondary school students are used to taking notes in the form of bulleted lists, and these commonplace classroom activities carry over to the design activities as well. Furthermore, drawings allow for both the visual and functional aspects to be equally displayed, both essential when representing a game idea.

4.2 Design Outcomes: Context and Content

The design session outcomes were analyzed using the framework for design activities with children suggested by Mazzone et al. (2010). In accordance with the dimensions of the framework, the workshops were first examined based on the contributions made by the outcomes: whether they provide abstract information that helps understand the design context or whether their contribution is more practical, giving concrete directions for content, e.g. specific functionalities (Mazzone et al. 2010). Figures 2 and 3 display the number of contributions falling into each category.

The principal contextual aspects highlighted in the game ideas for the zoo application (Figure 2) were related to the children’s preferences for different types of games and – especially in the outcomes produced in the form of idea maps – to the learning point of view, i.e. the topics which could be taught with games. A noteworthy issue is that the game ideas did not particularly highlight mobility in terms of context; they were very general in the sense that they could have been intended for any platform and to be played in any setting.

In the ideas for the self-monitoring application (Figure 3), on the other hand, the context-related dimension brought up issues related to the use environment and purposes of use. In almost every design outcome, the aspect of supporting the user’s memory was included in some way. Moreover, the outcomes highlighted the need to be able to interact with others, and also with other technology. Also, the notion that mobile technology is often used due to its entertaining qualities was evident in several of the outcomes, as was the fact that it allows one to employ multiple modalities when using it (e.g. using a mobile phone for listening to music or foreign language vocabulary). The outcomes created in comic strip format had one particular distinctive feature from the other presentation formats: they provided information on the physical environment as well.


95

Figure 2. Design contributions in terms of context and content in the zoo application

Figure 3. Design contributions in terms of context and content in the self-monitoring application

When it comes to the content dimension, the game ideas in the zoo application project (Figure 2) entailed specific ideas for characters (particular animals), scoring (mechanism for how the winner is determined and what the scoring units are), and game controls (which keys or commands are used to play the game). The degree to which the game controls were present in the outcomes was a somewhat surprising observation, and particularly interesting because it was clearly implied that the children still saw mobile phones as having physical keypads instead of touch screens.

In the self-monitoring application ideas (Figure 3), the content aspect was focused on bringing up examples of 1) standard features of mobile phones that could be utilized for the purposes of everyday life management (timer, calendar, alarm clock, etc.), 2) existing applications that could be used in this context (such as Facebook and other social media), 3) ideas for completely new applications (e.g. a game to be used in class), and 4) interaction techniques (similarly as above, most entailing the use of a physical keypad).

4.3 Design Activities: Management and Engagement

Besides the content/context dimension for examining the design outcomes, the other point of view in the framework of Mazzone et al. (2010) is the organization of the design activities, i.e. how they can be arranged in an effective and enjoyable way (the management/engagement dimension).

From the management perspective, one of the principal issues highlighted in the process was the importance of the preliminary activities and the relaying of their outcomes to the participants to serve as a basis for idea generation in the workshops. In the zoo application project, in particular, the succession of activities from the zoo visit and map annotation to the actual workshop helped the children gradually develop their ideas and situate them within the zoo theme. The variety in forms of expression yields a versatile array of outcomes, which is useful in the sense that they emphasize different aspects to different degrees and thereby avoid the problem of the design outcomes becoming too focused on a particular point of view. The active role of the teacher in the design session was important as well, as noted also by Mazzone et al. (2010). The participation of the teacher helps make the design activities understandable and clear to the children, be it about the wording of instructions, fine tuning the way of carrying out a certain activity, or even including an extra activity to help children express their ideas better. In this study, the teacher input was valuable e.g. in leading the merging of children’s individual map annotations into a collective one, helping students form groups, and asking clarifying and prompting questions during the idea generation especially with respect to keeping the children focused on the learning point of view. In terms of research-related issues, the value of detailed field notes was emphasized when going through the design session material.

ISBN: 978-972-8939-66-3 © 2012 IADIS

96

When it comes to children’s engagement in the design activities, the most significant point is related to what was also the main premise of the workshops: allowing children to choose their preferred format of expression. While certain types of formats did dominate the range of outcomes, not everybody wanted to produce their outcome in a certain way. Meaningful preliminary activities are important also from the perspective of engagement: for example, the zoo visit and the positioning of the game to the zoo environment concretized the task for the children and boosted their enthusiasm to let their ideas be heard. Moreover, although one might assume that having to consider the learning point of view would decrease the children’s motivation (cf. Nousiainen 2008), this is not necessarily the case. The children did not solely focus on the entertaining aspect of the games at the expense of learning goals, but were actively thinking about learning as well. The focus on learning and the audience of the games is illustrated in the following excerpt from the field notes documenting the children’s actions while working:

[…] the students seemed to keep in mind really well the ‘background requirements’ related to the nature and the theme of the game (the learning point of view, suitability for the whole family etc.). For example, when one group was discussing their game characters and someone mentioned that a hedgehog can defend itself with its spines, another member of the group pointed out, ‘it can’t be violent because there are, like, 5-year-olds and 4-year-olds [visiting the zoo and using the game]’.


In this paper, we have analyzed the outcomes and activities of design workshops conducted in two projects aiming to develop mobile tools for school-aged children. The approach where the students were allowed to choose their preferred formats of expression yielded a versatile selection of different types of outcomes. When analyzing these on the dimension of the design contributions, the outcomes yielded a fairly balanced set of context- and content-related ideas for design. From the perspective of conducting the design activities, the importance of meaningful preliminary activities to set the context and give adequate starting points for idea generation was highlighted, as well as the teacher’s valuable role in carrying out the design sessions.

When looking at the results particularly from the point of view of mobility, some interesting observations emerge. In the workshop focusing on the game-like application, the game ideas on a general level did not particularly reflect the fact that the games were intended to be mobile – it was only on the more specific level (i.e. which keys would be used to control the game) that mobility was integrated into the ideas. In the workshop related to the self-monitoring tool, the mobility aspect was more comprehensively present – covering issues such as physical environment and use contexts as well as interaction with other people and other technology. This is possibly at least partially due to the somewhat different nature of the two applications, and it is likely to be also related to the extent to which the prompts for the activities emphasized aspects such as location, broad use context, and more specific functionality. One interesting area to explore in further research would thus be related to the question how the preliminary activities – the significance of which was clearly shown – could support the participants to incorporate the point of view of mobility more integrally in their designs both on the more general and the more specific level.

Based on the workshop outcomes, working mobile-phone prototypes were developed. These will be field-tested and evaluated in real settings with different user groups.

ACKNOWLEDGEMENT

The work described in this paper is being carried out as a part of the project “Personal Mobile Space”, funded by the Finnish Funding Agency for Technology and Innovation (Tekes). The authors would like to thank the Kilpinen lower secondary school in Jyväskylä and the University of Jyväskylä Teacher Training School who participated in the activities, as well as the representatives of the Ähtäri Zoo and the City of Ähtäri.


97

REFERENCES

Cahill, C. et al, 2011. Mobile Learning in Museums: How Mobile Supports for Learning Influence Student Behavior. Proceedings of Interaction Design and Children 2011, Ann Arbor, MA, USA, pp. 21-28.

Clark, A., 2005. Listening to and involving young children: a review of research and practice. Early Child Development and Care, Vol. 175, No. 6, pp. 489–505.

Dindler, C. et al, 2005. Mission from Mars – a method for exploring user requirements from children in narrative space. Proceedings of the 2005 conference on Interaction design and children, Boulder, Colorado, USA, pp. 40–47.

Erikson, E, 1968. Identity: Youth and crisis. New York: Norton. Guha, M.L. et al, 2010. Investigating the Impact of Design Processes on Children. Proceedings of the 9th International

Conference on Interaction Design and Children (IDC '10). Barcelona, Spain, pp. 198-201. Hall, L. et al., 2004. Using storyboards to guide virtual world design. Proceedings of the 2004 conference on Interaction

design and children, College Park, Maryland, USA, pp. 125-126. Harris, M.A. and Weistroffer, H.R., 2009. A New Look at the Relationship between User Involvement in Systems

Development and System Success. Communications of the Association for Information Systems, Vol. 24, No. 1, pp. 739-756.

Hart, R.A., 1997. Children’s participation: the theory and practice of involving young citizens in community development and environmental care. London: Earthscan Publications.

He, J. and King, W.R., 2008. The Role of User Participation in Information Systems Development: Implications from a Meta-Analysis. Journal of Management Information Systems, Vol. 25, No. 1, pp. 301-331.

Kiili, J., 2006. Lasten osallistumisen voimavarat. Tutkimus Ipanoiden osallistumisesta. [Resources for children’s participation.] Jyväskylä Studies in Education, Psychology and Social Research 283, University of Jyväskylä, Jyväskylä, Finland.

Kujala, S., 2008. Effective user involvement in product development by improving the analysis of user needs. Behaviour & Information Technology, Vol. 27, No. 6, pp. 457-473.

Lynch, T. and Gregor, S., 2004. User participation in decision support systems development: influencing system outcomes. European Journal of Information Systems, Vol. 13, pp. 286-301.

Mattila, E. et al, 2008. Mobile Diary for Wellness Management – Results on Usage and Usability in Two User Studies. IEEE Transactions on Information Technology in Biomedicine, Vol. 12, No. 4, pp. 501-512.

Mazzone, E. et al, 2010. Considering context, content, management, and engagement in design activities with children. Proceedings of the 9th International Conference on Interaction Design and Children (IDC '10). Barcelona, Spain, pp. 108-117.

Nousiainen, T., 2008. Children's Involvement in the Design of Game-Based Learning Environments. Jyväskylä Studies in Computing 95, University of Jyväskylä, Jyväskylä, Finland.

Nousiainen, T. et al., 2008. User-centred design of Virtual Peatland for in-depth understanding of peatland ecosystems. Proceedings of the 13th International Peat Conference (IPC), Tullamore, Ireland.

Read, J. and MacFarlane, S., 2006. Using the fun toolkit and other survey methods to gather opinions in child computer interaction. Proceedings of the 2006 conference on Interaction design and children, Tampere, Finland, pp. 81-88.

Read, J. et al, 2002. Endurability, engagement and expectations: measuring children’s fun. Proceedings of Interaction Design and Children, International Workshop, Eindhoven, The Netherlands, pp. 189-198.

Richey, R.C. et al, 2004. Developmental research: studies of instructional design and development. In D. Jonassen (Ed.) Handbook of research for educational communications and technology (2nd ed.). Mahwah, NJ: Lawrence Erlbaum, pp. 1099-1130.

Sandberg, J. et al, 2011. Mobile English learning: An evidence-based study with fifth-graders. Computers & Education 57, pp. 1334-1347.

van den Akker, J. 1999. Principles and methods of development research. In J. van den Akker, R.M. Branch, K. Gustafsson, N. Nieveen & T. Plomp (Eds.) Design approaches and tools in education and training. Dordrecht: Kluwer, pp. 1-14.

Verhaegh, J. et al, 2006. On the design of Camelot, an outdoor game for children. Proceedings of the 2006 conference on Interaction design and children, Tampere, Finland, pp. 9-16.

Yin, R.K. 1994. Case study research: design and methods (2nd ed.). Thousand Oaks: Sage.

ISBN: 978-972-8939-66-3 © 2012 IADIS

98

MOBILE SELF-EFFICACY IN A CANADIAN NURSING EDUCATION PROGRAM

Richard F Kenny1, Jocelyne M.C. Van Neste-Kenny2, Pamela Burton2 and Caroline L. Park1 1Athabasca University - Courtenay, BC, Canada 2North Island College - Courtenay, BC, Canada

ABSTRACT

The purpose of this study was to assess the self-efficacy of nursing faculty and students related to their potential use of mobile technology and to ask what are the implications for their teaching and learning in practice education contexts. We used a cross-sectional survey design involving students and faculty in two nursing education programs in a Western Canadian college. 121 faculty members and students completed the survey in January, 2011. Results showed a high level of ownership and use of mobile devices among our respondents. Their median mobile self-efficacy score was 75 on a scale of 100, indicating that they are highly confident in their use of mobile technologies and prepared to engage in mobile learning.

KEYWORDS

Self-efficacy, motivation, mobile learning, nursing education, practice education

1. INTRODUCTION

Previously, we (Kenny, Park, Van Neste-Kenny, Burton, & Meiers, 2009a, 2009b, Park, Van Neste-Kenny, Burton, & Kenny, 2010) have argued that mobile learning (m-learning) could be effective to support the teaching and learning of nursing students at a distance. We subscribe to the definition of Koole (2009; Koole, McQuilkin & Ally, 2010) that m-learning is a process resulting from the interaction of mobile technologies, human learning capacities, and the social aspects of learning. In the nursing education context, m-learning supports more situated, experiential and contextualized learning and affords the use of up-to-date and accurate content and information (Kukulska-Hulme & Traxler, 2005). In nursing practice education, m-learning has the potential to bring the instructor, peers and resources together virtually at the point-of-care to support the students’ safety and evidence-informed practice (Park et al., 2010).

This study was intended to provide further information on the current state of the use of mobile technology in nursing education and on the readiness of nursing instructors and students to engage in m-learning, especially in nursing practice education. As such, this is a replication, on a larger and broader scale, of a previous study (Authors, 2010). As before, we were interested in our respondents’ level of motivation to engage in m-learning, and specifically, in the concept of self-efficacy (Bandura, 1997) as applied to mobile learning in nursing practice education.

Self-efficacy refers to the personal beliefs of individuals that they are capable of learning and performing particular behaviors and is domain specific (Bandura, 1997; Schunk, 2008). Students’ perceptions of self-efficacy have been found to influence their decisions about the choice of activity in which they engage, their emotional responses (e.g., stress and anxiety) when performing the behaviors, and their persistence in carrying out these actions (Bandura, 1997; Compeau & Higgins, 1995; Schunk, 2008). In the m-learning domain, mobile use is both enabled and constrained by the physical and functional components of the specific mobile devices. They are the medium through which learners interact and, therefore, impact their physical and psychological comfort levels (Koole, 2009). These components directly impact device usability and, therefore, individuals’ ability to use their mobile device to engage in cognitive tasks, to locate and manipulate information, and to communicate and collaborate using social technologies (e.g., text messaging, email or audio conferencing). In an m-learning context, these applications in turn allow learners to interact in


99

social and learning communities where they can acquire information and negotiate meaning. The ensemble of these components then defines the m-learning process and domain.

Individuals’ self-efficacy judgments differ on three interrelated dimensions: magnitude, strength, and generalizability (Bandura, 1997, 2006; Compeau & Higgins, 1995). Magnitude refers to the level of task difficulty individuals believe they can attain. Those with high mobile self-efficacy would believe they were able to use their mobiles to accomplish difficult and sophisticated tasks, while those with low mobile self-efficacy would see themselves as only able to use them for limited and simple tasks. Self-efficacy strength refers to the level of confidence that individuals have regarding their ability to perform specific tasks; e.g., their level of confidence in their ability to easily learn and use the various features of, and applications provided by, mobile devices. Finally, self-efficacy generalizability reflects how much an individual’s judgment is limited to a particular domain of activity. Individuals with high mobile self-efficacy generalizability would expect to be able to competently use a variety of different devices, while those with low computer self-efficacy generalizability may perceive their capabilities as limited to particular devices, especially those with which they have had experience.

While a significant body of research exists on learners’ feelings of self-efficacy concerning computer technology, online learning, and even podcasting (e.g., Compeau & Higgins, 1995; Hodges, Stackpole-Hodges, & Cox, 2008; Johnson, 2005; Kao & Tsai, 2009; Koh & Frick, 2009; Liang and Wu, 2010; Loftus, 2009), this concept does not yet appear to have been examined in any detail in a mobile learning context.

2. METHODOLOGY

This study, then, replicates and extends our previous research (Authors, 2010) to assess the self-efficacy of nursing faculty and students concerning their use of mobile devices and to address the implications for their teaching and learning in practice education contexts. Our research questions were:

� In what ways are faculty and students currently using personal mobile devices in their teaching and learning?

� How do they foresee using personal mobile devices in teaching and learning in the future? � To what degree is the level of mobile self-efficacy of nursing faculty and students related to their

potential use of m-technology in teaching and learning? To investigate these questions, we used a cross-sectional survey design involving students and faculty in

two separate nursing education programs at a community college in Western Canada: a one-year Practical Nurse (PN) program and a four-year Bachelor of Science in Nursing (BSN) program. At the time of the survey, there were 55 students and 9 faculty members in the PN program and 134 students and 18 faculty members in the BSN Program, for a total of 216 potential participants. We developed an online survey to gather demographic information and mobile use data and to administer a mobile use self-efficacy questionnaire.

Bandura (1997, 2006) stresses that self-efficacy should measure judgments of capability that may vary across specific realms of activity. Our mobile self-efficacy questionnaire was based on a computer self-efficacy instrument (Compeau and Higgins, 1995) modified for a mobile learning context. This consisted of changing the question stem from “I could complete the job using the software package...” to (for students), “If I had a mobile device such as a smart phone or 3G phone (e.g., iPhone), I could use it in my Nursing program…” For instance, the wording for students in Question 1 was “If I had a mobile device such as a smart phone or 3G phone (e.g., iPhone), I could use it in my Nursing program if there was no one around to tell me what to do as I go”. See Appendix A for the full set of questions. Bandura (2006) describes the assessment of self-efficacy as follows:

In the standard methodology for measuring self-efficacy beliefs, individuals are presented with items portraying different levels of task demands, and they rate the strength of their belief in their ability to execute the requisite activities. They record the strength of their efficacy beliefs on a 100-point scale, ranging in 10-unit intervals from 0 (“Cannot do”); through intermediate degrees of assurance, 50 (“Moderately certain can do”); to complete assurance, 100 (“Highly certain can do”) (p. 312).

As stipulated by Bandura, we asked our respondents to rate their confidence about the mobile use behaviour presented in each question from 0 – 10. If their answer was "No" (Could not do), they selected "0". If their answer was "Yes", they chose between 1 and 10, with "1" indicating only slight confidence and "10"

ISBN: 978-972-8939-66-3 © 2012 IADIS

100

showing total confidence (“Highly certain could do”). Therefore, the scale ranges from a minimum of 0 to a maximum of 100. Nursing students and instructors scoring 0 believe that they are essentially incapable of learning and using mobile devices in their teaching and learning and those scoring 100 believe they are highly certain of their ability to learn and use mobile devices for this purpose. Bandura (2006) also stresses the need for item homogeneity within a domain-relevant scale. Cronbach’s alpha was 0.941 indicating that the mobile version of the scale could be considered strongly internally consistent.

3. RESULTS

3.1 Demographic Information

121 faculty members and students completed the survey in January, 2011, for an overall response rate of 56%. Table 1 provides the breakdown of respondents by program type, status as faculty or student, and gender.

Table 1. Demographic Information

Factor Grouping N %

Program PN 38 31.4

BSN 83 68.6

Status Faculty 17 14.0

Students 104 86.0

Gender Male 12 9.9

Female 109 90.1

The BSN program was much larger than the PN program and provided over two thirds of the respondents

in this study. Ninety percent were female, while slightly fewer than 10% were male.

Table 2. Age Data by Program

Status-Year N Mean Min Max Skew BSN Students Year 1 23 27.17 19 43 .800 BSN Students Year 2 21 24.90 20 50 2.841 BSN Students Year 3 16 28.69 21 52 1.293 BSN Students Year 4 11 32.64 22 49 .779 PN Students 33 34.39 19 53 .092 Regular Faculty 14 50.50 43 61 .331 Sessional Faculty 3 41.00 31 50 -.467 Totals 121 32.49 19 61 .599

PN students were substantially older than the BSN students on average and more uniform in age. The mean ages of the BSN students varied from an average of about 25 in the Year 2 group to nearly 33 in the Year 4 group. Overall, our student respondents tended to be mature adults.

3.2 Mobile Ownership and Use

The familiarity of ownership should impact users’ assessment of their capability to use a mobile device and, therefore, mobile self-efficacy scores. Only 10 of our respondents (8%) - two faculty members and eight students - indicated that they did not own a mobile device. Table 3 shows which mobiles our respondents owned. About 15% owned a classic (phone only) mobile, while 27% had a phone with a camera or MP3 player. Twenty-two percent possessed a smart phone (e.g., a Blackberry), while 24% had a 3G phone (e.g., an Apple iPhone). Just under 12% had “other” devices (such as an Apple iPod Touch or iPad), which provided them with email and internet access and nursing applications.


101

Among students, the types of devices owned were relatively uniform across program groups. Twenty-eight percent of BSN students and 30% of PN students owned a mobile with camera, while 24% of BSN students and 27% of PN students had a 3G phone. Faculty had a lower level of ownership with 11% owning a camera phone and 15 percent possessing a 3G phone.

Table 3. Type of Mobile Owned

Mobile Type

TotalClassic CellCell / CameraSmart Phone3G PhoneOtherBSN Students Year 1BSN Students Year 2BSN Students Year 3BSN Students Year 4PN Students Regular Faculty Sessional Faculty

7 4 4 7 1 23 2 8 8 3 0 21 2 6 3 4 1 16 0 2 5 3 1 11 3 10 3 9 8 33 3 3 4 2 2 14 1 0 0 1 1 3

Total 18 33 27 29 14 121

To explain their mobile self-efficacy, it was also important to detail how faculty and students used their devices in their daily lives as well as in teaching and learning in order. Table 4 shows which mobile features our respondents used weekly. Not surprisingly, the majority (83%) of respondents used the telephone function of their mobiles the most.

The number was not 100% because some respondents indicated buying their mobiles for emergency purposes only and other respondents may have instead tended to text more than telephone since text messaging (SMS) was the second most widely used feature at72%. Just under half (45%) of our respondents used their mobiles weekly to browse the Internet, while over one third used them for photography (37 %) or to do email (36%), and 21% to play games. Other uses included recording videos in the lab, listening to music, using the address book, alarm clock and calendar features, and keeping memos and lists.

Table 4. Mobile device features used at least once a week

Program Faculty-Student

Telephone Camera Email Browser SMS Audio MSG

Word pro

Health apps

Games Other

BSN Faculty 8 2 6 6 7 0 1 1 1 3 Student 65 31 28 34 56 4 6 9 20 12 PN Faculty 4 1 1 1 2 0 0 1 0 1 Student 24 11 9 13 22 5 4 4 4 2 Totals 101 45 44 54 87 9 11 15 25 18

We also asked which features respondents used at least once weekly to support their learning or teaching (Table 5) and they reported this use to be about 65% of their total mobile use. Fifty-four percent used the telephone for educational purposes, while 39% used their devices for browsing and texting, and 30% for email. It was surprising that only 17% of this sample reported using their mobiles for health applications since, in our previous research (Authors, 2009a), nursing students rated drug reference programs as the most useful mobile feature.

Table 5. Mobile Features used in nursing education by program

Program Faculty-Student

Telephone Camera Email Browser SMS Audio MSG

Word pro

Health apps

Games Other

BSN Faculty 4 0 3 4 4 0 1 1 0 2 Student 44 12 24 28 32 1 8 11 0 8 PN Faculty 3 0 1 1 0 0 0 1 0 0 Student 14 7 8 14 11 3 5 7 2 4 Totals 65 19 36 47 47 4 14 20 2 14

3.3 The Potential Use of Mobile Devices in Teaching and Learning

In the demographics section of the survey, our respondents were also asked to answer an open-ended question: What do you see as the potential uses of these technologies to support teaching and learning in the

ISBN: 978-972-8939-66-3 © 2012 IADIS

102

practice area? While space does not permit a full presentation of our qualitative data, we can report that our respondents made a wide range of comments about the perceived benefits and barriers to the use of mobile devices in their teaching and learning. This section presents the most common benefits and barriers expressed by the BSN faculty and students, who made up over two thirds of our respondents.

One major benefit noted by faculty and students for their teaching and learning was the use of mobile devices to provide quick, easy, and anytime access to current, professional information at the point of care. This included both the use of nursing resource applications such as drug guides and access to the Internet. This perceived importance of the use of mobiles to access resources is also supported by past research and our own studies (Authors, 2009a, 2009b). These comments by BSN students typify the comments made in this regard:

Technology can support nursing practice such as accessing current information quickly to support practice decisions, reducing errors (i.e., using programs to check drugs and calculate doses).

And If downloading is time effective, it can allow for faster access to information without having to track

down books or hardcopy resources. The information will be up-to-date. It can be accessed from the patient’s bedside for teaching and learning based on specific questions by the patient.

The other main benefit cited by our respondents was the use of mobile devices to improve communications between faculty and students who are off campus in practice placements and, therefore, to afford students greater access to their instructors. In this regard, one instructor noted that mobile devices could provide:

Instant communication with students (i.e., texting/emails) - texting re "checking in" with students who are in indirect supervision (i.e., community placements) - using blackboard to send messages to students, receive documents from them (i.e., domains of practice) -use of nursing resource software to support myself and students in the practice setting (i.e., medication software, psychomotor skills, nursing assessment) -access best evidence to support practice (i.e., databases to search for information related to practice).

And a BSN student noted that mobile devices could provide “support from teachers, we have two towns primarily that we are sent to for placements and our instructors may not be immediately available. We could get quick responses and support from them if we had communication on these devices.”

But our respondents also reported on barriers to the use of mobile devices in their teaching and learning. The most widely barrier discussed was the cost of both mobile devices and of wireless connectivity and who should pay for it. For instance, one BSN student asked “Not all people have these types of devices - they can be costly- with roaming time as well - will VIHA [Vancouver Island Health Authority, which runs the local hospitals and clinics] help in paying these bills? - will everyone be expected to have one?”

Our respondents also noted potential barriers pertaining to mobile use in the hospitals. One was a concern about infection control. One BSN faculty member commented that “[I] just wonder about infection control issues with these devices in the clinical setting, I can see this as being an issue and also wonder if the cleaning products required by the agency would damage the devices?” Another concern was about current hospital policies related to mobile use. Another BSN faculty raised this issue as follows:

Hmmmm... I think we need to inform and educate our colleagues in the agencies about the use of technology, that in fact using a cell phone near a cardiac monitor is not going to upset the monitor, nor will it upset communications, etc., within the hospital particularly. (I think this is true and I think there is a need to assure people that it is not going to get in the way of their practice...

And finally, while not a benefit or barrier per se, some faculty members discussed the overall need to adjust their teaching to take into account the mobile technology that their students are using in their daily lives. For instance, one BSN faculty member stated that:

Students are very comfortable with technology these days and it is very much the norm at breaks and meal times to see them pull out their phones or mobile device and start to text and so forth. Many students have pointed out applications to me in these settings which they frequently use to support their learning, such as drug guides or "apps" which quickly remind them of vital sign norms and so forth. I want to understand them and be able to relate on their level. I want to be able to communicate with them and not appear that I don't know. I also want to maintain a sense of where they are at and without understanding the technology that they use and how this influences their learning, I would feel somewhat of a disconnect. I am not saying that it surpasses other ways of teaching, but for them it is the new 'normal' and I must adjust to it to help support/understand them as well as using other teaching/learning techniques.


103

3.4 Self-Efficacy

Most of our respondents reported owning a mobile device and most used it weekly at least to make telephone calls. How did such familiarity with mobile use translate into feelings of self-efficacy? The average mobile self-efficacy score (Table 6) was 68 out of total possible score of 100. However, these scores were negatively skewed indicating a tendency to higher scores with individual lower scores affecting the average. Therefore, the median score of 75 is likely more reflective of the group as a whole.

Table 6. Self-Efficacy Scores – Program Comparison (Faculty – Student combined)

Program N Mean Median Std. Dev. Min Max Skew BSN 83 72.16 79.00 24.523 5 100 -1.014 PN 38 58.92 64.50 29.357 0 100 -.624 Total 121 68.00 75.00 26.734 0 100 -.898

There was also a substantive difference between programs. BSN students and faculty had a mean score of over 13 points higher than PN program members (72.16 as opposed to 58.92). An analysis of variance (Table 7) showed the mean self–efficacy scores between programs to be statistically significant at the α ≤ .01 level.

Table 7. Self-Efficacy Scores by Program ANOVA results

Sum of Squares df

Mean Square F Sig.

SE Score * Program Between Groups (Combined) Within Groups Total

4566.273 1 4566.273 6.692 .011 81197.727 119 682.334 85764.000 120

Table 8 compares the mean mobile self-efficacy scores by faculty and student. The mean student self-efficacy scores were higher than those of the faculty, but faculty median scores were higher, indicating that the faculty means were likely affected by an outlier. However, an ANOVA showed no statistically significant differences between the self-efficacy scores of these two groups.

Table 8. Self-Efficacy Scores - Faculty-Student Comparison

Faculty-Student N Mean Median Std. Dev. Min Max Skew Faculty 17 62.12 80.00 35.173 0 100 -.635 Student 104 68.96 74.50 25.176 0 100 -.913 Total 121 68.00 75.00 26.734 0 100 -.898

A Pearson’s r correlation between age and self-efficacy was -0.145. While this mild negative association indicated self-efficacy scores tended to be higher on average for the lower age groups, this relationship was not statistically significant.

4. CONCLUSION

M-learning has the potential to bring the instructor, peers and resources together virtually at the point-of-care to support the students’ safety and evidence-informed practice. This study assessed the current use of mobile technology by faculty and students in nursing education and investigated their predisposition to use this new technology in their teaching and learning.

Our first research question asked in what ways faculty and students were currently using personal mobile devices in their teaching and learning. The results of the demographics portion of our survey revealed that most respondents owned mobile devices and that nearly half (46%) owned smart phones or 3G devices. Furthermore, the ownership of these more sophisticated mobiles was spread fairly evenly across the groups and all ages. While our respondents’ used their mobiles weekly and predominantly for communications (cell phone, texting and email), they also used them regularly for a range of other activities, including web browsing, photography, word processing and health applications. More importantly, nearly two thirds (65%) of the time, our respondents used their mobiles in their teaching and learning. This data alone indicates that

ISBN: 978-972-8939-66-3 © 2012 IADIS

104

our respondents were not only predisposed to use mobile devices in nursing education, they have already begun to do so.

Our second research question queried how our respondents foresaw using mobile devices in their teaching and learning in the future? This question was addressed most specifically by our respondents’ replies to the open-ended question asking their views about the potential uses of these technologies to support teaching and learning in the practice area. They pointed out both benefits and barriers to such use. Among the benefits were just in time access to current, professional information at the point of care and improved communications between students and faculty, especially while students are out in clinical practice placements. Among the barriers to use of mobile devices were the cost of purchasing a device and for wireless connectivity, as well as issues of infection control and adhering to current hospital policies.

And finally, we also asked to what degree is the level of mobile self-efficacy of nursing faculty and students related to their potential use of m-technology in teaching and learning? Self-efficacy refers to individuals’ personal beliefs that they are capable of learning and performing particular behaviors. The stronger the sense of personal efficacy they possess, the greater will be their perseverance and the higher the likelihood that they will perform the chosen activity successfully (Bandura, 1997; Compeau & Higgins, 1995). The mean self-efficacy score for our respondents was 75, a rating that reflects a high level of confidence in their ability to use mobile technology.

These self-efficacy levels, however, were significantly different between program groups with BSN students and faculty an average difference of 13 points higher than PN students and faculty. Since, the PN program is a one year certificate, while the BSN is a four year, baccalaureate, program, it is possible that higher levels of education and experience could contribute strongly to an individual’s sense of mobile self-efficacy in learning contexts. No other comparisons resulted in significant differences. There was no discernible difference in mobile self-efficacy between faculty and students. While there was a slight relationship between age and self-efficacy in favor of younger respondents, this correlation was not statistically significant. It appears then that nursing faculty and students are familiar with the use of mobile technology and a substantial proportion is very comfortable using the various functionalities these devices afford. Therefore, it is reasonable to conclude that nursing students and faculty, as represented by our respondents, are well prepared and strongly motivated to engage in mobile learning.

REFERENCES

Bandura, A. (1997) Self-efficacy: The exercise of control. W.H. Freeman and Company. New York, NY. Bandura, A., 2006. Guide for constructing self-efficacy scales. In: Pajares,F. and Urdan, T. (Eds.), Self-efficacy Beliefs of

Adolescents (pp. 307–337). Information Age Publishing, Greenwich, CT. Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS

Quarterly, Vol. 19, No.2, pp. 189-211. Hodges, C.B., Stackpole-Hodges, C.L. & Cox, K.M. (2008). Self-efficacy, self-regulation, and cognitive style as

predictors of achievement with podcast instruction. Journal of Educational Computing Research, Vol. 38, No.2, pp. 139-153.

Johnson, R. D. (2005). An empirical investigation of sources of application-specific computer-self-efficacy and mediators of the efficacy—performance relationship. International Journal of Human-Computer Studies, Vol. 62, No.6, pp. 737-758.

Kao, C-P & Tsai, C-C. (2009). Teachers’ attitudes toward web-based professional development, with relation to Internet self-efficacy and beliefs about web-based learning. Computers and Education, Vol. 53, pp. 66–73.

Kenny, R.F., Park, C.L., Van Neste-Kenny, J.M.C., Burton, P.A. & Meiers, J. (2009a). Using mobile learning to enhance the quality of nursing practice education. In M. Ally (Ed.), Mobile Learning: Transforming the Delivery of Education and Training. Athabasca, AB: Athabasca University Press.

Kenny, R.F., Park, C.L, Van Neste-Kenny, J.M.C., Burton, P.A., and Meiers, J. (2009b). Mobile Learning in Nursing Practice Education: Applying Koole's FRAME model. Journal of Distance Education, 23(3), 75 – 96. Available: http://www.jofde.ca/index.php/jde/article/view/599

Park, C.L., Van Neste-Kenny, J.M.C., Burton, P.A. & Kenny, R.F. (2010). A model of mobile faculty presence in nursing education practice. Canadian Journal of Nursing Informatics, 5(3), 21-42. Available: http://cjni.net/Journal_original/Summer2010/Park.pdf


105

Koh, J.L. and Frick, T.W. (2009). Instructor and student classroom interactions during technology skills instruction for facilitating preservice teachers’ computer self-efficacy. Journal of Educational Computing Research, Vol. 40, No.2, pp. 211-228.

Koole, M. L. (2009). A model for framing mobile learning. In M. Ally (Ed.), Mobile Learning: Transforming the Delivery of Education and Training. Athabasca University Press, Athabasca, AB.

Koole, M.L., McQuilkin, J.L., and Ally, M. (2010). Mobile Learning in Distance Education: Utility or Futility? Journal of Distance Education, Vol. 24, No. 2, pp. 59-82. Available: http://www.jofde.ca/index.php/jde/article/view/644

Kukulska-Hulme, A., & Traxler, J. (2005). Mobile teaching and learning. In A. Kukulska-Hulme, A. & J. Traxler (Eds.). Mobile learning: A handbook for educators and trainers (pp. 25-44). Routledge, London.

Liang, J-C. & Wu, S-H. (2010). Nurses’ motivations for Web-based learning and the role of Internet self-efficacy. Innovations in Education and Teaching International, Vol. 47, No.1, pp. 25–37.

Loftus, J. (2009). Factors affecting implementation of educational media casting as an instructional resource in distance education. Unpublished Master’s thesis. Athabasca University, Athabasca, AB. Available: http://library.athabascau.ca/drr/searchdtr.php?textfield=Loftus&Submit=Find&subj=45&cnum=205

Schunk, D.H. (2008) Learning theories: An educational perspective (5th Ed.). Pearson Education, Upper Saddle Hill, NJ.

APPENDIX A: MOBILE SELF-EFFICACY SCALE QUESTIONS

If I had a mobile device such as a smart phone or 3G phone (e.g., iPhone), I could use it in my Nursing instruction…

Q1 ...if there was no one around to tell me what to do as I go. Q2 ...even if I had never used a device like it before. Q3 ...if I had only the device manual for reference. Q4 ...if I had seen someone else using it before trying it myself. Q5 ...if I could call someone for help if I got stuck. Q6 ...if someone else had helped me get started. Q7 ...if I had a lot of time to complete the task for which the device was provided. Q8 ...if I had just the built-in help facility for assistance. Q9 ...if someone showed me how to do it first. Q10 …if I had used similar devices before this one to do the same task.

ISBN: 978-972-8939-66-3 © 2012 IADIS

106

APPLYING MLEARNING IN SOFTWARE ENGINEERING EDUCATION: A SURVEY OF MOBILE USAGE

April Macphail, Thomas Hainey and Thomas. M. Connolly School of Computing, University of the West of Scotland

ABSTRACT Requirements collection and analysis is fundamental in software engineering education across various different modules at tertiary level. It is a highly important part of the software development lifecycle and the database application lifecycle and is vital for the success of any software project regardless of size and complexity. In terms of preparing graduates for real life software development projects, traditional teaching approaches such as tutorials, lectures and exams have been considered to be insufficient. Supplementary teaching approaches such as games-based learning have been used in the field of requirements collection and analysis recently to attempt to address this problem. Mobile learning (mLearning) is another form of supplementary learning that has the potential to enrich the learning process, however, like games-based learning, mLearning suffers from a lack of empirical evidence in terms of its effectiveness. In order to gauge the suitability of mLearning for teaching in tertiary education level a survey was constructed and deployed to gather empirical evidence regarding use, use for learning and perceived suitability in different contexts. This paper presents the findings of a literature review to ascertain the state of empirical evidence in the field of mLearning and will also present the analysis of the data obtained using the mobile technologies questionnaire.

KEYWORDS

Mobile learning, mLearning, Software engineering, requirements collection and analysis, mobile devices

1. INTRODUCTION

Requirements collection and analysis is fundamental in software engineering education across various different modules at tertiary level (Nuseibeh & Easterbrook, 2001). It is a highly important part of the software development lifecycle and the database application lifecycle and is vital for the success of any software project regardless of size and complexity. This paper will present empirical evidence in the field of mLearning through a survey performed to gauge the suitability of a mLearning approach to teach requirements collection and analysis at tertiary education level. The paper will have the following sections: firstly, a review of previous work discussing the empirical evidence gathered during a literature search associated with mLearning and requirements collection and analysis. Secondly, the data obtained from the mobile technology questionnaire will be discussed in terms of procedures used, participants and the material used. The material was split into three sections covering (i) demographics, (ii) mobile devices, their usage and the participants overall views on the devices and (iii) participants’ views towards mobile technologies for learning and in particular their views on what makes a device suitable for use within mLearning and how they would like to see mLearning material delivered. Finally, there will be a discussion of the results and future research directions for the project that have been identified from the results.

2. PREVIOUS WORK

mLearning can provide the rapid dissemination of information anytime and anywhere, however little research has been undertaken to ascertain the effectiveness of such learning resulting a lack of empirical evidence supporting these claims. To address this problem, a review was undertaken to identify the existing studies that contained either qualitative or quantitative data associated with the use of mLearning within tertiary education. The search was undertaken using the following search terms:


107

“(mobile OR mLearning OR podcast OR mHealth OR iPhone Or Android OR smartphone) AND (learning or education) AND (evaluation OR impacts OR outcomes OR assessment)”

The search period was constrained from 2000 to the present. The starting year for the literature review was selected as 2000 as mobile technologies that were capable of being used as a teaching tool within mLearning did not start evolving until the middle of 1999. The search was performed on a wide variety of databases that include mobile learning and mobile technologies. The search was performed using the following electronic databases: Science Direct, ACM, Emerald, ERIC, Blackwell synergy, IngentaConnect, InformaWorld, PsycINFO, EBSCO, ICTE, IEEE and Infotrac (Expanded Academic ASAP). Concentrating the search to filter on Title, Abstract and Keywords identified several hundred relevant papers. Only 23 papers contained either quantitative or qualitative empirical evidence. However, only a few were relevant as many focused on the evaluation of the software, as shown by Corlett, Sharples, Bull & Chan (2005), the need and usefulness of mobile devices being utilised by the students (Anaraki, 2007) and software platforms used for mobile learning evaluated for user friendliness and technical feasibility to name but a few.

mLearning has been around for many years but has yet to be fully embraced by either educational institutes or students. While there is some evidence available to support the effectiveness of mLearning there is little empirical evidence available for the use of mLearning within computing subjects and none has yet been identified involving requirements collection and analysis. Providing empirical evidence could be key to improve the popularity of mLearning. Relevant studies identified from the literature reviews have shown very little empirical evidence supporting that mLearning is an effective learning tool. Table 1 shows the empirical evidence that was gathered from the literature review on the effectiveness of mLearning.

Table 1. Summary of empirical evidence generated from Literature Review

Author Discipline Anaraki (2007) Management and ICT Master programs Corlett et al. (2005) MSc students Chao & Chen (2009) First year students enrolled in an Introduction to Computer Science Ferenchick, Fetters & Carse (2008) Undergraduate Medical students Georgieva et al. (2011) Language students Hwang & Chang (2011) Culture course (southern Taiwan) Jarvis & Dickie (2010) Physical geography and GIScience in particular. Shantikumar (2009) Medicine

In terms of comparisons with traditional teaching approaches, Chao and Chen (2009) performed a 6-week study to discover the differences when using two reading vehicles. This showed that while using a mobile phone to augment paper-based learning is possible and appears to promote the application of precise note taking as well as the ability to post comprehension questions for discussion, the results also indicated that subsequent learning improvement among the students were inconsistent. Further research in this field is required to evaluate the student’s attitudes and views on mobile technologies and mobile learning. For mobile learning to be embraced by the students we must ensure that it is being delivered using both a suitable device and method, this can only be accomplished through consultation with students. If these factors are not considered, students may find it difficult to embrace learning using a different style.

2.1 Requirements Collection and Analysis for Software Engineering

Requirements collection and analysis is an important part of software development but has been described as the weak link in many software projects (Nuseibeh & Easterbrook, 2001). This is due to the many inherent difficulties ranging from the variance of goals set by numerous stakeholders to the complexity of the problem. A number of issues surrounding the teaching of requirement collection and analysis using traditional methods were highlighted as, the complexity grows rather than decreases as a project develops, effective problem-solving skills are needed along with the formation of metacognitive strategies which are fundamental (Armarego & Roy, 2004). Shaw and Dermoudy (2005) believe that students have little understanding for the essentials of software engineering and students are not engaged enough through the use of traditional teaching methods such as lectures. A simulation game was introduced with the aim of providing students with a better understanding and appreciation of the software development process through the use of a graphical and entertaining environment. The results indicated that the students found the game to be both relatively easy and enjoyable to play and suggested that 67% of participants believed that it had the capability to teach software development processes well (Shaw & Dermoudy, 2005). As requirements collection and

ISBN: 978-972-8939-66-3 © 2012 IADIS

108

analysis and more generally software engineering are abstract subjects, it is important to understand the specific difficulties associated with teaching a subject of an abstract nature. Schön (1983, 1987) highlighted the following key problems in teaching an abstract subject of this nature:

• It is learnable but not didactically or discursively teachable: it can be learned only in and through practical operations.

• It is a holistic skill and parts cannot be learned in isolation but by experiencing it in action. • It depends upon the ability to recognise desirable and undesirable qualities of the discovered world.

However, this recognition is not something that can be described to learners, instead it must be learned by doing.

• It is a creative process in which a designer comes to see and do things in new ways. Therefore, no prior description of it can take the place of learning by doing.

It is also necessary to understand the advantages and disadvantages of traditional teaching approaches. A number of studies’ identified problems with teaching requirements collection and analysis concerning traditional teaching methods approach (Brooks, 1987). Some studies that have investigated traditional teaching methods have been highlighted within Bonwell (1996), Cashin (1985), Adprima instructional methods information website (2009), Andrianoff and Levine (2002), Cope and Horan (1996), Bernstein and Klappholz (2001) and Connolly, Stansfield, McLellan, Ramsay and Sutherland (2004).

3. METHODS USED TO COLLECT DATA IN THE STUDY

The primary reason for performing this study was to collect useful information on the mobile devices that are currently being used by students. This was considered extremely important as it will aid the design and development of any prototype ensuring the developed application would be accepted.

Participants 321 participants completed the Mobile Learning (mLearning) and Mobile Technologies Questionnaire.

240 participants (75%) were male and 79 participants (25%) were female. The average age was 28.34 years (SD = 8.93) with a range of 19 to 54.5. A Mann-Whitney U test revealed no significant different in age in relation to gender (Z = -1.792, p < 0.073). 300 respondents (93%) were students at Higher Education (HE) level and 21 participants (7%) were students at Further Education (FE). On average participants were on their 2nd year of study in their current course (SD = 1.11) with a range of 1 to 5. A Mann-Whitney U test indicated that males were in a significantly higher level of study than females (Z = -2.657, p < 0.008). 305 participants (95%) stated their courses were currently taught by traditional teaching approaches (lectures, tutorials, labs), 22 participants (7%) stated their current courses were taught using distance learning and 1 (0.003%) participant stated their course was currently taught using mobile learning.

Materials Questionnaire: As well as demographic questions, mobile device specific questions were asked including

whether participants owned a mobile phone or smart phone. The questionnaire asked participants to rate their happiness of the attributes of the devices they owned and to rate how often they used their main device for different activities. The questionnaire also asked participants to rate to what extent mLearning would be suitable for teaching computing and if they believed that mLearning would replace or supplement traditional teaching approaches. The questionnaire also asked participants to rate the following: the suitability of different delivery methods for mLearning, how important they believed different mLearning attributes were, how often they used different devices for learning, how suitability they were for learning, preventative factors associated with the devices and the importance of their features for learning.

Procedure The questionnaire was performed at Further Education (FE) and Higher Education (HE) in October 2011.

The questionnaire was made available online through SurveyMonkey and was available for a two-week period. Participants were informed of the questionnaire through email and a notice posted on The University of the West of Scotland’s Virtual Learning Portal (Blackboard). Participation was voluntary.


109

4. RESULTS

4.1 Mobile Devices

The majority of participants (313, 98%) stated that they owned a mobile phone or smart phone, while 8 participants (2%) stated that they owned neither. Those who do not own any mobile device gave the following two main reasons: the cost and not wanting to be contactable every minute of every day. 211 participants (66%) stated that their main device was a smartphone and 102 participants (32%) stated that their main device was a mobile phone. The most popular mobile devices were used by 183 participants (70%) and were Android-based, 52 devices (20%) were Apple-based and 25 (10%) were Blackberry.

Mobile phone users were asked if they would consider moving to a smartphone with additional features such as sending and receiving emails and the ability to access office documents. 55 participants (52.8%) indicated they would like to move over to a smartphone while the remaining 45 (47.2%) were happy to continue with their current mobile phones. For the participants who wished to move to a smartphone 61 (64.2%) would like to move within 6-12 months. The cost involved with changing over from mobile phones to smartphones was the main barrier with 58 (58.6%) citing this. The other main factor (22 participants 22.2%) for not changing more quickly was contractual constraints. The remaining participants gave a variety of reasons for not changing over including: not needing smartphone technology, not being comfortable using smartphone technology and their current mobile phone is adequate for calls and texting.

Participants were asked to rate their level of happiness with their main device. Participants who used a mobile phone as their main device were significantly happier with the battery life of the device than smartphone users (Z = -6.341, p < 0.000). Participants who used a smartphone as their main device were significantly happier with the following attributes than those who used a mobile phone as their main device: keyboard (Z = -1.959, p < 0.05), screen resolution (Z = -5.248, p < 0.000), screen size (Z = -5.848, p < 0.000), device connectivity (Z = -6.241, p < 0.000), quality of sound (Z = -3.055, p < 0.002), quality of video (Z = -6.042, p < 0.000) and GPS (Z = -5.868, p < 0.000). As mobile phones are used for activities significantly less than smartphones, mobile phone users are significantly happier with their battery life.

Participants were asked to specify how often they used their main mobile device for various activities. Table 2 shows the ranking of activities participants use their main mobile device for. These results appear to be broadly in line with Anaraki (2007) and Corbeil and Valdes-Corbeil (2007). Table 3 shows the main activities performed by participants on their main mobile device in relation to whether their main mobile device is a smartphone or a mobile phone. Mann-Whitney U tests indicated that participants used smartphones for significantly longer than mobile phones for the following activities: emailing (Z = -10.552, p < 0.000), calls (Z = -2.045, p < 0.041), games (Z = -5.762, p < 0.000), social networking (Z = -7.749, p < 0.000), Twitter (Z = -6.101, p < 0.000), Internet browsing (Z = -10.211, p < 0.000), using the camera (Z = -4.222, p < 0.000), MP3 (Z = -4.113, p < 0.000), MP4 (Z = -7.161, p < 0.000) and podcasting (Z = -4.927, p < 0.000). There was no significant different in texting in relation to the type of main device. This would indicate that smartphone users are making full use of the technologies available to them through the device. Mann-Whitney U tests indicated that females used their primary mobile device significantly more for the following activities: texting (Z = -2.429, p < 0.015), calls (Z = - 2.063, p < 0.039) and taking photographs/filming (Z = -3.677, p < 0.000). These results suggest that a females preferred methods of communication as being firstly texting and secondly calls.

Table 2. Rankings of main activities on main mobile device

Activities Rank Mean SD Texting 1st 4.37 0.85

Calls 2nd 4.11 0.84

Internet Browsing 3rd 3.51 1.47

Mp3 4th 3.40 1.42

Camera 5th 3.26 1.16

Email 6th 3.08 1.57

Social Networking 6th 3.08 1.61

Games 7th 2.71 1.32

Mp4 8th 2.59 1.25

Twitter 9th 2.08 1.49

Podcast 10th 1.79 1.20

Table 3. Main activates performed on smartphones and mobile phones

Phone Smartphone Mobile Phone

Activities Rank Mean SD Rank Mean SD

Texting 1st 4.42 0.79 1st 4.26 0.97

Calls 2nd 4.18 0.81 2nd 3.96 0.89

Internet Browsing 3rd 4.13 1.03 5th 2.14 1.36

Email 4th 3.75 1.26 9th 1.64 1.14

Mp3 5th 3.65 1.28 3rd 2.85 1.56

Social Networking 6th 3.57 1.45 7th 1.99 1.39

Camera 7th 3.46 1.02 4th 2.80 1.30

Games 8th 3.00 1.27 6th 2.05 1.17

Mp4 9th 2.93 1.12 8th 1.86 1.21

Twitter 10th 2.44 1.59 11th 1.32 0.86

Podcast 11th 2.00 1.26 10th 1.33 0.90

ISBN: 978-972-8939-66-3 © 2012 IADIS

110

4.2 Mobile Learning

Participants were asked to what extent they believed mLearning would be suitable to teach subjects within computing. 228 participants answered this question, 28 participants (12%) stated to a very great extent, 77 participants (35%) specified to a great extent, 79 participants (35%) were neutral, 31 participants (14%) specified to a small extent and 13 participants (6%) specified to a very small extent. A Mann-Whitney U test revealed no significant differences in ratings of suitability in relation to gender (Z = -1.099, p < 0.272).

Participants were asked to specify if they believed that mLearning could replace or supplement lectures, labs and tutorials. In terms of lectures, 151 participants (65%) believed that mLearning could be used in a supplementary capacity, 22 participants (10%) believed that mLearning could replace lectures and 58 participants (25%) stated mLearning would neither act as a replacement nor supplement. In terms of tutorials, 153 participants (67%) believed that mLearning could be used in a supplementary capacity, 19 participants (8%) believed that mLearning could replace tutorials and 58 participants (25%) believed that mLearning would neither act as a replacement nor a supplement. In terms of labs, 109 participants (47%) believed that mLearning could be used in a supplementary capacity, 19 participants (8%) believed that mLearning could be used as a replacement and 102 participants (44%) believed that it would neither acts as a replacement or a supplement. The results suggest students believe that mLearning may be more suitable to teach computing at a supplementary level in lectures and tutorials. The results also suggest that mLearning is less suitable for teaching computing in labs.

Participants were asked to rate the delivery methods of mLearning. Table 4 shows the results. Mann-Whitney U tests indicated that males found the following delivery methods to be significantly more suitable for mLearning than females: MP4 (Z = -3.722, p < 0.000) and Podcast (Z = -2.237, p < 0.025). This suggested that males prefer a video style delivery method for learning through the mLearning paradigm.

Participants were also asked to rate the importance of the attributes of mLearning. Table 5 shows the importance of attributes of mLearning. Mann-Whitney U tests indicated that revealed no significant differences in the importance of attributes in relation to gender. This shows that both genders rate the importance of attributes of mLearning similarly.

Participants were asked about their level of use of particular mobile devices for learning purposes. Table 6 shows the rankings of the level of utilisation of mobile devices for learning. Mann-Whitney U tests revealed no significant differences in the usage of mobile devices for learning in relation to gender with the exception of mobile phones. Females used their mobile phone for learning purposes for significantly longer than males (Z = -2.676, p < 0.007).

Participants were also asked to rank how suitable they thought the various devices were for use within mLearning. Table 7 shows the ratings of the suitability of the devices for mLearning. Mann-Whitney U tests indicated that males found the suitability of mobile devices to be significantly more suitable for mLearning than females: iPad (Z = -2.894, p < 0.004), Windows Tablet (Z = -2.391, p < 0.017) and smartphone (Z= -1.907, p <0.057). These results suggest that males were more likely to participate in mLearning if they were using a device such as an iPad or windows tablets.

Table 4. Suitable delivery methods for mLearning

Delivery Method Rank Mean SD MP4 1st 3.91 0.92

MP3 2nd 3.77 0.87

Podcast 3rd 3.70 0.98

Text-based 4th 3.54 0.98

Games-based 5th 3.32 1.09

Story-based 6th 3.32 0.90

Table 5. Ratings of importance of attributes of mLearning

Attributes Rank Mean SD Accessibility of learning materials 1st 4.28 0.79

Learning devices portability 2nd 4.10 0.87

Attributes student mobility 3rd 4.05 0.87

New innovative approach 4th 3.73 0.96

Different learning style 5th 3.65 0.91


111

Table 6. Level of device use for learning Table 7. Suitability of devices for mLearning

Device Rank Mean SD Smartphone 1st 3.11 1.61

iPod 2nd 2.30 1.48

Mp3 Player 3rd 2.05 1.40

iPad 4th 2.04 1.53

Mobile Phone 5th 1.99 1.40

Mp4 Player 6th 1.90 1.33

Android Tablet 7th 1.83 1.40

Windows Tablet 8th 1.51 1.06

PDA 9th 1.43 0.94

PalmTop 10th 1.41 0.91

Blackberry Playbook 11th 1.36 0.91

Device Rank Mean SD iPad 1st 4.22 1.00

Android Tablet 2nd 4.11 1.02

Windows Tablet 3rd 4.10 1.03

Smartphone 4th 3.78 1.09

Blackberry Playbook 5th 3.71 1.10

PDA 6th 3.26 1.08

PalmTop 7th 3.25 1.08

iPod 8th 3.18 1.18

Mp4 9th 3.10 1.09

Mp3 10th 2.86 1.14

Mobile Phone 11th 2.47 1.08

Table 8. Features that make mobile devices suitable for learning

Device Rank Mean SD Portable 1st 4.47 0.75 Ability to use a Variety of Media 2nd 4.24 0.80 Multiple Delivery Methods 3rd 4.21 0.81 Light Weight 4th 4.20 0.81 Apps to Aid Learning 5th 4.19 0.82

Table 9. Factors that might prevent the use of mobile devices for learning

Features Rank Mean SD Cost of device 1st 4.09 0.96

Connectivity 2nd 3.90 0.90

Battery life 3rd 3.77 1.08

Cost of Internet 4th 3.75 0.98

Screen size 5th 3.72 1.00

Type of content delivered 6th 3.66 0.98

Prefer personal material separate 7th 3.21 1.12

Technology distracting from learning 8th 3.17 1.18

Mann-Whitney U tests indicated that smartphone users found the suitability of mobile devices for learning to be significantly more suitable for mLearning than mobile phone users: smartphone (Z = -2.687, p < 0.007), Android Tablet (Z = -2.317, p < 0.021), iPad (Z= -2.267, p <0.023). These results indicated that users’ currently using smartphones had a greater appreciation of the smartphones suitability for use within mLearning.

Participants were asked to rate the features that make the above mobile devices suitable for use as learning tools. Table 8 shows the ratings of the features that make mobile devices suitable for learning. Mann-Whitney U tests revealed no significant differences in the features that make mobile devices suitable learning tools in relation to gender. This result showed that while there was no significant difference in relation to the features that make mobile devices suitable for mLearning there was a difference when viewing the ranking of these features. Females ranked the top two features as being portable and lightweight while males ranked their top two features as portable and the ability to use a variety of media.

Participants were also asked to rate the factors that might prevent them from using a mobile device for learning. Table 9 shows the ratings of the factors that might prevent them from learning using a mobile device. Mann-Whitney U tests indicated that females ranked the following factors that might prevent participants from using a mobile device for learning higher than males: prefer to keep personal and learning material separate (Z = -2.549, p < 0.011), screen size (Z = -2.144, p < 0.032), technology distracting from learning (Z= -2.048, p <0.041) and type of content delivered (Z= -1.953, p <0.051). The top two factors that might prevent participants from using a mobile device for learning are the cost of the device and connectivity issues. These factors are the same regardless of gender. Males ranked the battery life and internet costs as higher factors for preventing the use of mobile devices than females.

Participants were asked to provide information on the benefits of mLearning using an open-ended question which 131 participants answered. The two main benefits identified were accessibility and flexibility to learn within hours that suited. Some participants felt that material being made available electronically would mean they would not have to attend the educational establishment as frequently. Others indicated they felt electronic material being available through a mobile device would ensure they still had the ability to learn if they were prevented from attending classes due to illness or weather conditions. Only a few participants’ (6) indicated that the use of different learning might be a benefit of mLearning. 126 participants provided their views on the obstacles to mLearning and the main obstacles identified were cost, device limitations, lack of familiarity with technologies on device, lack of motivation.

ISBN: 978-972-8939-66-3 © 2012 IADIS

112

5. DISCUSSION

The majority of participants (313, 98%) stated they owned mobile devices and a clear view of the mobile devices currently favoured by the participants was evident, with two thirds of the participants (211, 66%) owning smartphones and 102 participants (32%) stating that their main device was a mobile phone. The majority mobile devices owned were running on the android operating system accounting for 183 participants (70%). While half of the mobile phone users were happy with their devices, the other half where eager to change to a smartphone within the next year with cost being the biggest preventative factor. Mobile phone users were significantly happier with the devices battery life, whereas smartphone users were significantly happier with many other factors such as keyboard, screen resolution/size and connectivity. Smartphone users indicated they used their devices significantly longer than mobile phone users for emailing, calls and games. Females indicated they used their devices far more than males for texting, taking photographs and filming.

Participants provided their general views on mobile learning (mLearning) and suggested that they thought mLearning might be suitable to teach subjects within computing. There were a high percentage of participants that believed that mLearning may be more suitable to teach computing at a supplementary level in lectures and tutorials. The results also suggest that participants thought that mLearning is less suitable for teaching computing in labs. Males believed that MP4 and podcasts would be significantly more suitable for delivering mLearning than females. A comparison was made between how often participants use their main device for specific activities and how they rated the suitability of these particular activities as delivery methods for mLearning. Participants indicated that the utilization of a particular activity was significantly higher than the rating of suitability of the activity as a delivery method. These results suggest that there is no significant relationship with time spent on activities and the rating of suitability of the activities as delivery methods for use within mLearning.

Participants indicated that there were no significant differences in the usage of mobile devices for learning in relation to gender with the exception of mobile phones. Females used their mobile phone for learning purposes for significantly longer than males. Males found the following devices to be significantly more suitable than females: iPad, windows tablet and smartphones. When a comparison of the devices usage for learning was made with the devices suitability for use within mLearning a Wilcoxon matched-pairs signed ranks test indicated device usage to be significantly higher indicating that just because students rate their usability as high - this does not result in suitability ratings being high. There were no significant differences in the features that make mobile devices suitable learning tools in terms of gender, but females ranked the factors that might prevent participants from using a mobile device for learning higher than males. The data gathered in this study provides valuable information to assist in future research.

6. CONCLUSIONS AND FUTURE RESEARCH DIRECTIONS

The questionnaire analysis indicated that a delivery method using a combination of video, audio and text could satisfy the majority of the participant’s preferences. Stats have been gathered to make informed design decisions and the next stage will be to design and develop a mLearning application to teach requirements collection and analysis. The results indicated the students would prefer an application that was more suited for the tablet devices but could also be available through a smartphone. The application which will then be embedded into courses will be introduced within the traditional teaching method of class tutorials. The application will be piloted with a small group before an experimental study will be performed to evaluate the effectiveness of this approach with more traditional teaching methods (e.g. lecturing; role-play) and also with a games-based learning approach. A comparison will also be performed with similar studies reviewing mobile device use with mLearning.

ACKNOWLEDGEMENT

This paper is a scientific publication as part of the Games and Learning Alliance (GaLA). GaLA is a Network of Excellence on ‘serious games’ funded by the European Union in FP7 – IST ICT, Technology Enhanced Learning (see http://www.galanoe.eu). GaLA gathers the cutting-edge European research and


113

development organizations on ‘serious games’, involving 31 partners from 14 countries. The University of the West of Scotland is one of the partners

REFERENCES

ADPRIMA Instructional methods information website (2009). Retrieved 21 May, 2009, from http://www.adprima.com/teachmeth.htm

Anaraki, F. (2007). Assessment of mLearning A Case Study: Assumption University of Thailand. International Journal. Armarego, J., & Roy, G. G. (2004). Teaching design principles in software engineering. Beyond the comfort zone

Proceedings of the 21st ASCILITE Conference (pp. 67–77). Citeseer. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.88.9693&rep=rep1&type=pdf

Andrianoff, S. and Levine, D. (2002). Role playing in an object-oriented world. Proceedings of the 33rd SIGCSE Technical Symposium on Computer Science Education, Kentucky, USA. ACM Press, 121–125

Bernstein, L. and Klappholz, D. (2001). Getting Software Engineering into Our Guts. CrossTalk, The Journal of Defense Software Engineering, July 2001, 25-26.

Bonwell, C.C. (1996). Enhancing the lecture: Revitalizing a traditional format. In Using active learning in college classes: A range of options for faculty, New Directions for Teaching and Learning No. 67 (Eds: T.E. Sutherland and C.C. Bonwell), 31 - 44. Place: Wiley Periodicals Inc.

Brooks, F. (1987). No silver bullet: Essence and accidents of software engineering. IEEE Computer, 20(4) 10-19. 160 Cashin, W.E. (1985). Improving lectures Idea Paper No. 14. Manhattan: Kansas State University, Center for Faculty

Evaluation and Development. Chao, P.-yao, & Chen, G.-dong. (2009). Interacting with Computers Augmenting paper-based learning with mobile

phones. Interacting with Computers, 21(3), 173-185. Elsevier B.V. doi:10.1016/j.intcom.2009.01.001 Connolly, T.M., Stansfield, M.H, McLellan, E., Ramsay J. and Sutherland J. (2004). Applying Computer Games

Concepts to Teaching Database Analysis and Design. In Proceedings of the International Conference on Computer Games, AI, Design and Education, Reading, UK, November 2004.

Cope, C. and Horan, P. (1996). The Role Played Case: An Experiential Approach to Teach Corbeil,J and Valdes-Corbeil, M. (2007) Are you ready for mobile learning? Educause Quarterly, Vol 30, No 2. Corlett, D., Sharples, M., Bull, S., & Chan, T. (2005). Evaluation of a mobile learning organiser for university students.

Journal of Computer Assisted Learning, 21(3), 162-170. doi:10.1111/j.1365-2729.2005.00124.x Ferenchick, G., Fetters, M., & Carse, a M. (2008). Just in time: technology to disseminate curriculum and manage

educational requirements with mobile technology. Teaching and learning in medicine, 20(1), 44-52. Georgieva, E. S., Smrikarov, A. S., & Georgiev, T. S. (2011). Evaluation of mobile learning system. Procedia Computer

Science, 3, 632-637. Elsevier. doi:10.1016/j.procs.2010.12.106 Hwang, G.-J., & Chang, H.-F. (2011). A formative assessment-based mobile learning approach to improving the

learningattitudes and achievements of students. Computers & Education, 56(4), 1023-1031. Jarvis, C., & Dickie, J. (2010). Podcasts in Support of Experiential Field Learning. Journal of Geography in Higher

Education, 34(2), 173-186. Nuseibeh, B., & Easterbrook, S. (2001). Requirements Engineering: A Roadmap. Cognitive Psychology. Schön, D.A. (1983). The Reflective Practitioner: How Professionals Think in Action. Basic Books, New York. Schön, D.A. (1987). Educating the Reflective Practitioner: Towards a New Design for Teaching in the Professions.

Jossey-Bass Inc., San Fransisco. Shantikumar, S. (2009). From lecture theatre to portable media: students’ perceptions of an enhanced podcast for

revision. Medical teacher, 31(6), 535-8. doi:10.1080/01421590802365584 Shaw, K. and Dermoudy, J. (2005). Engendering an empathy for software engineering. In Proceedings of the 7th

Australasian Computing Education Conference (ACE2005), Newcastle, Australia, 42, 135–144.

ISBN: 978-972-8939-66-3 © 2012 IADIS

114

TOWARDS MOBILE PERSONALIZED LEARNING MANAGEMENT SYSTEMS

Natalia Müller and Diana Dikke IMC information multimedia communication AG

Altenkesseler Str. 17 D3, 66115 Saarbrücken / Germany

ABSTRACT

There are two big challenges that eLearning is confronting nowadays. On the one hand, rapid changes in business environment require fast and flexible creation and adaption of learning materials and tools. On the other hand, smartphones and tablets are getting more and more advanced features that previously were only available on a personal digital assistant or a computer. The growing popularity of mobile devices is expected to lead to a mobile learning “boom” and opens up new opportunities for eLearning. Towards these challenges, this paper proposes the concept of mobile personalized learning management systems (MPLMS) providing the holistic mobile learning environment supporting different learning approaches by integration of external apps and mobile learning management systems in a well-structured way. Based on the analysis of current research and development projects on web-based personal learning environments, personalized learning management systems and mobile learning management systems, this paper defines requirements, roadmap and approach for design and implementation of MPLMS. This approach provides smooth and comprehensive support for learning and teaching activities of different – formal and less formal, self-regulated and mentored – learning processes affiliating the advantages of mobile technologies, personalized learning environments and capacious LMS.

KEYWORDS

Mobile e-Learning, Personalized LMS, OpenSocial

1. INTRODUCTION

In the last years, eLearning is confronting a lot of new challenges due to rapid changes in business environment and technological progress. Often slow processes of creating formal learning materials and delivering vocational training across the whole organisation can create barriers for the adoption and use of learning technologies. To overcome these barriers, the EU project ROLE developed the concept of personal learning environments (PLE) based on OpenSocial technologies. This approach offers adaptivity and personalization of technology-enhanced learning environments. The ROLE infrastructure provides a learner-centred PLE for learners and teachers to empower users for true lifelong learning across institutional boundaries. (ROLE Project 2009) Though, the classical LMS are still indispensable for more formal eLearning. To provide support for formal and informal learner-centred eLearning approaches within a single learning environment, the OpenSocial-based PLE developed in the ROLE project has been integrated in the open source LMS Moodle and in the feature-rich LMS CLIX.

Furthermore, mobile devices are increasingly used in parallel to PC or notebooks both in private and business context. Research and consulting agencies such as Gartner forecast a mobile learning “boom” in the next years. (Seegmüller 2010) More than a quarter of the world's population now uses mobile devices, and frequent mobile Internet use has almost doubled in the past year. (Bersin 2011) Towards this trend, a mobile version of the LMS CLIX has been developed within the Learn&Go project at the Saarland University. It based on detailed analysis of user requirements and evaluation of mobile technologies on different mobile platforms.

The research report of Bersin & Associates also notes that the informal use of mobile devices for learning vastly outnumbers the formal, and that new mobile applications increasingly empower today's workers to access the information they need on demand. (Bersin 2011) Whereas there are a lot of single apps in


115

application stores of different mobile platforms that can be used to support several learning activities, the added value can be provided by interoperability and integrated usage of apps. Within the EU projects ROLE and MIRROR, an integrated app bundle for self-regulated learner-centred learning of foreign languages has been developed for the Android platform. An entry point in form of an application store designed specifically for learning purposes is though still required to support structured searching for learning apps and to enable users to configure own mobile PLE.

To combine the advantages of mobile technologies, PLE and classic LMS, and to provide a comprehensive mobile learning environment for different learning approaches and processes, an integrated mobile personalized LMS is required, which can be used in combination with a web-based PLMS by learners and teachers.

At first, this paper reviews results of related projects and state-of-the-art of web-based PLE, personalized LMS (PLMS) and mobile LMS (MLMS) including discussions on mobile development strategies. Afterwards, it introduces an example of a learning scenario using integrated mobile apps, defines requirements for mobile PLE and discusses related technical issues. Finally, based on findings of the previous work on PLE, MLMS and MLE, requirements, roadmap and approach for design and development of mobile personalized LMS are defined.

2. PERSONAL LEARNING ENVIRONMENTS

PLE are based on the idea that learning often takes place informally and spontaneously in different contexts and scenarios, and that content is not provided by a single provider. It is a browser-based collection of tools integrated within an environment where learners access information from a variety of sources. With PLE, learners can control and manage their own learning, set their own learning goals and manage both the content and process. (Velasco 2009)

The process model of the self-regulated learning using a PLE has been defined in the ROLE project and includes four learner-centred phases: define and revise learner profile information, find and select learning resources, work on selected learning resources, reflect and react on strategies, achievements and usefulness. These phases are summarized as “plan-search-learn-reflect” loop (Figure 1). (Fruhmann 2010)

Figure 1. Self-regulated learning process model (Mödritscher 2010)

According to this process model, a PLE supporting self-regulated learning should include tools providing following functionalities and supporting following learner activities:

planning the learning process and defining learning goals, finding learning resources spread on different Internet platforms, sharing and rating of learning resources and tools, recommendations of learning tools and content depending on learning goals, learner’s skills and

knowledge, reflection on the learning process to adapt learning strategy. PLE in ROLE includes widget bundles, which are integrated sets of small web based software

applications (widgets) to support a specific learning or teaching task. (ROLE Showcase 2010) OpenSocial

ISBN: 978-972-8939-66-3 © 2012 IADIS

116

widgets can be integrated in several platforms supporting OpenSocial standards like iGoogle, LinkedIn, XING or orkut. Tools and content can be easily shared with other learners. Within the ROLE project, several widget bundles supporting learning activities of defined self-regulated learning phases have been created. These include both widgets implemented within the project and third-party widgets available on different OpenSocial platforms. In ROLE Widget Store, Widgets are categorized by learning activities and can be easily searched and added to users’ own PLE within a LMS or other OpenSocial compatible platforms. (ROLE Widget Store 2010).

3. PERSONALIZED LEARNING MANAGEMENT SYSTEMS

The necessity of personalization and adaptivity of LMS was identified already years ago. Graf and List evaluated the adaptation capabilities of open source eLearning platforms based on the four criteria: adaptability, personalization, extensibility and adaptivity. (Graf 2005) The evaluation showed that all nine open source learning platforms, which met general pre-evaluation criteria, provided basic adaptivity features. However, this evaluation was conducted in year 2005 at the very beginning of Web 2.0; therefore, it did not take Web 2.0 technologies into account. In this study, adaptability and personalization are almost limited to the customizing of the user interface. Extensibility is defined as simplification and support for development of LMS specific modules, e. g. implementing their API, and does not consider integration of tools based on other standards. Adaptivity is restricted to annotation and adaptation of content created within LMS. Nowadays, the proposed criteria can only serve as minimum requirements for an adaptive and personalized learning management system.

The subsequent step towards personalization and adaptivity of LMS is the usage of Web 2.0 and social network technologies within LMS, as well as adaptivity of learning content based on learner’s competency profile. Several ongoing commercial and founded projects analyse, implement and evaluate the integration of these functionalities in LMS. For example, the proposal OWLearn aims the creation of a learner-centric and interest-based learning environment within an open source LMS. Web 2.0 and social network features, as well as learning content adaptivity based on a learner profile are being implemented for the open source eLearning platform Moodle. (Tsolis 2011)

To get beyond the state-of-the-art of LMS adaptivity and personalization, the introduced PLE concept of the ROLE project has been adapted for the integration in LMS, extending it with several adaptivity and personalization functionalities. Within the OpenSocial-based PLE, not only learning content, but also external learning tools can be selected and recommended based on a learner profile and learning goals. Furthermore, recommendations are generated regarding user rating and feedback on learning tools and content. The OpenSocial PLE integrated in a LMS enables users (tutors and learners) to create a widget space embedding OpenSocial widgets that support particular learning activities and scenarios. Widget spaces can be added to an existing course by a tutor or used independently as a user-generated course. Thus, integration of such PLE enriches LMS not only with extended adaptivity features, but also with functionalities of external tools, and provides further advantages for LMS such as:

Additional features and functionalities can be supported within LMS without any effort for implementing them. There are thousands of gadgets, mainly in the iGoogle content directory, and a lot of them can be used to support particular learning activities.

An OpenSocial widget is usually easier to implement than a new LMS module. An integrated widget store allows external developers to distribute their learning widgets, which can be added to the PLE within the LMS.

An OpenSocial widget can be embedded for particular courses or learners without overloading the LMS with numerous features and affecting its usability.

External content can be dynamically embedded within a widget, shared with other users and rated. In scope of the ROLE project, an OpenSocial plugin has been already developed for the open source LMS

Moodle. (Bogdanov 2011) OpenSocial extension for the LMS CLIX is being developed, and its first version is being evaluated with an industry testbed for a professional training scenario.


117

4. MOBILE LEARNING MANAGEMENT SYSTEMS

The usage of a LMS on a mobile device entails some restrictions due to its small screen and lower capacity. Thus, not every feature available in a standard LMS can be meaningfully supported on mobile devices. Format and layout of content have to be adapted as well. Within the user requirements elicitation conducted at Saarland University by Centre for e-Learning Technology (CelTech) and involving learners, tutors and administrators, following key features have been identified and implemented for the mobile LMS:

access to news, personal schedule and standard learning content, overview of currently available courses, access to the learning content without being connected to the Internet, map view and navigation to a venue of in-class lectures, export and import of events in the personal calendar and contact data in the contact list, integration of particular Web 2.0 applications, micro-blogging for mobile voting. Besides of standard data access functionalities, the elicited user requirements result in the following

technical requirements: web-enabled mobile version to provide access to Web 2.0 and social networking features in real-time, local data storage to enable the usage in the offline mode, access to the native features of mobile devices, e. g. for GPS localisation, access to other apps installed on mobile devices for data sharing across apps, e. g. for import of dates in

the calendar. To enable the usage of an LMS on mobile devices, several LMS provide a mobile compatible web GUI. It

is indeed the cheapest and the simplest way to enable access to a LMS on almost all mobile platforms. However, even though a lot of features can be implemented using HTML, there are several device-oriented features and API that can only be accessed by native apps like access to camera, microphone, address book, some user interface elements, push-notification etc. Data upload is often restricted, and interactions with GUI are slower in web apps than in native apps. It has a negative impact on the usability of mobile browser-based web applications. The learner completely relies on the internet connection, which is not always available. Furthermore, native features of a mobile device and access to other mobile apps installed on it cannot be integrated in a browser-based application. The availability of learning content in the offline mode, as well as data exchange with other mobile apps and using native device features belong though to key requirements for a mobile LMS.

Another alternative for the multiplatform app development is development with mobile multiplatform frameworks like PhoneGap, which wrap web apps written using HTML, JavaScript and CSS by a container that makes them run without visible web browser. The PhoneGap supports Apple iOS, Google Android, Palm WebOS, Symbian, Blackberry OS, Windows Mobile and more. (PhoneGap) Functions that are not available for web apps like camera or address book can be called by this means. However, such frameworks are “least common denominators”. Native platform features are only supported if access to them can be implemented with the same code for different platforms. (Ross 2011) Further disadvantage is that even if e. g. Apple App Store approves such “hybrid” apps in the moment, it can be changed overnight, which brings a certain risk for providers of mobile LMS.

Developing native applications for every mobile platform and device available on the market is often not economical justifiable. The only mobile platforms, which market shares grew in the year 2010 compared to the year 2009, are Android and iOS. (Pettey 2011) According to the Gartner’s forecast, Android will grow by 167% and iOS will grow by 94% in 2011. (Vadlamani 2011) Thus, the golden mean strategy to reach most of potential mobile LMS users with reasonable effort is to provide native apps for Android and iOS and hybrid apps using a multiplatform framework for other mobile platforms.

ISBN: 978-972-8939-66-3 © 2012 IADIS

118

5. MOBILE PERSONAL LEARNING ENVIRONMENTS

To enrich the concept of PLE, introduced in the chapter 2, with advantages of the mobile learning, which are first of all time and place independency, the concept of mobile PLE has been created. The idea of mobile PLE is quite similar to the PLE implemented with OpenSocial widgets. The learner has a tool pool, e. g. in form of mobile application store, where apps can be selected, rated and recommended by other users or by a system based on set learning goals. The learner can then configure his or her mobile PLE choosing apps for different learning activities in the mobile learning application store. Like in case of OpenSocial-based PLE, also integrated app bundles can be configured and shared. The software that underlies mobile learning can include not only mobile apps designed specifically for learning proposes, but also those designed for other uses – such as geographical location, readers, and maps – that can be adapted for educational purposes. (EDUCASE 2010) For example, a task tracking tool recording working time spent on different projects and tasks, which is primarily designed for administration of time sheets, can be used to protocol time spent on learning activities for reflection on the learning process based on recorded data. Other examples are an eBook-Reader and a Translation App. The eBook-Reader can be extended to enable the learner to highlight an unknown word or expression while reading an eBook in a foreign language and send it to the Vocabulary Trainer App to train this word later. Thereby, the Translation App fetches possible translations, e. g. using Google Translation API, suggests the user to choose a translation that match to the context and sends the chosen translation to the Vocabulary Trainer App. This learning scenario was first implemented for the OpenSocial-based PLE and then has been adapted for the Android platform.

iOS and Android are the most popular platforms on the market today not only among users, but also among developers. (Schwarzhoff 2011) There are over 550,000 Android apps available in the Google Android Market (AndroLib 2011) and over 475,000 iOS apps available in the App Store (TrouserMac 2011), which is by far more than apps available for other mobile platforms. As it is shown in the scenario introduced above, even apps primarily developed for other purposes can be used to support learning activities.

However, the added value in this learning scenario results from interoperability of apps and data sharing between them. Whereas Android platform provides easy data sharing between apps and has proven to be very flexible, iOS hardly supports interoperability of apps. The latter provides several system integration frameworks and technologies that enable the access to hardware and software features on the device and to some user-specific information like user’s contacts or location of the device. To transfer files between applications, a document interaction controller or the pasteboard can be used. By these means, learning apps on iOS platforms can share data with each other, but they cannot be integrated to learning bundles as smoothly and flexibly as it is supported by the Android architecture. Thus, learning scenarios for mobile PLE running on an iOS platform have to be adapted considering the specific of iOS architecture.

To create his own mobile learning environment, the learner needs some kind of starting point, e. g. in form of a multiplatform learning application store. Along with basic App Store functionalities, the learning application store should provide following:

rating of learning apps for user orientation, sharing of apps and content between learners, framework for description and categorisation of learning apps, for example in form of simplified LOM

(learning objects metadata), automatically generated recommendations for apps and app bundles based on set learning goals, a

learner’s competency profile and a used mobile platform, configuration of app bundles consisting of integrated apps to support the entire self-regulated learning

process in a structured, consistent way, examples of learning scenarios demonstrating the usage of apps and app bundles. At the moment, there is no well-known learning application store that fulfils these requirements. For

example, Apple only provides an overview of learning apps on its web-site without any support for structured search for these apps based on learning goals, learner’s profile, etc. (Apple in Education 2011) Thus, the well-structured learning application store catered specifically to learners’ needs is still an open issue and is the first step towards mobile PLE. The next step is the integration of mobile LMS and mobile PLE to provide a holistic learning environment on mobile devices.


119

6. MOBILE PERSONALIZED LEARNING MANAGEMENT SYSTEMS

Whereas Web 2.0 and social network functionalities like mobile voting, twittering and annotation of learning content are taken for granted by users of mobile LMS nowadays (see chapter 4), a mobile personalized LMS (MPLMS) should enable and simplify the integration of third-party apps in a mobile LMS by the user. The basic idea of MPLMS is adapted from the concept of PLMS discussed above. The user can configure a mobile learning space for specific topics and learning goals consisting of external apps and content. Such mobile learning space can then be shared with other users as a user-generated mobile course. And the tutor can add a mobile app found in the learning application store to a LMS course as an additional learning resource. Therefore, a truly personalized mobile LMS have to fulfil all the requirements for mobile LMS, as well as for web-based and mobile PLE defined in this paper, and provide additional features by the integration of external learning apps (Figure 2). Thereby, mobile PLE and mobile LMS benefit from each other: a mobile LMS can be easily enhanced with external learning objects by users themselves, whereas a mobile PLE and single apps can use the LMS infrastructure and access relevant data stored in it, e. g. user profiles or a catalogue of learning objects.

Figure 2. Integrated MPLMS

Based on the former and ongoing work on PLE and MLMS, we have identified following technical and conceptual issues that have to be investigated to design and implement an integrated MPLMS.

As a starting point for the integration of a mobile PLE in MLMS, a multiplatform learning application store has to be implemented with a LMS, where external apps can be added, downloaded, rated, linked to courses or other LMS learning objects, and described according to a learning-specific categorization. In general, an application store has two critical elements: compliance standards to enable users easily to plug in the apps and use them, and marketing and communication between vendors and consumers. For example, in case of the App Store, the iPhone software development kit and usability guidelines form the standards to ensure that the apps work properly in the iPhone environment. (Severance 2011)

For the integrated learning application store, standards for interoperability between external apps and mobile LMS are required, and possible technologies for their support on different mobile platforms have to be evaluated. Thereby, two important specific criteria have to be regarded. On the one hand, mobile devices still have a restricted capacity and lower broad-width, therefore protocols and data formalisms used for data exchange and communication must be as light-weight and flat as possible. On the other hand, access to user data stored in a LMS can be required by external apps. Supported degree of data privacy and security play thereby a very important role. A consortium of vendors and end users is developing the IMS Learning Tools Interoperability (LTI) standards, which facilitates plugging apps into learning-management systems. (IMS 2011) The standards are supposed to be applied for mobile technologies as well, but they are not the main focus of this project. Furthermore, technologies for cross-platform data sharing and real-time communication for collaborative mobile learning have to be explored and evaluated in particular. The cross-platform mobile collaboration is though not an eLearning-specific issue and is currently being tackled by several development projects in different domains.

Beyond these technical issues, mobile and combined (partly executed on a mobile platform and partly in a web-based environment on a standard PC) learning scenarios have to be created and evaluated. In particular, it should be investigated, which learning or teaching activities can be meaningfully supported on mobile platforms and for which rather standard PCs and web-based tools should be used. For example, whereas an eBook-Reader is used by learners on mobile platforms, creation and editing of eBooks is rather more comfortable on large-screen devices with stable Internet connection to search for external learning resources. Thus, it has to be considered that smartphones and tablets still cannot completely replace computers. Finally, based on evaluated learning scenarios, cross-platform tool bundles can then be created within a LMS to smoothly and comprehensively support learning and teaching activities of different – formal and informal,

ISBN: 978-972-8939-66-3 © 2012 IADIS

120

self-regulated and mentored – learning processes affiliating the advantages of mobile technologies, personalized learning environments and capacious LMS.

7. CONCLUSION

In this paper, we first introduced the concept of OpenSocial-based PLE including the concept of widget bundles supporting learning activities of the defined self-regulated learning process. The advantages of integration of such PLE in LMS comparing to the state-of-the-art LMS personalization have been discussed. This approach enables users to create their own personal learning environments and user-generated courses within a LMS using not only features provided by the LMS and content created within it, but also numerous external tools and other learning resources, which can be found in a learning widget store. This idea can be basically adapted for mobile personalized LMS, whereby learners and tutors can use external mobile learning resources and tools in addition to and combined with a web-based PLMS.

The review of the state-of-the-art of and user requirements on mobile LMS showed that providing mobile access to learning content just by adapting the web-based GUI for mobile devices is not sufficient, learning content has to be available in offline mode. Furthermore, support of real-time collaboration based on Web 2.0 and social networks, personal annotation of learning content, as well as using of native features of mobile platforms are seen as a matter of course by most users nowadays. To fulfil all the user requirements, a mobile LMS has to be implemented as a native mobile app, whereby the challenge of development for numerous different mobile platforms arises. In this connection, we discussed different mobile development approaches and proposed an economic justifiable “golden mean” development strategy, namely, the development of native apps for the currently most popular platforms Android and iOS and hybrid apps, which might be kept simpler, for other mobile platforms.

Based on the result of work on web-based PLE, we discussed the idea of mobile PLE and identified two main characteristics to be fulfilled with it: an application store adapted specifically for learning needs, and interoperability of learning apps enabling creation of apps bundles for smoothly support of the complete learning cycle.

Specific requirements on a learning application store have been defined. The analysis of the state-of-the-art showed that there is no learning application store that fulfil these requirements and can be used as a mobile PLE. Thus, such learning application store has to be designed and implemented including standards for description and categorisation of apps and corresponding sample learning scenarios.

In regard to interoperability, we have evaluated the architecture of Android and iOS mobile platforms. The Android platform enables easy data sharing and interoperability between apps and is very flexible. Self-regulated learning scenarios created for the web-based PLE and implemented by integrated OpenSocial widget bundles could be implemented by the integrated app bundles on the Android platform without any restriction and even extended by additional functionalities provided by Android. Compared to the Android platform, iOS hardly supports interoperability of apps. Therefore, learning scenarios for mobile PLE running on an iOS platform have to be adapted considering its architectural characteristics.

Finally, we defined the roadmap for design and development of mobile personalized LMS and identified main issues to be investigated and solved in response to the defined requirements for MPLMS:

provide a multiplatform learning application store within LMS, evaluate and adapt cross-platform interoperability technologies and eLearning-specific standards for

integrated usage of MLMS and external apps, create and evaluate cross-platform sample learning scenarios. In this way, a holistic mobile learning environment supporting different learning approaches by

integration of external apps and mobile LMS will be created. It will provide well-structured access not only to learning content of LMS, but also to external learning tools and sources available world-wide in the Internet and different application stores. Mobile PLMS can be used by schools, high-schools, universities, enterprises, and also by individual learners for private needs enabling learning adapted to individual needs without any time or space constraints.


121

ACKNOWLEDGEMENT

The research towards PLE presented in this paper has received funding from the European Community’s Seventh Framework Program (FP7/2007-2013) under grand agreement 231396 (ROLE project) and 257617 (MIRROR project). The results related to the concept of mobile LMS came from the Learn&Go project conducted by Centre for e-Learning Technology of Saarland University and German Research Center for Artificial Intelligence. Furthermore, the authors would like to thank Daniel Dahrendorf from IMC AG for his valuable contribution to the idea of this paper.

REFERENCES

AndroLib.Com, 2011. Accumulated number of Application and Games in the Android Market. Available at http://www.androlib.com/appstats.aspx

Apple Inc., 2011. Apple in Education. Available at http://www.apple.com/uk/education/apps/ Bersin & Associates, 2011. New Bersin & Associated research Shows Mobile Learning Finally Goes Mainstream. PR

Newswire. Available at http://www.prnewswire.com/news-releases/new-bersin--associates-research-shows-mobile-learning-finally-goes-mainstream-118568989.html

Bogdanov, E., 2011. OpenSocial Gadgets Module. Moodle. Available at http://moodle.org/plugins/view.php?plugin=mod_widgetspace

EDUCAUSE Learning Initiative, 2010. 7 Things You Should Know About Mobile Apps for Learning. Available at http://net.educause.edu/ir/library/pdf/ELI7060.pdf

Fruhmann, K. et al, 2010. A Psycho-Pedagogical Framework for Self-Regulated Learning in a Responsive Open Learning Environment. 3rd eLearning Baltic Conference (ELBA-2010). Rostock, Germany.

Graf, S. and Beate, L., 2005. An Evaluation of Open Source E-Learning Platforms Stressing Adaptation Issues. Proceedings of the International Conference on Advanced Learning Technologies, ICALT 2005. Kaohsiung, Taiwan.

IMS Global Learning Consortium Inc., 2011. Interoperability Standards Project Groups. Available at http://www.imsglobal.org/interoperabilitygroups.html

Mödritscher, F. and Nussbaumer A., 2010. Self-Regulated Learning: Communities-Of-Practice vs. Self-Regulated Learning: Motivation, backgrounds, and modus operandi of this blog. Available at http://augur.wu-wien.ac.at/COPSRL/?cat=5

Pettey, C. and Goasduff, L., 2011. Gartner Says Worldwide Mobile Device Sales to End Users Reached 1.6 Billion Units in 2010; Smartphone Sales Grew 72 Percent in 2010. Gartner Newsroom, Egham, UK. Available at http://www.gartner.com/it/page.jsp?id=1543014

PhoneGap. PhoneGap:Build. Available at https://build.phonegap.com/ ROLE Project, 2009. Objectives. Available at http://www.role-project.eu/?page_id=1583 ROLE Project, 2010. Widget bundles. Available at http://www.role-showcase.eu/widget-bundles ROLE Project, 2010. Widget Store. Available at http://www.role-widgetstore.eu/ Ross, M. 2011. Plattformgrenzen überwinden. In Mobile Developer, 11 (2011), pp 23-27. Schwarzhoff, S. and Ellison, S., 2011. Appcelerator / IDC Q1 2011 Mobile Developer Report. Available at

http://assets.appcelerator.com.s3.amazonaws.com/docs/Appcelerator-IDC-Q1-2011-Mobile-Developer-Report.pdf Seegmüller, K. 2010. 80 neue Technologien werden das eLearning prägen. CHECK.point eLearning/INFObases GmbH.

Available at http://www.checkpoint-elearning.de/article/8789.html Severance, C. 2011. Toward Developing an Education App Store. In IEEE Computer. Vol. 44, No. 8, pp. 107-109. TrouserMac Industries, 2011. App Store Metrics. iOS Development News and Information for the Community, by the

Community. Available at http://148apps.biz/app-store-metrics/?mpage=appcount Tsolis, D. et al, 2011. An Adaptive & Personalized Mobile e-Learning Platform. Proceedings of the IADIS International

Conference on Mobile Learning. Avila, Spain. Available at http://mmlab-elearning.blogspot.com/p/our-papers.html Vadlamani, S., 2011. Analysis: Android isn’t eating iOS share. It’s creating new markets! Available at

http://thegadgetfan.com/mobile-smartphones/analysis-android-isnt-eating-ios-share-its-creating-new-markets.html Velasco, K., 2009: An Introduction to Personal Learning Environments. Making learning personal – using PLEs to

enhance learning. Available at http://www.towardsmaturity.org/article/2009/11/18/introduction-personal-learning-environments/

ISBN: 978-972-8939-66-3 © 2012 IADIS

122

A FRAMEWORK FOR APPLYING QUANTIFIED SELF APPROACHES TO SUPPORT REFLECTIVE LEARNING

Verónica Rivera-Pelayo, Valentin Zacharias, Lars Müller and Simone Braun FZI Research Center for Information Technologies

Haid-und-Neu Str. 10-14 Karlsruhe, Germany

ABSTRACT

This paper presents a framework for technical support of reflective learning. This is derived from a unification of theory on reflective learning with a conceptual framework of Quantified Self tools. Reflective learning means returning to and evaluating past work performances and personal experiences in order to promote continuous learning and improve future experiences. However, theories of reflective learning do not sufficiently consider technical support. Quantified Self (QS) is a collaboration of users who use and develop a variety of tools to collect personally relevant information with the purpose of gaining self-knowledge about one's behaviors, habits and thoughts. Hence, QS approaches, including mobile devices, sensors and social applications, offer a rich source of data that has not been available for learning processes before. However, these are rather experimental approaches and currently there is no unifying framework that clusters and connects these many emergent tools with the goals and benefits of their use. This paper brings these two strands into one unified framework that shows how QS approaches can support reflective learning processes on the one hand and how reflective learning can inform the design of new QS tools for informal learning purposes on the other hand.

KEYWORDS

Reflective learning, Quantified Self, Mobile applications, Framework.

1. INTRODUCTION

Mobile devices, sensors and social applications capture and make available an increasing amount of data about our lives. This data can be used for many purposes, including aiding reflective learning (MIRROR, 2011). According to Boud et al. (1985), learning by reflection (or reflective learning) means learning by returning to and evaluating past work and personal experiences in order to improve future experiences and promote continuous learning. Despite the existence of substantial theoretical work, there is not yet an agreed upon definition for reflective learning and while there are some approaches to support reflective learning through technology in different settings (Strampel 2007, Krogstie and Divitini 2009, Fleck 2009), a unifying framework that describes the role of technology in reflective process is missing as well.

On a pragmatic side, new lifelogging approaches pursued by a community known as Quantified Self (QS) (The Quantified Self, 2011) are becoming increasingly popular. QS is a collaboration of users and developers interested in self-knowledge through self-tracking with the principle "self-knowledge through numbers".

Whereas QS approaches are pragmatic, having as main driver the experimentation; reflective learning is driven by theories that are evolving since the beginning of the 19th century. Therefore, reflective learning provides strong contributions towards understanding the underlying mental process but technology wise often refers only to pen and paper diaries and thus neglects the potential of current technologies. In an approach to join these two streams, this paper presents a framework that shows how QS approaches can support the process of learning by reflection and informs the design of new QS tools for informal learning purposes. The starting point for the design of the framework was the survey of several QS tools, which allowed analyzing the common characteristics of these tools and their potential role in supporting reflection.

There are only a few related works that deal with structuring QS approaches towards the purpose of reflection and mainly from an HCI design perspective. Fleck and Fitzpatrick (2010) provide a literature review and framework on reflection together with guiding questions for designing for reflection. Their


123

framework identifies purposes, conditions and levels of reflection as different aspects and suggests uses of technology to support the latter aspect.

Li et al. (2010) conducted a study to survey and interview people who track and reflect on personally relevant information and derived a five-stage model of personal informatics systems. The stages comprise preparation, collection, integration, reflection, and action. In comparison to our framework, Li et al. aim at the design of personal informatics systems from a technical perspective whereas we focus on their use for reflective learning. In a subsequent study, Li et al. (2011) focused on the purposes or questions people have in mind when collecting data (see also [3.1.3]). However, these insights are disconnected from their model.

In the following, we describe the theoretical and pragmatic background of reflective learning and QS in Section 2, before we present our framework to apply QS approaches in order to support reflective learning (Section 3). We then illustrate the application of our framework by one exemplary QS tool (Section 4). Finally, we conclude this paper with its discussion in Section 5.

2. BACKGROUND OF THE FRAMEWORK

2.1 Theoretical Background

Decades of research in reflective learning have highlighted different aspects of reflective learning, leading to multiple theories (Dewey, 1938; Kolb, 1984; Boud et al., 1985; Schön, 1987). Hence, it is difficult to define a shared understanding about reflection. A more detailed description and discussion of existing approaches can be found in Moon (1999). Nonetheless, this research does not take into account the possibilities provided by technology. Even newer work like Moon (1999) and Daudelin (1996) uses only traditional instruments like learning journals and structured interviews. Therefore, we were looking for a theory that provides insights into the cognitive processes and can be a basis for the integration of technology into the reflection process. We chose the model introduced by Boud et al. (1985) as theory behind our framework because (a) it considers the complete cognitive process, including affective aspects, but (b) does not define the concrete activities around this process or a specific domain.

In the model by Boud et al. (1985), reflective learning refers to “those intellectual and affective activities in which individuals engage to explore their experiences in order to lead to new understandings and appreciations”. Therefore, the reflective process is based on the experiences of the learner, which are considered as “the total response of a person to a situation, including behavior, ideas and feelings”. The process consists of three stages in which the learner re-evaluates past experiences by attending to its various aspects, and thereby producing outcomes. The defined outcomes can be cognitive, affective or behavioral. The reflection process and its context, experiences and outcomes, are depicted in Figure 1.

A detailed look at the stages of the reflection process provides insights into the involved cognitive processes and opportunities for support. The learner starts by returning to an experience and thereby recalls details about an event or incident. In the second stage, this experience is evaluated attending to feelings. Positive feeling should be utilized to support the reflective process. Negative feelings that obstruct the process “need to be discharged or transformed”. In the final third stage, the experiences are re-examined by associating them to the existing knowledge and integrating them in an appropriate fashion in the conceptual framework of the learner. The whole process might repeat these three stages several times and by doing so skip stages. Nevertheless the desired process contains these three stages to produce outcomes. The outcomes of a reflection are mainly intangible, like the experiences and the reflection process itself. For instance, a new perspective becomes only apparent by articulating it or by a change in behavior.

ISBN: 978-972-8939-66-3 © 2012 IADIS

124

Figure 1. The reflection process in context (Boud et al., 1985)

A critical point is the start of the reflection process that triggers the return to experiences. Boud et al. do not explicitly define the beginning of the reflection process because “most events which precipitate reflection arise out of normal occurrences of one's life”. However, the provided examples can be easily linked to cognitive dissonance theory (Festinger, 1957). Cognitive dissonance theory describes how a mismatch between attitudes and behavior could lead to rethinking attitudes and experiences. This mismatch is perceived as psychological discomfort (dissonance) and motivates a reconsideration of existing attitudes and thus a learning process. This dissonance might be due to an external event or agent (external trigger/incident) or might develop from one's own thinking (internal trigger/inner need to reflect).

2.2 Pragmatical Background

On the pragmatic side, we have a new kind of lifelogging approaches. Lifelogging is the process of tracking personal data generated by our own behavioral activities like data about sleep, exercise, food, mood, location, alertness, productivity, or even spiritual well-being.

QS (The Quantified Self, 2011) has emerged as a community pursuing different lifelogging approaches. The experiments that they perform and the tools they use or develop have the intention of gaining knowledge about their own behaviors, habits and thoughts by collecting relevant information related to them. The starting points of the QS initiative are not scientific theories but are based on empirical self-experimentation. One of the success factors of the QS approaches is the attempt to make vaguely defined aspects of our lives measurable; for instance, our mood or the quality of our sleep.

Apart from QS, all these approaches and tools can also be found under a variety of names including personal informatics, living by numbers, self-surveillance, self-tracking and personal analytics (Li et al. 2010). This community of self-trackers is eager to experimentally learn more about human life: “people experiencing some change in their lives, going on or off a diet, kicking an old habit […]. These were potential experiments, not real experiments, because typically no data was collected and no hypotheses are formed. But with the abundance of self-tracking tools now on offer, everyday changes can become the material of careful study” (Wolf, 2009).

Besides all these personal experiments, plenty of tools are already available, which facilitate the tracking of different aspects of our lives. Some of these tools are web-based applications e.g. Dopplr, Daytum, Mycrocosm, Moodscope; others are devices provided with physiological or environmental sensors e.g. MIO, SenseCam, SenseWear, DirectLife, Nike; and yet others consist of mobile applications e.g. Sleep Cycle, Trixie Tracker, oneLog or My Tracks (for more details about these tools see Section 3.1 and References Section).


125

3. A FRAMEWORK TO APPLY QS APPROACHES TO SUPPORT REFLECTIVE LEARNING

In the previous section, reflective learning and QS were introduced and defined for the purpose of this paper. In the following we present a framework that combines these research strands into a model for the technical support for reflective learning; centered around the model of Boud et al. (1985).

Our framework defines three main support dimensions, namely: tracking cues, triggering and, recalling and revisiting experiences (see Fig. 2).

Figure 2. Role of the three QS potentials in the process of reflective learning

Figure 2 shows these three dimensions in relation to the reflective learning model of Boud et al. Firstly, (a) tracking cues is directly related to capturing and keeping track of behavior, ideas and feelings, which are the source of the reflective process on the one hand, and on the other hand related to the measurement of outcomes (e.g. new perspectives or change in behavior), which are continuously integrated with the original cues in order to feed future iterative reflection processes. Secondly, (b) triggering is related to fostering the initiation of reflective processes in the learner, based on the gathered data and the analysis performed on it. Finally, the (c) recalling and revisiting experiences supports the process of returning to and evaluating past experiences, as well as that of attending to feelings, through the enrichment and presentation of data. In order to satisfy these three support dimensions, QS tools allow (i) capturing and keeping track of data, (ii) processing and enriching data and finally (iii) presenting it to the user and sharing it with other applications or systems.

In the following we further differentiate the three support dimensions that are part of the framework, based on how they can be instantiated by QS tools.

3.1 Tracking Cues

Tracking means capturing data about a person and her context in order to aid the reflective process. Tracking strives to quantify (aspects of) a person's life in order to enable some objectivity in understanding it. Tracking facilitates reflective learning by collecting data on experiences and outcomes that can be used as objective

ISBN: 978-972-8939-66-3 © 2012 IADIS

126

basis in reflection and triggering. We further characterize tracking by (a) the means that are used, (b) the object that is tracked, and (c) the goal that is being strived for.

3.1.1 Tracking Means

Two main ways for tracking exist: self-reporting through often specialized software and hardware sensors that directly track behavior.

Software Sensors: Software sensors are applications (desktop-based, web-based or mobile-based) that aid the user in capturing experiences. Software sensors are particularly important for experiences that cannot (currently) be directly measured (such as feelings or ideas) and are often much simpler, more flexible and cheaper to realize than hardware sensors.

Software sensors are currently used in a broad variety of QS applications. For example, Daytum (2011) relies exclusively on software sensors: a web application and an iPhone app. It enables tracking any number of arbitrary things, categorizing them and viewing infographics based on this data. Another example is the more specialized Trixie Tracker (2011) that supports parents in tracking data about their child and their interaction with it (such as diaper changes, naps and bottles fed).

Hardware Sensors: Hardware sensors are devices that automatically capture data that can be used to describe experiences or collect contextual information. Common categories of sensors are: environmental sensors (e.g., light sensors, thermometers or microphone) and physiological sensors (heart rate sensors, sphygmomanometers, accelerometers, etc.).

One example is the application Sleep Cycle (SleepCycle, 2011) that makes use of an iPhone's acceleration sensor to track sleep states in order to help people better understand their sleep. Another application is Nike+ (NikePlus, 2011), an application built around an accelerometer attached to a shoe. Its goal is to measure and track the distance of a walk or run.

3.1.2 Tracked Aspects

Of crucial importance to QS applications is the selection of data about experiences and outcomes that is being tracked; what is tracked is likely to have a large effect on user acceptance and efficiency for reflective learning. The tracked aspects for a QS application can be very broad ˗ as for example in “total capture” applications like the SenseCam project (SenseCam, 2011) which strives to use a camera to track all aspects of daily life. However, research so far has found little evidence of such systems being effective in serving as a digital memory or supporting reflection processes (Sellen and Whittaker, 2010). Situation specific tracking applications ˗ as for example the above mentioned Trixie Tracker ˗ concentrate on only a small class of experiences (in this case some experiences related to child rearing).

The tracked aspects found in QS applications can be classified in the following way: Emotional aspects: Emotional aspects such as mood, stress, interest, anxiety, etc. Private and work data: Data from work processes and our lives such as photos, browser's history, digital

documents, music, or use of a particular software etc. Physiological data: Physical and biological data to describe a person's state of health. Main approaches

are the measurement of physical activity (focus on sport) and factors affecting health (e.g. glucose level). General activity: Data about a users' general activity comprises e.g. the number of cigarettes, cups of

coffee, hours spent in a certain activity or number of times that something is done.

3.1.3 Purposes

Another important classification dimension is that of the purpose of a QS application; the goal which the user tries to achieve by using it. This purpose drives and guides which aspects or parameters are tracked and which means are appropriate.

Within their framework, Li et al. (2011) have identified six different purposes people have in mind when tracking data. These are to get to know (1) their current status for determining if goals are met or correction in behavior is needed; (2) the history of their data for determining trends and progress; (3) (new) goals worth pursuing; (4) discrepancies between their set goal(s) and current behavior either to correct or maintain it; (5) the context that may influence their status; and (6) long-term influencing factors in order to monitor trends.

Seen within the reflective learning framework, the purpose is the outcome that the user tries to achieve. An example goal would be mood improvement in the Moodscope application (Moodscope, 2011) that encourages users to track and share their mood.


127

3.2 Triggering

In the reflective learning process, triggers are responsible for starting the actual reflection process and their role is to raise awareness and detect discrepancy. We differentiate between active and passive triggering.

3.2.1 Active Triggering

Active triggering consists of the tool sending a notification or catching the attention of the user explicitly. In order to support active triggering, an application must perform data analysis to detect experiences that are suitable for initiating reflection. Such an experience may contain a mismatch between a user's goals and current level, comparison to a global threshold or other persons or a deviation from personal patterns. Examples for active triggering are alerts on RescueTime (2011): the system sends emails to the user based on specified goals, for instance the maximum allowed time to spend on 'distracting' websites.

3.2.2 Passive Triggering

A system supporting only passive triggering does not identify experiences suitable for fostering reflection or it would not actively contact the user. This kind of system only displays the collected data in a suitable way. It relies on the user to be triggered by something outside of the system or on the user regularly visiting the site and then detecting something that starts a reflection process. Daytum (2011) (described above) is one application that relies purely on passive triggering.

3.3 Recalling and Revisiting Experiences

Different aspects affect the recalling and revisiting of past experiences, when analyzing the benefits that QS approaches could offer. Enrichment and presentation of the data may facilitate the revisiting of the data to analyze past experiences and reflect about them, and therefore enhance the learning process of the user. Support of QS applications can exist along multiple dimensions: Contextualization, Data Fusion, Data Analysis, and Visualization.

3.3.1 Contextualizing

The data being tracked can be enriched with other context data (other sources of information) and may be performed by the same tool or result from the interaction between tools (e.g. two mobile applications or a sensor with an application). An example for the contextualization for reflection is Garmin Connect (2011), which tracks heart rate, bicycle speed, cadency, altitude and location and displays this in a map.

Adapting the context definition from (Dey, 2001), we define context as any information that can be used to characterize the situation of a tracked entity and that can aid the reflection process. For this framework we need to consider as context everything that can aid the understanding of sequences of (data about) experiences and outcomes. Based on existing QS applications, we have identified the following classes:

Social context: Data can be augmented with information about the social context of the user. This could be a comparison of own performance to Facebook friends or a comparison to all users. Sharing in a social context provides additional data to others in expectation to retrieve more data in exchange and ultimately see one's own experiences in relation to other ones. An aggregation of data over multiple users may provide new perspectives on experiences and offer new abstraction levels. Such an aggregation can be useful for individual reflection but also at a collaborative level, e.g. reviewing team performance over one month (Müller, Krogstie and Schmidt, 2011).

Spacial context: The location in terms of city, street or even the room can aid reflection by helping the user to understand the relation between place and her behavior ˗ such as understanding the effects of high altitude on her heart rate, the calming effect of visits to specific places or the identification of the places where most time is lost in traffic.

Historical context: Historical data is a further type of context data that can aid in the reflection process. Comparing current values to historic ones allows to see upward and downward trends or to identify deviations from a historic norm that may indicate a problem. Historic data may also help to identify the difference between periodic fluctuations (such as variations in weight or fitness according to the seasons) and other deviations from the norm that may indicate progress or a problem.

ISBN: 978-972-8939-66-3 © 2012 IADIS

128

Item Metadata: Metadata might be available about the things a user interacts with – such as the information that a particular website a user is accessing is not work related but rather distracting, or the information that a food someone ate contains a large amount of sugar.

Context from other datasets: In addition there are numerous datasets (e.g. weather or work schedule) that might also be used in contextualizing.

3.3.2 Data Fusion: Objective, Self, Peer and Group Assessment

One important aid to the reflection process can be the fusion and comparison of different kinds of assessment: objective (i.e. measured by sensors), self (i.e. self-reported data from the user), peer and group assessment (reported data from others about a user). There may be differences and discrepancies between these views that can foster reflection, can help to bridge the gap from subjective to objective experiences and in this way yield new insights and lead to learning (see also Müller, Rivera-Pelayo and Schmidt, 2011).

3.3.3 Data Analysis: Aggregation, Averages, etc.

Different forms of data processing help to present the user useful measurements (e.g. number of cups of tea per day/week, average mood of my colleagues, etc.). Müller, Krogstie and Schmidt (2011) suggested formal, graphic and mathematic aggregation, depending on the data and purpose of the aggregation.

3.3.4 Visualization

It is necessary to choose attractive and intuitive presentation and visualization forms for the users that, at the same time, foster the analysis of the data for reflective learning purposes and being otherwise one of the major barriers (Li et al., 2010).

4. EXEMPLARY APPLICATION

In order to illustrate the application of the presented framework, we present Moodscope as an exemplary QS application in a more detail and show how it is classified. We have chosen Moodscope with the intention of covering several of the main presented points: having a web-based software sensor; dealing with data related to emotions; and finally having an approach with a fuzzy general goal.

4.1 Moodscope

Moodscope (http://www.moodscope.com) consists of a web-based application that allows users to track their mood through a card game, see its mood evolution on a graph and share the scores with friends. The purpose of this sharing is the support that the user can receive from her friends, when they are aware of her emotional state. According to the website of this tool, “measuring one's mood is a daily must do, just like cleaning one's teeth or washing your face” (Moodscope, 2011).

4.1.1 Tracking

Moodscope is based on a web application (see [3.1.1]) that supports the capturing and tracking of emotional aspects, concretely a person's mood (see [3.1.2]).

The measurement of the mood is done through a card game based on a psychological mood questionnaire called PANAS (Watson, 1988). Users can choose among twenty double-sided cards every day. They can do it once a day and it is suggested to do it best at the same time each day.

Having chosen a card, the user receives a score, which is a percentage between 0 (sad) and 100 (happy). The reason to choose this card game is the fact that cards engage the more thoughtful and reflective side of the human brain (Moodscope, 2011). The general goal that any user of Moodscope may have is being happier and thereby feeling better (see [3.1.3]), by following and sharing the history of his/her mood data.

4.1.2 Triggering

Moodscope follows the particular phenomenon called “The Hawthorne Effect” with the theory that when we believe that we are being observed our behavior can change for the better. Therefore, Moodscope sends an


129

email with the user's diary score and a progress graph to the people that act as a “buddy”. These buddies are chosen by the user him/herself and may be friends, colleagues or relatives. This sharing of the data acts as a motivation for the user and affects the progress of his/her emotions, but it is not a trigger itself. This tool may then support a kind of passive triggering, when it shows to the user the evolution of her mood (see [3.2.2]).

4.1.3 Recalling and Revisiting

Users can review the evolution of their mood in a timeline graph (see [3.3.4]). This historical context (see [3.3.1]) can help them to gain a more objective view of their emotions (see [3.3.2]) and the comments made in the progress graph supports the contextualization of the mood [3.3.1]. Regarding the analysis of the data, minimum, maximum and average of the moods are calculated (see [3.3.3]). The user can share her moods with the buddies (chosen by her) and these receive a diary email with his/her mood status and progress. Although data is shared, there is no comparison established with the mood of any other users (see [3.3.1]).

5. DISCUSSION AND CONCLUSION

The collection of personally relevant information through QS approaches offers a rich source of data that has not been available for learning processes before. Moreover, the continuous advances in technology can facilitate data gathering and therefore the quality and features of the tools. Sensor technologies are being improved, mobile technologies and devices are more widespread and Internet provides ubiquitous access to information. QS approaches offer a wide potential of awareness augmentation, quantification of abstract measures and analysis of data that has not yet been considered for learning processes. Approaches like emotional awareness provided, e.g., by self-tracking, or enrichment of data provided by, e.g., annotation, can broadly support learner's experiences and shed light on the process of personal learning and improvement.

This paper presented a framework for the application of QS tools to support reflective learning. In addition to providing a structured review of this strand of research, this framework is geared towards being used to understand the design space of this kind of applications as well as understanding which parts have not been addressed by research. Future work will include the design and implementation of new QS tools that will empirically validate the presented framework to support reflective learning.

In the following, we want to introduce some of the issues that were identified when reviewing existing research into QS applications within this framework.

There is currently almost no research that shows or even analyses the link between the use of QS applications and the achievement of the desired outcome. Similarly, there is no research into the question which properties of QS applications make them more or less successful.

Assuming that Quantified Self tools can be shown to help people achieve their desired outcomes, there is also a lack of understanding on how to identify the situations where they are likely to work, which are the right aspects to track and finally how to spread these tools beyond the current relatively narrow user base.

Overall the proposed combination of reflective learning and QS applications in this framework concretizes the vision of using certain mobile technologies for a particular learning model. This allows identifying promising venues for future research. It also shows the way how technology enhanced learning can be applied beyond classroom settings in daily life to support all kinds of learning and self-improvement.

REFERENCES

D. Boud, R. Keogh, and D. Walker, 1985. Reflection: Turning Experience into Learning, chapter Promoting Reflection in Learning: a Model. Routledge Falmer, New York, USA. pp. 18-40

A. Brockbank and I. McGill, 2007. Facilitating Reflective Learning in Higher Education. McGraw Hill. Society for Research into Higher Education and Open University Press. New York, USA.

V. Bush, 1945. As We May Think. Atlantic Monthly, 176(1) pp.641-649. M. W. Daudelin, 1996. Learning from experience through reflection. Organizational Dynamics, 24(3) pp. 36-48. Daytum, 2011. Available at: http://daytum.com/ (Accessed: 26 December 2011) J. Dewey, 1938. Experience and Education. Macmillan, London & New York. A. K. Dey, 2001. Understanding and using context. Personal and Ubiquitous Computing, 5 pp. 4-7.

ISBN: 978-972-8939-66-3 © 2012 IADIS

130

Dopplr, 2011. Available at: http://www.dopplr.com/ (Accessed: 26 December 2011) L. Festinger, 1957. A theory of cognitive dissonance. Stanford Univ. Press. R. Fleck, 2009. Supporting reflection on experience with SenseCam. In CHI Workshop on Designing for Reflection on

Experience. Boston, USA, ACM. R. Fleck and G. Fitzpatrick, 2010. Reflecting on reflection: framing a design landscape. In Proceedings of the 22nd

Conference of the Computer-Human Interaction Special Interest Group of Australia on Computer-Human Interaction, OZCHI '10, New York, USA. ACM. pp. 216-223

Garmin.connect, 2011. Available at: http://connect.garmin.com/ (Accessed: 26 December 2011) J. Gemmell, G. Bell, and R. Lueder, 2006. MyLifeBits: a personal database for everything. Communications of the ACM,

49(1) pp. 88-95. D. A. Kolb, 1984. Experiential Learning: Experience as the source of learning and development. Englewood Cliffs, N.J.:

Prentice Hall. B. Krogstie and M. Divitini, 2009. Shared timeline and individual experience: Supporting retrospective reflection in

student software engineering teams. In Proceedings of the 2009 22nd Conference on Software Engineering Education and Training, Washington, DC, USA. IEEE Computer Society. pp. 85-92

I. Li, A. Dey, and J. Forlizzi, 2010. A stage-based model of personal informatics systems. In Proceedings of the 28th International Conference on Human Factors in Computing Systems,CHI '10, New York, USA. ACM. pp. 557-566

I. Li, A. K. Dey, and J. Forlizzi, 2011. Understanding my data, myself: supporting self-reflection with ubicomp technologies. In Proceedings of the 13th international conference on Ubiquitous computing, UbiComp '11, New York, NY, USA. ACM. pp. 405-414

MIO, 2011. Available at: http://www.mioglobal.com/ (Accessed: 26 December 2011) MIRROR, 2011. EU Project MIRROR – Reflective Learning at Work. Available at: http://www.mirror-project.eu/

(Accessed: 26 December 2011) L. Müller, B. Krogstie, and A. Schmidt, 2011. Towards capturing learning experiences. In A. Ravenscroft and M.

Sharples, editors, Context and Technology Enhanced Learning (ConTEL): Theory, methodology and design, ECTEL 2011, Palermo, Italy.

Moodscope, 2011. Available at: http://www.moodscope.com (Accessed: 26 December 2011) J. A. Moon. Reflection in learning and professional development. Routledge, 1999. L. Müller, V. Rivera-Pelayo, and A. Schmidt, 2011. MIRROR D3.1 – User studies, requirements, and design studies for

capturing learning experiences. MIRROR project deliverable D3.1. My Tracks, 2011. Available at: http://mytracks.appspot.com/ (Accessed: 26 December 2011) Mycrocosm, 2011. Available at: http://mycro.media.mit.edu/ (Accessed: 26 December 2011) NikePlus, 2011. Available at: http://www.nikeplus.com (Accessed: 26 December 2011) oneLog, 2011. Available at: http://www.schmitzware.org/Software/OneLog/index.shtml (Accessed: 26 December 2011) Philips DirectLife, 2011. Available at: http://www.directlife.philips.com/ (Accessed: 26 December 2011) RescueTime, 2011. Available at: https://www.rescuetime.com (Accessed: 26 December 2011) D. A. Schön, 1987. Educating the Reflective Practitioner. Jossey-Bass, San Fransisco, 1 edition. A. Sellen and S. Whittaker, 2010. Beyond total capture: a constructive critique of lifelogging. In Proceedings of

Commun. ACM. pp. 70-77. SenseCam, 2011. Available at: http://research.microsoft.com/en-us/um/cambridge/projects/sensecam/ (Accessed: 26

December 2011) SenseWear, 2011. Available at: http://sensewear.bodymedia.com/ (Accessed: 26 December 2011) SleepCycle, 2011. Available at: http://mdlabs.se/sleepcycle/ (Accessed: 26 December 2011) K. Strampel and R. Oliver, 2007. Using technology to foster reflection in higher education. In ICT: Providing choices for

learners and learning. Proceedings ascilite Singapore 2007. D. Sugerman, K. Doherty, and D. Garvey, 2000. Reflective learning: theory and practice. Kendall/Hunt Pub. Co. The Quantified Self, 2011. Available at: http://quantifiedself.com (Accessed: 26 December 2011) Trixie Tracker, 2011. Available at: http://www.trixietracker.com/ (Accessed: 26 December 2011) D. Watson, L. A. Clark, and A. Tellegen, 1988. Development and validation of brief measures of positive and negative

affect: the panas scales. Journal of Personality and Social Psychology, 54(6) pp.1063-1070. G. Wolf, 2009. "Know Thyself: Tracking Every Facet of Life, from Sleep to Mood to Pain, 24/7/365". Wired Magazine.


131

‘MEETING THEM WHERE THEY’RE AT’ – EXPLORING STUDENT PERSPECTIVES OF MOBILE LEARNING IN

HIGHER EDUCATION

Kate Reader, Sian Lindsay and Ajmal Sultany City University London

ABSTRACT

This study takes a fresh look at the role of mobile learning in Higher Education (HE) by drawing on the opinions of students. With rapidly evolving mobile technologies and assumptions of mobile learning abound, it is critical that HE institutions keep up-to-date in their knowledge of the type of mobile devices owned by students, how students currently use their mobile devices and how students would like to use them in the context of formal and informal education. We conducted a Student Mobile Device survey (SDMS) to address these questions. Survey results showed that virtually all students owned a mobile phone, the majority (but not all) owned smartphones and many use their mobile devices for web browsing, email and VLE access. Many students want to use their mobile devices to download lectures and receive grades and feedback, however use in the classroom was unpopular. We conclude that nearly all students want to use their mobile devices for learning in some way; however approaches to this are diverse. It is therefore the institution’s responsibility to ensure that its educational tools and materials are accessible to enable all students to build their own personalised learning environments on the mobile device of their choice.

KEYWORDS

Mobile_learning student_voice survey

1. INTRODUCTION

The recent global explosion of smartphones and tablets has led to new and exciting possibilities in Higher Education (HE). In recent years it has been argued that it is more cost-effective that educational institutions take advantage of the mobile devices that students own, rather than rely on institutional provision of similar hardware (Attewell, 2009; Traxler, 2010; Lindsay 2010). However assumptions in HE can be made in relation to the types of mobile devices that students own, how students currently use them, and students’ willingness to use them as part of their formal education. A Student Mobile Device survey (SMDS) was conducted in January 2011 in order to evaluate the current usage of smartphones and tablet computers at City University London. The aims of this survey were: 1) to understand the types of mobile devices owned by students; 2) to understand the ways in which students currently use their mobile devices (generally and in the context of HE) and 3.) to identify student attitudes towards mobile learning.

In addition to pedagogical implications, there were several reasons for obtaining this data. Firstly, student data would help inform lecturers, academic and administrative staff in developing appropriate learning opportunities and communication methods. Secondly it would help inform City in its policy-making, and when developing a mobile strategy. Thirdly the data would be used to inform those departments responsible for both implementing computer systems, new security systems and wireless provision, when making changes to the network, or when thinking about redeveloping or building new teaching and learning spaces. Finally we would anticipate that the SMDS data would provide valuable evidence to support other HE institutions currently developing mobile strategies.

ISBN: 978-972-8939-66-3 © 2012 IADIS

132

2. BODY OF PAPER

2.1 Background

In 2009 the Horizon Report clearly stated that mobile learning would be widely adopted for learning within a year (Johnson et al. 2009), yet this has been a silent revolution (Livingstone, 2009) rather than the predicted big bang. In 2009, studies such as Wang et al (2009) and Maniar and Bennett (2007) were warning us of the technical challenges of mobile learning, citing restrictions such as small screen size, short battery life and lack of standardisation. At the same time, smartphones were relatively new on the market and limited in their functionality, they were also expensive for the majority of students, as was the data needed to use them to their full capacity. However in the last two years with rapid advancements in smartphone technology, the introduction of longer contracts (bringing down the initial cost of the smartphone), and the significant drop in the price of bundled data, in this study we now find that 99% of our students own a mobile phone and 77% own a smartphone.

In late 2009 when we began to investigate the ways in which students were using their mobile devices, we observed increasing levels of smartphone ownership amongst students, along with the predicted educational influence of upcoming tablets. There were also several case studies that demonstrated academic use of mobile technologies both inside and outside lectures (Price, 2007; Lai et al., 2007; Lindsay et al., 2010),. Yet we found few published cases whereby institutions had evaluated the ways in which students were using their mobile devices for informal learning.

Liu et al (2010) advise that the key success factor for mobile learning is to “understand the concerns of learners and to identify the determinants which lead to learners’ willingness to adopt mobile learning” (Liu et al, p 220). It was our aim to use the SMDS to fill an apparent gap in knowledge in relation to broader student perceptions toward using their own mobile devices as part of their formal education. In relation to this, we also wanted to explore the ways in which we should be supporting student owned devices. We had several questions to answer: what kinds of educational activities did students want to use their mobile devices for but perhaps couldn’t? How would students feel if their lecturers co-opted their mobile devices to enhance student learning, particularly in a traditional teaching environment such as a lecture? Are students already using their mobile devices to support their education, and if so how? Whilst we could attempt to guess at the answers to these questions it became evident that we had no empirical evidence to back our predictions, and in fact the results of the study ended up challenging and contradicting many of our original assumptions.

It was clear from the out-set that in order to gain reliable data of this type, we would need to capture a broad range of data from students across the institution, and an online survey was fitting for this purpose. Survey questions were carefully constructed to avoid attracting only those students that were most engaged with new technologies, and to avoid using language that only the “tech-savy” would understand. This enabled us to gain an accurate and fair picture of student mobile device use.

2.2 Methodology

To generalise survey responses to the wider student population, a sample of students was randomly selected using probability sampling where each student at City had a known, nonzero probability of being included in the sample (Henry, 1990). The target population for this study was all undergraduate and postgraduate students at City with the exception of 3rd year undergraduates (who were in their 3rd year during the 2010/11 academic year). We excluded 3rd year undergraduates to prevent student fatigue in the completion of the National Student Survey, which was seen as a priority survey.

The population size was 13,218 and an appropriate sample size was selected to enable us to meet a 95% confidence level and a ±3% sampling error (EDIS, 2011). The sample was then stratified according to School so that students from all Schools were fairly represented. A total of 1390 students were randomly selected and contacted; 411 students completed the online questionnaire however following elimination of partially completed surveys the final count was 369 responses. Thus the response rate was 27%. Low response rates are a well-documented weakness of web surveys and can create the problem of sample bias (Bryman, 2008). However, sample bias can be detected by comparison of the demographics of the sample with that of the population (De Vaus, 2002). The demographics of this study’s sample (in terms of gender, age, ethnicity and


133

School) are comparable to those of the wider population; therefore any effect of sample bias is minimal. Once the scope of the population was established, a sampling frame was obtained. Permission was granted to access all student (except 3rd year undergraduates) contact details available from City student administration records database on Monday 17th of January 2011. The dataset was carefully vetted for any inconsistency in accordance with Dillman et al.’s (2008) recommendation of questioning secondary datasets.

The Student Mobile Devices questionnaire had 23 questions, one of which was an open-ended question. Due to the exploratory nature of the study, a large proportion of the questions were multiple-choice. The questionnaire was created around the mobile learning discourse to better gauge student behaviour, perceptions, values and attitudes with mobile devices and mobile learning. As such, the questionnaire covered topics such as type of devices owned, how mobile devices are used, time and money spent on mobile devices, social networking, and beliefs about mobile learning. The full list of questions used in the survey is given in Table 1. Each potential participant was sent an electronic invitation to take part in the online survey to both their personal and University email addresses.

The survey research received ethical approval from the City University Learning Development Advisory Group and the Senate Research Ethics Committee.

2.3 What Mobile Devices do our Students Own?

Our survey was fully completed by 369 City students and of these only 3 said that they did not own a mobile devic (i.e. a mobile phone, smartphone or tablet). This means that at a 95% confidence level, 99% (+/- 6%) of City students own a mobile device. This figure is slightly higher than the national level - Ofcom found that 91% of adults personally own or use a mobile phone in the UK (Ofcom, 2011). Approximately 76% of City students own a smartphone, the most popular student choice was an equal split between Blackberry and iPhone, at 28% each, with a small percentage of students owning both (3%). A quarter of our students did not own a smartphone, all of these students owned a regular mobile phone instead. Of the students who did not own a smartphone, the majority were from the School of Health Sciences. A very small percentage of students without a smartphone (1%) said that they owned a tablet instead.

Most popular amongst tablet ownership was the iPad, owned by 8% of students in our sample. Of the iPad and iPhone owners, roughly 70% were male, and the majority were from the Cass Business School and in the 26 - 35 age group. Blackberry smartphone owners were mainly female students, again from the Cass Business School but in a younger 17 - 20 age category. These differences were observed even when the data was normalised according to the proportions of various groupings in the sample.

2.4 How are Students currently using their Mobile Devices?

We asked students to indicate how much time they spent using their mobile device on an average weekday. Most students identified that they spent 1 - 2 hours each weekday using their mobile devices. We could not detect any significant correlation between the amount of time students spent on their mobile devices and any other variables such as type of mobile device owned or number of activities carried out on a mobile device. This challenged our earlier assumption that the more sophisticated the device, the more time a student would spend using it. It is interesting that over 10% of our students are using their mobile devices for more than 5 hours per day. This figure may rise in the near future, as web access via mobile devices is anticipated to overtake desktop web access within the next five years (mobiThinking, 2011). This result highlights the potential for institutions to utilise mobile technologies in order to engage their students.

We asked students to indicate what they had used their mobile devices for in the past ten days; this period of time was selected to highlight differences in frequency of task over a reasonable time period. The four most popular tasks were text messaging (99%), making and receiving phone calls (97%), web browsing (71%) and emailing (70%). The proportion of students using their mobile devices to access the Internet is more than double that of the national trend of 32% (Ofcom, 2011). This difference clearly highlights the value of mobile internet access for students.

Students are carrying out study-based tasks traditionally reserved for computers on their mobile devices. For example web browsing (71%), using email (70%), viewing documents (35%), accessing Moodle (27%) and editing documents on their device (6%). It is probable that the number of students engaging in these sorts of activities via a mobile device will increase. However, it is important to highlight that students will

ISBN: 978-972-8939-66-3 © 2012 IADIS

134

only be able to take advantage of such technological advances provided that the institution’s supporting infrastructure remains up to date and resilient. It is interesting that for City, 27% of students were accessing Moodle (the University’s Virtual Learning Environment) on their mobile devices. This is a surprisingly high proportion seeing that at the time of the survey there was no compatible Moodle “app” and Moodle had limited functionality via a mobile browser. Also when the survey was being conducted, City was migrating over to Moodle with less than 50% of its programmes having completed migration. This finding is later reinforced by results that show the number of students who want to access the VLE and educational materials via their mobile device.

We asked our students what social media they had interacted with in the last 72 hours on their mobile devices. Unsurprisingly the majority of students (59%) said that they had accessed Facebook, which ranks as number 1 in the world for highest number active users (800 million) with 44% of these accessing it through their mobile device (Facebook statistics, 2011). Thirteen percent of our students said that they had used Twitter on their mobile devices in the past 72 hours. The popularity of mobile Facebook and Twitter access by our students reflects global trends. Half of the students had updated their status or posted to their wall in the last 72 hours. Thirty-five percent of students had commented on something such as a friend’s status, whereas 19% had shared something (e.g. re-tweeting) and 14% had uploaded something such as a photo. Students that selected ‘other’ wrote comments like “viewing my wall”, “reading wall posts from friends, but I never post any of my own”, “reading Twitter posts”, and “accepting professional invitations”. These findings demonstrate that students are using their mobile devices in web 2.0 interactive ways and student familiarity with these types of interactions may inspire and provide opportunities for engagement in teaching and learning activities that utilise mobile technologies.

Universities need to remain aware that while smartphones are becoming both popular and affordable in the student population, they are by no means owned by all. Around 25% of our students do not currently own a smartphone, which in real terms at City University London equates to approximately 3,500 students. Institutions therefore have to keep in mind (for at least the next couple of years) that whatever opportunities they are providing for students that own sophisticated devices, this should not impact the quality of education received by those without.

2.5 What are Student Attitudes towards using their Mobile Devices formally or informally as Part of their Education?

We asked our students which activities they would like to carry out with their mobile devices to support their learning. As Figure 1 shows, the top 5 activities that students want to carry out are: 1) viewing timetable information (71%); 2) receiving grades and feedback (63%); 3) receiving text alerts from administrators and tutors (61%); 4) accessing lecture materials and documents online (54%); and 5) accessing lectures online (48%).

In order to address these student requests we have initiated several changes to enhance the student experience. For example in the School of Arts and Social Sciences at City we have introduced 100% electronic submission of assignments, and bulk upload of feedback and grades via Moodle, to enable students to collect their grades and feedback via their mobile devices. We have introduced Edutext text messaging for SMS alerts from administrators and tutors. And we have implemented lecture capture via Echo360 and iTunesU that can be subscribed to via RSS (Podcast) on student mobile devices allowing them to watch lectures online. It will be interesting during evaluation of these new tools and processes to determine whether the percentage of students utilising them matches those that requested these services.

Whilst interaction with teaching and learning activities and administrative systems outside of the classroom were popular with students, use of their mobile devices in class was not. Sixty-four percent of students said that they did not want to use their mobile devices in class as part of their education, whereas 72% said that they did want to use their mobile devices for any learning that takes place outside of the classroom without the aid of a lecturer (Figure 2). That said there were still 19% of students who wanted to ask questions in class with their mobile device, and 22% of students that wanted to use their mobile device for in-class voting (Figure 1). Whilst these represent a minority of students, when scaling from sample to population this could be approximately 3,000 students and therefore arguably important.

We carried out a content analysis of 204 individual student comments relating to the use of their mobile devices in class. All comments were analysed and categorised. Most students said that using a mobile device


135

for informal learning or e-learning was useful, however using mobile devices in class was a real cause for concern on the grounds of them becoming a distraction for students and their peers. In addition to this ‘self-policing’ response, other student comments were anxious to describe how using mobile devices might somehow diminish the learning experience and take away from traditional student-lecturer interactions in class. Fourteen percent of students said that they did not want to use their mobile devices in any of the suggested learning contexts. This is interesting as it is a relatively high percentage of students ‘resistant’ to mobile learning. Amongst these students we did not detect any significance due to age or gender, however all were from either the City Law School or the School of Arts, so there may be a disciplinary distinction in relation to the learning activities that students want to carry out on their mobile devices.

We asked our students to tell us which of Winters’ four mobile learning perspectives they most agreed with. The majority of students (36%) felt that mobile learning was about an individual learning whilst mobile (i.e. learner-centred). Only 8% of students opted for mobile learning as adding something to face-to-face teaching (i.e. augmenting formal education). This finding perhaps demonstrates that students do not see the learning potential for using their mobile devices in class.

2.6 Figures and tables

Table 1. Student Mobile Device Survey questions

1. Do you own a mobile device (i.e. a tablet, smartphone or regular mobile phone)?

2. Do you own any of the following tablets?

3. Do you own any of the following smartphones?

4. Do you own any of the following mobile phones?

5. Within the past ten days, which of the following have you used your mobile device(s) for?

6. In the last 72 hrs which of the following social media have you used on your mobile device(s)?

7. How have you interacted with social media through your mobile device in the last 72 hours?

8. How much do you pay per month for your contract mobile devices (in total)?

9. How much do you spend on pay as you go mobile devices each month?

10. On an average weekday how much time do you spend using your mobile device(s)?

11. What features does your mobile device(s) have?

12. Which mobile network do you subscribe to?

13. Which of the following devices do you own?

14. If your mobile device(s) can connect to a wireless network (WiFi), how would you rate your wireless connectivity experience at City?

15. If accessibility was improved at City what would you like to use your mobile device(s) for?

16. If for whatever reason you couldn’t use your mobile device(s) for a couple of days, how might you feel?

17. How do you feel about the following statements [about using mobile devices in class]?

18. What do you think the term 'mobile learning' means? Please select the statement that most closely fits with your definition

19. How old are you?

20. What is your gender?

21. In which School at City are you studying?

ISBN: 978-972-8939-66-3 © 2012 IADIS

136

Figure 1. Activities that students would like to use Figure 2. Student Opinions on using their mobile their mobile devices for to support their learning devices in-class and for informal learning

3. CONCLUSION

In this study we have conducted a University-wide Student Mobile Device survey (SMDS) to update our knowledge regarding student-owned mobile devices. We find that students are using their mobile devices in sophisticated ways for everyday use, many of our students already have smartphones, and we predict many more will be purchasing tablets in the future. Many students are using their mobile devices for informal learning by accessing the VLE, podcasts, and other institutional systems. For the majority of our students, use of their mobile devices for social networking activities (specifically Facebook) is ingrained into their everyday life. However whilst we can identify these trends on the basis of the majority, it is important that we do not ignore the minority and make false assumptions that all students own smartphones, and are familiar with the technologies and affordances that they provide. We also cannot assume that all students are both willing and able to use their mobile devices for their education, and it is important to remember that the majority of students were negative about using their mobile devices in a formal classroom setting, our students were clear that they viewed mobile learning as a learner-centered activity and not one that augments formal education, the majority were opposed to mobile learning supporting face to face teaching.

In establishing what students want to use their mobile devices for in an educational context, we find much diversity: many students want to access grades and feedback, others want to download lectures, most are unhappy with the prospect of using their mobile devices in class, yet others feel in-class use could be beneficial. In short there is not one solution that fits all when it comes to enabling students to use their own devices, or how they are used. This finding is consistent with Traxler’s view that “Student devices unlock the dreams of agency, control, ownership and choice amongst students” (Traxler, 2009, p 80.). Therefore as an institution we need to allow students to make their own decisions in relation to how much they want to engage with institutional systems on the mobile device of their choice. Furthermore, if we ask students to use their own mobile devices as part of their formal education, we must ensure that they are all equipped and able to do this.

In assessing the educational activities that the majority of students currently do and aspire to on their mobile devices, we would recommend that institutions take steps to improve or enhance mobile support for document editing, email and timetabling access, accessing materials on the VLE, access to grades and feedback, and downloading lectures and podcasts. Our survey findings support the notion that if institutions can provide the platforms that enable students to pick and choose these activities it is likely that this would result in a large improvement to the student experience.


137

ACKNOWLEDGEMENT

We would like to thank David Marks from City University London for providing us with the details of students to contact for the survey. We would also like to acknowledge the support of the Student Union at City University London in encouraging students to take part in the survey. Finally we would like to thank Mike Cameron from Newcastle University for his contributions help and support during the pilot year of this study.

REFERENCES

Attewell, J., Savill-Smith, C. and Douch, R. (2009) The impact of mobile learning, examining what it means for teaching and learning (Bedford, LSN).

Bryman, A. (2008) Social Research Methods 3rd edition (Oxford, Oxford University Press). De Vaus, D. (2002). Surveys in Social Research 5th edition (London, Routledge). Dillman D.A., Smyth J.D., & Christian L.M. (2009) Internet, Mail, and Mixed-mode Surveys: The Tailored Design

Method 3rd edition (New Jersey, John Wiley & Sons). EDIS (2011) Determining Sample Size. (University of Florida) Available online: http://edis.ifas.ufl.edu/pd006, last

accessed: 9th July 2011. Facebook (n.d.) Statistics. Available online: http://www.facebook.com/press/info.php?statistics last accessed: 3rd

November 2011. Henry, G.T. (1990) Practical Sampling (London, SAGE Publications). Johnson, L., Levine, A., and Smith, R. (2009) The 2009 Horizon Report (Austin, The New Media Consortium). Lai, C. H., Yang, J. C., Chen, F. C., Ho, C.W. and Chan, T. W. (2007) Affordances of mobile technologies for

experiential learning: The interplay of technology and pedagogical practices, Journal of Computer Assisted Learning, 23, 326 – 337.

Lindsay, S., Parmar, N., Cameron, M., Reader, K., & Sultany, A. (2010) Before I begin, can I ask all students to switch their mobile devices ON? (Oxford, ALT-C 2010 – Conference Introduction and Abstracts). Available online: http://repository.alt.ac.uk/798/ , last accessed 3rd November 2011.

Liu, Y., Han, S. and Li, H. (2010) Understanding the factors driving m-learning adoption: a literature review, Campus Wide Information Systems, 27, 210 – 226.

Livingston, A. (2009) The Revolution No One Noticed: Mobile Phones and Multimobile Services in Higher Education (Educause Quarterly) Available online: www.educause.edu/EDUCAUSE+Quarterly/EDUCAUSEQuarterlyMagazineVolum/TheRevolutionNoOneNoticedMobil/163866 , last accessed: 3rd November 2011.

Maniar, N. and Bennett, E. (2007) Media influence on m-learning? (Tampere, Finland, Proceedings of VideoFunet conference).

mobiThinking (2011) Global mobile statistics 2011: all quality mobile marketing research, mobile Web stats, subscribers, ad revenue, usage, trends… (dotMobi) Available online: http://mobithinking.com/mobile-marketing-tools/latest-mobile-stats last accessed: 20th September 2011.

Ofcom (2011) Facts and Figures (Ofcom) Available online: http://media.ofcom.org.uk/facts/ last accessed: 22nd September 2011.

Open University (2009) Mobile Learner Support blog Available online: http://www.open.ac.uk/blogs/mLearn/ , last accessed: 3rd November 2011.

Price, S. (2007) Ubiquitous computing: Digital augmentation and learning, in N. Pachler (Ed.) Mobile learning: Towards a research agenda (London, WLE Centre).

Traxler, J. (2009) Students and mobile devices: choosing which dream (Oxford, ALT-C 2009 – Research Papers) available online at: http://repository.alt.ac.uk/643/1/ALT-C_09_proceedings_090806_web_0288.pdf , last accessed 25th November 2011.

Winters, N. (2006) What is mobile learning?, in M. Sharples (Ed.) Big Issues in Mobile Learning: Report of a workshop by the Kaleidoscope Network of Excellence Mobile Learning Initiative (Nottingham, University of Nottingham)

Wang, Y. S., Wu, M.C. and Wang, H. Y. (2009) Investigating the determinants and age and gender difference in the acceptance of mobile learning, British Journal of Educational Technology, 40, 92 – 118.

Woodill, G. (2011) The Mobile Learning Edge: Tools and Technologies for Developing Your Teams (McGraw-Hill, New York).

ISBN: 978-972-8939-66-3 © 2012 IADIS

138

PROFESSIONAL DEVELOPMENT ENHACED IN NUMERICAL METHODS COURSE BASED ON

B-LEARNING: DESIGN AND FOLLOW UP

Francisco Javier Delgado Cepeda Tecnologico de Monterrey, campus Estado de Mexico

Carretera a Lago de Guadalupe km. 3.5, Atizapan, Estado de Mexico, MEXICO. CP. 52926

ABSTRACT

Information and communication technologies development grows continuously, holding areas which previously have corresponded to classroom learning. Particularly, impact of mobile resources has been documented in mathematics teaching. This paper presents a strategy and a blended learning-based design for a Numerical Methods for Engineering course, combining class, online and mobile activities to strengthen and to develop different skills related to it. Mobile activities have been incorporated into the latest design -which includes tools like Blackboard, Winksite, App Inventor, Wolfram Alpha and Socrative- based on two mobile sites: the first one is online and the last one is an Android local application. In addition, the use of an electronic book with online resources (which was prepared specifically for this course) is included. Finally, follow up for the last three years is shown based on the growing impact of technology on the skills development. In this study, the historical records show a significative impact associated with generic skills, due to growing use of technology in the course, compared to the previous version which did not include online applications and mobile activities.

KEYWORDS

Mobile resources, Blended, Design, Following, Mathematics.

1. INTRODUCTION

Some of the current educational trends are related with the acquisition of technology skills, which has been identified as successful factor in professional life. At same time, new generations have growing expectative for freedom to work, learn and study anywhere and everywhere. It states a growing demand on easily accessible resources through different media. Other challenges are present, such as increasing professional value of digital skills, growing pressure for economy of educational models and greater outstanding educative results. In parallel, there is greater demand in personalized education. Last scenario contrasts with some change resistance in faculty areas and with the fact that students are turning to alternative education in order to learn different subjects by several media (Johnson, Adams and Haywood, 2011). These aspects are developed by a fast technology evolution which is impacting to each discipline which uses it. Mobile technology is now an option to stay connected to information. It is proving to be a creative and innovative media through which education may reach its final consumer. It is estimated that in the following year, it will be the first channel for Internet access by at least 80% of users (Johnson, Smith, Willis, Levine and Haywood, 2011).

Numerical Methods courses are mandatory in engineering programs. They have been rapidly evolved with technology evolution. Its traditional teaching has changed dramatically in last decades, since its birth as modern discipline in the early forties with the growing use of computer systems, and academically in the past three decades because of their affordability. It forced a fast ongoing adaptation of curricula. Spread of programming languages, the use of software and the inclusion of applications let a transition from a numerical analysis course into a computer simulation one. Absence of emphasis on visualization and simulation left a gap between theory and practice (Delgado, 2008b), actually this integration has allowed to integrate curriculum and to develop higher-order thinking skills (Delgado and Martinez, 2011).


139

In the engineering curricula, this course has evolved in the depicted way. Ten years ago it barely contained the use of Fortran or C++ as programming languages, limited time for programming practice and rarely applied problem solving. There was a change in the use of information technologies also: a course not only based on mathematical content, but including programming, use of software, examples and complex applications which result in the ability to visualize and apply mathematics, approaching them to real problems through the use of technology and greater curriculum integration by considering items which require numerical computation (Delgado, 2005, 2008a). The use of Mathematica software (Wolfram, 2011) or Python (2011) as programming languages and computational tools, made possible the delivery of a programming-oriented course allowing to solve applied problems using technology with Problem-Based Learning (PBL) and Project Oriented Learning (POL) (Delgado, 2008b). For this reason, in the engineering curricula, this course has been selected as an integrating curricula course for engineering programs, since it allows naturally the integration of knowledge for the first third of them through visualization projects to understand and analyze issues of physical sciences and engineering. At this point, the course became a blended learning course, primarily only by the use of Blackboard (2011) to ensure delivery of all course elements and other online practice activities based on cooperative work (Briceño & Coiman, 2008).

This paper shows the strategy, design, impact and capitalization of the course evolution into blended learning scheme which combines the use of computer and mobile resources. In that design, mobile technology has solved different needs arisen by the own technology implementation to enhance the professional use of discipline. Analysis presented includes high-level abilities (González, 1997) which are developed by a complementary use of technology, in order to understand their mutual relation.

2. BODY OF PAPER

The increasing inclusion of content and skills development in the course, beyond those corresponding to numerical methods topics, has generated some weaknesses because they implied more educational elements as support for students, particularly, use of software and repositories.

2.1 Design

Class was insufficient to cover contents and practice of programming, so it was necessary design mobile resources to introduce materials in Blackboard, which were planned to support classroom and laboratory. Another weakness was a poor parameters identification related with numerical methods, because an immediate practice was absent before that programming. To overcome these two weaknesses, a third element of delivering was introduced with Winksite mobile platform (2011), illustrated in Figure 1 (Delgado, 2011).

Figure 1. Views of mobile site on Winksite: (a) main menu, (b) poscasts menu, (c) Wolfram Alpha link, and (d) virtual room in Socrative.

In addition, an alternative site was created to be downloaded and installed as an application of App Inventor (Delgado, 2011b) for Android phones (Fig. 2). Both sites include short mobile activities to cover at free time. Other resources available in the mobile sites were podcasts specifically created with Cam Studio and placed in a You Tube channel (Fig. 1b), which contain introductory descriptions and instructions for each

ISBN: 978-972-8939-66-3 © 2012 IADIS

140

Mathematica notebook delivered in Blackboard. A link of Wolfram Alpha (Wolfram, 2011b) was included in the mobile site to practice Mathematica syntax online (Fig. 1c), letting the programming practice.

Figure 2. Views of mobile site in App Inventor: (a) main menu, (b) and (c) App Inventor applications about numerical

methods.

By adding these resources, the course evolved until 40% or 50% of online activities (Fig. 3) in agreement with blended learning definition (Allen, Seaman & Garrett, 2007) or b-learning, in contrast with classroom learning (p-learning) and online learning (e-learning).

Figure 3. Historic evolution of numerical methods course.

This figure shows time evolution from p-learning toward b-learning. In 2000, the course was completely p-learning, but since 2009, it evolved into b-learning, starting with Blackboard (based on e-learning) until recent implementations based on mobile activities (m-learning).

Figure 4. Course electronic book views: a) text and contextual information, b) interactive files. Two views of Blackboard repository: c) general schedule, and d) detailed schedule including media descriptions.


141

Additional elements were several mobile applications (Apps) created with App Inventor (2011) related with some numerical methods and their parameters, in order to practice them. Another element included was a virtual classroom used as assessment tool based on Socrative (2011) as shown in Figure 1d, in which students receive tests to be evaluated in specific topics. Some of these resources are mandatory but others have been considered as alternative activities designed to cover learning needs on demand. Thus, podcast and App Inventor activities are optional. The first ones are used before class by introducing Mathematica files in Blackboard and the second ones, after of class by practicing the use of numerical methods parameters. The use of Wolfram Alpha at the beginning of the course is a valuable element in the practice and learning of programming syntax. Instead, the virtual classroom in Socrative room is mandatory as an evaluation tool.

On the mobile site, an electronic book was prepared for this course (Fig. 4a), which is intended for different times and activities on computers, tablet or mobile phones depending on intention. The electronic book is a connection between Blackboard (Fig. 4b) and mobile resources.

2.2 Abilities Development and Follow Up

All these activities are based on identified weaknesses. The use of different delivery media facilitates their access and their impact on the skills acquisition in the discipline, being distributed in time and resources, as is shown in Figure 5, where "p", "e" and "m" represent the delivery media of each one: face to face, online based on computer and mobile respectively. All these skills are related to the reviewed Bloom's taxonomy (Anderson & Krathwohl, 2001) and theoretical aspects of Bloom's taxonomy in digital technology issues (Churches, 2007), giving a value in terms of professional curriculum development.

Figure 5. Delivery media for different course activities types.

The course contents had not undergone to dramatic changes in decades (Delgado, 2009), nevertheless the use of technology has enabled the introduction of more complex issues such as solving equations in two and three dimensions, cubic sections and partial differential equations in more than one dimension. In other aspects, skills are enhanced, being a course that not only develops mathematical techniques but it summarizes differential and integral calculus courses too. In addition, it develops skills in programming and applied mathematics. The use of information systems in programming, delivery, work, discussion and use of computational tools to enhance learned concepts towards solving problem in the course have promoted the inclusion of activities which developing abilities in students. The latter aspect was reinforced when it was selected as an integrating curricula course for the first third of all engineering programs.

Now, what implications have the inclusion of technology for learning quality assurance? In a parallel study about course (Delgado and Martinez, 2011), the following higher-order thinking abilities were identified: mathematical skills in several course activities (comprehension, application), problem solving (memorization, analysis, evaluation), project development (analysis, evaluation, creation), cooperative work (analysis, evaluation) and programming (memorization, application, creation). All of them found relation with the use of technology. In terms of activities and development of basic skills and high-level abilities, Table 1 shows a comparison between activities under the current approach and activities in the ten years ago approach (without the explicit use of technology, inclusion of repositories providing support to programming codes, complex simulations and problem scenarios, and the inclusion of mobile learning). Table is based on the 96 course activities and a prior definition of each skill developed in the course. Quantities marked with an

ISBN: 978-972-8939-66-3 © 2012 IADIS

142

asterisk are assumed induced by the introduction of computer systems and information. Based on a total of approximately 128 hours of work by semester, it is estimated each skill development time, including class and extracurricular activities. The time reported in the table does not add last amount because new activities usually develop several abilities at time. Use of technology has promoted an increase of 6 hours of development in basic skills and 193 hours of development of high-level abilities. In the traditional course, the use of technology was related with the occasional use of Excel and project programming as a method (based on Fortran or C++, but not due the use of information systems for knowledge management and delivery). Exercises solving set out in its didactic character.

Table 1. Abilities developed comparison between the traditional course and the latest course with technology tools included, based on each one of its 96 activities

Traditional course Current course Basic abilities Time Higher level

abilities Time Basic abilities Time Higher level

abilities Time

Calculation abilities

38 Math abilities

32 Technology basic use

24* Math abilities 9

Exercise solving 30 Teamwork 8* Exercise solving 22 Programming 22* Hard work capacity

48 Problem solving

8* Hard work capacity

52 Problem solving

33*

Basic software 18* Concept comprehension

34 Project development

34*

Concept comprehension

32 Teamwork 42*

Professional software use

78*

Total 166 (18*)

Total 48 (16*)

Total 132 (24*)

Total 218 (209*)

For this course, the results of standardized tests are available as final exam in the last three years, involving statistics for 234 students, which are divided in the following areas: basic concepts comprehension in numerical methods, programming skills, applied problem solving and use of professional software. There are track records over the past five years on the quality and complexity of projects also (POL), and depth in development of complex problem solving (PBL scenarios). Additionally, at the end of the course, a co-evaluation is applied on the POL activities that enables evaluate the average quality rating of collaborative work. From this information, each ability performance can be traced in the past three years.

Figure 6. Abilities demonstrated on first term exam and first team activity related with high-level abilities included in the final exam.

By extending this analysis to tests and activities related with the historical performance of students in the last three years and comparing them with those when the course was not blended learning-based, by exploiting an important aspect: for these students, the first term exam for five years has been consistently based on three aspects: concepts understanding in arithmetic methods, exercises solving and initial programming skills. Additionally, the grades of the first team activity during the first fifteen days of course are available. Assuming as approximation that these evaluations can to serve as a baseline measure of

First term exam performance

Final exam, POL and PBL performance

First team activity performance

Concept comprehension

Exercise solving

Programming skills

Teamwork

Mathematical skills

Problem solving

Project development

Teamwork

Programming skills


143

performance upon course admission, a comparison of the effect of the course can be established. This relationship has been assumed in Figure 6, indicating how some of these abilities may explain the high-level abilities (in terms of its deconstruction).

Establishing a weight for each item in the first column of Figure 6 (whether grade in items of the first term exam, the first team activity, or both) and combining their average in agreement with relations in Figure 6, it is possible establish a baseline assessment per student in high-level abilities expected in the second column (understood from his deconstruction from core competencies). Later, through grades by item in the final exam, the performance in the project development (POL) and the activities of PBL, we get a final evaluation of them. This performance can be assumed to have two dominant explanations: initial skills or skills acquired in the course (neglecting those skills acquired in parallel by other courses during the course period, which could be partially reasonable). The performances in this analysis were scaled between 0 and 1, with 1 being the best performance and 0 the worst.

Table 2. Average student’s high-level abilities performance at the beginning and at the end of course, including the percentage gain in each one

High-level abilities Performance in without online components course

Performance in with online components course

Percentage gain

Mathematical abilities 0.77 0.81 5% Problem solving 0.72 0.89 19% Project development 0.64 0.86 26% Cooperative working 0.72 0.89 19% Programming 0.54 0.79 32%

Table 2 shows the average performance for the students involved in the study, any time series study was made here. At first glance, some abilities seem to have a remarkable gain, particularly programming skills and project development. With these results can be established a two-way ANOVA test to analyze the variability sources in the results, either by the ability type (rows in Table 2) or the effect of the course (columns in Table 2).

Table 3. Two way ANOVA test for performance variability in high-level abilities, showing variability on the initial and final performance (p=0.235>0.05) and no significant variability in performance levels between abilities (p=0.009<0.05).

SUMMARY Frequency Sum Average Variance Mathematical abilities 2 1.58 0.79 0.001 Problem solving 2 1.61 0.81 0.014 Project development 2 1.50 0.75 0.024 Teamwork 2 1.61 0.81 0.014 Programming 2 1.33 0.67 0.031 Initial performance 5 3.39 0.68 0.008 Final performance 5 4.24 0.85 0.002

ANALYSIS OF VARIANCE Variation source Square sum Degrees of freedom Square average F p-value Critical F

Current course impact 0.028 4 0.007 2.175 0.235 6.388 Ability type 0.072 1 0.072 22.403 0.009 7.709 Error 0.013 4 0.003 Total 0.113 9

The results of this test are shown in Table 3. Until 0.05 significance level, it shows that there is significant variability due to the course (p = 0.235> 0.05) and that there is no significant variability in relation to uneven development in the types of abilities (p = 0.009 <0.05). That is, the course provides a clear impact on the generic high-level abilities based on the use of information systems in relation to delivery and course work as well as technological tools to facilitate work on more complex problems, but it cannot be assured that this change is dramatic in relation with a particular ability. Even with the evidence of this impact on the knowledge and abilities, some additional aspects should be remarked at level of capitalizing the experience, besides the course abilities development.

ISBN: 978-972-8939-66-3 © 2012 IADIS

144

2.3 Capitalization

Currently, the Higher Education Institutions (HEI’s) are embedded in the new market dynamics called knowledge economy, where a central concept is intangible capital, in particular, it means intellectual capital among others. For Kieso and Weygandt (quoted by Flores, 2001), is related to capital assets with present value equal to zero, which allow increase or reduce future human or economic capital. In terms of intellectual capital generated by HEI’s (its graduates), the introduction of use technology to solve problems (in this case, the use of Python or Mathematica) or knowledge management (the use of Blackboard and mobile resources) are immediate practical abilities for knowledge capital. Universities are responsible for training students in a cooperative work environment. This is an issue that smart companies give value in their employees, creating jobs and organizational competitiveness (Gordillo, Licona and Acosta, 2008). The inclusion of computing technologies in education promotes the quality and speed of analysis, increasing the intellectual capital. Meanwhile, the inclusion of information systems for knowledge management improves structural capital in these companies. An important aspect about mobile technology is that since the use of mobile resources and the applications development on it, the decision was to capitalize it for the students themselves through the development of integrated projects based on this technology.

3. CONCLUSION

The technology advance has suggested its use in the achievement of educative contents delivery and the development of high-level abilities. Over ten years our university introduced an educational model based on several strategies which develops a meaningful learning (teaching techniques as PBL and POL, which in turn find support in information systems and computer technologies) and introducing the use of technology, understood for delivery in an ongoing portfolio, as in its use to solve real problems. Certainly, in several disciplines such as applied mathematics, and specifically for the numerical methods course, the impact has been sensible over curricular and methodological changes brought by it.

The use of Internet and mobile resources to build the activities schedule which complement the class, have been useful to redirect the learning process. Currently there is already a large amount of public resources that allow their use for teaching. Some of them, like Blackboard (where repositories are robust but are not yet fully mobile friendly), work cooperatively with others (more slender) as Socrative and Winksite. They help to build specific activities to generate an almost personalized delivery on demand. In addition, the increase of mobile sites to test and use software freely (as is the case Wolfram Alpha for Mathematica) allows the creativity of teacher by designing different resources for students. Thus, by combining several of them in an appropriate way, it is possible to meet learning needs and facilitate their access.

The introduction of e-book along the development of applications based on mobile learning (podcasts and design of small-scale simulations or Apps) allowed to direct the delivery in mobile devices which are widespread among the student population. While in the first stage, some of these devices do not allow the development of complex calculations and simulations, they allow the reproduction of concepts, technological tools tutorials and online work. For the numerical methods course, this meant designing activities that could be delivered through different channels and using different tools depending on learning needs. This has improved critical thinking and self-study. The overall approach shows better results in the whole high-level abilities. For the author, these implementations have been an opportunity to analyze how different mobile resources can be managed for the advancement of learning (Toomey, 1997), to evaluate progress and student outcomes (Oliver, 2007). In this sense, the evolution of a blended course has been useful for the current demand of students. Future work should be based in the research about how each mobile resource is helping to students in specific ways, in particular with programming and numerical methods abilities development. In addition, by redirecting development projects on augmented reality applications, it should be encouraging for students. In addition, a Mathematica certification given by Wolfram Research based upon course performance is in process.


145

ACKNOWLEDGEMENT

Support to produce several technologies depicted in this work is acknowledged: Monterrey Tech digital press office due to e-Book design and development, and Monterrey Tech campus Estado de Mexico principal office by economical support.

REFERENCES

Allen, K., Seaman, J. & Garret, R., 2007. Blending in: The extent and promise of blended education in the United States. Sloan Consortium. Retrieved September 3rd, 2011, from: http://www.blendedteaching.org/special_report_blending_in

Anderson, L. W. & Krathwohl, D. R., 2001. A taxonomy for learning, teaching and assessing: a revision of Bloom's Taxonomy of educational objectives. Longman, New York, USA.

App Inventor, 2011. App Inventor Webpage. Retrieved September 25th, 2011, from: http://www.appinventorbeta.com Blackboard, 2011. Blackboard Webpage. Retrieved September 25th, 2011, from: http://www.blackboard.com Briceño, J. & Coiman, R., 2008. Trabajo cooperativo y sus principios. PMG, Distrito Federal, México. Churches, A., 2007. Bloom's and ICT Tools. Educational Origami. Retrieved August 12th, 2011, from:

http://edorigami.wikispaces.com/Bloom%27s+and+ICT+tools Delgado, F., 2005. Problem Based-Learning in Sophomore and Freshmen Engineering Students: A Six Year Follow-Up.

4th Conference of European Research in Mathematics Education proceedings. CRM, Barcelona, Spain. Delgado, F., 2008. Designing PBL scenarios for a course with integrated curriculum, teamwork environment and use of

technology. 10th International Conference of Mathematical Education proceedings. UANL, Monterrey, Mexico. Delgado, F., 2008. Innovaciones y resultados comparativos en los cursos de Métodos numéricos para posgrado en

ingeniería. Proceedings of the PBL 2008 Congress. PBL Consortium, Colima, México. Delgado, F., 2009. Innovaciones en los cursos de Métodos numéricos de posgrado en Ingeniería. Memorias de la XXXVI

Conferencia Nocional de ANFEI. ANFEI, Mérida, México. Delgado, F., 2011. Mobile site for the Numerical Methods course. Retrieved October 10th, 2011, from: http://

winksite.mobi/fdelgado/m2009 Delgado, F., 2011. Downloadable mobile site for the Numerical Methods course based on Android. Retrieved October

10th, 2011, from: http://homepage.cem.itesm.mx/fdelgado/recm2009/download.htm Delgado, F. & Martínez, S., 2011. Cambios curriculares generados por el empleo de tecnología en la enseñanza de los

métodos numéricos. Memorias de la XXXVIII conferencia de ANFEI. ANFEI, Querétaro, México. Flores, P., 2001. Capital Intelectual: Conceptos y Herramientas. Retrieved February 10th, 2011, from:

http://www.sistemasdeconocimiento.org/Produccion_intelectual/notas_tecnicas/2001_PDF/csc2001-01.pdf González, M. S., 1997. Pensamiento Complejo. En torno a Edgar Morin, América Latina y los procesos educativos.

Editorial Magisterio, Bogotá, Colombia. Gordillo, A., Licona, D. y Acosta, E., 2008. Desarrollo y Aprendizaje Organizacional. Editorial Trillas, Distrito Federal,

México. Johnson, L., Adams, S. and Haywood, K., 2011. The NMC Horizon Report: 2011 K-12 Edition. The New Media

Consortium, Austin, USA. Johnson, L., Smith, R., Willis, H., Levine, A. and Haywood, K., 2011. The 2011 Horizon Report. The New Media

Consortium, Austin, USA. Oliver, V. C., 2007. La evaluación desde la complejidad: una nueva forma de evaluar. Encuentros multidisciplinares,

Vol. 9, No. 25, pp. 47-57. Python, 2001. Python Webpage. Retrieved September 25th, 2011, from: http://www.python.org Socrative, 2011. Socrative Webpage. Retrieved September 25th, 2011, from: http://www.socrative.com Toomey, R., 1997. Teachers Approaches to Curriculo Planning. Curriculo Inquiry, Vol. 7, pp. 121-129. Winksite, 2011. Winksite Webpage. Retrieved September 25th, 2011, from: http://winksite.com Wolfram Research, 2011. Mathematica 8.0 Webpage. Retrieved September 25th, 2011, from: http://www.wolfram.com Wolfram Research, 2011. Wolfram Alpha Webpage. Retrieved September 25th, 2011, from: http://m.wolframalpha.com

ISBN: 978-972-8939-66-3 © 2012 IADIS

146

UNDERSTANDING, REFLECTING AND DESIGNING LEARNING SPACES OF TOMORROW

Isa Jahnke, Peter Bergström, Krister Lindwall, Eva Mårell-Olsson, Andreas Olsson, Fredrik Paulsson and Peter Vinnervik

Umeå University, Department of Applied Educational Science, Interactive Media and Learning (IML) SE-901 87 Umeå, Sweden

ABSTRACT

This conceptual paper describes challenges in the field of Interactive Media and Learning (IML), striving towards a research and teaching field for mobile learning. The theoretical background is provided and arguments are listed, specifically what challenges researchers, practitioners (e.g., teachers, employers, employees) and designers face today on the way to mobile learning. This will be done from an educational perspective, in particular from Educational Technology from a Scandinavian community. The leading issue is how to educate the Homo Interneticus? Is learning supported by mobile devices one option? Is there a need to rethink the learning spaces of today? The paper provides answers by illustrating challenges in research and teaching with regard to mobile learning.

KEYWORDS

Mobile Learning * Flexible Learning * Formal Education * Informal Learning * Work-based Learning

1. EDUCATING THE HOMO INTERNETICUS

With regard to new technologies and social media, universities are responsible for fostering competence development and skills in order to reflect different concepts of new technologies for both students and teachers. In this paper we argue that research and teaching needs a deeper understanding of social media, including the use of media such as technical skills, reflection and the design of cutting-edge technologies, as well as the awareness of advantages, for example fostering networking, collaboration, knowledge exchange, and disadvantages such as the misuse of personal data, bullying, and plagiarism/copyright. However, the question is why should we redesign our formal education, and is there an obvious need? With regard to information and communication technology (ICT), media and learning, the following problems occurred:

1. There is an increasing number of online bullying/mobbing, where children and teenagers at schools spread information about other kids, lie and blame other people, and repeatedly harass others (Cyberbullying Research Center, 2012).

2. People use information (images, files, etc.) from other people without understanding copyright issues; information is used without correctly citing sources; duplication & plagiarism is increasing (Derby, 2008).

3. We have perceived that some directors and teachers at schools do not know how to handle and adopt ICT in their classrooms. Some other teachers have the technical skills but do not know how to use iPads for educational purposes. Sometimes the result is that the use of such devices is prohibited, expressed in ‘It is not allowed in my classrooms.’ Sweeping the problem under the rug is probably not an appropriate solution because children use the Internet and their mobile devices after class and at home, and they bring their social problems back to the classroom.

4. A fourth example specifies the assessment of information; to understand its different quality (critical thinking). Within the same topic, different information online is available written by competitive firms, people at different ages, from different generations & cultures; diverse designers as well as researchers from different disciplines. They all have information but from their own perspectives. How can we teach our children to handle this huge difference in information? How do we teach critical thinking?

These above mentioned examples illustrate our point: • Yes, we need to educate the Homo Interneticus, but how?


147

Some people say we have to understand how informal learning in online settings takes place because it seems that there is a great success story of informal learning (e.g., Collins & Halverson, 2009; Thomas & Brown, 2011). What does this mean for formal schooling? Instead of learning through textbooks, to what extent can we transform characteristics of informal learning into formal teaching?

When we choose the option to implement new technology in learning environments, new questions come up: how can a teacher use these new technologies in their learning settings? Do we need new methods and tools, or is there a need to develop new educational methods, or both? Certainly, there are also questions such as, what problems will occur when teachers use new technology? What is a useful design to support interactions among learners when using new technologies (co-located, distance, blended learning)? To what extent, and for which learning scenarios, are different kinds of new technologies helpful, or not?

In order to provide answers to those questions, a research and teaching group called Interactive Media and Learning (IML) has started creating a research and teaching center for mobile learning. Developing mobile learning may be one step in establishing a creative learning place where students, teachers and researchers meet. The idea is simple. We design learning spaces of tomorrow, put them into practice and learn from them. We describe mobile learning as a place where learning is constructed, designed and reflected (instead of being there). The terms “learning spaces” and “classroom of the future” are not reduced to a physical space or to formal schooling. It is a metaphor for designing different forms of learning, and embraces formal learning and learning out of institutions.

Based on 12 years of experience in eLearning, including four years of experience in conducting workshops (each 1-2 days, 13 workshops so far, titled ‘Web 2.0, Social Media, eLearning and Co. in Higher Education’ for university teachers from different disciplines, for example math, social sciences, architecture, and languages at different universities), this paper illustrates the case of a Scandinavian group, reflects on the challenges of mobile learning, and develops scenarios.

2. THEORETICAL BACKGROUND

In order to describe social media and its dynamics in a broader framework, there is a need to reflect on the underlying theoretical approaches. In particular, these are Mediatization (e.g., Krotz, 2008), media-constructed social awareness (Medialitätsbewusstsein, e.g., Groeben & Hurrelmann, 2002), and the socio-technical approach (e.g., dePaula & Fischer, 2005; Mørch & Skaanes, 2010). The approaches stress the duality of social processes and their interwoven structures (“A wicked problem”, Conklin, 2005). New media affects society, and “media is integrated into the operations of social institutions” (Hjarvard, 2008), but on the other hand society designs new forms of communication. Media is formed by society but also became an active agent that influences human interactions (Giddens, 1984, “Duality of structure”).

The media-constructed social awareness approach underlines that people live in a media-constructed world with a difference between a social-constructed “reality” and “reality given by different media”. For example, when new technologies transform into an “old already there object” (e.g., school system), we call this “objective facticity” (adapted by Berger & Luckmann 1966), that is people do not have influences or enough resources to change this object although it is constructed by the society. Our school systems serve as an objective institution; however, these social structures are changeable (regardless what it takes to affect some changes). To know (a) the differences of given realities by social media and to act meaningful, and (b) that social media serves as an objective facticity, but for others as a designable item, and to handle this in the classroom—in different learning spaces—is one aspect of teaching media competencies and one central objective of designing educational technology, that is technology for educational purposes.

2.1 A Complex Design Problem

When developing learning and its environments, the complexity theory (e.g., Pavard & Dugdale, 2000)—a contribution to a deeper understanding of the sociotechnical approach—must also be considered.

From this point of view, technical, social and didactical developments are required simultaneously, but this is not easy to solve. For example, from a pedagogical point of view, we need to cultivate a Portfolio system for students to support reflections in learning; however, years ago there was no specific technology that provided this method, as we lacked technology (now we have PebblePad or Mahara). As a second

ISBN: 978-972-8939-66-3 © 2012 IADIS

148

example, we have technology like mobile devices but do not know how to use it for educational purposes, as useful applications for mobile teaching have not been developed until now. Technological design (UT) and didactical approaches (DA) in different disciplines (TLC) (e.g., physics, math, social sciences, and computer sciences) means designing interdependencies among these elements (DA, UT, TLC).

Inter-dependencies

Use of Technology ( UT) ( Socia l Media)

Teaching and Learning Cultures ( TLC) ( different facult ies, disciplines, subjects)

Didact ical approaches ( DA) ( e .g., problem - based learning; learning to be creat ive)

I nter- act ions Trans- form at ions

Figure 1. Designing the interdependencies among technical and didactical design in different teaching cultures.

Introducing mobile devices into teaching also means facing the challenges of software administration. In contrast to laptops, an iPad is a personal device that makes it difficult to administer because the user decides what app to install via the iTunes store, as central administration is currently not possible.

Each implementation of technology needs a creative design environment where teachers, researchers, designers, and administrators plan the introduction of IT together; therefore, the support of knowledge integration of different stakeholders is a plausible consequence (Herrmann, Loser, Jahnke, 2007).

2.2 A New Understanding of Learning

In the past few years, new forms of learning have emerged. John S. Brown writes (2009): “Whatever your particular interest is, there is some niche community, already formed on the network you can join. (…) These resources not only provide facts. They are also tools you can use to build things to tinker with, to play with, to reflect on, and to share with others. And most importantly, you will learn form other people’s comments and from what they do with your creations.” (p. X). Because complex societies need teams of workers, collaboration is one important aspect in learning today (Stahl, 2006). It is not possible anymore to collaborate efficiently without having social media (e.g., think about how easy it is to share information online).

Collins and Halverson (2009), both are professors of education, write, “Technological innovation is breaking out in administrative office with data systems and among students with gaming, leaving the teachers behind to maintain their traditional classroom practices. The pressure to change the classroom with computing is coming from outside the classroom, in different forms from children and families and central offices.” (p. 127). We currently do not know if formal schooling will be replaced or not, but new forms of both formal and informal learning will emerge around the edge of formal schooling (Brown, 2009). For example, see the case of InPUD: this informal online learning community is part of a formal computer science study at a European university. Research showed a change in communication, distributions of information and shared knowledge, which together supported the formal study better than without it (read Jahnke, 2010 in detail). Social media affects the relationship between formal schooling, informal learning out of the school (Jahnke, 2010) and collaborative learning at the workplace (e.g., Goggins, Jahnke & Wulf, 2012). These studies illustrate a transformation in education and learning through innovation in mobile computing (read also Tuomi-Gröhn & Engeström, 2003). Fischer (2011) stresses such new forms of lifelong learning as “cultures of participation”. New research questions emerge, for example to what extent do teachers in formal schooling reflect on their understanding of learning towards a culture of participation?


149

A new understanding of learning is provided by George Siemens. In his concept about “connectivism”, he illustrates how existing knowledge and information in the world can be connected via a network and its nodes; his central metaphor for learning. The idea is that any node (e.g., textual information, data, images, videos, figures) can be connected to another node. Learning in this approach is defined as “the process of creating connections and developing a network” (Siemens, 2005), where decision-making is the central part of the learning. “Choosing what to learn and the meaning of incoming information is seen through the lens of a shifting reality. While there is a right answer now, it may be wrong tomorrow due to alterations in the information climate affecting the decision”. With his Massive Open Online Courses (MOOC), Siemens provides new ideas about an open model of education that is supported by new technologies.

Laurillard (2007) specifically discusses different pedagogical forms of mobile learning; Kolb’s “learning cycle”, wherein learning includes a concrete experience, reflective observation, abstract conceptualization, and active experimentation by learners. According to this cycle, designers and teachers have to ask if the “design of mobile learning” motivates and enables students to (Laurillard, 2007, pp.163-164):

a) Access the theory, ideas or concepts? b) Ask questions of (a) the teacher or (b) their peers? c) Offer their own ideas to (a) the teacher or (b) their peers? d) Use their understanding to achieve the task goal by adapting their actions? e) Repeat the practice using feedback that enables them to improve performance? f) Share their practice outputs with peers for comparison and comment? g) Reflect on the experience of the goal-action-feedback cycle? h) Debate their ideas with other learners? i) Reflect on their experience by presenting their own ideas, report designs (productions) to peers and to

teachers? This approach is a good starting point to reflect on teaching and learning. However, mobile learning today

is a huge field and different understandings of mobile learning are available. Some people conceptualize mobile learning in terms of devices and technologies, while others focus on the mobility of learners and the mobility of learning. Further, others stress the learners’ experience with mobile devices (Traxler, 2007). Sharples et al. (2005), Sharples (2006), Traxler (2007), and Pachler (2007) stress the importance of a theory of “mLearning” and a research agenda. “Such a base would provide the starting point for evaluation methodologies grounded in the unique attributes of mobile learning” (Traxler, 2007). Several challenges go along with a new understanding of learning enabled by new media like mobile devices. One of the most important challenges, however, is how can we design learning how to learn?

3. REFLECTIONS ON MOBILE DEVICES IN PRACTICE

For more than 15 years, mobile devices have been part of the daily work practice of a research and teaching group called Interactive Media and Learning (IML). The first mobile devices (Palm Pilot PDAs) allowed the group to take notes and synchronize a personal calendar with a system called FirstClass. IML discovered that these devices were successful as a personal tool but had shortcomings as a collaborative tool: it was not successful in teaching due to the limited functionality for communication and knowledge sharing. A new category of mobile phones called smartphones generation 1 started to emerge in the late 1990s. These devices offered additional features such as applications for calendar scheduling, e-mail messaging, audio/video recording, and web browsing. Two of the smartphones we evaluated at the time were the Nokia Communicator and the Sony Ericsson P900. In the Uninet project, the Sony Ericsson P900 was used as a mobile learning device for streaming lectures across the GSM Telenet, but it was very expensive. Students could not afford the extra cost for data traffic over GSM.

In 2006, IML introduced portable media players—iPod’s—into courses. Funded by the Faculty of Teacher Education and in collaboration with the Department of Creative Studies, IML conducted a one-year project called Podcasting in Teacher Education (Vinnervik & Lindwall, 2006). The project studied how portable media players and course content could be used to support distance learning in the Sloyd subject. With the iPod, media content on the web was supported by a new technology called RSS. It made it possible to subscribe to content that could easily be transferred to portable media players. iPod’s were also tested in the eLene-TT project about podcasting and blogs (Bergström & Lindwall, 2008). Podcasting was also studied

ISBN: 978-972-8939-66-3 © 2012 IADIS

150

in mathematics “Podcasting i skolan” (PIS), reported by Bergqvist, Hudson, Lithner, & Lindwall (2008). With the introduction of the iPod Touch, the graphical interface was also improved, and wireless Internet access (WiFi) became standardized in the device. Web 2.0 became integrated into more learning environments. The collegial discussions and use of these devices were the starting point for further projects like the P@rable project that involved the iPod Touch for teaching and learning.

The iPod Touch was followed by the iPhone in 2008 and a new category of smartphones were introduced to the market. These devices were identified as useful for the entire IML staff, which solved issues related to communication, collaboration and knowledge sharing in teaching, learning and research. In 2009, the department decided to equip each staff member with an iPhone 3GS. The amount of devices is one of the critical challenges since collaboration and sharing is strongly supported by the iPhone 3GS. Additionally, different applications needed to be tested during the everyday life of the staff involved in teacher education and research on ICT, interactive media and learning. Finally, in 2010, the first iPads were bought.

In summary, the IML group learned that not only did the teaching concepts need to be adjusted but also concepts for work-based learning needed to be considered. A critical mass of people is required who has the device for gaining insights into different educational applications. The informal collegial discussions at coffee breaks became a professional development. This professional development has involved all staff, no matter the position. The borders between formal and informal professional development is blurred.

4. CHALLENGES TOWARDS MOBILE LEARNING

From the IML experience, the sociotechnical-didactical design of mobile learning is one of the most important challenges in formal schooling over the next years. The guiding questions for us are: (a) For what educational purposes is a specific technology (e.g., mobile devices) a good choice; when do we need other media (could we combine them, creating new technology), when to use what kind of learning environment?; (b) What is the look of a future classroom—what equipment, devices, software, for example, is needed?; (c) To what extent can teachers use mobile devices to support students in becoming a reflective community?

4.1 Challenge 1 – The Shift from Textbook Learning to Learning to be Creative

One challenge is to cultivate cultures of learning that foster collaborative reflection. One question is what learning today means when we see people who use the Internet, get information easily, and learn informally outside of schools and workplaces. Besides the traditional teaching objectives called (a) learning what (e.g., textbook knowledge) and (b) learning how (e.g., methods, techniques), there is a need to design teaching as (c) “learning to be”, This means that to become a school teacher, a researcher or an employee in a specific sector involving different values/norms that includes to learn must take on a new role and develop it (Jahnke, 2010). This is often expressed in notions like “We want our students to think like a researcher (or etc.)”.

Furthermore, an innovative society needs people who develop skills to find solutions when the answers are unknown. How do teachers teach creativity and enable learning “when the answer to a problem is not known” (Fischer, 2011)? This shows a need to design teaching as (d) “learning to be creative”.

When we shift the focus of traditional teaching objectives and student-centered learning from textbook learning more in the direction of learning to be and learning to be creative, we then need a new understanding of learning. New technologies and interactive media (and its deeper understanding) might be useful to foster this shift (Jahnke, 2011; Mårell-Olsson & Hudson, 2008). This leads us to Thesis 1.

• Thesis 1. Mobile learning can support a shift from textbook learning to learning to be creative.

4.2 Challenge 2 – Informal Learning Affects Formal Education

Mobile technology (iPads, Android, IOS-based smartphones, etc.) can support flexible learning. The Australian Flexible Learning Framework (2008) defines flexile learning as enabling people to learn

anywhere, at anytime with anyone. This learning approach has a strong focus on lifelong learning. The main idea is to support students moving from a reflective practitioner to a reflective community.


151

The teachers at IML have a flexible work situation, as students study at diverse times (e.g., evenings, weekends). This means that the service to students is not supported between 8am-5pm only. Of course, we know, this is controversial from a work-life-balance viewpoint. However, besides the main time slot for providing services, some teachers and administrators have a flexible approach with our students by answering their questions after the daily work. This could affect avoiding a) drop-out students and b) decreasing the learner’s motivation. However, this assumption needs more research. The challenge is to design mobile learning for learners with different needs, and also for teachers and their needs. To what extent is mobile learning able to support flexible learning and also support the teachers? There is a need for research: to what extent does flexible learning need flexible services at universities?

Have you ever asked yourself why you should learn something at school/university? Someone in the past said this is important knowledge and therefore it is part of our curriculum. And for what purpose is it helpful to know this? Knowledge and the attribution of “what knowledge is important” change over time. In informal learning outside of schools the problem is often the trigger for learning. A person wants to know something and starts searching for answers and solutions (for instance, “problems” are improving a swim style, learning a foreign language, checking the existing information of a citation if this is valid, true or wrong). This does not exclude other learning forms like serendipitous learning. What can we learn from informal learning for formal teaching? One answer is textbook learning is not enough, as we need classrooms where the problem is at the center and the students are able to learn and become creative in order to solve this problem, and foster critical thinking and creative practices. Sure, professional knowledge is often necessary to find an appropriate answer to a problem. So, with a problem at the center, people develop various different skills.

• Thesis 2. Mobile learning can bridge informal learning approaches to formal education and new flexible teaching methods, where the problem, and not only the textbook, is at the center of teaching.

4.3 Challenge 3 – It is not one or the other; it is not Technology or Didactics

The younger generation (e.g., digital natives), as well as people who are more or less online around the clock, (Homo Interneticus, it does not matter what age) already created new forms of communication and knowledge sharing. However, the problem remains that ICT use in schools and universities is behind this social change. Some teachers are happy about the new technologies (group A), but some other teachers are not able to revise their didactical designs supported by the mobile devices in their classrooms; they need support (group B). Some teachers do not want to use mobile devices because of different reasons (group C).

For example, on September 30, 2011, KVL (anonymous person) posted a question on the POD mailing list. Almost all of the Centers for Excellence in Teaching & Learning in the U.S. subscribe to POD. POD has almost 1,800 members). He asked: “Anyone out there doing any workshops for faculty on useful iPad apps to support student learning….?” (September 30, 2011, POD). There were just a couple of answers, which is a surprise because normally the community discusses teaching issues over several days or weeks depending on the issue. After some e-mails, where people just gave a few examples of mobile learning and iPads, a new answer was given: “I'm not sure that I like the direction of this conversation... My approach has tended to be to look at what I wish to achieve and then find the appropriate means of so doing, rather than start with the latest toy and see what I can do with it” (answer by BT on October 2, 2011).

The point is, it is not one or the other—it is not technology or didactical approaches. To develop and to improve teaching practices, teachers look for tools but sometimes they do not exist yet, are too expensive, or beyond the skillset and so forth. This is probably clear for researchers in the field of Technology-Enhanced Learning but some teachers have a different understanding.

With the mobile devices, which are almost anywhere, as each student has a smartphone, the pressure to rethink how to handle this omnipresent online presence is increasing. This is different to the laptop age. The mobile devices are small; when the users don’t want, nobody can see it; a huge mass of learners use it, you can communicate in seconds, and they do not take much time to reboot. Teachers ask themselves how can I handle the omnipresent online presence when students in my class google my talk and scrutinize what I said? From a didactical point of view, we would say, “Fantastic!” We want to have students, thinking as a researcher, who are engaged, critical and active. Yet, it seems that some teachers need support. One way is to design mobile learning together with teachers and students.

• Thesis 3. Mobile devices bring innovations from daily life into schools and universities, and are able to crack traditional teaching routines.

ISBN: 978-972-8939-66-3 © 2012 IADIS

152

4.4 Challenge 4 – Creating CSCL@Work for All

Challenge 4 focuses on the creation of a collaborative work-based learning environment for all staff members (teachers, researchers, designers, administration), or in the case of firms for all employees.

With the IML group we did test different applications for supporting teaching, and we also applied those mobile devices for our own daily work. One such approach started with the synchronization between our Google calendar and the iPhone. This supports the daily work for all staff and supports mobile learning at work. In this environment, students, researchers and teachers as well as administrators and people who organize the courses had a mobile device. For instance, in cases where students have questions like, “How do I apply for a course?”, they often go first to the study administration. Based on our experiences, we also saw the need for teachers to implement this type of CSCL@Work friendly environment.

In their edited book, Goggins, Jahnke & Wulf (2012) illustrate that work-based learning is not restricted to learning places within an organization (see also Jahnke & Koch, 2009 “Web 2.0 makes a difference”). Instead, the cases show that CSCL@Work—collaborative learning at the workplace—means to enable unexpected and unusual online learning places, and to design technology-embraced collaborative learning across established boundaries (social- and technology-constructed boundaries).

• Thesis 4. Mobile learning can bridge informal learning with work practices. It is important to outline that these four theses (Section 4.1-4.4) above are created with the assumption

that mobile learning is designed correctly and useful with regard to specific teaching objectives and ideas of learning outcomes. However, the question is, of course, what are appropriate, correct and useful designs?

5. SCENARIOS FOR MOBILE LEARNING AT FORMAL SCHOOLING

We define mobile learning as a form of learning where mobile devices (e.g., iPads, Androids) are used for educational purposes in particular at formal schooling and in universities. Specially designed mobile content is time- and location-independent. This mobile content can be varied from text to figures to documents, blog entries, pictures, photos, Podcasts, videos, simulation, movies and so forth. Simple examples of learning materials are texts or presentations. Learners have access to the manuscripts, photos or short stories, read them, set bookmarks, and mark specific passages in the text or edited small notes (e.g., Evernote).

From a pedagogical perspective, the design of mobile learning usually starts with certain considerations: “How to use mobile devices and for what purposes?”, for example “What are the teaching objectives?”; “Which teaching problem can be solved by applying mobile learning?”; and “Do any of the learners have a mobile device?” These lead to questions such as: “Is content to be developed (or done by others)?”; and “Are new apps required or are they made by others”? Technical skills are required to fulfill the pedagogical aims, as both go hand in hand.

5.1 Mobile Learning at Schools

In this section, we describe ideas of how to integrate iPads into formal schooling from a didactical viewpoint. Scenario. A biology teacher offers one idea. She explained to her class (10-year-olds) that a mushroom is

a special plant, and tasked the students (a group of 3) to use an iPad outdoors and take photos of mushrooms, find photos online and discuss different kinds of these plants online. The scaffolding question was to identify an edible from a toxic plant. In this case, the teaching objective was to support professional knowledge but also to foster collaborative reflections among the pupils. In this setting, formal learning has been connected to learning outside of the school. The teachers brought the problem (identify toxic mushrooms) to the center of learning. When the activity is done, the class reflects on the technical device (what was good, how does the iPad help, what was not so good, where were the problems?)

Advantages. Pupils seem to integrate mobile devices into their personal learning environment easily. YouTube, for example, is a source often used for learning. The use of mobile devices is part of youth culture outside of schools. When using it at formal schooling, teachers have the chance to critically reflect on the use of media within their classes.

Possible problems. In Sweden it is not uncommon for teachers and schools to debate the prohibition of the use of smartphones during class. The debate is often about whether smartphones disrupt teaching and


153

whether students cheat by using these devices. Is the mobile technology revolution only for the teachers that are already interested and not reaching teachers who also would benefit from this technology? How can the design of teaching resources and activities change in order to utilize the features of modern mobile devices?

5.2 Mobile Learning at Universities

In this section, we illustrate a mobile learning scenario with the didactical focus on learning to be creative. Scenario A. In order to understand and apply production processes to new standards in production

engineering, students are tasked to develop a new machine (or parts of it). The problems with the existing machines are more or less well known. A solution does not exist yet.

Scenario B. Social sciences students are tasked with making social changes in society. The reflection on theoretical approaches and a small survey or interviews are part of the learning assignments.

What is new? Creativity can be learned; at least the environment of getting new ideas can be prepared (see Jahnke & Haertel, 2010). The support of creativity is usually done within the following phases:

• Collection of ideas (e.g., using brainstorming, Synectic Technique; de Bono, 2005); • Condensing ideas, tracking one or several ideas to find a suitable solution; and • It could be that the first ideas need to be rejected, as a combination with other ideas leads to a better

solution. The generation of new ideas can be supported by using mind-mapping tools like Freemind or

Mindmeister, and can be performed synchronously and asynchronously. Those mobile devices tools also include small communication functions where the ideas can be discussed and evaluated. Other communication tools are, for example, Springpad, Evernote and PebblePed. Some face-to-face meetings could be helpful for developing knowledge sharing and learning (“Where are we with our new machine?” and “What have we achieved so far?”). The instructor coaches the creative process at the beginning and pays attention during the process to ensure that all employees have the opportunity to participate.

The cultivation of a reflective community (e.g., with Ning.com, Elgg.org) has the advantage that learners get the chance to immediately communicate their ideas. Furthermore, reflections on new ideas can be fostered by the instructor who uses creative techniques (e.g. PMI, Plus Minus Interest).

Advantages. Notes can be made quickly, easily and are available for all learners through a shared online folder (flash notes), and developing a community is useful when establishing a culture of “being and becoming creative”.

Possible problems. Rather than establishing a “culture of making failures” and learning from them, which fosters creativity, failures are treated as taboo.

5.3 Mobile Learning at the Workplace

In this section, we illustrate a mobile learning scenario at the workplace. Scenario. New employees are tasked with adopting knowledge that will fulfill their work tasks within a

firm or a university. A conventional continuing training is not suitable because of limited time and lack of individual attention, or because the knowledge does not yet exist.

Mobile learning is introduced in a broader knowledge management concept. Employees have access to databases (e.g., via Dropbox) and retrieve knowledge through the use of mobile devices. Through social networking sites (e.g., LinkedIn), learners are able to look for colleagues and read about their work areas. Through communication functions like chatting or text messages (e.g., Skype), they can directly contact their colleagues or other experts. Employees can illustrate the problem through mobile devices (uploading descriptions, photos, videos). Such documentation can be uploaded quickly to the server (for instance via Dropbox). The documentation is based on multimedia such as photos and small videos. Via the iPad and iPhone, photos or videos are easily made and in a second they are uploaded to a Dropbox shared folder or similar. Sometimes a photo says more than a thousand words, meaning it makes the problem much more visible than a written document. Other employees create comments, annotations and notes easier and directly on the documented problem. Using mobile knowledge management, the employees are able to search already documented files. Searching mechanisms are supported by tagging and crowdsourcing, and integrating new tags is possible each time.

ISBN: 978-972-8939-66-3 © 2012 IADIS

154

What is new? The difference between a normal PC and mobile devices is that mobile devices are more flexible, they do not take much time to reboot, and have an omnipresent online presence. Mobile devices are especially useful for workplaces that do not employ PCs, for example outdoors jobs (timber, biology) or in production plants and long-haul trucking. Mobile knowledge management can be useful for those workplaces (e.g., Herrmann et al., 2005).

Advantages. Information can be retrieved directly in the doing of work when needed, new experience can be uploaded to the network (e.g., wiki principle), and the small size of the devices increases mobility and supports flexible learning, thus allowing searching already solved problems and communicating with others by sending a photo or video of the problem (e.g., in the foresting, timber sector).

Possible problems. Reluctance to link learning and work (employer could invent learning as cultural event, see for example the Ideo company/U.S.); it is too time-consuming to create a comprehensive knowledge base or to conduct quality assurance; updates for mobile devices are required; and often there is more than just one perfect solution, so how does one handle this from a learner’s point of view?

6. CONCLUSION

We started with the question of how to educate the Homo Interneticus and provided answers creating four theses that illustrate the challenges of rethinking formal education supported by mobile devices.

1. Designing mobile learning fosters the shift from textbook learning to learning to be creative. 2. Implementing mobile learning bridges informal learning approaches with formal education and new

flexible teaching methods, where the problem and not the textbook is at the center of teaching. 3. Mobile devices bring innovations from daily life into schools and universities, and crack traditional

teaching routines. 4. Mobile learning bridges informal learning with collaborative work practices (mobileCSCL@work). The design of learning spaces is a complex design problem that involves technology and didactical

approaches in different cultural disciplines. It means to design the interdependencies among these elements (see figure 1). Mobile devices are one option when mobile learning is designed correctly and useful with regard to specific teaching objectives, learning outcomes and competencies. However, the question is, of course, what are appropriate, correct and useful designs? We illustrated several scenarios for formal education (schools and universities) but also for the workplace, where the possible problems have been addressed, for example group dynamics prevent online collaboration, role conflicts occur, and a culture of failure is not allowed.

With this conceptual paper, we wanted to highlight the potentials and challenges of mobile learning today. What already exists in daily life (Twitter and Facebook via smartphones around the clock) will affect the school and formal education of tomorrow. The question is do we respond to this and how? What is an appropriate answer? We need to conduct more research on designing mobile learning together with teachers and students, and study/learn from them in order to find appropriate didactical solutions to enhance learning in forms of “learning to be creative”.

REFERENCES

Berger, P. and Luckmann, T., 1966. The Social Construction of Reality. Anchor Books, New York. Bergström, P. and Lindwall, K., 2008. Teaching and Learning Podcasting through Blogging. In Tidskrift för

lärarutbildning och forskning no 3–4, 2008, pp 13-34. Bergqvist, T., Hudson, B., Lithner, J. and Lindwall, K., 2008. Podcasting in School. Sixth Research Seminar of the

Swedish Society for Research in Mathematics Education (MADIF 6), Stockholm, 29-30 January 2008. Brown, J. S., 2009. Foreword. In Collins, A. and Halverson, R., 2009. Rethinking in the Age of Technology. Teachers

College Press, New York, pp. ix-x. Collins, A. and Halverson, R., 2009. Rethinking in the Age of Technology. Teachers College Press, New York. Conklin, J., 2005. Dialogue Mapping: Building Shared Understanding of Wicked Problems. Wiley, Hobiken, NJ/USA. Cyberbullying Research Center, 2012. Summary of our cyberbullying research from 2004-2011. Download on Jan/13,

2012 from http://www.cyberbullying.us/research.php


155

deBono, E., 2005. The Six Value Medals. Random House, London. dePaula, R., and Fischer, G., 2005. Knowledge Management: Why Learning from the Past is not Enough! In J. Davis, E.

Subrahmanian, & A. Westerberg (Eds.), Knowledge Management: Organizational and Technological Dimensions, Physica Verlag, Heidelberg/Germany, pp. 21-54.

Derby B., 2008. Duplication and plagiarism increasing among students. In Nature. 2008 March; 452 (7183): 29-29. Fischer, G., 2011. Understanding, Fostering, and Supporting Cultures of Participation,. In: Communications of ACM

Interactions XVIII.3 (May + June 2011), pp. 42-53. Giddens, A., 1984. The Constitution of Society. Outline of the Theory of Structuration. Polity, Cambridge/UK. Goggins, S., Jahnke, I. and Wulf, V., 2012. CSCL@work, Computer-supported collaborative learning at the workplace.

Springer, New York (in press). Groeben, N. and Hurrelmann, B., 2002. Medienkompetenz. Voraussetzungen, Dimensionen, Funktionen. Juventa, Wein-

heim/Germany. Herrmann, Th., Loser K-U. and Jahnke, I., 2007. Sociotechnical walkthrough: a means for knowledge integration. The

Learning Organization. Vol. 14, Number 5, pp. 450-464. Herrmann, Th.; Schöpe, L., Erkens E. and Hülder, M., 2005. Mobile Speditionslogistikunterstützung

(Verbundforschungsprojekt SpiW "Mobile Spedition im Web"). Shaker Verlag, Aachen/Germany. Hjarvard, S., 2008. The Mediatization of Society. A Theory of the Media as Agents of Social and Cultural Change.

Nordicom Review 29 (2008) 2, pp. 105-134. Jahnke, I., 2011. How to Foster Creativity in Technology Enhanced Learning. In B. White, I. King, & Ph. Tsang (Eds.),

Social Media Tools and Platforms in Learning Environments. Springer, New York. pp. 95-116. Jahnke, I., 2010. A Way out of the Information Jungle – a Longitudinal Study About a Socio-technical Community and

Informal Learning in Higher Education. In International Journal of Sociotechnology and Knowledge Development (IJSKD), No. 4, pp. 18-38. DOI: 10.4018/jskd.2010100102.

Jahnke, I., 2010. Dynamics of Social Roles in a Knowledge Management Community. In Computers in Human Behavior, 26 (2010), pp. 533-546. DOI 10.1016/j.chb.2009.08.010.

Jahnke, I., and Haertel, T., 2010. Kreativitätsförderung in der Hochschule – ein Rahmenkonzept (Fostering creativity in higher education – a conceptual framework). In Das Hochschulwesen. 3/2010, pp. 88-96.

Jahnke, I. and Koch, M., 2009. Web 2.0 goes Academia: does Web 2.0 make a Difference? In International Journal of Web Based Communities, Vol. 5, No. 4, 2009, pp. 484-500.

Krotz, F., 2008. Media Connectivity: Concepts, Conditions, and Consequences. In A. Hepp, F. Krotz & S. Moores (Eds.), Network, Connectivity and Flow: Key concepts for Media and Cultural Studies. Hampton Press, New York.

Laurillard, D. 2007. Pedagogical Forms for Mobile Learning: Framing Research Questions. In Pachler, N. (ed.) Mobile learning: towards a research agenda. WLE Centre, IoE, London, pp. 153-175.

Mårell-Olsson, E. and Hudson, A., 2008. To Make Learning Visible: In what way can ICT and Multimedia Contribute? In Tidskrift för lärarutbildning och forskning, no 3–4, 2008 pp 73–90.

Mørch, A.I. and Skaanes, M.A., 2010. Design and Use of an Integrated Work and Learning System: Information Seeking as Critical Function. In Ludvigsen, S. Lund, A., Rasmussen, I. and Säljö, R. (eds.). Learning Across Sites: New Tools, Infrastructures and Practices. Routledge, London/UK, pp. 138-155.

Pachler, N., 2007. Mobile Learning: Towards a Research Agenda. WLE Centre, IoE, London. Pavard B. and Dugdale J., 2000. The Contribution of Complexity Theory to the Study of Socio-technical Cooperative

Systems. International Conference on Complex Systems. May 21-26 2000, Nashua, NH, USA. Siemens, G., 2005. Connectivism: A Learning Theory for the Digital Age. Download Nov/26, 2011 from

http://www.elearnspace.org/Articles/connectivism.htm. Sharples, N. 2006. Big issues in Mobile Learning. Report of a workshop by the Kaleidoscope Network of Excellence

Mobile Learning Initiative. LSRI, University of Nottingham. Download Jan/14, 2012, from http://www.lsri.nottingham.ac.uk/msh/Papers/BIG_ISSUES_REPORT_PUBLISHED.pdf

Sharples, M., Taylor, J., and Vavoula, G., 2005. Towards a Theory of Mobile Learning. Proceedings of mLearn 2005 Conference, Cape Town. Download Jan/14, 2012, from www.mlearn.org.za/CD/papers/Sharples.pdf

Stahl, G., 2006. Group cognition: Computer support for building collaborative knowledge. Cambridge, MA: MIT Press. Thomas, D. and Brown, J.S., 2011. A New Culture of Learning: Cultivating the Imagination for a World of Constant

Change.

Traxler, J., 2007. Defining, Discussing, and Evaluation Mobile Learning. International Review of Research in Open and Distance Learning, June, Volume 8, Number 2, pp. 1-12.

Tuomi-Gröhn, T. and Engeström, Y., 2003. Between School and Work: New Perspectives on Transfer and Boundary Crossing. Pergamon, Amsterdam/Netherlands.

ISBN: 978-972-8939-66-3 © 2012 IADIS

156

MOBILISING” WEB SITES AT AN OPEN UNIVERSITY: THE ATHABASCA UNIVERSITY EXPERIENCE

Rory McGreal1 and Regina Wasti2 1Athabasca University

2Independent

ABSTRACT

This mobile implementation study provides a general idea of how existing Athabasca University sites work with the tested mobile devices and identifies the underlying issues as to why they work that way. Factors considered in the implementation include screen size, the use of advanced features, the display of large images, file formats and linking to embedded objects. In the effort to make the sites as mobile-friendly as possible, it is also important to consider what some possible solutions are. Redesigning all those sites carefully, with due consideration to mobile devices, is one possibility considered. This creates a huge burden of site maintenance, as we need to maintain multiple versions of the same page for different devices. Another problem with this approach is that as the capability of mobile devices changes, those sites need to be updated accordingly to reflect the device’s capability. This issue is addressed to some extent by creating template-based dynamic pages, and rather than redesigning the pages whenever the device capability changes, one could change the profile of the device.

KEYWORDS

Mobile web sites, screen size, formatting, style sheets, mobile devices

1. INTRODUCTION

Athabasca University (AU) is a leading university in Canada, providing open and distance education to more than 38,000 students per year from all over the world. Students can acquire education and degrees without ever having to be physically present at a university campus. This highlights the importance of unconventional but effective and efficient media for providing education and services to students. With the widespread availability of Internet technology, the University is now dependent on the use of the Internet to deliver course materials, to enable students to interact, to provide students with online library access, and to facilitate students in performing administrative tasks such as enrolling into or withdrawing from courses, and even writing exams, remotely.

Originally, AU websites were developed with desktop computers in mind. They have been traditionally designed with the assumption that the user accessing the website has a large, colourful screen and adequate bandwidth for downloading multimedia-rich pages. This assumption cannot be relied on anymore, given the pervasive use of small-screen, low-bandwidth mobile devices as well as the latest 3g and 4g phones and tablets.

This study investigated the mobile-friendliness of various AU websites and some external sites that are linked from AU sites, specifically journal databases. The websites were tested for visual integrity and functionality retention using less capable mobile devices in order to ensure that students with the less capable phones could still be used if students had not upgraded. It was felt that it is not necessary to test the capacity of the different websites in supporting the more powerful 3g and 4g phones and tablets because they can (for the most part) display the contents adequately if not better in some cases than on many larger computer screens. The less capable mobile phones have difficulty supporting more sophisticated features such as Java, JavaScript, and ActiveX. Some websites provide a fallback mechanism to accommodate these less capable mobile devices; others simply send the web page without considering what kind of device the request came from (Wasti, 2006).


157

The objective of this study was to evaluate how well the AU websites worked with low bandwidth mobile phones with limited capabilities. The results of the study could then be used to determine how the University can make its websites useful for users with diverse choices of mobile devices. For an open university like AU, it is very important to make its online resources accessible to as wide a range of users and devices as possible.

The M-library project of the AU Library was implemented previously in an attempt to build a platform for AU to develop an effective mobile-friendly library (Cao, Tin, McGreal, et al. 2007). The Digital Reading Room (DRR), Digital Thesis and Project Room (DTPR), Digital Reference Centre (DRC), and AirPAC are some of the outcomes of the project (McGreal, Tin & Cheung, 2006). These projects formed part of a research focus on mobile learning using stylesheets and proxies (Cheung, McGreal, Tin, et al., 2007) and building a demonstration course specifically for use on mobile phones (Ally, Schafer, McGreal, et al., 2007).

In this investigation, a variety of low bandwidth test devices and a selection of AU websites were studied. Features at the sample websites were tested to see whether they worked as would be expected. There were two key aspects of the test: (1) visual display, and (2) functionality. Some sites rendered well, with their layout intact on small screens, but some features were “crippled” because of the limitations of the underlying device and platform. Similarly, other sites appear relatively deformed but have their features intact. The sites were evaluated for both of the abovementioned factors.

2. DISPLAY MODES

Numerous types of mobile devices capable of accessing the Internet are available. Because of time and resource constraints, it was not possible to test each available device for compatibility with the websites, so for the purposes of this study, three low bandwidth smart phone devices were chosen, each with a different screen size and slightly different browsing characteristics: (1) the HP iPAQ hw6500 (iPAQ), (2) the BlackBerry 8700r (BlackBerry), and (3) the Audiovox SMT5600 (SMT). These devices were chosen specifically because they were low bandwidth older phones. Tablet computers can easily display web sites without formatting or other problems and so were not used, because the purpose of the investigation was to test the sites with the lowest common denominator types of devices.

Using these devices the following modes were generally possible: 1. Single-column mode: In this mode, the web content was presented in a single-column format. It

functioned similarly to the BlackBerry but did not use as many optimization techniques. If a table consisted of more than one column, the columns were presented vertically, one after the other. This eliminated the need for horizontal scrolling, but the original page layout was lost, sometimes resulting in pages that were more difficult to read and navigate.

2. Desktop mode: In desktop mode, the page was rendered as if it were being displayed on a desktop computer screen. The sizes of all page elements were kept unchanged. Viewing a page in this mode required significant horizontal and vertical scrolling to view the complete page.

3. Default mode: In the default viewing mode, the relative positioning of page elements was preserved, but the size of the page was proportionally reduced. The width of the resulting page can be larger than the width of the device screen, which required some horizontal scrolling. When trying to proportionally reduce the size of various elements of the page (text, tables, images), the elements sometimes overlapped.

Although some problematic web pages were viewed in different modes to find out whether the problem exists in all viewing modes, the test was primarily conducted in the default viewing mode. The default mode is the most likely choice of users and is the one that is likely to produce the best viewing experience for most websites.

There is some variation among the devices used in this study in terms of what web features and file types are supported. Some of the observations in our research represented limitations of the devices themselves and no solutions existed to remedy those limitations; other findings from our study are owing to unavailability of third-party add-on programs for that device’s platform. With the exception of DocHawk Platinum and eOffice Professional for BlackBerry, no attempt was made to install third-party software that is only available by purchase. Thus, it is possible that there may be some third-party software programs available for a particular device’s platform that would allow opening certain types of files or attachments from that device. Nevertheless, it should only affect the ability to open certain types of files and should have no effect on the

ISBN: 978-972-8939-66-3 © 2012 IADIS

158

HTML page-rendering or the look and feel of web pages when viewed on that device. It is also possible that there may be more advanced web browsers available for those devices that have better page optimization and page-rendering abilities. However, such programs are not easily available or are unavailable for free, which limits their benefit to a small number of mobile device users.

3. WEBSITE TESTING

A varied sample of websites was tested. The sites selected were library-related sites, journal databases, hosted journal sites, and some other popular AU sites. Although these sites are mainly library- and journal- related, the results of this research are general in nature and should be applicable to most university websites.

Tests were performed on the devices by going to various AU websites and assessing them on a scale of 0–3, where 0 represents not very mobile-friendly, and 3 represents very mobile-friendly. Two factors were considered and assessed accordingly: the visual display of the website as it is rendered on the screen of the device, and the functionality of the page (links, buttons, tabs, navigation, etc.). The following scheme was used in assessing the websites:

Visual display 0 – Page cannot be opened by the device at all. 1 – Page displays on the device with some deformation and/or requires excessive scrolling. 2 – Page displays reasonably well. Some scrolling may be required. Frames and fixed-size tables may cause some problems. 3 – The page displays perfectly and does not require horizontal scrolling. Functionality 0 – Page cannot be displayed, or none of the navigation links work. 1 – Only some browsing features work (e.g., many links cannot be opened, or page cannot be properly navigated). 2 – Most browsing features work (e.g., most links, buttons, and navigation items work). 3 – All links and all features work. Form submission and buttons, and so on, all work.

4. TEST RESULTS

Flash player presented a significant problem as any site using Flash would not display properly on the majority of phones. The phones also generally did not support a PDF reader, so trying to open a PDF file from any website was problematic. Such limitations are considered the limitations of the device itself and not shortcomings of the website. However, if a site primarily relied on the device being able to make use of those features, the mobile-friendliness grading of that site was reduced accordingly.

The sample pages showed the following results Athabasca University Home Page http://www. athabascau.ca/ The BlackBerry had a default single-column view and displayed the AU home page well. The iPAQ and

SMT could also display the page in single-column format that was similar to the display in the BlackBerry but looked less polished. The default mode in the iPAQ and SMT required horizontal scrolling, and the page looked slightly deformed. Regardless of the display mode, however, all navigation links worked well on all three devices.

myAU http://my.athabascau.ca The iPAQ and SMT both display this site fairly well, and all navigation links and site logins worked as

expected. On the other hand, the BlackBerry could not open this site at all. It generated a dialogue box: “HTTP error 406: Not Acceptable”. This appears to be caused by a configuration problem on the server side; the server incorrectly assumed that the client device was unable to render the page and so did not send any content.

Online Registration https://tux.athabascau.ca/oros/jsp/welcome.jsp This main registration site rendered well in all three devices. All links and form submissions worked as

expected. AU Intranet http://intra. athabascau.ca/


159

The BlackBerry rendered this site fairly well in its one-column layout. In the default viewing mode of the iPAQ and SMT, extensive horizontal scrolling was required and navigating was more difficult. The excessive horizontal scrolling was made necessary by the use of fixed-size tables. Setting up vacation notices and changing forwarding email addresses worked well in all three devices.

AU Webmail https://secure. athabascau.ca/webmail Webmail worked well with the iPAQ and BlackBerry but did not open in SMT because of frames. Research Centre http://www. athabascau.ca/research The Research Centre site rendered well in the single-column layout of the BlackBerry and fairly well in

the default layouts of the iPAQ and SMT. The site used fixed-size tables, so it requires a lot of horizontal scrolling. All links on the page worked well.

Open Journal Systems (OJS) http://www.irrodl.org/ Open Journal Systems (OJS) was tested by going to the journal site of the International Review of

Research in Open and Distance Learning (IRRODL). This site rendered well in the BlackBerry and in the single-column format of the iPAQ and SMT. However, it rendered rather poorly in the default layout of the iPAQ and SMT: two columns of the table almost overlapped. Editing and saving submissions worked well, but files could not be uploaded through any of the tested devices.

Open Conferencing System (OCS) http://tools.elab. athabascau.ca/tools/open-conference-system This site rendered very well on all three devices. Single-column and default views all worked well. All

links on the site also opened nicely. The file-upload feature on the paper submission page was the only part of the site that did not work. Public Knowledge Project’s Open Conferencing System (OCS) worked as the back end of the paper submission system; so the file-upload problem was determined to be with OCS rather than with the OCS site.

Moodle Forums http://www. athabascau.ca/moodletrain/forums.htm The Moodle forum site displayed well on all three devices. Posting, reading, and editing messages

worked well. As with other sites that required file uploads, none of the devices were able to upload files from this site.

AUSpace http://auspace. athabascau.ca/ The AUSpace site displayed well in the BlackBerry and in the single-column layout of the iPAQ and

SMT. The default layout of the iPAQ and SMT required horizontal scrolling because of tables. Searching and viewing files worked well in all devices. However, when trying to submit articles to AUSpace, it was not possible to upload files because the input box for the filename and browse button were missing in all three devices. This was not a problem of the site itself but rather a limitation of the mobile devices.

AU Library Sites Main Site – http://library. athabascau.ca/

Digital Reading Room (DRR) – http://library. athabascau.ca/drr

Digital Thesis and Project Room (DTPR) – http://library. athabascau.ca/

DTPR Digital Reference Centre (DRC) – http://library. athabascau.ca/drc All AU Library sites tested were found to be very mobile-friendly. The DRR, DTPR, and DRC used

similar layouts that are fluid, allowing a smooth flow of text. As those sites did not use fixed-size tables, the display was consistent and predictable across all the devices. AU Library sites adapted to the client device for optimal mobile-friendliness without sacrificing the richer web content. This was done by detecting what type of device was accessing the pages and then sending the appropriate version of the web page to the device.

The AU Library has integrated the mobile conversion services Google Mobile, Skweezer, and IYHY into some of the reading resources in DRRs. These third-party services work as proxy servers to provide suitable formatting of existing websites for mobile devices (Athabasca University Library, 2011).

AU Library Catalogue: AirPAC http://aupac.lib. athabascau.ca/airpac/ This site is a mobile-optimized version of the AU Library catalogue. AirPAC formats its response for the

type of device that is used to access the site. It sends a smaller version of the page to the SMT and BlackBerry to accommodate the small screen area, while it sends a larger version to the iPAQ with more screen area available. The site displayed very well in all three devices and in all view modes, and all links from this site worked flawlessly.

Journal Databases An extensive test was performed on all journal databases linked from the AU Library website. The

journal databases were assessed on a scale of 0–3, where 0 represents not very mobile-friendly, and 3

ISBN: 978-972-8939-66-3 © 2012 IADIS

160

represents very mobile-friendly. The grading scheme used for assessing the journal databases was the same one used for evaluating the other AU websites listed in Table 3. However, for the databases, the visual display and web functionally were considered together and graded accordingly. More than 120 databases were examined and their scores ranged from 0 to 3 on all devices, with varied mixes of accessibility, some being high with one device and low with another.

5. DISCUSSION OF RESULTS

Based on this study’s test results of the AU websites and the journal databases, the following visual display and functionality issues were identified as affecting the mobile-friendliness of the sites tested:

1. Some pages were displayed with unnecessary spaces at the top of the pages and large gaps in the middle. This is normally caused by the use of complex structures in the HTML page design, such as tables, nested tables, transparent pictures used for layout, and so on. When the mobile browsers try to optimize such pages to fit a small screen, the page may be deformed in many ways, depending on the optimization method used by the browsers.

2. If a page contains fixed-width blocks, excessive scrolling is necessary when viewing through mobile devices.

3. Flash-dependent websites pose another challenge for mobile browsers. Some websites depend on Flash for navigation menus. It is impossible to successfully visit such sites through devices that do not support Flash (e.g. iPhone, iPad).

4. Because the mobile devices only partially support JavaScript, the result of visiting a JavaScript-dependent site is unpredictable. Some features may work; others may not. For example, some sites extensively use JavaScript to open new browser windows. Such links almost always fail to open in the tested mobile devices. Other sites have entirely JavaScript-dependent navigation menus. In such cases, it is not possible to visit the pages linked from the menus.

5. Extensive use of specialized file formats—such as PDF, e-book, Microsoft Word, and PowerPoint—can be problematic for some mobile devices. Some browsers do not support opening those file types, so sites making heavy use of those file formats would not be friendly to these devices.

6. The use of frames also reduces the mobile-friendliness of the site. Different mobile devices support frames to different degrees. The iPAQ does not have a problem with frames, whereas the SMT cannot open horizontal frames. The BlackBerry linearizes the frames and displays them one at a time.

7. Some web servers make assumptions about the device accessing the website. For example, in one instance, the BlackBerry could not open a site because the server refused to send content; the server assumed that the device could not render the file.

8. One major problem common to all devices is the inability to upload files. None of the tested mobile browsers allowed files to be uploaded because they could not recognize the file browsing buttons.

The following chart (Figure 1) provides a mobile-friendliness score, which is the sum of the scores assigned to the different sites for individual devices. For example, adding the scores of the three devices used, the total score for the AU home page would be 14 out of the maximum 18. These scores were then normalized for each site to a maximum 100 points. Thus, the normalized score of the AU home page would be 77.77 points out of a maximum 100. The chart should be interpreted this way: “Two of the tested sites scored higher than 90, five sites scored between 80 and 90, five sites scored between 70 and 80,” and so on. As we can see from the chart, in general, most AU websites are quite mobile-friendly.


161

Figure 1. Histogram of mobile friendliness of tested AU websites

A similar chart (Figure 2) provides a sites linked to the AU Library website. The majority of websites scored 60 or higher in terms of mobilefriendliness. Some sites were problematic for the mobile devices, and scored lower thanexternal sites were not as mobile

Figure 2. Histogram of mobile friendliness of journal databases

Nevertheless, overall, the websites and journal databases were found to be quite mobilestudy shows that most AU websites are viewable and operable from the tested low bandwidth mobile phones. Some sites did not retain their layout and visuastill functional. Some sites could be rendered nicely but lost some functionality, such as their navigation links

0 1

0-10

10-20\

20-30

30-40

40-50

50-60

60-70

70-80

80-90

90-100

0 10

0-10

10-20\

20-30

30-40

40-50

50-60

60-70

70-80

80-90

90-100

Figure 1. Histogram of mobile friendliness of tested AU websites

2) provides a mobile-friendliness score for the more than 120 journal database sites linked to the AU Library website. The majority of websites scored 60 or higher in terms of mobilefriendliness. Some sites were problematic for the mobile devices, and scored lower thanexternal sites were not as mobile-friendly as the AU websites.

Figure 2. Histogram of mobile friendliness of journal databases

Nevertheless, overall, the websites and journal databases were found to be quite mobilestudy shows that most AU websites are viewable and operable from the tested low bandwidth mobile phones. Some sites did not retain their layout and visual design when they were viewed from the test devices but were still functional. Some sites could be rendered nicely but lost some functionality, such as their navigation links

2 3 4

20 30 40 50

friendliness score for the more than 120 journal database sites linked to the AU Library website. The majority of websites scored 60 or higher in terms of mobile-friendliness. Some sites were problematic for the mobile devices, and scored lower than 50, so in general the

Nevertheless, overall, the websites and journal databases were found to be quite mobile-friendly. This study shows that most AU websites are viewable and operable from the tested low bandwidth mobile phones.

l design when they were viewed from the test devices but were still functional. Some sites could be rendered nicely but lost some functionality, such as their navigation links

5 6

60 70

ISBN: 978-972-8939-66-3 © 2012 IADIS

162

and some JavaScript-dependent features. Some sites (especially the AU Library ones) were almost perfect visually and functionally when accessed from the smart phones.

This study determined that most of the AU Library websites (the main site, DRR, and DTPR) were designed with specific attention to the requirements of mobile devices: the server sent responses custom-tailored to the device being used to access the sites. The benefit of this approach is that mobile device users can conveniently enjoy their device’s resources at the same time as desktop users can make full use of their respective capabilities, receiving multimedia-rich content and more advanced graphical display. The downside is the need to maintain different versions of the same web page for different device profiles.

6. CONCLUSION AND RECOMMENDATIONS

Whether to characterize a website as mobile-friendly is not a simple yes or no question. There are variations in the degree to which various sites are friendly to mobile devices. Making a general statement about a website being mobile-friendly or mobile-unfriendly is not always accurate. There are so many different mobile hand-held devices with differing feature sets that it is difficult to make a generic statement about a website – while at the same time covering all possible devices and browsers that may access that site. The objective of this study was not to pronounce various sites as “mobile-friendly” or “not friendly,” but to get an overall picture of how the sites are visually displayed and function when viewed through the hand-held devices that were used for testing.

The capabilities of mobile devices are also rapidly changing. Manufacturers of those devices continuously add new features, and software developers develop more capable and “smart” software solutions to overcome some of the inherent limitations of those devices. For example, even if this study found that a device currently does not support native viewing of PDF files, that capability has since been added in the more recent models, making these findings somewhat obsolete. Thus, the direct results stated in this study are time-sensitive; that is, their accuracy is valid only for the current time and only for the specific models of those devices. Even so, despite the time- and device-sensitive nature of the results, we can draw some conclusions as to what factors contribute to making a website more mobile-friendly or less mobile-friendly:

1. Screen size considerations. One of the main constraints of small devices such as smart phones is the screen size. So, any web page that relies on various HTML elements being displayed in a fixed size is bound to cause problems on small-screen devices. To avoid such problems, it is recommended that the use of fixed-size tables be minimized or eliminated altogether. The positioning of HTML elements should be relative as opposed to absolute, so that when the page is resized and viewed on small screens, its layout remains intact.

2. Careful use of advanced HTML features. Many smart phones provide only partial support for Cascading Style Sheets (CSS) and JavaScript. Thus, if a web page is intended to be viewed on both desktop computers and small-screen low bandwidth mobile devices, the page integrity can be preserved on the mobile devices by limiting the use of CSS and JavaScript features to those that are supported by both.

3. Large images. Avoiding the use of large images in websites helps to make the site friendlier to mobile devices. When a large image is rendered on a small screen, the device may either reduce the size of the image to fit the screen, or keep the size of the image unchanged, which then causes the need for excessive scrolling. If a large image is resized, important details of the image may be lost, defeating the purpose of the image. This is especially problematic if an image map is used for page navigation. If the image is not resized, the required excessive scrolling makes it harder to navigate the page.

4. File format of the web content. Excessive use of file formats that are not supported by mobile devices also makes the site less friendly to mobile devices. Most devices are capable of viewing simple HTML pages, but they may not be able to open other types of media, such as PDF files, PowerPoint files, videos, or Flash content. In such a case, even if the device is able to access some pages of that website, it cannot fully take advantage of the materials and links provided.

5. Embedded objects. Special care should be taken when embedding objects on websites. Embedding objects such as audios, videos, and Flash in a web page enriches the page for desktop computer users, but it assumes that all browsers accessing the site are capable of handling those embedded objects. This is a precarious assumption in terms of the access of mobile devices. Mobile browsers usually disregard embedded objects. Therefore, if the embedded object is a crucial part of the page, the rest of the page may not make sense to the mobile device user. Instead of embedding an object on the web page, it is generally better to


163

include a link to such a file. That way, the user can download the file and open with a third- party program, if such a program exists. Even if the user chooses not to download the file, the web page integrity remains intact.

This study provides a general idea of how existing AU sites work with the tested mobile devices and identifies the underlying issues as to why they work that way. However, in the effort to make the sites as mobile-friendly as possible, it is also important to consider what some possible solutions are. Redesigning all those sites carefully, with due consideration to mobile devices, is one possibility, but it is a very impractical one. The cost of resources associated with this route can be enormous. Another possibility is creating a mobile-friendly version of each AU web page and serving those pages instead of the regular pages whenever mobile devices make page requests. This creates the huge burden of site maintenance, as we need to maintain multiple versions of the same page for different devices. Another problem with this approach is that as the capability of mobile devices changes, those sites need to be updated accordingly to reflect the device’s capability. However, this issue can be addressed to some extent by creating template- based dynamic pages, and rather than redesigning the pages whenever the device capability changes, one could change the profile of the device, which in turn would be reflected in the dynamic page.

A totally different approach that is gaining some popularity is the use of an intermediary proxy- like adaptation layer for the web content. That way, there is no need to maintain multiple versions of the same website, and it also does not require redesigning existing websites. In effect, whenever a user makes requests to a web page, the request can be routed through an intermediary service that identifies the requesting device, gets the page from the web server on behalf of the device, and reformats the page – thus making it suitable for that particular device – and then passes it on to that device. The success of such an approach depends entirely on the capability of the intermediary service. One advantage of this approach is that the burden of making the web pages user-friendly now shifts to the intermediary service from the web server or the web page administrator. Another advantage is that end users do not need to make any special adjustments or install special software on their devices.

There are some websites that provide such intermediary services. Skweezer http://www.skweezer.net/ , IYHY (http://www.iyhy.com/ , and Google Mobile http://www.google.ca/mobile/ are examples of such services. The AU Library is experimenting with the integration of those services with some of the Digital Reading Room resources. Few AU sites employ such service at this time. In the testing, most sites that required login/authentication could not be viewed through those services. However, when those services mature and become more capable, they might make mobile web access much more comfortable.

REFERENCES

Ally, M., McGreal, R., Schafer, S., Tin, T., & Cheung, B. (2007). Use of mobile learning technology to train ESL adults, Sixth International Conference on Mobile Learning Available from http://www.ccl-cca.ca/CCL/Research/FundedResearch/201009AllyMcGrealSchaferTinCheung.html

Athabasca University Library. (2011). AU Digital Reading Room Home (integrated mobile conversion services) Retrieved from http://library.athabascau.ca/drr/mobile2.php?course=mba&id=441&sub=5

Cao, Y., Tin, T., McGreal, R., Ally, M., & Schafer, S. (2007, November). Building an effective mobile-friendly digital library to support mobile learners: A case study of the Athabasca University M-library Project. Paper presented at the First International M-Libraries Conference, Milton Keynes, UK.

Cheung, B., McGreal, R., & Tin, T. (2007, July). Implementation of mobile learning using smart phones at an open university: From stylesheets to proxies. Paper presented at the IADIS Mlearn 2007 Conference, Lisbon, Portugal.

McGreal, R., Tin, T., & Cheung, B. (2006). Digital media at Athabasca University – Canada’s Open University – Going Mobile. International Council for Distance Education (ICDE) 2006 Retrieved .from http://www.icde.org/oslo/icde.nsf/CEFB5A35F7FC2EF8C1257298004C8616/$FILE/461.pdf

Wasti, R. (2006, March). A study of the mobile-friendliness of selected Athabasca University websites. Available from http://library.athabascau.ca/drr/Paper/final_web.pdf

ISBN: 978-972-8939-66-3 © 2012 IADIS

164

JOURNALISM 2.0: EXPLORING THE IMPACT OF MOBILE AND SOCIAL MEDIA ON JOURNALISM

EDUCATION

Thomas Cochrane1, Helen Sissons2 and Danni Mulrennan2 AUT University, New Zealand

1Centre for Learning and Teaching, 2Department of Journalism, AUT University

ABSTRACT

According to Hirst (2011) Journalism must change to survive in response to Web 2.0, however in “The Cult Of The Amateur” Keen (2007) argues that Web 2.0 (social media) is f***** (Ha, 2009), as it undermines and decimates the ranks of our professional literary ‘gatekeepers’. In response this paper explores the impact of social media upon Journalism education from two perspectives: both from the pedagogical changes Web 2.0 and mobile devices enable, and within the context of the changes in Journalism that social media use are driving. A participatory action research approach was adopted (Swantz, 2008), focusing upon pedagogical change while allowing the project to develop within a series of reflective interventions within the course. These interventions, or critical incidents (Brookfield, 1995, Sharples, 2009), included the exploration of Twitter, blogging, QR Codes, and Facebook as part of the course. Drawing on this experience, the paper presents an emergent framework for a response to social media within Journalism education, illustrating the positive impact of integrating the use of Web 2.0 tools on student engagement and contextualising theory within authentic learning environments.

KEYWORDS

Journalism, Pedagogy 2.0, Social Media, Web 2.0.

1. INTRODUCTION

Journalism is in crisis (Hirst, 2011); how does traditional Journalism respond to a world where consumer preference is for music that is now distributed via the Internet rather than purchased on CDs, video that is streamed either live or on demand rather than DVD, and news that is distributed via a host of social media channels such as Twitter, YouTube, Facebook and viewed on mobile devices such as the iPad rather than print media? Not only is traditional Journalism in crisis but Journalism education also needs to respond to the implications of the wave of social media.

The Internet has transformed the news industry: its ability to make money, the means it uses to distribute its product and the way news workers practise their trade. The rise of social media sites has even affected the nature of Journalistic identity, altering how journalists are viewed and how they view themselves. The editor in chief of The Guardian newspaper and executive editor of its sister Sunday paper, The Observer, writes that in the past journalists were considered figures of authority because they had the access to news sources. They were the gatekeepers and the public trusted them to set the news agenda and to tell the important stories of the day accurately, fairly and quickly. Now many readers want to make their own judgements, create their own content and learn from peers as much as from traditional media sources (Rusbridger, 2011).

Consequently, there has been a decline in the number of people relying on conventional sources of news. According to the most recent study by the Pew Research Center for the People and the Press (2011) in the United States more people in the 18 to 20 age bracket (65 percent) now say they get their news from the Internet and only 21 percent cite newspapers as their main source. Even among the over 50s, 34 percent use the Internet to access the news while 38 percent read a newspaper . Further, more people are getting news via smartphones, tablets and other mobile devices. In fact nearly half of American adults claim to get some local news and information on their cellphone or tablet computer (Rosenstiel et al., 2011).


165

It’s a situation that has been developing in the fifteen years since most newspapers went online and this period has seen a long-term decline in newspaper sales. Between 2005 and 2009 newspaper companies saw drops in circulation in North America (11 percent), Western Europe (8 percent) and Oceania (6 percent). The biggest declines in the UK (15.9 percent) and US (13.3 percent) coincided with two of the highest penetrations of social media. The third country with a high social media use, Australia, saw a smaller decline in newspaper circulation of 2.5 percent (The Economist, 19 July 2011, p4).

With increasing numbers of consumers getting their news for free online, it is clear that the traditional media business models are no longer working and new ways of thinking about news gathering, distribution and the news audience are required. Some news organisations are adjusting well, recognising the opportunities afforded to those willing to adapt.

Television news now includes more amateur footage, often taken from video-sharing websites such as YouTube. During events such as the London riots and the Oslo bombing some of the most dramatic pictures came from amateurs. The unsteady shots, often including the voice-over reaction of the person holding the camera, add an honesty and authenticity to the footage that viewers respond to. During the Arab Spring, organisations such as Al Jazeera aggregated social media content, including YouTube video, material from Facebook and Twitter messages and delivered it to its television viewers, many of whom did not have access to the Internet. Journalists at the BBC constantly monitor Twitter and use postings either to gauge opinion, get reaction to or eye witness accounts of events or to drive the public to their news site.

Rusbridger (2011), one of the pioneers of innovative web journalism, describes these new practices as offering a partnership with readers, creating a mutualised news organisation where there is a democracy of ideas and information. He believes that collaboration between journalists and readers makes for better and more effective storytelling. In this new environment, readers, listeners and viewers have the chance to become more than passive consumers of news. However journalists using or learning to use social media need to be aware of the possible pitfalls. They must learn:

1. How to filter huge volumes of information. Who is good to follow and who will fill their in-box with irrelevant information.

2. How to build a community of followers and feed them information without scooping their own organisation.

3. How to identify fake Twitter accounts. 4. How to avoiding lazy journalism that uses social media sites for a quick but weak angle on important

stories. 5. That social media is a public forum and requires professional behaviour. In response to these emerging issues, the authors have decided to explore the possibilities and

implications of Journalism 2.0 within the context of Journalism education. Journalism 2.0 as defined by the authors of this paper involves the exploration of two parallel aspects of social media in Journalism education: exploring the embedding and modelling of social media in the delivery and pedagogy of a Journalism course, and the exploration of the use and impact of social media on the practice of Journalism in authentic contexts. This is based in the collaboration between an educational technology expert and expert Journalism lecturers within the framework of a community of practice (COP) investigating the potential of social media in the context of Journalism education. This was the first foray into integrating the use of social and mobile web 2.0 within the delivery of the journalism course, and the technology stewards previous mobile web 2.0 experiences in a variety of educational contexts were used to broker examples of mobile web 2.0 pedagogy to the journalism lecturers.

While there is a significant body of literature exploring the pedagogical affordances of web 2.0 (McLoughlin and Lee, 2010) and mobile learning (Traxler, 2011), these two are seldom explicitly linked, and there is limited available literature on the pedagogical impact of these tools within the specific context of Journalism education, see for example Ashton (2009).

The paper explores learning theories and pedagogical frameworks that can inform, support, and critique these innovations in communication studies and journalism. These include, for example: Social Constructivism, Communities Of Practice, Authentic Learning, Pedagogy 2.0, and Learner Generated Contexts. The paper discusses plans to build on this to create a foundation for potential international collaboration between student groups and industry experts. For example: (Cochrane et al., 2011, Cochrane, 2010b).

ISBN: 978-972-8939-66-3 © 2012 IADIS

166

2. BACKGROUND

In preparation for the social media course, the course lecturer travelled to the UK and the US and spoke in depth to journalism industry professionals at the BBC (British Broadcasting Corporation) in the UK and the Los Angeles Times in the US. She also spoke to leading journalism schools in Cardiff and Arizona. In addition, she has interviewed an online editor at a major organisation in New Zealand and a news editor at a local paper. This information was used to inform the project in several ways:

1. How the journalism industry in three countries is using social media to gather and to disseminate information.

2. How leading schools of communication are reacting to changes in the industry in terms of their curriculum.

3. How the University might respond. However the approach taken by the Journalism lecturers was to present case studies of the impact of

social and mobile media on Journalism rather than integrate and model the use of these tools within face-to-face classes or beyond the classroom, making these explorations of social and mobile media theoretical rather than experiential. Consequently observed student use of mobile web 2.0 was limited to social networking with friends. Therefore another initial driver for the project was responding to the disruptive cellphone use in class by students leading to developing an appropriate response from the lecturer that would engage the students while providing an authentic use of cellphones as tools within a Journalism context. Discussions around an appropriate response to the disruptive (Sharples, 2001, Stead, 2006) nature of cellphones in class between the technology steward and the course lecturer formed the catalyst for a collaborative partnership. The technology steward brought educational technology (in particular mobile learning) experience and expertise, while the course lecturer brought professional Journalism expertise within the context of Journalism education. The key was to bridge theory and practice (Cochrane, 2009, Cochrane et al., 2009, Cook et al., 2008, Vavoula, 2007), rather than talking about social media use in class, the classes were reinvented as social media experiences with students encouraged to use their mobile devices actively for investigating social media use during the classes and then link these experiences to their out of class experiences and investigations of social media.

Thus the core of a community of practice (COP) was established consisting of a technology steward (Wenger et al., 2009, Wenger et al., 2005) and the course lecturer who began meeting weekly to explore ways to include social media in the journalism curriculum. The goal of the COP is to draw in other lecturers from the Journalism department and establish social media experts and evangelists that will bring about change within the department. The course lecturer is also among the first to teach in a new interactive classroom environment within the School of Communications. The lecturer has begun employing some of the ideas born out of this COP in conjunction with the use of a smart-board in the teaching of Specialist Writing, the core second semester post-graduate journalism writing paper, and Journalism Theory and Practice, a postgraduate Communications paper.

2.1 Theoretical Frameworks

This section introduces the learning theory and pedagogical frameworks that inform the choice and use of social media within the project, including: Social Constructivism, Communities Of Practice, Authentic Learning, Pedagogy 2.0, Mlearning, and Learner Generated Contexts.

2.1.1 Social Constructivism

According to theorists such as Vygotsky (1978) learning is a social process of student exploration guided by more experienced peers. Social constructivism forms a theoretical foundation for pedagogy 2.0 and communities of practice that are enabled by the use of social media (Wenger et al., 2005).

2.1.2 Communities of Practice

Communities of practice (COP) is a social learning theory (Lave and Wenger, 1991, Wenger, 1998, Wenger et al., 2009) that emphasises the process of membership in a community from initial peripheral participation to full participation as core members of the learning community.


167

2.1.3 Authentic Learning

Authentic learning (Herrington and Oliver, 2000, Herrington and Herrington, 2007, Herrington et al., 2009) is based upon situated learning (Brown et al., 1989) where explicit links are made between theory and practice using real-world (authentic) scenarios to represent and critically reflect upon on-the-job experiences.

2.1.4 Pedagogy 2.0

Pedagogy 2.0 (McLoughlin and Lee, 2007, McLoughlin and Lee, 2010) is a term coined to link social learning approaches with social media use. Pedagogy 2.0 forms a critical framework for integrating social media into education, focusing upon learner-generated content and learner-generated contexts rather than the delivery of teacher-generated content.

2.1.5 Learner Generated Contexts

Learner-generated contexts is a framework that bridges the gap between teacher-directed pedagogy and student-directed heutagogy (Luckin et al., 2010, Pachler et al., 2010).

2.1.6 Mlearning

Mobile learning is a powerful tool for enabling learner-generated content and learner-generated contexts (Cochrane, 2010a, Cochrane, 2011, Cochrane and Bateman, 2010). The ubiquitous nature of cellphones and the increasing student ownership of smartphones create a foundation for bridging both the digital divide and bridging formal and informal learning contexts (Vavoula, 2007). In particular, the rapid rise of Twitter uptake (McGiboney, 2009) is firmly associated with its essential link with cellphone use.

3. METHODOLOGY

A participatory action research approach was adopted (Swantz, 2008), focusing upon pedagogical change while allowing the project to develop within a series of reflective interventions within the course. Each of these interventions were borne out of discussions between the COP participants, tentatively implemented in class, student feedback sought, and then the impact reflected upon before refinement informing the implementation of further interventions. Critical incidents (Brookfield, 1995, Sharples, 2009) included the following activities:

Implementing and evaluating blogging to enhance the course discussions Surveying the students to find out what social media and mobile computing devices they currently use

and own. Creation of a simple in-class Poll to do this e.g. using Polleverywhere

(http://www.polleverywhere.com) that can be accessed via almost any cellphone or Internet connected computer. For example: http://www.polleverywhere.com/multiple_choice_polls/LTE1MTE1MzUwNDA

Embedding the use of Twitter in class Exploring QR Codes (Bar codes that can be scanned by cameraphones) Exploring the use of Google Plus (http://plus.google.com) for interviews Exploring the potential of mobile devices in Journalism, including smartphones and the iPad. AUTonline (The University’s Blackboard-based Learning Management System) Blogs were used within

the course “Journalism Theory and Practice”, where students were required to comment and post twice weekly. The theme of the course was the exploration of journalism practice in the digital age. Therefore it was logical to embed the learning within an authentic context. In addition, case studies were used to illustrate how journalists have used social media such as Twitter to great effect. Some students chose to discuss these in their blog posts. As part of the assignment, students were required to write a short reflection on how effective they found the use of the blog for their learning.

The expected outcomes of the project centred on the following: Generating research informed practice Enabling student-generated contexts in journalism education Establishing international collaboration

ISBN: 978-972-8939-66-3 © 2012 IADIS

168

3.1 Participant Profiles The project encompasses both Bachelor of Communications students who are majoring in Journalism and students on the Post Graduate Diploma in Journalism course. The lecturers participating in the project and forming the core of the Journalism 2.0 community of practice at AUT University include:

A senior lecturer in journalism. She teaches third year undergraduate and post graduate classes. Her research interests include the future of journalism and journalism-source relations.

A senior lecturer and Academic Advisor with the Centre for Learning And Teaching (CfLAT) at AUT. His research interests are in using technology as a catalyst for pedagogical change, with a focus upon mobile, web 2.0, and communities of practice.

A lecturer in television journalism. She teaches second and third year undergraduate and post-graduate classes. Her research interests include the future of broadcast journalism and television journalism practice.

These three bring complimentary expertise to the project and form core members of the community of practice encompassing the project.

4. RESULTS

An initial survey of the participating 50 students was conducted using Polleverywhere, with the results showing that all of the students owned a cellphone, with 83% owning cameraphones, and 48% of the students owned iPhones. After establishing student access to Twitter via their own cellphones, the project explored the use of Twitter in the classroom. It was to encourage group discussion and involve students normally reluctant to speak publicly. For example: Using a Twitter hashtag to collate student Tweets and displaying them live in class from a video projector via Twitterfall (http://twitterfall.com) or Visible Tweets (http://www.visibletweets.com). It was particularly effective when used in the weekly news quiz. Students formed five groups and competed in a University Challenge style quiz based on the news of the week. The live Twitter feed in class saw a student’s friend randomly joining the Twitter stream and commenting out of context. An initial hashtag used the class number only resulting in communication without context. As this led to rather random looking tweets in students’ twitter streams further use of the Twitter news quiz used the words “class quiz” in the hashtag to provide some context for their followers. Students who had already built up a following on Twitter were initially concerned that “random Tweets” would annoy these followers and so we decided they should inform them that for the next half-an-hour the student was taking part in a class quiz and all Tweets should be ignored.

Another mobile media format explored was QR Codes. The students’ initial response was to label QR Code use as a "gimmick". This led to an exercise asking students to 'be aware' and recognise QR Codes in their daily environment, for example: Design News NZHerald 28 Sept. The exercise raised awareness and the students running the student online news site, TWN Online, experimented with QR codes on short summaries or “teaser stories” as a way of encouraging readers to go via the QR code to the full story online. Some also then investigated how QR codes could enhance their CVs. In journalism, it is expected that a CV will be no longer than one page. Inserting a QR code into the CV is potentially an effective way for the student to link to further content such as a “showreel” or set of clippings.

Class discussion, and the reflective statement, around the use of AUTonline blogs revealed that those students who were the most reserved in face-to-face debate were the most empowered by the use of Blogging as a form of expression, reflection and critique. Some wrote in their reflections that they believed the blog was a more democratic environment, as it was “harder for people to dominate the discussion as can happen in class” (Student). And: “One can let one’s thoughts be known without being interrupted” (Student). Others initially felt apprehensive about commenting in a small class environment on a blog post of someone they did not know in case they caused offence. However, all students grew in confidence across the semester. “Our posts have progressed from initial tentativeness and brevity to greater length and depth, written with more confident voices” (Student). It was generally agreed that the blog was a valuable learning tool.

The most common view among the students was that the blog helped them discover the beliefs and motivations of others. The following were typical of the comments:

“I learnt from my peers, their ideological standpoints and they way they reason.” (Student1) “Other students’ posts enabled me to see the same things from different perspectives.” (Student2)


169

5. DISCUSSION

Students were initially reticent to publish their thoughts publically via social media (either via blogging or using twitter). This was a new classroom experience for them beyond their previous social use of these tools with their friends only. To scaffold their introduction to the educational use of social media the ‘safe’ environment of the closed Blackboard blog tool was used to host students first course-related blogging attempts. This raised interesting discussions around the benefits and pitfalls of open versus closed media use. The key benefit of using open access social media tools is to facilitate the establishment of students’ professional social networks that can also enable commenting and interaction from peer groups and industry experts around the world. Therefore future iterations of the project will use open access blogs rather than the closed access AUTOnline blogs. Student blogs will also be introduced into more classes to establish a culture of critical reflection and engagement with social media throughout the journalism course.

An issue raised by lecturers is that of technology access: will the prescribed use of web-based social media within the course create a digital divide in Journalism education? Focusing upon mobile web 2.0 tools (for example: Twitter, mobile blogging) will ensure that all students have access to the necessary tools, as our survey indicated that all of the students owned a cellphone, with the majority owning a smartphone capable of high levels of integration with social media within virtually any context. This will also drive the ability to bridge the classroom environment with students’ informal learning experiences in the real world beyond the classroom, enriching their learning experiences, and enabling student-generated content and student-generated learning contexts.

The project has had a significant impact on assessment strategies: because we are using a social constructivist foundation formative feedback and peer assessment strategies become more important than in the previous teacher-directed learning environments, and these will be explored more in 2012.

The implications of the project will inform a social media integration plan for 2012 courses, resulting in a social media integration framework for 2012. Key elements of this will include the following:

Scaffolded by establishing communities of practice A focus upon student-owned devices as enabling tools Exploration of social media platforms: Twitter, Blogging, and emergent tools Collaboration in authentic scenarios For example, during 2012 we plan to extend the use of Twitter as a way of brainstorming in journalism,

for example, by asking the students to tweet their story ideas. The 140 character limit will be used to test the clarity of the news angle and therefore the robustness of the idea, before the story is written as a blog post or online story and then pitched to followers via Twitter. One concern is that story ideas may need to be kept private until the story is written, otherwise the student could get “scooped” by another journalist. Therefore we could use the Smartboard environment in the classroom and the Postit software. Once the story is completed, it can then be pitched via Twitter to drive traffic to the AUT online news site, TWN Online (Te Waha Nui Online, Student Journalism Blog, http://www.tewahanui.info/wordpress2/). Two specific examples of the pedagogical impact of the exploration of social and mobile web 2.0 so far include:

The personal engagement with Twitter as a virtual community building tool and collaboration tool by the lecturers and students, rather than the previous theoretical case studies only. Thus modelling an authentic use of these tools and appropriate etiquette.

The use of Google Docs to collaboratively write, edit, and share this research paper itself, including previewing and critiquing its development on iPads during the weekly lecturer COP while drinking coffee in local cafes – nurturing a social atmosphere to the COP.

The initial COP comprised of two course lecturers and the technology steward proved to be a fruitful strategy for designing and supporting pedagogical change within the Journalism course. The Journalism lecturer COP has continued and been expanded in 2012, bringing into the COP two additional lecturers and funding teaching release time of one of the lecturers to take on the role of Learning and Teaching Fellow within the department to support and broker the integration of social and mobile web 2.0 within the curriculum. Thus the integration of social media and mobile web 2.0 within the Journalism course will be explored in depth in 2012, with a focus upon the lecturers modelling the use of social and mobile web 2.0 in response to the five issues of web 2.0 use in Journalism identified in the introduction of this paper, as these issues were evident in students’ initial explorations of the integration of the pedagogical use of these tools during 2011.

ISBN: 978-972-8939-66-3 © 2012 IADIS

170

6. CONCLUSION

The exploration of the integration of social media, and in particular mobile web 2.0 tools in a Journalism course has had significant impact upon the classroom experiences of the lecturer and the students. Scaffolded by a supportive community of practice, the lecturers have been empowered to try new approaches to move beyond teaching about social media in journalism to modelling and integrating the use of social media within authentic contexts within the classroom and students learning experiences. Instead of attempting to put up barriers to the crisis created for journalism by user-generated news tools, the project demonstrates that journalism education can instead embrace and harness the potential of these tools in authentic scenarios.

REFERENCES

Ashton, D. 2009. The professional in the age of the amateur: Higher education and journalism on-the-job. Available: http://theendofjournalism.wdfiles.com/local--files/danielashton/Daniel%20Ashton.doc.

Brookfield, S. 1995. Becoming a Critically Reflective Teacher, San Francisco, Jossey-Bass Inc. Brown, J. S., Collins, A. & Duguid, P. 1989. Situated cognition and the culture of learning. Educational Researcher, 18,

32-41. Cochrane, T. 2009. Mobile Web2.0: Bridging Learning Contexts. In: Caballe, S., Xhafa, F., Daradoumis, T. & Juan, A.

A. (eds.) Architectures for Distributed and Complex M-Learning Systems: Applying Intelligent Technologies. Hershey, PA 17033, USA: IGI Global.

Cochrane, T. 2010a. Beyond the Yellow Brick Road: Mobile web 2.0 informing a new institutional elearning strategy. Special Issue 'The Transformational Impact of Learning technology' of ALT-J, Research in Learning Technology, 18, 221–231.

Cochrane, T. Year. Twitter Tales: Facilitating international collaboration with mobile web 2.0. In: Steel, C. H., Keppell, M. J., Gerbic, P. & Housego, S., eds. Curriculum, technology & transformation for an unknown future. Proceedings 27th ASCILITE Conference, ASCILITE 2010, 5-8 December 2010b Novotel Sydney Brighton Beach, Sydney, Australia. The University of Queensland, 195-205.

Cochrane, T. 2011. Exploring the Pedagogical Affordances of Mobile Web 2.0. In: Chao, L. (ed.) Open Source Mobile Learning: Mobile Linux Applications. Hershey, PA 17033, USA: Information Science Reference (an imprint of IGI Global).

Cochrane, T. & Bateman, R. 2010. Smartphones give you wings: Pedagogical affordances of mobile web 2.0. Australasian Journal of Educational Technology, 26, 1-14.

Cochrane, T., Bateman, R., Buchem, I., Camacho, M., Gordon, A., Keegan, H. & Rhodes, D. 2011. Mlearning 2.0: Fostering International Collaboration. In: Candel Torres, I., Gomez Chova, L. & Lopez Martinez, A. (eds.) ICERI2011: 4th International Conference of Education, Research and Innovations. Madrid, Spain: IATED.

Cochrane, T., Bateman, R. & Flitta, I. 2009. Integrating Mobile Web 2.0 within Tertiary Education. In: Mendez-Vilas, A., Solano Martin, A., Mesa Gonzalez, J. A. & Mesa Gonzalez, J. (eds.) Research, Reflections and Innovations in Integrating ICT in Education. Badajoz, Spain: FORMATEX.

Cook, J., Pachler, N. & Bradley, C. 2008. Bridging the Gap? Mobile Phones at the Interface Between Informal and Formal Learning. Journal of the Research Center for Educational Technology (RCET), 4, 3 - 18.

Ha, P. 2009. Interview with Andrew Keen at the Next Web 2009: "Web 2.0 Is F*Cked" [Online]. TechCrunch. Available: http://techcrunch.com/2009/04/16/interview-with-andrew-keen-at-the-next-web-2009-web-20-is-fcked/ [Accessed 29 September 2011].

Herrington, A. & Herrington, J. 2007. Authentic mobile learning in higher education. In: Jeffery, P. L. (ed.) AARE 2007 International Educational Research Conference. Fremantle, Australia: AARE.

Herrington, J. & Oliver, R. 2000. An instructional design framework for authentic learning environments. Educational Technology Research and Development, 48, 23-48.

Herrington, J., Reeves, T. & Oliver, R. 2009. A guide to authentic e-learning, London and New York, Routledge. Hirst, M. 2011. News 2.0: Can journalism survive the Internet?, Crows Nest NSW, Australia, Allen & Unwin. Keen, A. 2007. The cult of the amateur: how today's internet is killing our culture, New York, Doubleday/Currency. Lave, J. & Wenger, E. 1991. Situated Learning: Legitimate peripheral participation, Cambridge, Cambridge University

Press. LuckinN, R., Clark, W., Garnett, F., Whitworth, A., Akass, J., Cook, J., Day, P., Ecclesfield, N., Hamilton, T. &

Robertson, J. 2010. Learner-Generated Contexts: A Framework to Support the Effective Use of Technology for


171

Learning. In: Lee, M. & Mcloughlin, C. (eds.) Web 2.0-Based E-Learning: Applying Social Informatics for Tertiary Teaching. Hershey, PA: IGI Global.

Mcgiboney, M. 2009. Twitter's Tweet Smell Of Success. Nielsen Online [Online]. Available: http://blog.nielsen.com/nielsenwire/online_mobile/twitters-tweet-smell-of-success/ [Accessed 30 June].

Mcloughlin, C. & Lee, M. 2007. Social software and participatory learning: Pedagogical choices with technology affordances in the Web 2.0 era. In: Atkinson, R. J., Mcbeath, C., Soong, S. K. A. & Cheers, C. (eds.) Proceedings of Ascilite 2007, ICT: Providing Choices for Learners and Learning. Centre for Educational Development, Nanyang Technological University, Singapore: ascilite.

Mcloughlin, C. & Lee, M. 2010. Pedagogy 2.0: Critical Challenges and responses to Web 2.0 and Social Software in Tertiary Teaching. In: Lee, M. & Mcloughlin, C. (eds.) Web 2.0-Based E-Learning: Applying Social Informatics for Tertiary Teaching. Hershey, PA: IGI Global.

Pachler, N., Bachmair, B. & Cook, J. 2010. Mobile Learning: Structures, Agency, Practices, London, Springer. Pew Research Center For The People And The Press. 2011. Internet Gains on Television as Public’s Main News Source:

More Young People Cite Internet than TV [Online]. Pew Research Center. Available: http://pewresearch.org/pubs/1844/poll-main-source-national-international-news-internet-television-newspapers [Accessed October 2011].

Rosentiel, T., Mitchell, A., Rainie, L. & Purcell, K. 2011. State of the News Media 2011: Mobile News and Paying Online [Online]. Pew Research Center’s

Project for Excellence in Journalism . Available: http://stateofthemedia.org/2011/mobile-survey/ [Accessed October 2011]. Rusbridger, A. 2011. Does Journalism Exist? In: FOLKENFLIK, D. (ed.) Page One: Inside the New York Times and the

Future of Journalism. 1 ed. Philadelphia: Participant Media. Sharples, M. 2001. Disruptive devices: mobile technology for conversational learning. International Journal of

Continuing Education and Lifelong Learning, 12, 504-20. Sharples, M. 2009. Methods for Evaluating Mobile Learning. In: Vavoula, G., Pachler, N. & Kukulska-Hulme, A. (eds.)

Researching Mobile Learning. Bern: Peter Lang. Stead, G. 2006. Mobile Technologies: transforming the future of learning. In: Pinder, A. (ed.) Emerging Technologies for

Learning. Coventry: British Educational Communications and Technology Agency. Swantz, M. L. 2008. Participatory Action Research as Practice. In: Reason, P. & Bradbury, H. (eds.) The SAGE

Handbook of Action Research: Participative Inquiry and Practice. Second ed. London: SAGE Publications. Traxler, J. 2011. Introduction. In: Traxler, J. & Wishart, J. (eds.) Making mobile learning work: case studies of practice.

Bristol: ESCalate, University of Bristol, Graduate School of Education. Vavoula, G. 2007. Learning Bridges: a role for mobile technologies in education. Educational Technology Magazine, 47,

33-37. Vygotsky, L. 1978. Mind in Society, Cambridge, MA, Harvard University Press. Wenger, E. 1998. Communities of Practice: Learning, Meaning, and Identity, Cambridge, Cambridge University Press. Wenger, E., White, N. & Smith, J. 2009. Digital Habitats: stewarding technology for communities, Portland, Oregon,

CPsquare. Wenger, E., White, N., Smith, J. & Rowe, K. 2005. Technology for Communities. In: Langelier, L. (ed.) Working,

Learning and Collaborating in a Network: Guide to the implementation and leadership of intentional communities of practice. Quebec City: CEFIRO.

ISBN: 978-972-8939-66-3 © 2012 IADIS

172

AUTOMATIC EVALUATION SYSTEM OF DRIVING SKILL USING WEARABLE SENSORS FOR PERSONALIZED SAFE

DRIVING LECTURE

Masahiro Tada1, Haruo Noma1, Akira Utsumi1, Masaya Okada2 and Kazumi Renge3 1Advanced Telecommunications Research Institute International 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto, 619-0288, Japan

2Graduate School of Science and Technology, Shizuoka University 3-5-1, Jyohoku, Naka-ku, Hamamatsu, Shizuoka, 432-8011, Japan

3Tezukayama University, 3-1-3, Gakuen-minami, Nara-shi, Nara, 631-8585, Japan

ABSTRACT

In this paper, we propose an automatic evaluation system of safe driving skill for personalized driving lecture. Our system use small wireless wearable sensors to directly measure drivers' behavior without giving much stress. By using the sensors together with GPS and driving instructors' knowledge, our system automatically evaluate drivers' safe driving skill. Through experiment in real traffic condition, we have confirmed that our system can point out shortcomings in driving skill with accuracy of over 80%. As the next step, we have applied our system into a driving school and have performed large-scale demonstrational experiment of personalized safe driving lecture. Questionnaire result shows that our system works well as an effective support tool for personalized driving lecture.

KEYWORDS

Automatic Evaluation System, Driving Skill, Personalized Safe Driving Lecture

1. INTRODUCTION

To reduce the amount of traffic accidents, a lot of effort has been made for the improvement of vehicle and road safety equipment. However, generally the number of traffic accidents is still at high level. In addition to improving vehicles and roadside safety, driving behavior should also be considered for traffic accident reduction.

According to the traffic accident report by the National Police Agency (Traffic bureau 2010), 55.0% of all traffic accidents in Japan occurred at intersections. As statics of law violation in the accidents on the report, lack of scanning behavior to confirm the safety is the most frequent cause of traffic accidents (31.8% of all traffic accidents). The statistics show the fact that drivers can reduce traffic risks significantly by their own driving behavior, e.g. scanning around for any potential hazards as well as covering the brake when approaching a blind intersection (bad visibility due to buildings, other structures, etc.). Our objective in this research is to develop an automated evaluation system of each driver's safety driving skill to promote safe driving by giving personalized training program based on his/her own evaluation result.

Event Data Recorders (EDRs) are widely used to record vehicle information and driving scene videos related to dangerous driving situations (Gabler 2008). According to Takeda et al.(Takeda 2011) and a risk consulting company (Tokio Marine & Nichido Risk Consulting), traffic accidents were reduced more than 30% by installing EDRs into vehicles to record drivers' daily driving behavior and by providing them safety guidance in regard to recorded behavior later on (not prompt feedback). This result supports our expectation that giving personalized training program could be an effective way to reduce traffic accidents.

As a key information to detect dangerous driving situations, most of EDRs focus on sudden change in vehicle motion (e.g. sudden brake). However, in addition to these kinds of explicitly dangerous situations easily detectable from vehicle motion data, there are many other potentially dangerous situations EDRs can not detect. For example, let us assume that a driver enters a blind intersection with excessive speed without scanning around. Fortunately, if there is no approaching vehicle on intersecting road, collision will not


173

happen. Although these kinds of situations are potentially dangerous, EDRs misjudge the situations as "not dangerous". Detecting these potentially dangerous situations and feed-backing to drivers would be useful to improve overall traffic safety. To achieve this, it is necessary to directly measure driver's behavior.

Eye-mark recorder has been widely used to record drivers' eye movement patterns (Chapman 1998) (Falkmer 2005). However, since eye-mark recorder strongly restricts drivers' movements, continuous use of the recorder could be very stressful to drivers. Moreover, since eye-mark recorder data requires high processing cost to use them for driver training, prompt feedback is difficult.

As another approach, Takeda et al.(Takeda 2011) tried to detect potentially dangerous situations using specially equipped vehicle installed many kinds of sensors in it. However, Takeda's method manually detect drivers' scanning behavior, prompt feedback is also difficult.

Therefore, in this paper, we propose an automatic evaluation system of driving skill using wearable sensors for personalized safe driving lecture. Our system use small wireless wearable sensors to directly measure drivers' scanning behavior and pedal operation behavior without giving much stress to drivers. By using the sensors together with GPS and driving instructors' knowledge, our system automatically evaluate each driver's safe driving skill by analyzing how he/she behave (including NOT behave for safety) at potentially dangerous spots (e.g. accident prone area).

In this paper, we discuss the validness of our system by comparing its evaluation results with an evaluation given by a professional driving instructor. Furthermore, we discuss efficiency of our system as a support tool for personalized driving lecture through large-scale demonstrational experiment at driving school.

2. WEARABLE MOTION RECORDING SYSTEM

2.1 Wearable Sensors

We use three small wireless wearable sensors that contain a three-axis gyro/accelerometer chip and a PDA to measure driver's behavior. A driver wears a cap with one sensor as shown in Fig. 1. Another one was placed on the driver's right shoe, and the other was placed on the dash board of a vehicle. The sensor is enough small (39.0mm(W) x 44.0mm(H) x 12.0mm(D), 20g), so the sensor never disturbs drivers while driving. The cap/shoe mounted sensor measures driver's head/toe motion, while vehicle mounted sensor measures vehicle motion. The sensors send measured data sampled at 25Hz to a PDA (72.0mm(W) x 115.0mm(H) x 17.8mm(D), 170g) with Bluetooth. Transmitted motion data from the sensors are stored on memory with timestamp. A PDA also receives and stores GPS location data at 1 Hz.

Since wearable sensors and a PDA are both small, wireless, and running on battery power, we can easily adapt our system to various kinds of vehicles and drivers.

Figure 1. Wearable motion recording system

2.2 Noise Reduction Using ICA

When measuring head/toe motions using a three-axis gyro/accelerometer sensor on a moving vehicle, measured data would be linear combination of head/toe motion and vehicle motion. If local coordinate systems of cap/toe mounted sensor are the same as those of vehicle mounted sensor, it is easy to cancel vehicle-caused noise by subtracting vehicle mounted sensor data. However, local coordinate systems of cap/ toe and those of vehicle would be different depends on various kinds of factors such as type of vehicle, type

ISBN: 978-972-8939-66-3 © 2012 IADIS

174

of cap, and driving form. When thinking of applying the system to various kinds of situations, automatic noise reduction method requiring no prior information is necessary. In this paper, we propose an automated method to reduce vehicle-caused noise using independent component analysis (ICA).

ICA is a method to extract statistically independent components from their linear mixtures without using any prior information (Hyvarinen 2001). Let us assume that the m-dimensional vector of sensor data x(t) = [x1(t),...,xm(t)]T is generated by an unknown linear mixture model,

x(t) = As(t), where s(t) =[s1(t),...,sn(t)]

T is the n-dimensional (n≤m) vector whose elements are called sources. Based on assumptions that {si(t)} are mutually independent signals, ICA finds demixing matrix W by minimizing statistical dependence among output signals y(t),

y(t) = Wx(t). Here, if WA = I, y(t) equals to s(t). In this paper, we employ fastICA algorithm [Hyvarinen 2001] to

estimate W, where WA = I. Since cap mounted sensor data xcap(t) is linear mixtures of head motion shead(t) and vehicle motion scar(t), by applying ICA to x(t) = [xcap(t), xcarX(t), xcarY(t), xcarZ(t)]T, we can estimate scap(t). Here, xcarX(t), xcarY(t), xcarZ(t) denote tree-axis (X, Y, Z) vehicle mounted sensor data.

As the same way, we also apply ICA to toe mounted sensor data.

2.3 Detecting Scanning/Pedal Operation Behavior

After applying ICA, by integrating head motion data, we calculate driver's head-rotation angle. When integrating head motion data, to ignore small head motions not related to scanning behavior, we only use head motion data whose absolute value exceeds experimentally preset threshold. In addition, to tackle the cumulative error, if no head motion is measured for 3.0 seconds while driving, we reset head-rotation angle to zero. The reset policy above is based on the assumption that drivers would usually look ahead while driving.

After calculating head-rotation angle, to identify whether the detected head-rotation is scanning behavior or not (e.g. look away behavior), we use Support Vector Machine (SVM) (Bishop 2006). In this paper, by using 209.7 minutes manually annotated data, we have trained SVM classifier. We have also trained SVM classifier for pedal operation behavior using the same data, and identify driver's pedal operation behavior (acceleration/brake pedal).

3. AUTOMATIC EVALUATION METHOD OF SAFE DRIVING SKILL

3.1 Evaluation Criteria of Safe Driving Skill

As a result of an interview for three professional driving instructors, we have found out that they usually evaluate drivers' skill from following viewpoints.

(1) Scanning Behavior To prevent traffic accidents at potentially dangerous spots, collecting any potential hazards by widely

scanning around with head movement is essential. To collect sufficient information to check safety, driver should appropriately perform scanning behavior according to the situation (e.g. Checking left blind spot for pedestrians and/or cyclists by rotating your head to left-back side is necessary when turning left at crowded intersection. However, the same behavior could be a risky distraction in another situation such as driving straight). The driving instructor evaluates one's scanning behavior whether he/she scans to the appropriate orientation taking enough time to collect information in traffic environment (not a perfunctory manner) or not. In addition, since scanning after entering potentially dangerous spots is useless to prevent accidents, timing of scanning is also regarded as an important viewpoint.

(2) Vehicle Speed Another important viewpoint of driving skill evaluation is the maintenance of appropriate speed. Even if a

driver could detect hazards in advance, excessive speed make it difficult to avoid them. Moreover, approaching potential dangerous spots slowly give a driver enough time to carefully scan hazards.

(3) Pedal Operation Behavior


175

From the viewpoint of active safety, there are big difference in driving skill between drivers who cover the brake in advance to approaching potential dangerous spots and drivers who do not.

Based on the interview results above, in this paper, we defined checklist of "minimum" required safe driving behavior at each potentially dangerous spot (i.e. minimum requirement for all drivers to prevent accident at the potentially dangerous spot) using following evaluation criteria; (1) orientation of scanning, (2) the number of scanning, (3) scanning time (i.e. a driver takes enough time to detect hazards or not), (4) timing of scanning, (5) vehicle speed, (6) pedal operation behavior. Here, different type of potentially dangerous spot have different type of checklist of minimum required safe driving behavior. Therefore, in this paper, for each potentially dangerous spots, we manually defined checklist of minimum required safe driving behavior based on driving instructors' knowledge.

Our system has no limitation for the number of pre-defined potentially dangerous spots.

3.2 Evaluation Procedure of Safe Driving Skill

Evaluation procedure of safe driving skill is as follows. Step1 By analyzing GPS data, detect driver's approaching time to a pre-defined potential dangerous spot.

Start evaluation procedure for the detected spot. Step2 Applying ICA to wearable sensor data to reduce vehicle-caused noise. Step3 By using SVM, detect scanning behavior and pedal operation behavior from wearable sensor data. Step4 Calculate scanning orientation and scanning time from detected scanning behavior data. Step5 Calculate vehicle speed from GPS data. Step6 Evaluate driver's skill by comparing driving behavior detected in step3-5 to pre-defined checklist

for the spot. Step7 If whole evaluation criteria are satisfied, evaluate the behavior as "good". If not, display the

message to request for improvement related to unsatisfied criteria. Step8 Score driver's skill at the spot according to achievement ratio of pre-defined checklist.

Figure 2. An example of evaluation result of our system (these screen shots are originally described in Japanese)

Since our system runs evaluation procedure automatically, we can promptly feed-back evaluation result to the driver. Fig.2 shows an example of evaluation result of our system. Our system can integrate driver's evaluation result at each potential dangerous spot and scores his/her total driving skill with five level (A:Execellent - E: Worst). Here, note that our system is designed for left-handled traffic in Japan.

ISBN: 978-972-8939-66-3 © 2012 IADIS

176

4. EXPERIMENTS

4.1 Validation Study of Our Method

In this section, we discuss the validness of our system by comparing its evaluation results with an evaluation given by a professional driving instructor. We performed an experiment with 23 subjects (aged from 40 to 69) on public road in Kyoto, Japan. All subjects usually drive in their daily life. For safety, in our experiment, we use a driving school vehicle (1500cc, automatic transmission) that has a secondary brake pedal for a driving instructor sitting on the passenger seat. The subject wore a cap with one sensor to measure head motion. Another one was placed on the subject's right shoe to measure pedal operation, and the other was placed on the dash board to measure vehicle motion. In addition, the position and speed data of the vehicle was obtained by GPS with a frequency of 1Hz. We also use video cameras to record driver's head/foot motion as well as traffic environment around to ask a driving instructor subjectively evaluate each driver's skill as ground truth data. Note that video data is used only to evaluate validness of our system. Our system works without video cameras.

In this paper, we focused on 8 intersections (7 unsignalized intersections and a signalized intersection) selected as potentially dangerous spots by a professional driving instructor. Since some subjects could drive only part of the course because of a limitation of the driving instructor's schedule, we measured totally 138 driving behavior sets of 23 subjects at 8 potentially dangerous spots.

Firstly, we asked the driving instructor to give subjective evaluation of subjects' safe driving skills based on evaluation criteria as discussed in Sec.3.1. In the subjective evaluation procedure, we showed the driving instructor our experiment video data and never showed our system's evaluation results. The video data consisted of the front view, driver's face and driver's feet. As a result of subjective evaluation, 52 driving behavior sets were evaluated as "good", while 84 behavior sets were evaluated as "risky". The driving instructor also pointed out 182 shortcomings of 84 risky behavior sets (see Tab.1 for detail).

Turning to evaluation result of our system, 50 driving behavior sets were evaluated as "good" and 86 were evaluated as "risky". Among 50 driving behavior sets evaluated as "good" by our system, 45 sets were matched with the instructor's subjective evaluation (precision ratio: 90.0%, recall ratio: 86.5%). Likewise, among 86 driving behavior sets evaluated as "risky" by our system, 79 were matched with the instructor's (precision ratio: 91.9%, recall ratio: 94.0%).

Here, let us look deeper into "risky" driving behavior sets from the viewpoint of "what kinds of shortcomings make behavior risky". Tab.1 shows detail of shortcomings and detection accuracy of our system. As shown in Tab.1, although most of shortcomings pointed out by the instructor are potentially dangerous behavior that EDRs can not detect (e.g. no scanning behavior when approaching potentially dangerous spots), our system can point out most of them with accuracy over 80%.

Table 1. Accuracy of our system

Type of shortcomings Num of Detected by Instructor

Num of Detected by Our System

Num of Correctly Detected

precision ratio

Recall ratio

No scanning behavior 48 45 40 88.9% 83.3% Insufficient scanning 68 65 52 80.0% 76.5% Scanning time is not enough 19 17 16 94.1% 84.2% Timing of Scanning is bad 2 2 2 100.0% 100.0% Look away 2 2 2 100.0% 100.0% Excessive speed 30 30 30 100.0% 100.0% Ignoring stop sign 8 8 8 100.0% 100.0% Not covering brake 5 4 4 100.0% 80.0%

4.2 Large-Scale Demonstrational Experiment at Driving School

As discussed in Sec.4.1, we have confirmed that our system allows us to point out shortcomings in drivers' scanning behavior/pedal operation with accuracy of over 80%. As the next step, we have applied our system into safe driving lecture for retraining licensed drivers at a driving school and have performed large-scale demonstrational experiment.


177

In demonstrational experiment, firstly, we let each driver drive on public road giving no preliminary information (we use the same course as mentioned in Sec.3.1), and measure his/her driving behavior using wearable sensors. 10 minutes after coming back to driving school (i.e. after finishing driving), a driving instructor give safety driving lecture for 1 hour using each driver's skill evaluation result as a textbook. After the lecture, all drivers are required to answer a questionnaire.

Through demonstrational experiments, we have trained 171 drivers aged from 22 to 73 (everyone drives at least once a week). Fig.3 shows distribution of total score of all drivers' skill evaluation result ("A" denotes "excellent" and "E" denotes "worst"). As shown in Fig.3, almost 50% of all drivers were evaluated as "D (bad )" or "E (worst )" driver. This result indicates the necessity to retrain licensed drivers.

Figure 3. Distribution of total score of skill evaluation result

Figure 4. Distribution of scanning behavior score Figure 5. Distribution of vehicle speed score

Let us now look at the result in detail. Fig.4 shows distribution of "scanning behavior score" corresponds to evaluation criteria (1) to (4) as mentioned in Sec.3.1. X and Y axis of Fig.4 represent scanning behavior score to the left/right side, and every dot in Fig.4 represents each driver's scanning score. Fig.4 indicates diversity of scanning skill among drivers; whereas some drivers were performing good scanning behavior, some scanned right/left side only and some did not perform scanning behavior. As shown in Fig.5 , distribution of "vehicle speed score" corresponds to evaluation criterion (5) also shows similar diversity. These results indicate importance of giving personalized driving lecture according to each driver's skill.

Tab.2 shows results of questionnaire. In the questionnaire, we asked each driver score our system based on following 3 measures with 5 levels (1:worst - 5:best): (A) Do you think the evaluation result is valid? (validness of evaluation result), (B) Can you look at your driving behavior objectively? (understandability), (C) Do you think you should change your driving style safer as the system proposed? (encouragement for improving safe driving motivation). We also show part of free answers from questionnaires (Tab.3). As shown in Tab.2 and Tab.3, most of trained drivers are favorable to our system saying "I feel that I can drive

ISBN: 978-972-8939-66-3 © 2012 IADIS

178

safer by keeping in mind my shortcomings the system pointed out", "I have noticed my shortcomings by objectively looking at my driving behavior".

Table 2. Results of questionnaire (1: worst, 5: best)

average S.D.

(A) Validness of evaluation result 4.79 0.45 (B) Understandability 4.78 0.45 (C) Encouragement for improving safe driving motivation 4.68 0.57

Table 3. Part of free answers from questionnaires

[positive] I think this lecture is very useful because I feel that I can drive safer by keeping in mind my shortcomings the system pointed out.

[positive] Before taking this class, I believed I could have driven safely. But since the system allows me to look at my driving behavior objectively, I can find out my driving behavior is insufficient to avoid risk.

[positive] By using the system, I have noticed that I have a tendency not to scan to the left side so frequently.

[negative] For me, pedal operation behavior displayed on the evaluation result is a little bit difficult to intuitively understand.

Although most drivers are favorable to our system, there are some comments saying "pedal operation behavior in the evaluation result is a little bit difficult to intuitively understand". Therefore, improving intuitive understandability is our future work.

We also interviewed to three driving instructors who are in charge of the demonstrational experiment (Tab.4). As shown in Tab.4, they all evaluate our system as a good support tool for personalized driving lecture saying "thanks to the system, letting the driver understand their shortcomings become easy", "the system is very helpful for me, because I can check each driver's shortcomings before giving lecture. This allows me to customize a lecture according to his/her skill".

Table 4. Part of interview result of the instructors

[positive] In conventional safe driving lecture, one of major problems is how to quantitatively show a driver his/her shortcomings of safe driving skill in easy-understandable way. In contrast, since the system quantitatively evaluates and scores each driver's skill, it is easy to explain and let the driver understand their shortcomings.

[positive] Since the system can promptly show driver's evaluation result, it is possible to check his/her shortcomings before giving a lecture. This is very helpful for me, because I can customize a lecture according to his/her skill.

5. CONCLUSION

In this paper, we proposed an automatic evaluation system of safe driving skill for personalized driving lecture. Our system use small wireless wearable sensors to directly measure drivers' behavior without giving much stress. Whereas conventional EDRs can not detect potentially dangerous situations (e.g. a driver enters a blind intersection with excessive speed without scanning around), our system allows to detect potentially dangerous situations by using the sensors together with GPS and driving instructors' knowledge.

Through experiment in real traffic condition, we have confirmed that our system can point out shortcomings (many of them are classified as potentially dangerous situations) in driving skill with accuracy of over 80%.

As the next step, we have applied our system to a driving school and have performed large-scale demonstrational experiment of personalized safe driving lecture. By analyzing 171 drivers' data measured in demonstrational experiments, we have revealed the diversity of safe driving skill among drivers. This result supports our assumption that giving personalized driving lecture according to each driver's skill is useful to improve traffic safety.

Through interviews to driving instructors who are in charge of demonstrational experiment, we confirmed that our system could be a good support tool for personalized safe driving lecture. We also confirmed that personalized safe driving lecture using our system could encourage drivers’ motivation for safe driving.

Our future work is (1) to improve intuitive understandability of our system and (2) contribute to improve traffic safety through personalized safety driving lecture.


179

ACKNOWLEDGEMENT

This work is supported by the Strategic Information and Communications R&D Promotion Programme (SCOPE) of Ministry of Internal Affairs and Communications, Japan.

REFERENCES

Bishop, C.M., 2006, Pattern Recognition and Machine Learning, Springer. Chapman, P.R. and Underwood, G., 1998, Visual Search of Driving Situations: Danger and Experience, Perception,

Vol.27, No.8, pp.951-964. Falkmer, T. and Gregersen, N.P., 2005, A Comparison of Eye Movement Behavior of Inexperienced and Experienced

Drivers in Real Traffic Environments, Optometry & Vision Science, Vol.82, No.8, pp.732-739. Gabler, H.C., Hinch, J.A. and Steiner, J., 2008, Event Data Recorder: A Decade of Innovation, SAE International. Hyvarinen, A., Karhunen, J., and Oja, E., 2001, Independent Component Analysis, John Wiley and Sons. Takeda, K., et al., 2011, Improving Driving Behavior by Allowing Drivers to Browse Their Own Recorded Driving Data,

Proceedings of 14th International IEEE Conference on Intelligent Transportation Systems, Washington D.C., USA, pp.44-49.

Tokio Marine & Nichido Risk Consulting Co., Ltd., (http://www.tokiorisk.co.jp/consulting/auto loss/) (in Japanese) Traffic bureau. National police agency, 2010, Report of traffic accident in 2010.

ISBN: 978-972-8939-66-3 © 2012 IADIS

180

OPENCAST 2 GO: MOBILE CONNECTIONS TO MULTIMEDIA LEARNING REPOSITORIES

Markus Ketterl1, Leonid Oldenburger2 and Oliver Vornberger3 1Fraunhofer IAIS

Schloß Birlinghoven - 53757 Sankt Augustin, Germany 2Center for Information Management and Virtual Teaching - University of Osnabrück

Heger-Tor-Wall 12, 49074 Osnabrueck, Germany 3Dept. of Computer Science - University of Osnabrück

Albrechtstraße 28, 49069 Osnabrück, Germany

ABSTRACT

The paper presents a mobile frontend for the Opencast audio and video project. Opencast Matterhorn is a community driven collaboration to develop an end-to-end, open source solution that supports the scheduling, capture, management, encoding and delivery of educational audio and video content. The presented application has been developed in the context of the Opencast initiative. It can be used on all major mobile platforms and leverages Opencast Matterhorn’s navigation and analysis features for accessing audio and video based learning material created by universities worldwide. Users can easily switch content repositories, watch multi stream videos, harvest fine grained lecture recordings from running Matterhorn instances or use the information provided by the framework for advanced multimedia navigation possibilities on modern mobile devices. The development and end user experience decisions for the presented application applies lessons learned from previous m-learning activities and survey results from the university with extern and intern students.

KEYWORDS

Flash, Mobile learning, Multimedia, Opencast, Podcast, Web lectures

1. INTRODUCTION

Flexibility and availability are common needs in our modern world. This holds also true for students and learners from different disciplines trying to balance their spare, study and work time. The convergence of data and media content now also available on the go through modern mobile devices, applications and networks enables users to merge their needs regarding time and space. Especially lecture recordings have become a highly demanded student service at today’s universities and the produced contend extends the classical text based e-learning material portfolio. If done right eLectures can be automatically produced for many lectures and seminars without high expenses and they allow a flexible usage that extends the curriculum by simply augmenting a lecture up to marketing purposes including platforms like iTunes U, Facebook or YouTube (Ketterl and Morisse, 2009). Since its formation in 2007, Opencast has become a global community around academic video and its related areas with over 650 members. One of Opencast’s major projects to emerge from the community, Opencast Matterhorn, is a community-driven collaboration to develop an end-to-end, open source solution that supports the scheduling, capture, management, encoding and delivery of educational audio and video content plus develops tools for the engagement of users with that content (Ketterl et al., 2010). The mobile video learning revolution started already a couple of years ago. Accelerated by the success and the simple usage model provided by feeds (RSS, Atom) including audio, video or enhanced learning podcasts from universities and enthusiastic individuals (Ketterl et al., 2006). This new models combined with popular distribution platforms like iTunes and the iPod revolution enabled universities to easily share multimedia based learning content also with mobile users (intern students as well as interested learners from outside the university). Studies conducted in 2007 based on student interviews (Schulze et al., 2010) however indicated that mobile learning support is actually a highly demanded feature request but the real learning process in the end still takes place in the private room at home in front of a


181

laptop or desktop computer. In this previously mentioned work the authors identified and discussed problems why students preferred to use web based e-learning applications instead of the provided video and audio material for their mobile equipment. Two major concerns have been the concentration around Apple products or hardware and the lack of fine-grained navigation features like pinpoint access to information in audio and video based learning material on common handheld devices.

The focal points of this contribution is therefore referring to these identified problems by providing solutions for today’s major mobile platforms and also extend the navigation and search capabilities for multimedia based learning material used on the devices. The paper describes technical implementation aspects that enable mobile learners to find and use fine grained lecture recordings (learning objects) from content repositories provided by different universities worldwide running Opencast Matterhorn instances. The work also gives insight in handling fully searchable and synchronized multiscreen recordings even with fluctuant network connectivity. Section 2 elucidates related work regarding learning and mobility from a technical perspective. Section 3 gives a short introduction about the baseline of the Opencast Matterhorn project and community. Section 4 starts with technical explanations, used frameworks and selected technologies. The final chapter concludes the contribution by comparing the presented system with aims expressed in the introduction and gives insight into planed experiments and surveys.

2. RELATED WORK

Generally, mobile learning (m-learning) is a part of e-learning by using mobile devices. While e-learning was previously characterized by the fact that students worked on stationary computers, mobile learning enables a location and time independent use (Elst et al., 2006), (Boyinbode et al., 2010). Mobile devices are widely distributed, especially among students. There are mobile phones, smartphones, PDAs, tablet PCs and notebooks (Bradley and Holley, 2010), (Wain Yee Au et al., 2011). Today smartphones or tablet devices combine the flexibility of portability and the feature set of desktop computers (Woodill, 2010). Since some time now there are less restrictions regarding bandwidth and network connectivity (flatrate). These smart devices have web-access, either by logging in the local w-lan or a mobile carrier network (UMTS, HSDAP). This enables for example permanent connections to web-based platforms. The most widespread operating systems for todays´ smartphones are Android, iOS, Windows Mobile and Blackberry OS. Typically applications for smartphones can be provided, downloaded and installed via markets (e.g. Android market, iTunes store). Modern mobile devices can also support a better communication with other users. Learning platforms can leverage the new flexibility in interactive learning scenarios or provide content in an easy and engaging new way. Popular examples for m-learning are developments such as the success of the podcast distribution [Ketterl et al., 2010]. In the context of m-learning this procedure has been used to provide lecture recordings, seminars and conferences to the audience and their mobile devices as audio or video files. The distribution is carried out either through own webpages or through the iTunes store (iTunes U) (Boyinbode et al., 2010). Mobility is also getting more and more important for learn management systems (LMS). Quite popular examples are MLE-Moodle and MOMO. Both are extensions for the open source platform Moodle (Sakharkar et al., 2009). The Mobile Learning Engine (MLE)-Moodle offers almost the same functionality as it is offered by the web based e-learning platform. The users have the ability to learn while being on the road by using lecture material or simply keep in touch with other users of the platform. With MOMO teachers have the ability to provide educational contents and examine the results of the student users (Woodill, 2010), (Sakharkar et al., 2009). Mobile learning application can also be found outside the university context. Examples that are available in the online markets are vocabulary training programs, dictionaries or math trainers. Epocrates Mobile CME (Continuing Medical Education) is an application for medical education and training. Doctors can start with this application at any time of CME courses and work through this without having to connect to another system anymore. There are 1 million courses finished through this application by 2008. Another example is C-Shock (Sobri et al., 2010). It is a game-based mobile application that helps international students to handle culture shock. The application was developed at the University of Portsmouth. The application let students adjust to university life in Britain (Brown, 2008), (Sobri et al., 2010). There are many more mobile applications that simplify users' lives but it appears that applications in the category education are very scarce compared to games, communication or entertainment. Similar

ISBN: 978-972-8939-66-3 © 2012 IADIS

182

multimedia based mobile applications as being described in this work have – to the author´s knowledge – not been implemented yet.

3. OPENCAST LEARNING REPOSITORY

The Opencast projects aim is to help to create, manage, archive and distribute audio- and video recordings of lectures in a cost-efficient way. Opencast Matterhorn provides ready to use open source software components and gives hardware recommendation for equipping lecture halls for an automatic content production and re-use. After a successful recording and publication users can find the material for example in their university learn management system, a media portal or watch podcast versions over iTunes U and YouTube. In some scenarios users can choose to watch and focus only the presenter, the presentation slides, or both content streams in parallel. In addition, users may search inside the recordings or add annotations specific to video passages to ask questions or to mark important parts for themselves or others. Opencast Matterhorn creates virtual elements for e-learning to assist the user in the learning process (Rüttger, 2009). Due to the rapid development of mobile devices, it was a highly demanded community feature request to adapt Matterhorn’s learning objects also to mobile needs. In contrast to the previously mentioned lecture podcasts that can be mainly used on Apple devices (iPod family) these new app includes better navigation functionalities (e.g. slide segmentation and search capabilities) that leverage Matterhorn’s underlying media-analysis and segmentation features and make them available for today’s major mobile platforms and devices. Basically the application includes features and navigation possibilities that have been indentified as missing in our previously mentioned student experiments (Schulze et al., 2007). See (Brooks and Ketterl, 2011), (Ketterl, et al., 2010) for further information about the Opencast project, the history, adoption, roadmap and used technology.

4. CONNECTING THE CLIENTS

The following section describes technology decisions and showcases the build in features of the mobile application that can be used to grasp the recorded audio and video based learning material from available Opencast Matterhorn multimedia repositories.

4.1 Development of Mobile Applications

If you want to develop mobile applications today, you will be faced with the problem which of the different mobile platforms should be targeted. Each one is unique and has different requirements from a developer’s perspective. Major differences are especially related to programming languages, development environments or how end users can get and install the provided applications. When comparing the two major operating systems Android and Apple's iOS for example, you realize that Android applications are written in Java or C++. For the development of Apple’s iOS Objective-C is being used. There are also various development environments. Eclipse for Android and Apple´s Xcode for iOS are prominent examples (AT&T Developer Program, 2010), (Shabash et al., 2010). Therefore, the question for a developer is how to continue at this point. Focus on one platform? Take into account the amount of work that one needs to spend on developing for several or even all platforms. Adobe´s Flash as a technology has a heavy standing in today’s Internet world. Pros and cons of this technology are splitting today’s Internet communities. Traditionally this plug in, platform and related products can be used to develop Rich Internet Applications (RIAs) without even thinking about different browsers and their restrictions or pitfalls. Recently Adobe also announced to discontinue their endeavors related to support the mobile version of the Flash plug in for the mobile browsers and to focus on a broader HTML5 support. However Adobe is going to further extend and strengthen the tools and platforms that can be used to create standalone (native) apps for different devices. The latest open source Flex framework (part of the Flash universe) allows to deploy applications for Android or Blackberry devices by using the AIR runtime or in the same manner package and translate the written code to a native iOS application. In other words this allows developing and compilation of one application that can be used


183

on different platforms without further tweaks (Cole and Robison, 2010), (O'Rourke, 2012). Different simulated devices provided by the IDE help to test the running code and to ensure the quality and look and feel on handhelds with different screen ratios or resolutions.

4.1.1 Setting the Application Goals

eLectures in general, the creation processes, distribution possibilities and pedagogic scenarios for web lectures are a major research aspect at the University of Osnabrück since 2003 (M.Ketterl et al., 2010). Since the onset of the first experiments until now many ideas and features have been implemented in tools for the learners to support fully online learning scenarios based on recorded learning material. These applications have become a highly demanded service at the university. The mobile version of the web lecture user interfaces should include a major set of the navigation possibilities of the browser based solution as requested by students. Compared to the podcast versions (audio, video or enhanced podcasts) these applications should capture the whole classroom experience and provide advanced navigation possibilities. Multiscreen video support played back in sync for the talking head and the corresponding screen capture plus an additional optional audience stream will enable students to understand and follow the instructions even on a small display. Pin point access to information and the possibility to search inside the video streams plus a fine grained division of the 1.5h videos based on slide segmentation and chapters help the learners to not get lost or repeat only a certain part. Opencast Matterhorn provides this segmentation and search capabilities via comfortable REST services that can be also used for the mobile development. The available services also allow for episode filtering or access control. In the context of educational audio and video it is very important to consider that most of the recordings are not open for the public (e.g. kept hidden in learn management systems). Reasons for this have been discussed in further work (M.Ketterl et al., 2010).

4.2 Used Technology and Architecture

The Flash platform still includes highly demanded features that have not fully be finalized by the W3C consortium regarding the HTML5 specifications and a possible realization in today’s Internet browsers (e.g. digital rights management, cross platform video standards without patent restrictions, flexible and reliable video streaming, multi-stream support, webcam access). Currently it is also not clear if users prefer stand alone (native) or web applications on their mobile devices. Cross platform multimedia support is a major domain of the platform. Adobe´s Flex framework can be used to target the Flash runtime by writing code once in Action Script 3. The latest version of the Flex framework (4.6) in combination with the Eclipse IDE (device and platform simulation) can be used to deploy applications to the desktop, web or to mobile devices (Moock, 2007), (Widjaja, 2008). The Flex framework contains a collection of Action Script classes, which simplify the development process by providing a reusable set of libraries and classes. These class libraries contain visual components, data containers, managers, data services etc. (Rüttger, 2009), (Widjaja, 2008). In the latest version the framework includes also components for mobile development. Next to Action Script, which is meant especially for the logic of an application, there is the XML-based layout language MXML, which simplifies the design and layout of user interfaces and interaction. The class libraries can be accessed via Action Script or with the declarative MXML approach which simplifies the access to the same classes. Developers will be more familiar with this technology, if they have knowledge about XML and HTML (Widjaja, 2008). The applications logic and structure follows the Model View Approach (MVC pattern) to keep the source code extensible and flexible. The application package has been separated in views, business logic and events. Figure 1 depicts the application architecture.

ISBN: 978-972-8939-66-3 © 2012 IADIS

184

Thapplichandlweb sview classeto get

Thformato selextern(Bellainstanthe X“videlayoutThis informperfor

DuBasebe chindiviextendThe Cpositithe ele

Thphysicreturncustom

he business clcation controlller", "rendererservices "searcrepresentation

es. The data ht the data fromhe "search" sat has been chlect elements nal XPath clahsène, 2004)nce. This handXML object. O

oLoadedEvents (new sinceallows displa

mation be reprmance reasonue to visibiliteRenderer canged after a idual elementded class shouCreateChilon of each eleements are filhe ItemRendecs). Now the

ned by the "sem itemRender

lasses represenler. In additionr" and "core"ch" and “annns. The packahandler sends m the recordedservice providhosen because

(Elst, et al., lass library "). Before a reqdler waits for Once the dat

nt” and the da Flex 4.5.1), waying informapresented e.gns, one shouldty problems dclass should iclick. In add

ts in each itemuld have the fldren geneement is definled with value

erer can then ItemRenderer

earch" servicerer.

Figur

nt the modelsn to the mode

". The data hanotation". The

age of the corea request to th

d lectures. des informatioe the Flex fram

2006). In or"XPath-AS3"quest is sent a response an

a is availableata is being rwhich are poation from thg. as a list od implement cduring the useimplement thedition, the Datm, you need functions crerates new elened in the upes (Cole and Rbe used in th

r of this list ne). The code s

re 1. System Ar

s, the logic of el classes in "bndler classes wrenderer clas

e classes incluhe service end

on about the mework supporder to proceis necessary

to the endpoind when the ee as an XMLrendered. Thesitioned by ushe XML objeof available ustom ItemRe

er interaction e interface Iteta Object is into implemen

eateChildrements (like tpdateDisplRobison, 2010he "List". Th

needs to be bosnipped in Fig

Figure 2. Li

rchitecture

the applicatiobusiness", therwill communises will accepudes style-cladpoint of a ru

recordings inorts XPath expess calculationy. For instanint, an event event triggeri

L object, the e view has dising MXMLect for examvideos, an I

enderers in plawhile clicking

emRenderer. Fnitialized in thnt a subclassren, updattextfield) and ayList func

0). his element suound to the dagure 2 depicts

ist

on. The packare are three oticate with the pt data and preasses, which aunning Openca

n JSON or XMpressions in ans or complence, this allolistener is addng calls a calview is inforfferent mobilin the applica

mple as simplItemRenderer ain Action Scrg on individuFor example, he class. Nowof the BaseteDisplayL

adds them toction. With th

upports touchata provider (t the binding o

age "events" cther sub-packaOpencast Ma

esent them to are used by thast Matterhorn

ML format. Ta simple XMLx XML strucws counting ded to the datllback functiormed by the e enabled con

ation (O'Rourke labels. Shois necessary

ript. ual items in th

the backgrouw in order to Renderer cList and seo the elementhe function se

h scrolling (anthe XML thatof a dataProvi

contain the ages "data atterhorn’s the visual e renderer

rn instance

The XML L structure ctures, the

elements ta handler

on, it takes controller ntrols and ke, 2012). ould more y. Due to

he list, the und should define the class. The etValue. t list. The etValue

nd gesture t has been ider to the


185

Fimobilthat th

If detailThe o"pushallowa viewbasedpresenbehavallowdevicethe semobilusers protocthe laprovidflip fuparallthe us

gure 3 presenle applicationhe screenshot

a user selectsed informatio

object, which ih view (video)s to add a new

w from the nad Opencast Mnted slides). vior in the mos implementines. It enables equential and le version. If tneed to down

cols prevent uast minutes ofding the Paraunction of molel in sync). Fser to switch fr

nts the previo. A list of avais created from

s a recording on about the seis located at th" or "popVieww view as paraavigation stack

Matterhorn verThis sources obile version ng a flexible mto use RTMPparallel play

two or more vnload huge a

users from dowf a lecture). OallelElem

obile devices igure 4 depict

from one view

ously mentionailable recordm the IDEs de

Fig

from the listelected episodhe top of the n

w()" that allowameter which k can be deletrsion users ca

can be playthe Open So

media player tP or HTTP (liback of videovideo sources amount of vidwnloading fraOSMF helps ment class (A

and the three ts the present

w to the other (

Fi

ned data renddings based onevice simulati

gure 3. Matterho

(figure 3 left de. The naviganavigation sta

w the user to nis then added

ed (Cole andan choose betyed simultaneource Media Fto playback anive) streamingo content (Adneed to be pl

deo data fragmagments that ato synchroniz

Adobe, 2010).kinds of videer and presen(only presente

igure 4. Video-

ering (itemRen the users seion.

orn2GO

hand side), a ation is controack is the actunavigate betwed to the applicRobison, 201

tween differeneously (KetterFramework (Ond sync high-qg, progressivedobe, 2010). Blayed in parallments which nare not imporze video sourThere are six

eo representatntation video ser, presentation

-Views

enderer) in thearch query is

new view wiolled through ual view. Thereen different scations view st0), (O'Rourkent video sourrl et al., 201OSMF) is beiquality media e download, aBandwidth islel it is mandaneed to be syrtant for them rces (streaminx different vietions (presentesync view. Thn or both in p

he user interfas being presen

ill be loaded wa stack of view

re are functionscreens. "pushtack. With "pe, 2012). In thrces (e.g. pres0). To imple

ing used as bobjects even

also supports a major factatory to underynchronized.

(e.g. only intng and progreews possible der, presentatio

he icons (buttoarallel).

ace of the nted. Note

with more w objects.

ns, such as h view(...)" opView()"

he browser senter and ement this baseline. It

on mobile DRM and tor for the rstand that Streaming terested in essive) by due to the on or both ons) allow

ISBN: 978-972-8939-66-3 © 2012 IADIS

186

Athand right conten

Thapplicconten

5. F

The pOpencmarkeinformlike oBesidare mchoosinformpart oallow commfeaturvieweExperquesti

ACK

The wat the contrisource

t each time of side the applihand side (fignt repository b

his means thacation customnt search. FUTURE

presented appcast´s video aets are promimation regardoperating systdes the hardwa

major differencse the menu mation could of the recorded

users to domunication cores currently bed informatioriments and sions regarding

KNOWLE

work has beenUniversity of

ibutions and ee. Matterhorn

f the playback ications capabgure 6 endpoby providing t

Fi

at learners canmization or com

WORK A

plication "Maand audio leasing and mor

ding the new mtems, models,are informatioces between th

item "settingbe used for dd lecture was vownload the sts. This imp

being discusseon on Facebosurveys aboug features rich

EDGEMEN

n done during f Osnabrück. Tendurance. Th2Go is part of

user commenbility to add uints) presentsthe path to ano

igure 5. Comme

n grasp and umpilation. The

AND CONC

atterhorn2GO"arning contentre users will im-learning be, SDK versionon, it would bhe learning begs", if they

data mining anviewed the m

multimedia plies that the ed by the comook and bookut the applicahness and usag

NT

a web technoThe authors w

he application f the Opencast

nts or further qser-generated

s a view that other Matterh

ents

use recordingsese repositori

CLUSION

" should contt. The growinincrease the tehavior of stun, resolution

be interesting ehaviors of wewant to divu

nd recommenost (Ketterl etcontent to trecordings a

mmunity like ukmarking ofation usage wge preferences

ology seminarwould also tha

and its sourcet initiative.

questions can comments orallows to eas

horn instance.

Figure 6. End

s from other Ues can (if nee

N

tinue alongsidng download ntotal usage thudents and the

and CPU areto know, whe

eb or mobile uulge feedback

ndations. For et al., 2010). Atheir devices

are open for upload video f

already watcwill be condus.

r that was partank Philipp Bae code are fre

be posted. Figr questions to sily switch th

dpoints

Universities weded) also be

de the web bnumbers of th

hat allows coleir expectatione being collecere the users users. The stuk about themexample teach

A further impos to prevent the public. Ffrom mobile dched lectureucted to answ

t of a regular auer and Karinee to download

gure 5 shows the media ob

he Opencast M

without time cincluded in a

based engage he applicationllecting more ns. Currently ction with thicome from an

udents should mselves. The hers could knrtant aspect mhigh mobile

Finally, there devices, sharefor a quick

wer the initia

computer scina Meyer for d and availab

on the left bjects. The Matterhorn

consuming a federated

tools for n over the statistical only data

is version. nd if there be able to collected

now which might be to e Internet are other

e/comment recovery.

ally asked

ence class their code le as open


187

REFERENCES

Adobe, 2010, Open Source Media Framework, Bereitstellung effektiv verwertbarer Videos in hoher Qualität, 2010 Adobe Systems Incorporated, printed in Germany, pp. 1-2.

AT&T Developer Program, 2010, Developing Applications for Android, White Paper 1.0, Document Number Revision 0.6, Revision Date 04/08/2010, AT&T Knowledge Ventures, pp. 10-15.

Bellahsène, Z., 2004. Database and XML Technologies: Second International XML Database Symposium, Xsym 2004 Toronto, Canada, August 2004 Proceedings, Springer Berlin Heidelberg New York, printed in Germany.

Boyinbode, O., Bagula, A. and Ngambi, D., 2010. An Opencast Mobile learning Framework for Enhancing Learning in Higher Education Department of Computer Science and Centre for Educational Technology, University of Cape Town, South Africa, pp. 11-15.

Bradley, C. and Holley, D., 2010. How students in Higher Education use their mobile phones for learning Learning Technology Research Institute, London Metropolitan Business School, London Metropolitan University, pp. 2-

5. Brooks, C. and Ketterl, M., 2011. Opencast Matterhorn 1.1: Reaching New Heights. ACM Multimedia 2011, Scottsdale,

Arizona, USA, November 28 - December 01, 2011 to appear Brown ,J., 2008. 10 Quick Mobile Learning Examples, MASIE Learning Fellow. Brown, M. and Diaz, V., 2010. Mobile Learning: Context and Prospects, A Report on the ELI Focus Session

EDUCAUSE Learning Initiative, May 2010, pp. 5-7. Cole, A. and Robison, E., 2010. Learning Flex 4: Getting Up to Speed with Rich Internet Application Design and

Development, O'Reilly Media. Elst, P., Yard, T., Jacobs, S. and Drol, W., 2006. Object-oriented ActionScript for Flash 8, Printed and bound in the

United States of America. Ketterl, M., Schulte, O. and Hochman, A., 2010. Opencast Matterhorn: A community-driven Open Source Software

project for producing, managing, and distributing academic video, International Journal of Interactive Technology and Smart Education, Emerald Group Publishing Limited, Vol. 7 Issue: 3, pp.168-180.

Ketterl, M. and Morisse, K., 2009. User Generated Web Lecture Snippets to Support a Blended Learning Approach World Conference on Educational Multimedia, Hypermedia & Telecommunications (ED-Media 2009), Honolulu, HI, USA, 22-26. Juni 2009, pp. 2886-2893.

Ketterl, M., Mertens, R. and Morisse, K., 2006. Alternative content distribution channels for mobile devices. microlearning 2006 International Conference on Micromedia & e-learning 2.0: Getting the Big Picture, Innsbruck, Österreich, 8.-9. Juni 2006. pp. 119-130.

Ketterl, M., Metens, R. and Vornberger, O., 2010. Bringing Web 2.0 to Web Lectures, International Journal of Interactive Technology and Smart Education (ITSE); 6(2), Emerald Group Publishing Limited, 2010, pp. 82-96.

Moock, C., 2007. Essential ActionScript 3.0, O’Reilly Media, August 2007. O'Rourke, J., 2012, Flash Mobile Application Development for Dummies, by John Willey & Sons, Inc. Hoboken, New

Jersey. Rüttger, M., 2009. Adobe Flex 3, mitp-Verlag. Sakharkar, H., Iyer, S. and Baru, M., 2009. MOLE: An Extension to MLE Moodle, Department of Computer Science and

Engineering Indian Institute of Technology Bombay, pp. 1-2. Shabash, B., Hamarneh, G., Zhi Feng Huang, and Luis, I., 2010. ITK on the iOS, Release 1.00, School of Computing

Science, Simon Fraser University, BC, Canada, The Insight Group, August 31, 2010, pp. 1-2. Schulze, L., Ketterl, M., Hamborg, K.-C. and Gruber, C., 2007. Gibt es mobiles Lernen mit Podcasts? - Wie

Vorlesungsaufzeichungen genutzt werden. 5. e-Learning Fachtagung Informatik, Siegen, 17.-20. September 2007. pp. 233-244.

Sobri bin Hashim, A., Fatimah, W., Ahmad, W., and Ahmad, R., 2010. Mobile Learning Implementation: Students’ Perceptions in UTP, World Academy of Science, Engineering and Technology 62 2010, pp. 817 – 818.

Wain Yee Au K., Fan Zhou Y., Huang Z., Gill P. and Lie D., 2011. Short Paper: A Look at SmartPhone Permission Models, Dept. of Electrical and Computer Engineering, University of Toronto, Canada, pp. 64–65.

Widjaja S., 2008. Rich Internet Applications mit Adobe Flex 3, Carl Hanser Verlag München 2008. Woodill G., 2010. The Mobile Learning Edge: Tools and Technologies for Developing Your Teams, The McGraw-Hill

Companies.

ISBN: 978-972-8939-66-3 © 2012 IADIS

188

BROWSER-BASED MOBILE CLICKERS: IMPLEMENTATION AND CHALLENGES

Monika Andergassen, Victor Guerra, Karl Ledermüller and Gustaf Neumann WU - Vienna University of Economics and Business

ABSTRACT

Didactic strategies in the classroom are influenced by factors like class size, prior class knowledge and level of class attention. In large classes, student activation has to follow different didactic approaches in order to obtain ad-hoc feedback from individual students than in small classes. One approach to increase class attention are classroom voting tools (known from quiz show formats for real-time audience feedback) that provide the teacher with feedback about the students’ prior knowledge and learning progress. Additionally, feedback and attention increasing systems seem to be essential within spatially distributed classes (following the lecturer via web streaming), due to the fact that two-way communication is limited in these cases. Supporting the demanded didactic functions, we developed a browser-based mobile clicker application within Learn@WU, the large-scale online learning environment of the WU (Vienna University of Economics and Business). We introduced and evaluated the application in lectures of the introductory study period. The integration into the established online environment shall support teacher acceptance and usability.

KEYWORDS

Mobile learning, classroom response system, activation, student feedback, mobile clicker.

1. INTRODUCTION

Since the first decade of the 21st century, universities in Austria have been facing the challenge of stagnant budgets, paired with an increasing number of freshmen students each academic year (OECD, 2011). University access is mostly free in Austria, meaning that in most cases no tuition has to be paid by students, and every student with a high school degree can start to study without having to pass any selection criteria in most faculties.

This situation has led to the demand to offer economically effective studies. E-learning facilities have been gaining increasing importance in order to support the learners in the learning process (Cross, 2004). Furthermore, especially in the first year of study, most lectures are held for large audiences. Universities have started to introduce live broadcasting to multiple lecture halls, and to provide live streaming on the Internet and lecture recording to be able to serve the students (Lorenz, 2011). However, one drawback is that feedback from a high number of (remote) students is hard to obtain without technical support.

Interactive elements in the classroom have the potential for critical reflections about newly learned topics (Draper et al., 2002). One approach to increase class attention are classroom voting tools (also known as clicker systems, classroom performance systems, audience/classroom response system, personal response system and other synonyms). Clicker systems are mostly known for their applications in quiz show formats to obtain real-time audience feedback. Applications in an educational environment were introduced by Harden et al. (1968) and Dunn (1969) in 1968 with machine readable paper based cards (see also Elliot, 2003). Draper et al. (2002) define the following didactic reasons for using clicker systems:

1. Formative feedback on learning within a class (i.e. within a contact period) 2. Formative feedback to the teacher on the teaching (i.e. “course feedback”) 3. Peer assessment which can be done on the spot 4. Community mutual awareness building 5. Experiments using human responses 6. Initiation of discussions using the equipment


189

Furthermore, the usage of clicker systems in the classroom might enhance the motivation of the students (Deci et al., 1996; Perry et al., 2002). It is well known that motivation plays an important role in the learning process (Pintrich, 2003). However, as shall be discussed in the next section, conventional clicker systems bear some drawbacks, particularly when they are used in large classes.

At the same time, it is noted that in recent years, market penetration of mobile devices (i.e. smart-phones, tablets, netbooks or laptops) has strongly increased. Ebner et al. (2008) found that already in 2008, 80% of students at the University of Technology Graz (Austria) possessed a laptop. The Mobile Marketing Association Austria (2011) reports that in 2011, 56% of the Austrian population possess a smart-phone, a plus of 25% regarding 2010. Furthermore, 10% of the population report to use a tablet computer. These numbers point to a wide distribution of mobile devices and to an increasing dissemination of such devices.

2. PROBLEM STATEMENT AND PROPOSED SOLUTION

Conventional technical solutions for clicker systems comprise radio or infrared based transmitters and hand held receivers. However, these solutions require a specific hardware infrastructure and cannot be used for spatially distributed classes. Additionally, many radio transmitting products contradict the Austrian law due to the regulation of used radio frequencies. Furthermore, universities with large cohorts of students especially within spatially distributed classes might not be able to provide the demanded infrastructure.

Therefore, a new solution is proposed and presented in this paper. It is supposed to incorporate the advantages of a clicker system, a browser-based e-learning environment and a mobile device. Such a browser-based mobile clicker system, i.e. a system which can be operated platform-independently with mobile devices, is supposed to fulfill the didactic demand for interaction with remote students, and therefore adding a seventh didactic reason to Draper et al.’s list for using clicker systems:

7. Formative interaction with spatially distributed classes in live lectures We are developing this browser-based, mobile clicker system to didactically support the teaching in large

local as well as spatially distributed classes as follows: • two-way and spatially distributed communication • structured and unstructured, open questions • ad-hoc and predefined questions from the teacher • combination of students’ answers with the grading scheme • feedback to the lecturer about the crucial didactic parts of his lecture • evaluation of the response data for further learning behavior studies, and • easy deployment without the need of purchasing and distributing specific clicker devices. Furthermore, the development of a browser-based, mobile clicker system is based on the following

assumptions: Firstly, a browser-based mobile clicker system enables a teacher to communicate with a large audience, in

a location-independent way. This potential can be used both for large classes and for live streamed lectures within spatially distributed classrooms. By using their mobile devices, spatially distributed students can give instant feedback to polls triggered by the teacher.

Secondly, a browser-based mobile clicker system is well suited for integration into existing e-learning platforms. The setup of the clicker polls as well as the analysis of the poll results can be managed seamlessly through the e-learning platform. The results can be used for further purposes like grading and analysis of the learner activation. By integrating the system into an existing e-learning platform, the environment is familiar to the lecturer and the students, and therefore the acceptance and usability of the mobile clicker solution is believed to be high.

Finally, a central goal of the project is to develop a platform-independent tool which can be operated via any Internet-enabled device. No costs for handheld receivers need to be calculated due to the high penetration rate of student owned mobile devices.

ISBN: 978-972-8939-66-3 © 2012 IADIS

190

3. IMPLEMENTATION

The technical implementation was realized in the e-learning environment Learn@WU. The e-learning environment is institutionally offered by the WU (Vienna University of Economics and Business) to enable teachers and students to collaborate online. The platform is accessed via a web browser, from within or outside the university premises. One of the characteristics of the platform is that practically all page views are generated dynamically. This fact allows us to personalize every page and to adjust its presentation according to the client devices. Therefore, it is straightforward to provide tailored interfaces for users navigating with, e.g., mobile devices. For the mobile façade of the clicker application, we decided to use the JavaScript library jQuery Mobile (Reid, 2011).

Figure 1. Item Management (left), Survey Management (middle) and Test Item Answering (right) Workflows

The clicker application was developed over the XoWiki Content Flow (Neumann, 2008) package, which is an extension of the XoWiki Framework (Neumann, 2007). The XoWiki Framework is a wiki based content management system providing revisioning over structured and unstructured content fields. This way XoWiki is capable to provide a text based interface for wiki-like applications as well as a form based interface of structured content (or a mixture of both). The Content Flow package extends XoWiki by managing state changes of content objects via a set of transitions. The basic mechanism follows the State Design Pattern (Gamma et al., 1994). Typically, in different states, different content is presented to the user. Furthermore, in every state, it is well possible to present different content to different kinds of users. Per state, the valid transitions are offered to the user via potentially multiple submit buttons. Using this mechanism, one can define various kinds of workflows, like, for instance, for filling in questionnaires with multiple forms, for providing various kinds of individual feedback and for defining online exercises or exams.

In our project, we defined three workflows based on XoWiki Content flow: • Item management workflow: create, publish and unpublish test items (questions). • Survey management workflow: create, publish and unpublish surveys (polls). • Test item answering workflow: collect answers from the survey participants. Figure 1 shows the workflows with their state transitions. The graph on the left shows the possible state

transitions of the item management workflow, the graph in the middle shows the state transitions of the survey management workflow, and the graph on the right shows the state transitions of the test item answering workflow. The first two workflows define the interactions of the lecturer, the third one is for the participants. From a user’s perspective, a lecturer has to perform two tasks to run a clicker poll.

A) Definition of test items A1. The teacher can select a type of question from a predefined set of templates via a web interface. A2. In a second step, the teacher can fill in a title, the question and prompt, and the text for the

alternatives. It was a design goal that the definition and editing of test items should be achieved without technical knowledge and without any kind of external tools. The typical question types for mobile devices are quite simple and return only responses to a single variable. Therefore, this is well suited for summarizing the results later with a single tool.


191

B) Publishing of the poll B1. The teacher selects a question from the defined test items and publishes it as a poll to the members of

the class: in this state the students of the class are informed about the pending poll via a highlighted button in the banner of every page. By clicking on a single button, the students can open the poll (Figure 2). Every student can provide only a single response to a poll.

B2. To unpublish the poll, the teacher might close the poll at any time. Once the poll is unpublished, the students can no longer provide answers. In this state the poll is presented to the teacher with a pie chart diagram in the browser (Figure 3).

4. PILOT STUDY

A pilot study was undertaken to test the mobile clicker application. The pilot study was realized in the “Introduction to Finance” course at the WU. A total of 174 students was subscribed to this course which is held parallel to seven other “Introduction to Finance” courses at the WU. As with all courses at the WU, the course is supported by the online learning environment Learn@WU, where several applications like multiple choice questions, forums, automated and home exercises with random numbers, sample tests, a glossary and additional download material, are implemented.

The lecture of the pilot study was attended by 118 students. The pilot study was conducted in one lecture hall without broadcasting, and thus no remote students took part in this lecture. The students were informed in advance by email about the study and they were invited to bring their mobile devices to the lecture. The pilot study consisted of 2 clicker polls which were published consecutively during the lecture. The first clicker poll was a yes/no poll to check the technical functionality of the system (“Are you able to answer the question via the clicker poll?”), whereas the second clicker poll contained a five-category single-choice question which was subject related to the Introduction-to-Finance course. It gave the lecturer and the students feedback about their learning progress.

To investigate how the clicker application worked in the class context, a mixed methods design (Creswell & Plano Clark, 2006) was applied in the pilot study, consisting of qualitative and quantitative data collection. To gain qualitative insights, participant observation was carried out during the lecture. According to Jorgensen (1989), participant observation is particularly appropriate, among others, for explorative studies and for studies where participants can be observed in everyday life settings. A group of 5 researchers was in the lecture hall to observe the students’ behavior and to conduct an observation protocol. To gain quantitative insights, a paper-based questionnaire was handed out to the students after the lecture. The questionnaire comprised questions about the mobile devices used as well as the usability and satisfaction with the clicker application.

Figure 2. Mobile e-learning interface showing a pending poll (left) and clicker poll interface (right).

ISBN: 978-972-8939-66-3 © 2012 IADIS

192

Figure 3. Clicker poll result pie chart in web based e-learning environment.

5. RESULTS

5.1 Results of Participant Observation

The first clicker poll consisted of a question to check whether the students were able to use the clicker application. The poll was open for submission for five minutes. In this period it was answered by 28 students (24% of participants), where 19 students responded within the first 2 minutes. The second clicker poll comprised a question related to the lecture content. It was open for submission for about 10 minutes, and 42 students (36%) answered.

It was observed that some students had problems connecting to the Internet or loading the website (this experiment was the first time the students had contact with the system). Furthermore, it was observed that some students (n=8) continued clicking on their smart-phones after the poll was over. Although no detailed information was available about what exactly the students were doing, the observers noted that on most smart-phones, Facebook was opened. However, about 30 minutes later, no student was using his smart-phone any more.

In the second half of the lecture, and thus after the clicker polls, a higher amount of student questions regarding the lecture content than usual was observed. This might be an indication that a clicker poll plays an activating role in a lecture. However, more data need to be collected to be able to confirm this observation.

5.2 Results of Questionnaire

The paper questionnaire was completed by 76 students (64% of the students in the lecture hall). Participating in the questionnaire was voluntary; 36% of students did not fill in the questionnaire. One reason for this might be that this student cohort had another lecture subsequent to the test lecture and might therefore have had to leave quickly. Thus, future test settings will be planned in a way that the questionnaire is distributed earlier in the lecture.


193

Figure 4. Questionnaire result about mobile device usage for the clicker polls (left side) and ease of use of clicker application (right side); n=31

Figure 5. Questionnaire result about students’ wish to use clicker application again (n=44)

The sample contained 36 male students, 35 female students and 3 students who did not specify their gender. Student’s age was between 19 and 26 years. Among the respondents, 31 students reported to have participated in the clicker poll, 45 students did not. Major hindrances included the website loading too slowly (n=8), the Internet connection not being available or not working (n=12), and not being equipped with a mobile device (n=14). Only a small number of students (n=3) reported to have difficulties with the user interface.

A broad variety of mobile devices was used to participate in the clicker poll, as is shown in Figure 4, and over 90% of the devices were smart-phones. Those students who did participate in the questionnaire reported that they found the clicker application excellent (n=16) or good (n=10) to use. Only 5 students found the application to be not so nice or difficult to use. Figure 4 shows these results.

Although only 31 respondents of the questionnaire participated in the clicker poll, 37 students reported that they would like to use the clicker application again in a lecture, as is shown in Figure 5. Only 5 respondents were unsure about re-using it, and 2 students would not like to use the clicker application again. All the other students (non-participants to the clicker poll) did not answer this question.

6. DISCUSSION AND FIRST LESSONS LEARNED

According to the demand for live communication with large audiences, mobile devices show high potential to reach the students in live lectures.

The integration of a mobile clicker system into the existing e-learning platform regarding the initial assumptions worked generally well in the test setting. With the e-learning platform Learn@WU, an example

ISBN: 978-972-8939-66-3 © 2012 IADIS

194

was shown about a browser-based mobile clicker system being integrated into an existing e-learning platform. The lecturer was able to set up the clicker poll and present the poll results through the browser interface. However, it was noted in the pilot study that, although the lecturer was familiar with the e-learning platform, he had to carefully think about how to publish and unpublish the clicker poll, and how to show the poll results to the audience. Thus, it can be assumed that some adaptation time is needed in order to get familiar with the application.

The results of the pilot study support our assumption that the usage of an e-learning environment which is familiar to the students helps them to navigate quite easily through the clicker poll and to answer the stated question with the help of their mobile device. Indeed, most students reported to find their way easily through the application (see Figure 4)

The results of the pilot study indicate that the initial goal to provide a platform-independent clicker solution can be fulfilled. Figure 4 shows that the students accessed the clicker application with a variety of devices and operating systems. While platform-independence is a positive aspect, improvement is needed to reach more students through the clicker application in the future. Although it can be assumed that most students possess laptops, as Ebner et al. (2008) report, many seem not to bring their devices to the lectures. At the same time, although the penetration of smart-phones is strongly increasing in Austria, a significant percentage of students does not possess a smart-phone yet. One of the next steps in the mobile clicker project will therefore be to motivate more students to bring their alternative mobile devices, i.e. laptops, netbooks or tablets, to the lectures. Additionally, the smart-phone penetration rate should be monitored over the next semesters.

Building up on the implementation and the findings of the pilot study, some points for further research and next steps are suggested. Firstly, usability tests with teachers and students should be conducted to optimize the user interfaces. Although learning advances within classical clicker environments are highly investigated, usability issues regarding clickers are discussed less intensively in academia. However, usability is crucial within mobile and large lecture environments, because both the lecturer and the student attention on technical issues have to be minimized.

Secondly, the potential of gaining student feedback in a device independent way and from remote students should be investigated in the next step. A pretest of the mobile clicker application in a spatially distributed class should be conducted.

Thirdly, it should be investigated to what extent different question types can be handled easily in a mobile clicker application. While a conventional clicker system is able to handle only, for instance, up to four single-choice answers, a web based mobile clicker system could support various kinds of interaction types.

7. CONCLUSION

This paper described the implementation and pilot study of a mobile clicker system which is web based and accessible through the web with mobile devices. The advantages of such an approach were outlined. These include didactic advantages such as standardized communication with (or feedback from) spatially distributed classes as well as student activation and student performance testing like in traditional clicker systems. Furthermore, technical or usability advantages such as ubiquitous availability and platform independence of a web based system were discussed.

The implementation of the browser-based mobile clicker application was developed in the e-learning platform Learn@WU. Focus was laid on providing teachers with web-based interfaces for the management of questions and polls, and on providing students with interfaces suitable for mobile devices, specifically on the process that allows students to submit their answers to the published polls.

Additionally, we conducted a pilot study in a lecture with 118 students. The introduction of 2 clicker polls was accompanied by participant observation and a survey. The findings indicate that the mobile clicker poll is accessed with a variety of devices and therefore the promise of platform-independence can be held, and that through the application being based in the existing e-learning platform, the students quickly find their way through the poll. Although more systematic research would be needed, the participant observation in the pilot study indicated that students pose more content-related questions to the lecturer after a clicker poll.

However, it was also found that many students either do not posses or do not use their mobile devices in the lectures. The next steps therefore will address the motivation of more students to bring their mobile


195

devices to the lecture. Nevertheless, the browser-based mobile clicker system is believed to be a valuable tool for activating students in large lecture halls.

REFERENCES

Creswell, J.W., Plano Clark, V.L. 2006. Designing and Conducting Mixed Methods Research. SAGE. Cross, J., 2004. An informal history of eLearning. On the Horizon, 12 (3), 103 - 110. Deci, E. L. et al., 1996. Need satisfaction and the self-regulation of learning. Learning and Individual Differences, 8 (3),

165–183. Draper, S. et al., 2002. Electronically Enhanced Classroom Interaction. Australian Journal of Educational Technology,

18 (1), 13-23. Dunn, W., 1969. Programmed Learning News, Feedback Devices in University Lectures. New University, 3 (4), 21–22. Ebner, M. et al., 2008. Has the Net-Generation Arrived at the University? -oder der Student von Heute, ein Digital

Native? In: Zauchner, S., Baumgartner, P., Blaschitz. E., Weissenbäck, A. (eds): Offener Bildungsraum Hochschule. Medien in der Wissenschaft (48), Waxmann, 113.123.

Gamma, E. et al., 1994. Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley. Harden, R. et al., 1968. An Audio-Visual Technique for Medical Teaching. Journal of Medical and Biological

Illustration, 18 (1), 29–32. Jorgensen, D.L., 1989. Participant Observation. A Methodology for Human Studies. Applied Social Research Methods

Series (15). SAGE, Thousand Oaks. Lorenz, A., 2011. Universities on Air. FNMA Working Group ‘Streaming Technology and Learning Innovation’. 14th

International Conference on Interactive Collaborative Learning, Piestany, Slovakia, 656-665. Mobile Marketing Association Austria (2011) Mobile Communications Report 2011. Neumann, G., 2007. XoWiki – towards a generic tool for web 2.0 applications and social software. OpenACS and .LRN

Spring Conference, International Conference and Workshops on Community Based Environments, Vienna, Austria. Neumann, G., 2008. XoWiki Content Flow – From a Wiki to a Simple Workflow System? Proceedings of 7th OpenACS /

DotLRN Conference, Valencia, Spain. OECD, 2011. Education at a Glance 2011: OECD Indicators. OECD Publishing. Perry, N. E. et al., 2002. Investigating teacher–student interactions that foster self-regulated learning. Educational

Psychologist, 37 (1), 5–15. Pintrich, P.R., 2003. A motivational science perspective on the role of student motivation in learning and teaching

contexts. Journal of Educational Psychology, 95 (4), 667-668. Reid, J., 2011. jQuery Mobile. O’Reilly Media, Sebastopol.

ISBN: 978-972-8939-66-3 © 2012 IADIS

196

A QUICK PROTOTYPING FRAMEWORK FOR ADAPTIVE SERIOUS GAMES WITH 2D PHYSICS ON MOBILE

TOUCH DEVICES

Juan Haladjian, Damir Ismailović, Barbara Köhler and Bernd Brügge Technische Universität München, Munich, Germany

ABSTRACT

In recent years mobile devices like the iPhone and Android became even more powerful than netbooks. This computational power can be used for complex simulations and games that were until now limited to desktop computers. We propose adaptive games with 2D physics on mobile devices that can be used for learning purposes. We argue that even young children can understand and apply physical laws in such games. Abstract physical concepts can be made more tangible as one can directly touch objects on the screen. Furthermore, digital games can provide an individualized learning and playing experience for each child with the integrated Adaptivity. In this work we show the problems that arise when developing serious games featuring adaptivity and physics and we propose a solution to them: a quick prototyping framework called TangoPhysics. TangoPhysics suggests a new way of prototyping mobile games: The prototypes are constructed directly on the mobile device, and can be tested at any moment. We show that the development time of a serious game can be dramatically reduced with our framework. At the same time, the framework allows not only programmers, but also teachers and in the long run maybe even students to develop their own games.

KEYWORDS

Serious-Games, Physics, Prototyping, Adaptivity, Mobile

1. INTRODUCTION

Since the development of iPhone in 2007, mobile technology is the main technological power. More than one million applications are counted in the Apple App Store and Google’s Android Market. Apple counts over 100.000 game and entertainment titles. Mobile technology represents a big and quickly growing potential market for serious games. Even more interesting to the area of mobile learning is the fact that even young children are able to operate mobile touch devices (Dignan, 2011).

Serious games are games that fulfill other purposes than mere joy. These purposes range from teaching concepts to changing a person’s behavior. The idea of serious games is not new and was already introduced in 1968. Since then, several researchers (Gee 2008, Prensky 2008) discussed how the experience delivered by games could contribute to learning. A big advantage of computer serious games is the individualized learning experience tailored to a person’s strengths and weaknesses. Ideally such games can speed up the learning process and avoid the development of false mental models about the learning content. Furthermore, keeping the learning speed in the ideal area for the current learner helps to keep up motivation, as there is no discouragement through tasks that are too hard or boredom due to too simple tasks.

Another benefit of serious games is their ability to teach the content in a more interactive way than other instructional media. This helps to make abstract concepts more tangible as the learner can visualize them and even interact directly with them on the device, rather than simply reading or hearing about them. For example explaining someone the effect gravity has on earth and all other planets in our solar system on a black board using drawings and formulas might not give students as much insight. If they are on the other hand given a simulation where they can manipulate the size and density of each of the planets and observe the results of their changes, the experience becomes more memorable and tangible. Furthermore, being able to change the world with a fingertip motivates players by making them feel empowered.

Development of adaptive games that use physics is extremely hard for programmers and basically impossible for instructors. Implementation of adaptivity requires not only deep programming knowledge, but


197

also understanding of learning theories. This knowledge is often not present in one person. Bigger teams are required, which is often not affordable. The development time of games with physics, on the other hand, is in great part limited by the complexity of the different parameters needed by the physical simulation. The combination of these parameters is hard to predict at compile time, which causes developers to repetitively test the application after every modification.

We propose a framework for the creation of games with 2D physics on mobile devices. Games can be created and tested on the device without the need to write source code. It provides a toolbox with pre-defined objects and behaviors. This allows non-programmers to create and easily test games. Additionally, created games can be exported as a source code project, allowing programmers to further refine them. The framework can be used by game developers to save time thanks to ready to use game elements, by educators to create games they want their learners to experience, or even by learners to learn physics by creating their own games. Furthermore, it improves communication and collaboration between developers and instructors as every change in the editor can be directly tested on the device’s screen when running the game.

The contribution of this paper is threefold: First we provide a model for adaptive serious games for mobile devices with 2D physics. Then we introduce TangoPhysics, a framework for the generation of quick prototypes of such games. We finally describe a multiple-case study and a quasi-experimental study, which show the application of this tool in the development of adaptive serious games with 2D physics. We show that the creation of prototypes for serious games with physics is multiple times faster using TangoPhysics than coding them.

2. BACKGROUND

2.1 Serious Games Definition

In (Ulicsak 2010) an extensive literature review about serious games was provided. This report concludes that: … within the research community there is no fixed definition of a serious game (Ulicsak 2010). But there is nothing new about serious games. The term was introduced already in 1968 with the publication of Clark Abt’s book “Serious Games” (Abt 1970). This book is one of the results of his work in the previous ten years, about war games and simulations. The definition he used for such games was: “… they have an explicit and carefully thought-out educational purpose and are not intended to be played primarily for amusement. This does not mean that serious games are not, or should not be, entertaining.”

Finally the authors in (Ulicsak 2010) conclude that “... majority view serious games as: having a learning model embedded, the content is integrated into the game so learning is intrinsic to play, and the assessment of learning may be integral to the game or occur through mediation around the game.”

2.2 Serious Game Engineering

(Crawford, C. and Peabody, S., 1984) describes the game engineering process as a sequence of phases. Because game engineering is a concrete case of software engineering, the phases in the creation of the game are very similar to the phases in the creation of software. The main phases the author identifies are: selection of topic and goal, research, design, implementation, and testing.

Serious games engineering requires special considerations like what and how should be taught, different kind of functionality, like tools for assessing learning, and a higher level adaptability to the different target platforms, hardware and users.

Serious games typically run on slower and more heterogeneous hardware. They typically target a wider range of users. Simplifications done in normal games such as generating random numbers or compressing time may not apply to serious games, as it may lead to teaching wrong concepts to learners. Serious games may require a way of assessing learning, as possibly a way of adapting the game to the player as well. Serious games may require additional functionality for teachers, like an observer mode that displays what the player sees, or a way of controlling learning content. (Michael and Chen 2005)

ISBN: 978-972-8939-66-3 © 2012 IADIS

198

2.3 Prototype Based Programming

Object oriented programming languages can be categorized in two big families: class based programming languages (CBL), and prototype based programming languages (PBL). In CBL, classes define behavior and structure and instances are objects that carry the data and behave according to the class’ specification. Behavior is shared by what is known as inheritance. In PBL objects are created either from nothing (called ex-nihilo creation) or by cloning another existing object (the prototype). PBL that support ex-nihilo object creation require mechanisms to define structure and behavior. Cloned objects are initially identical to the prototype and can reuse its structure and behavior by what is known as delegation. Delegation is the process by which an object assigns tasks (behavior) to other objects. Objects typically keep a reference to the prototype they were cloned from, where structure and behavior are defined.

The main advantage of PBL over CBL is that no model is needed to create objects. Creating an object model that correctly represents different instances requires abstract thinking. Humans, however, prefer to think about concrete cases rather than abstractions. Using models may also cause some overhead in a project when requirements change, since they may not be valid anymore.

2.4 Physics Editor

A physics editor is a tool that allows developers to visually and interactively add and edit physical objects to an application. Physical objects are squares, circles, polygons, etc. with different properties like density, and friction. The physical properties defined via physics editor are exported either directly to source code or to an intermediate format like XML.

Current physics editors do not run on mobile devices. Deploying the created game to the mobile device requires generating source code and integrating it to a software project. Alternatively, most tools have functionality to simulate the game in a new window. But this limits the usage of device specific capabilities, such as multitouch and accelerometer input.

Most physics editors do not have the purpose of quick prototyping and target expert users. They offer advanced features like polygonal and bezier shapes, profiling, different kinds of joints, like revolute and distance joints, etc. This is provided at the cost of a crowded GUI, with functionality that is sometimes unclear even to expert users and ends up never being used. Behavior, on the other hand, is in most cases not directly available in the tool but added afterwards via source code.

2.5 Adaptivity

Several authors state that the best way to learn is by having a personal tutor. (VanLehn et al. 2005, Niemiec and Walberg 1987). Vygotsky define the difference of the learning outcome between children learning with a personal tutor and without a tutor as the Zone of Proximal Development (ZPD). ZPD is the difference between what a learner can do without help and what he or she can do with help: �”ZPD is the distance between the actual developmental level as determined by independent problem solving and the level of potential development as determined through problem solving under adult guidance, or in collaboration with more capable peers” (Langford 2005).

In his theory Vygotsky argues that human tutors provide help to learners by working with them, observing them and talking to them. Based on observations, tutors are able to adapt to learners by recognizing his/her skills. Then they use this knowledge to help the learner. This adaptive behavior is also desired for serious games. Unfortunately, the development of such adaptive behavior in games is a complex task (Kickmeier-Rust and Albert 2007). The goal for developing compelling serious game should be “…to make the serious game adaptive to the learner and acting intelligently to achieve a higher individuality of the serious game” (Ismailović et al. 2011). The following definition of Adaptivity is used in this work: “Adaptivity is a non-invasive approach that enables a serious game to learn from learner’s behavior by intelligently monitoring and interpreting learner’s actions in the game’s world and adjusts automatically learning and game elements according to the student’s individual ZPD as necessary.” (Ismailović, D., 2011).


199

3. QUICK PROTOTYPING OF ADAPTIVE PHYSICAL GAMES

We present here a model for 2D physics for serious games that enables the development of 2D game objects. Furthermore we will present the Adaptivity Metamodel, responsible for the automatic individualization of the game and the content. Finally, we present the framework called TangoPhysics that can be used for generating quick prototypes of games with 2D physics.

3.1 Game World Model

The World represents a game, and it is composed of elements that are typically present in games, like images, animations, sounds, particle systems, and elements that are specific to games with physics, like physical objects and joints. The World decides how the different elements should interact with each other, like for example how two objects react to collisions.

Figure 1. Game World Model (UML Class Diagram)

PhysicalObjects are squares, circles, polygons, or combinations of them. For example a rag doll may be composed of arms and hands. While an arm may be a simple rectangle, a hand may be composed of other shapes (five rectangles for the fingers and one circle for the palm). This is achieved via composite pattern (Gamma et al. 2000). Joints are used to constrain the behavior of physical objects. For example they can make two physical objects rotate around a common point, called hinge point.

GameObjects are PhysicalObjects with specific behavior. An arm for example can be an instance of the PhysicalObject class as far as no specific behavior is needed, or it can subclass PhysicalObject in order to implement additional methods, like the bend method that rotates the forearm around the elbow.

3.2 Serious Games Adaptivity Metamodel

The Adaptivity Metamodel is responsible for the individualization of content and game objects. A design goal of this model is the ability to include the adaptivity to existing games. The Adaptivity Metamodel is modeling the learner by representing the knowledge of the learner and his actions. Every learner has a profile with the history of executed actions. Based on these actions, a set of skill-acquisitions is rated.

Figure 2. Learner model (UML Class Diagram) (Ismailović et. al 2011)

Additionally, this metamodel is responsible for monitoring the events in the game. It is used to define what can be monitored and how the monitored event can be interpreted. Therefore each event has a relation to a game object. Furthermore, each game object is related to a skill. This model of knowledge with skills is based on the Knowledge Space Theory (Alan et. al 2003) and it represents the knowledge structure in a serious game. Using this model, we can calculate the acquisition value of a skill, when a learner is interacting with different game objects.

ISBN: 978-972-8939-66-3 © 2012 IADIS

200

Figure 3. Event based monitoring of game events (UML Class Diagram)

3.3 TangoPhysics Framework

TangoPhysics is a game creation framework that runs on the iPad. Its functionality can be divided in three modules: edition, simulation and code generation.

The edition module has a pre-defined set of ready to use objects. Once added, different properties of these elements can be modified and tuned to the specific game. Different game objects can be grouped together into a single higher-level object, which can be added to the framework and reused across projects.

The edition module is also responsible for setting game’s behavior. Behavior is defined by means of a rule-based system based on triggers and actions. Triggers represent a condition. When the condition is fulfilled, actions are executed. A trigger can be connected to different actions. The system currently supports ten different triggers and actions. Some of them are: timeTrigger (an event is generated every x seconds), scaleTrigger (an event is generated whenever a specified object or group of objects are bigger or smaller than a specified limit), moveAction (moves one or more objects to a certain position), imageAction (changes the image of an object). If, for example, an object should disappear after it collides against another object, a collisionTrigger can be connected to both objects and to a disappearAction, and the disappearAction should be connected to the object that should disappear.

The simulation module uses a physics engine to let objects interact following physical laws. The code generation module is able to export the game to an intermediate format that can be downloaded from the iPad, although this is still under development.

Figure 4. GameObjects in the framework (UML Class Diagram)

4. EVALUATION

In the first step we introduce a prototypical implementation of TangoPhysics. Then we present a multiple-case study where we developed some serious games with the three characteristics: mobile, using 2d physics and adaptive. We will describe the results of this study and present its results by stating they influenced the development of TangoPhysics. Finally we will present a quasi-experimental study that was set up to analyze the application of adaptive serious games with 2D physics.

4.1 Prototypical Implementation

During the Edition mode, a palette with three tabs is displayed. The first tab contains the available game elements. These elements can be dragged from the palette to the game scene. Once added to the scene, they can be selected. Selected elements display a red dot in the center. The second tab is the edition tab, and it displays the properties of the selected element and lets the user edit them. If no element is selected, general


201

game parameters such as gravity and background image can be configured. If more than one physical object is selected, the second tab allows the user to group them into a composite physical object. Grouped physical objects can be added to the palette in order to create a new clonable prototype. Clonable prototypes map to classes when source code is generated, where their behavior can be defined. Different objects have different properties. For example PhysicalObjects have the density and friction properties, Animations have the list of images to be animated, ParticleSystems have number of particles, colors, etc. The third tab is the behaviors tab. It contains the different triggers and actions that can be added to the game.

Figure 5. TangoPhysics used for the creation of “Cut the Rope”. Edition mode (left) and Simulation mode (right)

4.2 Multiple-Case Study

We conducted an exploratory multiple-case study to explore the development of adaptive serious games with physics engines in a small software development organization. We describe five projects developed for two companies. Three cases were developed in six months by a group of seven engineers. Another case was developed by a group of seven developers in three months. A single developer developed the last one in two months. All the cases were games with 2D physics and used the adaptivity framework.

Table 1. Multiple-case study

Case 1-3 4 5 Members 7 7 1 Project length / development time 6 / 4 months 3 / 2 months 2 / 1 months 2D physics development 2 months 1 months 2 weeks Adaptivity considerations 1 month 2 weeks 1 week

Design: Every game was initially designed together with an expert in pedagogy. Together with the expert, a professional painter provided initial paper-prototypes for all games. After the prototypes were available, the development process started. Requirements were unclear at the beginning; the prototype only presented the initial idea. Case studies 1-3: These games were developed in a team of seven members; four students, two pedagogic experts and one lead developer and software architect. The team had contact regularly to the pedagogic expert that designed the game. Case 4: This game was developed by a group of seven undergraduate students in three months. Case 5: This game was developed in three months full time by a single developer. We used the following methods to collect data: Observations, shadowing participants, and unstructured interviews before and after the project.

Results: When observing the developers we found that even with popular open-source frameworks for 2D physics on iPad, the teams spent the most of the time developing the physical behavior of the games. From the observations and interviews with developers, and by shadowing them, we found out that approximately more than 50% of the development time was spent in the development of the physical behavior.

Additionally we found that the time used for 2D physics development was spent mostly in developing and testing the specified physical behavior. About 20% of time was also used to consider, model and implement adaptive behavior in the game. The conclusion we had when observing the results in Table 1 is that improving the development of the physical behavior can decrease the development time of such games.

ISBN: 978-972-8939-66-3 © 2012 IADIS

202

4.3 Quasi-Experimental Study

This section presents a quasi-experimental study conducted with two professional developers. We assume that a prototyping tool can reduce the development time presented in Table 1 “2D physics development”. Additionally we assume that an integrated adaptivity model can reduce or partly remove the time necessary for adaptivity considerations. TangoPhysics generates for each game object an instance of the class GameObject that is connected to necessary and affected skills. This means, that when a domain model is provided, adaptive behavior can be integrated just by mapping game elements to skills. While the generation of the domain model takes some time, only one model is needed for different serious games based on the same content.

Design: We designed three projects (A, B and C) for this study. A professional developer implemented two of the projects (A and B) without TangoPhysics, after being provided with a description and scribbles of the games. The third project (C) was selected from the top ten list of games in the Apple App Store and was given to the developer of projects A and B. The developer was already familiar with the functionality available in TangoPhysics. A second developer was asked to reproduce the games A and B using TangoPhysics. Images, animations and sounds necessary in the games were already available in the palette of TangoPhysics. Minimal functionality needed to be added programmatically.

Results: Both developers were able to create an initial prototype of the games with TangoPhysics in about 20 minutes. The prototypes could already be used for discussions with the client and tested by users already on the second day. Basically this took so long due to organizational issues, rather than technical problems. It can be observed in Table 2 that the number of iterations increased although the development time decreased. Our framework proved flexible enough to allow the creation of one of the currently most popular iOS games in the App Store: “Cut the Rope”.

Table 2. Quasi-Experimental Study

Project Project A Project B Project C TangoPhysics NO YES NO YES NO YES Initial prototype 2 weeks 1 day 2 weeks 1 day N/A 1 day First usability test 3 weeks 2 days 2 months 1 months N/A 2 days First improvement 3 weeks 4 days 1 months 2 weeks N/A 2 days # Iterations 2 5 3 6 N/A 3 Development time 1 month 2 weeks 2 weeks 1 week N/A 4 days

Limitations: In the conducted studies, the images and sounds were already imported to the tool. This would add some preparation time in real projects. However this can be achieved very easily with the mobile technology. Cameras and microphones can be used to quickly have images and sounds available for use in the creation of a game. With respect to project C, we just designed one level of the game in the App Store. The original game consists of more than 50 levels. Furthermore, the prototype of the games made by TangoPhysics is not App Store ready. Automatic code generation is currently under development. The development process used in this study will not change in future.

5. CONCLUSION

We showed in this work that with today’s most modern mobile technology like an iPad, and complex physical simulations, the creation of compelling and adaptive games should not be a hard task. Therefore we presented a framework that enables the creation of such games directly on an iPad. Games created in this way can be tested without the need of writing code.

A tablet is even more portable than a laptop or desktop computer. This allows learners to play anywhere, not only inside computer rooms, and developers to show progress to clients during any meeting and to discuss requirements. It also offers more direct ways of interaction, like by touching a physical object directly on a screen. This makes an application running on a tablet more likely to be understood by users with no IT experience. As opposed to laptops and desktop computers, more than one person can use tablets at the same time. This promotes collaborative work between different users trying to solve a common problem. So different kids can create a game, or clients and developers can work on initial prototypes.


203

TangoPhysics works with hierarchical structures, which allows users to create complex structures out of pre-defined objects. Behavior can then be assigned to the complex structures, giving them a more semantic meaning. Furthermore, these structures can be added to the palette and reused across games.

Integrating physical and particle simulations in a game represents a new and promising way of motivating players to learn physics, astronomy, mathematics, etc. TangoPhysics goes beyond a physics game; it is a physics game creator. Players can not only play the games created with it by others or by themselves; they can also create their own games, which promotes learning. TangoPhysics can also be used by educators to create games that fit into their curriculum. Letting the educator create the game helps ensure “quality and relevance of the serious content featured in the game”. The fact that public schools are typically limited in budget couples good with the quick prototyping character of TangoPhysics.

As we presented in our work, TangoPhysics can also be used as a prototyping tool. A big advantage with respect to most of the other prototyping tools is that the prototypes produced by TangoPhysics are meant to evolve into the final application. The entire game can be exported to an intermediate representation and then loaded from the game software project. The simulation engine integrated in TangoPhysics can be directly used in created applications.

REFERENCES

Abt C. C., 1970 Serious Games. University Press of America, 1987. ISBN 0819161489. Alan Y. et. al, 2003. Implementation of Knowledge Spaces in Ontologies. Proceedings of SCI, (2):183– 185. Anderson J. A., et. Al 1995. Cognitive tutors: Lessons learned. The journal of the learning sciences, 4(2), 167-207. Bloom B. S., 1984 The 2 sigma problem: The search for methods of group instruction as effective as one-to-one

tutoring. educational researcher, 13(6), 4-16. Bruegge B. and Dutoit A. H., 2009 Object-Oriented Software En- gineering Using UML, Patterns, and Java. 3rd Edition.

Prentice Hall, New Jersey, USA. Crawford, C. and Peabody, S., 1984 The Art of Computer Game Design. Osborne/McGraw-Hill. California, USA. Dignan Aaron, 2011. Game Frame – Using Games as a Strategy for Success. Free Press, New York Gamma E, et al. 2000 Design Patterns Elements of Reusable Object-Oriented Software. Addison-Wesley, Mas-

sachusetts. Gee J. P., 2008. What Video Games Have to Teach us About Learning and Literacy. St. Martin’s Press Ismailović, D., 2011. Adaptivity in Serious Games, ongoing Ph.D. dissertation, Technische Universität München. Ismailović, D., et. al 2011. weMakewords – an adaptive and collaborative serious game for literacy acquisition. IADIS

International Conference Game and Entertainment Technologies. Rome. Kickmeier-Rust M. D. and Albert D., 2007 The {ELEKTRA} Ontology Model: A Learner-Centered Approach to

Resource Description. In ICWL, pages 78–89. Kickmeier-Rust M. D, et al., 2006 The ELEKTRA project: Towards a new learning experience. M3, 3:19–48. Michael D.R. and Chen S.L, 2005. Serious Games: Games That Educate, Train, and Inform, Course Technology PTR Niemiec R. and Walberg H. J., 1987 Comparative effects of computer- assisted instruction: A synthesis of reviews.

journal of educational computing research, 3, 19-37. Prensky M., 2008. Digital Game-Based Learning. Paragon House Publ Ulicsak M., 2010. Games in Education: Serious Games. Technical report, Futurelab. VanLehn K., et. al, 2005 The andes physics tutoring system: Five years of evaluations. in g. mccalla and c. k. looi (eds.),

artificial intelligence in education. ios press.

ISBN: 978-972-8939-66-3 © 2012 IADIS

204

REAL WORLD EDUTAINMENT BASED ON BRANCHED GAME STORY AND ITS APPLICATION TO

EARTHQUAKE DISASTER PREVENTION LEARNING

Yusuke Noda1, Keiji Miki 1, Kazuhisa Iwaka1, Hiroyuki Mitsuhara2, Yasunori Kozuki2 and Yoneo Yano3

The University of Tokushima 1Graduate School of Advanced Technology and Science

2-1 Minami-josanjima, Tokushima, 770-8506, Japan 2Institute of Technology and Science

3Center for Administration of Information Technology

ABSTRACT

Real World Edutainment (RWE) is a game-based learning in the real world and enables learners to learn by viewing digital learning materials and interacting with real objects and humans in the real world, according to a game story. The RWE system had the weaknesses. For example, the system did not support a branched game story and could not switch the next learning scene tailored to a learner’s characteristics and behaviors. To remove the weaknesses, we extended the RWE system by implementing the functions of branched game story interpreter, etc. Then we created a branched game story for earthquake disaster prevention learning and conducted a preliminary experiment. The results of the experiment showed that the extended RWE could increase learning motivation in comparison with the traditional class.

KEYWORDS

Edutainment, branched game story, learning motivation, real world, earthquake disaster prevention

1. INTRODUCTION

Edutainment, which combines learning with the fun of video games, has recently attracted attention. In most cases, they play games and learn things in the virtual world. This means that learners cannot learn through the five senses in the real world. In addition, they often focus on audiovisual effects and cannot give each learner proper information (e.g., hint, feedback, and instructions). Therefore learners cannot learn flexibly depending on their characteristics and choices. These points can be regarded as the weaknesses in edutainment.

To remove the above weaknesses, we proposed Real World Edutainment (RWE for short) and developed the RWE system (Mitsuhara, et al., 2010). RWE may be positioned as the next generation edutainment by the fusion of the virtual world and the real world. The RWE system has standalone architecture and works on a PDA (Personal Digital Assistant) so that learners can learn anywhere. In addition, RWE adopts human-human interaction (HHI for short) that human actors give proper information on the basis of each learner’s characteristics (e.g., knowledge level, interest, and preferences). It also adopts story-based learning in the real world, that is, it applies a role-playing game or an adventure game in the real world. According to a game story loaded and interpreted on a PDA, the system recognizes learning scenes by RFID (Radio Frequency Identification) and/or GPS (Global Positioning System). Then the system presents learning materials (single-choice quiz and text-based explanation) corresponding to the scenes.

Recently, ubiquitous/mobile learning systems have been actively developed and practiced. In a project called "AMULETS", a mobile learning system consisting of smartphones, PDAs and GPS devices bridges outdoors and indoors educational activities (Kurti, et al., 2008). In a language learning system, visual markers are attached near the learning zones and when learners read them, learning materials are shown (Liu, 2009). In a museum learning, learning materials to help visitors understand exhibits are presented in location-aware


205

and game-based manners (Ghiani, et al., 2009) (Sung, et al., 2010). The use of ubiquitous/mobile devices may help make learning fun as learners can learn in different settings from usual.

There have been some edutainment systems similar to RWE. Klopfer and Squire (2008) have developed an augmented reality game that has a game story revolved in the real world and furnishes students with scientific augmentation skills. In this game, a learner role-plays an environmental detective and identifies the source of the pollutant, receiving location-based fictitious environmental data and advisory messages from virtual characters. Schwabe and Göth (2005) have developed a mobile game for university orientation (for learning university life), focusing on interaction with real humans. In this game, learners have to find not only places but also people to get important information by interviewing them.

We conducted an evaluation of our RWE at an educational event for elementary school students and confirmed that many participants had fun, and reported it enhanced their learning motivation and learning efficacy. At the same time, however, we found that the RWE system had the three weaknesses. Firstly, a branched game story was not supported. It is very important to overcome this weakness as Chang et al. (2008) pointed out the importance of story in game-based learning and proposed a method for personalizing a game story (learning path) based on each learner’s characteristics. Secondly, learning scene recognition was not sufficient. Thirdly, earning materials were not multimedia-rich enough.

The rest of this paper is organized as follows. Section 2 overviews the extended RWE system, mainly focusing on how to support the branched game story. Section 3 shows an application of RWE for earthquake disaster prevention learning. Section 4 reports a preliminary experiment of the application. Finally section 5 summarizes this paper.

2. EXTENDED SYSTEM OF REAL WORLD EDUTAINMENT

To remove the three weaknesses, first of all, we adopted not a PDA but a UMPC (Ultra Mobile PC) as the platform to obtain high extendibility, processing speed and capacity of memory and disk. Then we extended the RWE system so that it can work based on a branched game story, recognize more various learning scenes with additional sensors, and present multimedia learning materials. Figure 1 shows the composition of the extended system and a snapshot in experimental use of the system.

Figure 1. Extended RWE system

2.1 Branched Game Story Interpreter

We implemented the branched game story interpreter, which can switch the next learning scene for each learner based on a branched game story. The branched game story consists of some learning scenes. Each learning scene consists of some events (quiz, expository video, etc.). The branched game story deals with the two kinds of branches: irreversible branch and reversible branch.

2.1.1 Irreversible Branch

Figure 2 shows two typical patterns of the irreversible branch. The irreversible branch has neither backtracking nor loop in the story flow. There are two and more options for the next learning scene. Learners

ISBN: 978-972-8939-66-3 © 2012 IADIS

206

are not allowed to return to the previous learning scene nor to alternate learning scenes (to move to the other learning scenes that they did not visit).

In a typical branch, the next learning scene is selected corresponding to a learner’s answer to the quiz. For example, if the answer is correct, he/she is directed to move to the advanced topic. If the answer is wrong, he/she is directed to move to the basic topic (Figure 2-left). In this manner, the learner is expected to understand learning topics steadily. Moreover, the irreversible branch allows a learner to choose the next learning scene from some candidates (Figure 2-right). In other words, the game story changes depending on the learner’s choice and provides self-directed learning and multi-ending. These characteristics of the irreversible branch can increase learning motivation because learners can proceed along more personalized learning path and often hope to experience all learning paths (endings).

Figure 2. Irreversible branch

2.1.2 Reversible Branch

Figure 3 shows two typical patterns of the reversible branch. The reversible branch has both backtracking and loop in the story flow. For example, a learner with wrong answer can return to the previous learning scene to brush up his/her understanding. As an example of loop, a learner can retry a quiz immediately after his/her answering it. If the system suggests some locations (the learner’s location being detected by GPS) for the next learning scene, a learner can visit all the locations and move back and forth among the learning scenes (Figure 3-left). The reversible branch can provide supplementary, secondary, or game-oriented learning scenes. For example, a mini game is rewarded to the learners who gave the correct answer to a difficult quiz (Figure 3-right). The reversible branch can offer high flexibility of learning by giving them more choices for the next learning scene.

Figure 3. Reversible branch


207

2.2 Extended Scene Recognizer

To enable the RWE system to recognize more various learning scenes, we extended the learning scene recognizer by introducing sensors such as an electronic compass and a Web camera. These sensors enable recognizing a learning scene in terms of his/her direction of eyes at the current location.

2.3 Extended Learning Material Presenter

We extended the RWE system so that it could handle multimedia learning materials (e.g., audio, image, and video). For example, a learner can deduce the correct answer to a quiz, watching a video as a hint.

3. EARTHQUAKE DISASTER PREVENTION LEARNING

On March 11, 2011, Tohoku Region Pacific Coast Earthquake occurred and the catastrophic earthquake and tsunami devastated the north-east part of Japan. In the wake of this earthquake, it is being reconsidered how to transfer knowledge about earthquake disaster prevention (EDP for short) more effectively to residents. For the effective knowledge transfer, ICT has been used in EDP learning. For example, Kobayashi et al. (2008) developed a GIS-based table-top simulation system to enable residents to make their local evacuation plans. Kameda et al. (2010) developed a Web-based database system where users (e.g., policy makers, community leaders, etc.) can collect and disseminate knowledge about various kinds of disaster prevention.

We think that ICT should be used for more experiential EDP learning within a local area in the real world. We believe that RWE is suited for EDP learning because learners can acquire knowledge for not only acting to survive but also helping others in an earthquake disaster thorough experience in the real world.

3.1 Game-based Disaster Prevention Learning

Nowadays, game-based EDP learning is attracting attention due to its high interactivity. For example, “Crossroad” is a traditional card game-based learning, in which player groups discuss dilemmas faced in earthquake disasters according to a scenario written on each card (Yamori, 2011). Kaji et al. (2005) developed a computer-based gaming simulation model to train local government officials to response operations at emergency headquarters in a disaster. In this model, decision-making processes of the headquarter staff are designed as a role-playing game. UN/ISDR (United Nation/International Strategy for Disaster Reduction) produced “STOP DISASTERS!” which is a web-based disaster prevention learning game for children (http://www.stopdisastersgame.org). In this game, the players simulate city planning to withstand disasters (earthquake, tsunami, etc.) and learn dangers, early warning systems, evacuation plans, etc. in each disaster. Game-based EDP learning can improve EDP motivation due to “fun” inherent in game.

3.2 Our Game Story

With specialists of EDP, we created a branched game story for learning how to survive and help others in Nankai earthquake, a large earthquake anticipated in the mid-west part of Japan including Tokushima prefecture. The game story focuses on an evacuation drill in the campus of the University of Tokushima and therefore targets students of the university.

3.2.1 Storyline

To motivate the students and emphasize the reality, we adopted the following storyline that is like a dating simulation game and takes place on campus. Learning follows this storyline.

A boy university student has a secret crush on his classmate Rina. He asks her to meet at the parking lot of the library after class. He is determined to confess his love to her. But suddenly a large earthquake happens during class. He takes an immediate action to survive the earthquake, to meet her, and confess his love.

ISBN: 978-972-8939-66-3 © 2012 IADIS

208

3.2.2 Learning Flow

The game story is composed of seven learning scenes. Figure 4 shows the learning flow of the game story. Figure 5 shows snapshots of learning using this game story.

Figure 4. Learning flow of the game story for learning the Nankai earthquake

� Scene 1 : Attending class This game story begins from the scene where learners attend class in a school building. First of all, the

learner has a briefing to learn that he, university undergraduate, has a crush on his classmate, Rina and is determined to confess his love. Suddenly an emergency earthquake alert is sent out over on his UMPC. About several seconds later, a quiz about the alert is presented. If the answer is correct, the learner can move on to the next learning scene immediately. If the answer is wrong, the learner must view an expository video about the alert before moving on to the next learning scene― this is an irreversible branch.

� Scene 2 : Earthquake occurrence As a matter of course, the real Nankai earthquake does not happen in the real world. In this scene, a video

representing the earthquake (shaking classroom) is presented to let the learner recall the earthquake fears. After that, two quizzes about the earthquake’s power are presented. After the two quizzes, the learner is directed to evacuate from the building and find Rina.

� Scene 3 : Evacuating from the building The learner must choose one of two routes to evacuate from the building― this is another irreversible

branch. The proper choice is to take stairs and the improper choice is to use an elevator. A different quiz and an expository video are presented according the choice.

� Scene 4 : Treating first aid situations An injured student is calling for help near the building exit. The learner must give a first aid to the injured

student, viewing a first aid video and using real objects (newspapers and a string) available for the first aid (Figure 5-left).

After being given the first aid, the injured student says, “I guess you are finding Rina. Before the earthquake, she said that she was going to the parking lot of the library. But, she might be now around the gym because it is the designated evacuation site of this university.”

After that, the learner can move freely to the evacuation site (Figure 5-middle). Information on his/her current location is gathered from GPS and two learning scenes, location A and B, are recognized. The learner can move to both the location A and B, either A or B, or move directly to the evacuation site without A or B― this is a reversible branch.

� Scene 5 : Building collapse on the way to the evacuation site


209

At the location A on a narrow path between the two buildings that leads to the evacuation site, a video representing the afterquake (a shaking landscape viewed from the location) is presented. Then, a quiz about general afterquake is presented. After the quiz, the learner is directed to continue the evacuation.

� Scene 6 : Tsunami on the way to the evacuation site When the learner visits the location B in the parking lot of the library near a river, the learner is directed

to look toward the river. Then, a tsunami alert is popped up. Then two quizzes about the tsunami are presented. After the quizzes, it turns out that Rina is in the evacuation site and the learner is directed to go to the evacuation site.

� Scene 7 : Ending The learner moves to around the gym (the evacuation site) and watches an expository video about refuge

life. Finally, the learning (game) is completed with an epilogue showing that his confession was accepted.

Treating first aid Moving to the evacuation site User interface showing the current location

Figure 5. Snapshots of learning using this game story

4. PRELIMINARY EXPERIMENT

4.1 Procedure

We conducted a preliminary experiment to survey whether the extended RWE can increase learning motivation and learning effect. The participants were 32 graduate and undergraduate students majoring in computer science at the University of Tokushima, aged between 18 to 24 years old. We conducted a pre-survey questionnaire asking about their interest and learning motivation for the Nankai earthquake. Then we divided the participants into the following three groups as homogeneously as possible according to their answers.

� Group A : Eleven participants learned in a traditional class about earthquake disaster prevention focusing on the Nankai earthquake.

� Group B : Ten participants learned through the semi-extended RWE that had the extended functions but was based on a linear structure version of the game story. In this linear game story, the branches (irreversible and reversible) were removed from the story flow shown in 3.2.

� Group C : Eleven participants learned through the extended RWE, which had the extended functions and the branches in the story flow shown in 3.2.

All the participants took a posttest about what they learned. Then they answered a questionnaire asking about their interest and learning motivation for the Nankai earthquake, etc. Two months later, all the participants took the same posttest again and answered the questions asking the change of their interest and learning motivation, etc.

4.2 Results and Considerations

4.2.1 Immediately after the Learning Session

Table 1 shows the results of the questionnaire conducted immediately after the learning session. About the mean values of Post1-Q1, there were statistically-significant differences between Group A & B, and Group A & C. This result indicates that participants of Group B and C learned the Nankai earthquake with fun. About the mean values of Post1-Q2, there were statistically-significant differences between Group A & B, and

ISBN: 978-972-8939-66-3 © 2012 IADIS

210

Group A & C. We think that the results of the Post1-Q1 and the Post1-Q2 were similar and endorse the advantages of the RWE. About the mean values of Post1-Q3, there was a statistically-significant difference between Group A and C. We think that this result was influenced positively by the branched game story but not good enough. We should create a game story with many branches and multi-endings so that participants can have more choices and can be encouraged to give more thoughts on their choices at each learning scene.

About the mean values of Post1-Q4, there were statistically-significant differences between Group A & B, and Group A & C. This result indicates that participants of Group B and C learned the Nankai earthquake with higher learning motivation. We believe that the mean values of the Post1-Q4 were influenced positively by those of the Post1-Q1 and the Post1-Q2. However, about the mean values of Post1-Q5 and Post1-Q6, there were no statistically-significant differences among the three groups.

4.2.2 Two Months after the Learning Session

Table 2 shows the results of the questionnaire conducted two months after the learning session. However the results of Post2-Q1 and Post2-Q2 show that some Group B and C participants made some research or actually prepared for the Nankai earthquake after the learning session held two months ago. On the other hand, Group A participants did nothing after the session. These results indicate that the participants of Group B and C were motivated to learn and prepare for the Nankai earthquake. They kept a higher level of motivation. We believe that they will learned more and kept it longer. We should consider how the extended RWE should retain high learning motivation as long as possible.

4.2.3 Posttests

Table 3 shows the mean scores of the two posttests, which were given immediately and two months after the learning session. These scores indicate that the participants could not retain their obtained knowledge regardless of the learning styles. The advantages of the RWE were not detected from the posttest results.

Table 1. The results of the questionnaire conducted immediately after the learning session

Question (five-point scale: 1-5) Mean (SD) ANOVA Ryan’s method (Answer : 1 = Definitely no … Answer : 5 = Definitely yes)

Group A

Group B

Group C

Pair(A-B)

Pair(A-C)

[Post1-Q1] Did you enjoy the today’s learning? 3.09 (1.00)

4.50 (0.50)

4.45 (0.50)

p=0.0001 p=0.0002 p=0.0002

[Post1-Q2] Did you have unusual experiences in the today’s learning?

2.73 (1.29)

4.20 (0.40)

4.36 (0.64)

p=0.0004 p=0.001 p=0.0002

[Post1-Q3] Did you feel a sense of controlling your learning activities in the today’s learning?

2.09 (1.08)

2.90 (0.94)

3.45 (1.16)

p=0.03 p=0.11 p=0.01

[Post1-Q4] Were you motivated to learn the Nankai earthquake in the today’ learning?

3.18 (0.83)

4.20 (0.49)

4.18 (0.39)

p=0.001 p=0.002 p=0.001

[Post1-Q5] Do you want to learn the Nankai earthquake after the today’s learning?

3.27 (1.14)

3.70 (0.90)

3.27 (0.75)

p=0.53 ―― ――

[Post1-Q6] Did you decide to prepare for the Nankai earthquake in the today’s learning?

3.73 (0.75)

3.50 (1.20)

3.73 (0.45)

p=0.80 ―― ――

Table 2. The results of the questionnaires conducted two months later

Question (“Yes” or “No”) No. of “yes” Group

A Group

B Group

C [Post2-Q1] Did you learn the Nankai earthquake and/or earthquake disaster prevention after the learning session held two months ago?

0 1 1

[Post2-Q2] Did you actually prepare for the Nankai earthquake after the learning session held two months ago?

0 3 2

Table 3. The mean scores of the two posttests

Posttest (20 questions) Mean (SD) ANOVA Group A Group B Group C

Immediately after the learning session 16.55 (2.46) 16.40 (1.02) 15.64 (1.30) p=0.46 Two months later after the learning session 10.09 (3.03) 8.70 (2.41) 9.36 (2.90) p=0.56


211

5. CONCLUSION

This paper described the extended RWE system that works based on a branched game story to increase learning motivation and learning effect. The irreversible branch and the reversible branch improve the flexibility of a game story (learning) and help to make learning more fun and effective. This paper reported the preliminary experiment where university students learned the Nankai earthquake using the extended RWE system with the branched game story. Overall, from the results of the experiment, we can safely say that the extended RWE increases learning motivation in comparison with the traditional class.

A current weakness of the extended RWE system is that the branching conditions are not sufficient enough. A learner’s answer to a quiz is the fundamental branching condition but it only covers his/her understanding to the quiz. For example, we should branch a game story based on a learner’s learning history (e.g., accuracy rate of the quizzes and visited scenes), surroundings (e.g., temperature and luminance), and other learners’ current situations (e.g., location and learning scenes). Another weakness is that the multimedia learning materials are not well integrated with the real world and do not increase the reality enough. For example, the learning materials should be superimposed on real-time camera images using markerless AR (Augmented Reality) technology.

Another important future work is to clarify the effect of the extended RWE through a large-scale experiment. To prepare for the experiment, we are designing a new branched game story that adopts many branches and multi-ending.

ACKNOWLEDGEMENT

This study was supported in part from the Panasonic Education Foundation, Japan. Grateful thanks are expressed to Ms. Mari Morimoto who is developing a story authoring system for RWE.

REFERENCES

Chang, M. et al., 2008. Making the Real World as a Game World to Learners by Applying Game-Based Learning Scenes into Ubiquitous Learning Environment. Transactions on Edutainment I, pp.261–277.

Ghiani, G. et al., 2009. UbiCicero: A location-aware, multidevice museum guide. Interacting with Computers, Vol. 21, No. 4, pp. 288-303.

Klopfer, E. and Squire, K.D., 2008. Environmental Detectives—the development of an augmented reality platform for environmental simulations. Educational Technology Research and Development, Vol. 56, No. 2, pp. 203-228.

Kaji, H. et al., 2005. Use of Gaming for Training Emergency Headquarters in Responding to Earthquake Damage: VEQRES/SAITAI—Virtual Earthquake RESponses—. GAMING, SIMULATIONS, AND SOCIETY, Part I, pp.29-38.

Kameda, H. et al., 2010. Disaster Reduction Hyperbase (DRH) - Allied Knowledgebase Platforms for Disaster Risk Reduction. Proc. International Disaster and Risk Conference IDRC Davos 2010, pp.378-383.

Kobayashi, K. et al., 2008. DIGTable: A Tabletop Simulation System for Disaster Education. Proc. of the Sixth International Conference on Pervasive Computing (Pervasive2008), pp.57-60.

Kurti, A. et al., 2008. Bridging Outdoors and Indoors Educational Activities in Schools with the Support of Mobile and Positioning Technologies. International Journal of Mobile Learning and Organization, Vol. 2, No. 2, pp. 166-186.

Liu, T.Y. 2009. A context-aware ubiquitous learning environment for language listening and speaking. Journal of Computer Assisted Learning, Vol. 25, No. 6, pp. 515–527.

Mitsuhara, H., et al. 2010. Real World Edutainment Focusing on Game Story and Human-Human Interaction in the Real World. The Journal of Information and Systems in Education, Vol. 9, No. 1, pp.45-56.

Schwabe, G. and Göth, C. 2005. Mobile learning with a mobile game: design and motivational effects. Journal of Computer Assisted learning, Vol. 21, No. 3, pp. 204–216.

Sung, Y.T. et al., 2010. Designing an electronic guidebook for learning engagement in a museum of history. Computers in Human Behavior, Vol. 26, No. 1, pp. 74-83.

Yamori K. 2011. Using Games in Community Disaster Prevention Exercises. Group Decision and Negotiation (Online first).

ISBN: 978-972-8939-66-3 © 2012 IADIS

212

MOBILE AND COLLABORATIVE TIMELINES FOR REFLECTION

Anders Kristiansen, Andreas Storlien, Simone Mora, Birgit R. Krogstie and Monica Divitini Department of Information and Computer Science, Norwegian University of Science and Technology

Trondheim; Norway

ABSTRACT

In this paper we present the design and evaluation of TimeLine, a mobile application to support reflective learning through timelines. The application, running on Android devices, allows users to capture traces of working and learning experiences in a timeline with the aim to provide data that can be used to promote reflection and learning after the experience. The paper presents the design of the application, its evaluation, and identifies challenges connected to the development and deployment of timelines for reflection.

KEYWORDS

Reflection, mobile learning, timeline, cooperation

1. INTRODUCTION

Timelines are widely used metaphors for organizing presentation and navigation of information. For example, Facebook has recently introduced a timeline feature for showing the story of the user (http://www.facebook.com/about/timeline). Timelines have two important characteristics. First, the metaphor is widely used and easily understandable. Second, most digital information has a timestamp that makes easy to organize and visualize a variety of information from different sources, e.g. text, photos, data from environmental sensors or from other applications. Recent commercial and research projects have developed different user interaction modalities to create and manipulate timelines, exploiting mobile and tangible technologies. For example the Path app (path.com) available on iOS and Android devices, allows for collecting different aspects of life experiences (including moods and feelings) by providing a user-initiated input mechanisms and enabling sharing contents on social networks. A different interaction approach is built into the Evertale app (evertale.com) which automatically collects pieces of context of daily experiences (from locations to songs listened while doing an activity) on behalf of the user while running in background on an Android smartphone. The goal is to enable the user to reminisce a past experience using pieces of context that characterized it. Aiming at enhancing genealogy research practices and personal production of rich family histories for future generations, the ChronoTape (Bennett et al. 2012) is a wood box interface designed to enable a tangible representation and control of time by annotating, manipulating and reviewing paper timelines mounted on reels. Other examples of use of timelines include clustering and exploring search results (Alonso et al. 2009), summarizing and abstracting information about events in order to identify patterns (Wongsubhasawat 2011), and supporting collaborative planning work among stakeholders (Bohøy et al. 2010).

In this paper we focus on the usage of timelines for organizing information for purposes of reflection. Considering the process of reflective learning as outlined by Boud et al (1985), reflection can be seen as a re-evaluation of experience, involving a return to previous experience as well as the production of reflection outcomes, and with explicit attention to emotions as well as ideas and behaviour Timelines have a potential to support the reflective process by providing a structure for the re-construction of experience (e.g. helping learners chronologically order a set of events), and by providing a structure to enable comparison and evaluation of experiences. For example, in project teams, individually and collaboratively constructed timelines of project events have been shown to support reflective learning about project work (Derby 2006, Krogstie and Divitini 2009, Krogstie 2009).


213

Reflection might rely on human memorapproach which at times can causefound to be among the reasons why many organizations choose lack of adequate data to help participants reconstruct the process (Kavi et al. 2008).a large interest in technologies that support collection and organization of data for supporting refusing tag clouds in (Glahn et al. 2009) or

In this paper we present a mobile application intended to support individual and collaborative reflective learning with timelines. First, iinformation that might be useful for reflection on action (an experience to rethink the working or learning process with the goalal (1985), the application supports capturing of different types of information, ideas, behaviour, and emotions. Second, using the notion of timelines, the application provides a way to organize and visualize the information. The visualization on a timeline provides a temporal contextualizationinformation is presented together with other relevant information that users might have decided to collect, shedding light on different aspects of an event. Ttimelines, capturing in a coherent representation different perspectivecomparing their input with the ones of other group members.

The application has been developed through an iterative process including an expert evaluation and small focus groups. In the paper we present only the latest version of the prototype and its final evaluation.paper is organized as follows: Inits implementation. In Section 4 we present some scenarios of usage and in Section system in one of these scenarios. In

2. THE TIMELINE APPLICATION

The TimeLine application runs on Android devices and has been developed following the Android user interfaces guidelines (see http://developer.android.com/guide/practices/ui_guidelines/index.html). The main menu is available through the timelines, groups, and tags, and for navigating sharing and synchronizing timelines. With the application, a user can capture traces of an experience by annotating a timeline.

2.1 Constructing Timelines

TimeLine provides an empty timeline as starting point to which users can attach dannotations (Figure 1-b).

Figure 1.

Reflection might rely on human memory to reconstruct events, but this is a rather subjective and faulty cause problems. For example, in software development teams

found to be among the reasons why many organizations choose not to conduct retrospective reflection is the lack of adequate data to help participants reconstruct the process (Kavi et al. 2008). There has

in technologies that support collection and organization of data for supporting refg clouds in (Glahn et al. 2009) or the geo-location of information in (Mora et al. to appear).

In this paper we present a mobile application intended to support individual and collaborative reflective learning with timelines. First, it supports users in collecting traces of their experiencesinformation that might be useful for reflection on action (Schön 1983), i.e. activities conducted at the end of an experience to rethink the working or learning process with the goal of learning from it. Following Boud et al (1985), the application supports capturing of different types of information, ideas, behaviour, and emotions. Second, using the notion of timelines, the application provides a way to organize and visualize the

ormation. The visualization on a timeline provides a temporal contextualizationinformation is presented together with other relevant information that users might have decided to collect,

ding light on different aspects of an event. Third, the application provides the possibility to build shared capturing in a coherent representation different perspectives of an event and

comparing their input with the ones of other group members. en developed through an iterative process including an expert evaluation and small

focus groups. In the paper we present only the latest version of the prototype and its final evaluation.In Section 2 we provide an overview of the system and in Section 4 we present some scenarios of usage and in Section

in one of these scenarios. In Section 6 we draw some implications for design and deployment.

MELINE APPLICATION

The TimeLine application runs on Android devices and has been developed following the Android user interfaces guidelines (see http://developer.android.com/guide/practices/ui_guidelines/index.html). The main menu is available through the dashboard (Figure 1-a), providing access to functionalities for managing timelines, groups, and tags, and for navigating sharing and synchronizing timelines. With the application, a user can capture traces of an experience by annotating a timeline.

Timelines

TimeLine provides an empty timeline as starting point to which users can attach d

. The timeline dashboard (a) and main annotation types (b)

y to reconstruct events, but this is a rather subjective and faulty problems. For example, in software development teams, one challenge

to conduct retrospective reflection is the There has therefore been

in technologies that support collection and organization of data for supporting reflection, e.g. location of information in (Mora et al. to appear).

In this paper we present a mobile application intended to support individual and collaborative reflective traces of their experiences in the form of

, i.e. activities conducted at the end of of learning from it. Following Boud et

al (1985), the application supports capturing of different types of information, ideas, behaviour, and emotions. Second, using the notion of timelines, the application provides a way to organize and visualize the

ormation. The visualization on a timeline provides a temporal contextualization, and any piece of information is presented together with other relevant information that users might have decided to collect,

hird, the application provides the possibility to build shared and supporting people in

en developed through an iterative process including an expert evaluation and small focus groups. In the paper we present only the latest version of the prototype and its final evaluation. The

ew of the system and in Section 3 describe 4 we present some scenarios of usage and in Section 5 the evaluation of the

some implications for design and deployment.

The TimeLine application runs on Android devices and has been developed following the Android user interfaces guidelines (see http://developer.android.com/guide/practices/ui_guidelines/index.html). The main

a), providing access to functionalities for managing timelines, groups, and tags, and for navigating sharing and synchronizing timelines. With the application, a

TimeLine provides an empty timeline as starting point to which users can attach different types of

ISBN: 978-972-8939-66-3 © 2012 IADIS

214

Users can capture audio or video by using the mobile device, they can write notes, or add files and information available in other applications, e.g. in Gmail, Dropbox, or Facebook. Since one important, often neglected, aspect of an experience is connected to feelings, the application explicitly provides the possibility to add emoticons to the timeline, capturing in a very simple way how one feels at a certain moment. For more details on different design choices, see (Kristiansen and Storlien 2011).

2.2 Collaborating Around Timelines

TimeLine allows cooperation around a shared timeline collecting information about a working experience. Users can create groups and share timelines within groups. By default, information added to a shared timeline is private, but the user can decide at any moment to share it (Figure 2-b). In this way, a timeline can be used at the same time for capturing private and shared information. On a shared timeline, cooperation is supported by: (1) Commenting of content, for example adding a comment to a picture or adding a picture to an event recorded by another user (Figure 2-a); (2) Assessing content, by adding an emoticon to an event; (3) Sending reports, the system can generate and send via email a list with all the items collected in the timeline to provide information also to people without the application; (4) Calculating mood average, each user can annotate the timeline with mood represented by one of four emoticons. Emoticons are used to calculate the average mood of the group. This is not intended to capture with precision the mood of the team, but rather to provide an indication of the current mood and its changes.

(a) (b)

Figure 2. Sharing information in a group timeline

The application also supports the visualization of the information in a map where elements are presented based on the geographical position at creation.

2.3 Integration with Other Applications

TimeLine can connect with third-party devices and services. At the current stage, we have experimented with multiple visualizations of average moods using three types of technologies: tangible, ambient and social (Figure 3). This integration is mainly intended to demonstrate the possibility to trigger collaborative reflection by provoking discussion through extended visibility. The tangible interface (Figure 3-a), named Nabazmood, runs on a hardware mash-up of two devices: a Nabaztag rabbit (http://www.karotz.com) and a pico-projector. The average mood is visualized through the movement of the ears and colour of the rabbit. This visualization is intended to be provocative and the users can monitor the evolution of the average mood with low cognitive effort. The ambient interface (Figure 3-b) is a projection on the wall of a 2D mood-map based on Russel’s Circumplex Model of Affect (Russel 1980), indicating the position of the timeline average


215

mood by a moving pinpoint displayed on the map.regularly posting the average mood on within larger communities and users that are not capturing mood are described in

Figure 3. Tangible, ambient and social visualization of the TimeLine (only average mood)

2.4 Implementation

TimeLine is implemented following a clientdevices acts as a client (TimelineApp) and a cloud servicTimelineApp provides user interaction interfaces, data storage for private timelines as well as functionalities for adding contents to a timeline. frequently used to implementing Android applications because of its flexibility.

TimelineCloud, the server-side, implements collaboration features like synchamong clients and the integration with the thirdcommunicate via a RESTful interface using JSON as markup language for data object exchange.is exploiting the Google App Engine frameworkstorage for the service. In the current prototypea button to initiate synchronization between the server and the client. To overcome some of the disadvantages of this solution we did however implement automatic push of timeline contents onevents, items and moods are immediately pushed to the servercontent, while clients sync on user request content generated using the app offline (e.g. using a smartphoTimelineCloud also acts as email gateway for sending timeline reports, an email messtored in a timeline (either private or shared).

3. SCENARIOS OF USE

The application is flexible and can TimeLine in three different scenarios.

TimelineApp(Android OS 2+)

TimelineApp(Android OS 2+)

JSON/REST

mood by a moving pinpoint displayed on the map. The social visualization builds on social networks by regularly posting the average mood on Twitter (Figure 3-c). This integration can provoke reflection also

larger communities and users that are not co-located. These interfaces and challenges connected to described in (Mora et al. 2011).

Tangible, ambient and social visualization of the TimeLine (only average mood)

TimeLine is implemented following a client-server paradigm: a mobile application running on android devices acts as a client (TimelineApp) and a cloud service works as a server (TimelineCloud), Figure 4.

provides user interaction interfaces, data storage for private timelines as well as functionalities for adding contents to a timeline. It is developed adopting a model-view-adapter (MVA) architectfrequently used to implementing Android applications because of its flexibility.

side, implements collaboration features like synchronizamong clients and the integration with the third-party interfaces described in Section communicate via a RESTful interface using JSON as markup language for data object exchange.is exploiting the Google App Engine framework, which also provides web hosting and permanent data

. In the current prototype, synchronization of contents is manual, i.e. users a button to initiate synchronization between the server and the client. To overcome some of the disadvantages of this solution we did however implement automatic push of timeline contents on-events, items and moods are immediately pushed to the server. In this way the server content, while clients sync on user request to keep updated. The synchronization mechanism also uploads any content generated using the app offline (e.g. using a smartphone in flight mode or without ITimelineCloud also acts as email gateway for sending timeline reports, an email message listing all the items stored in a timeline (either private or shared).

Figure 4. Client/server architecture

SCENARIOS OF USE

The application is flexible and can be used in different scenarios. Here we briefly sketch TimeLine in three different scenarios.

TimelineCloud(Google App Engine)

Thi

The social visualization builds on social networks by This integration can provoke reflection also

and challenges connected to

Tangible, ambient and social visualization of the TimeLine (only average mood)

server paradigm: a mobile application running on android e works as a server (TimelineCloud), Figure 4.

provides user interaction interfaces, data storage for private timelines as well as functionalities adapter (MVA) architecture,

ronizing of shared timelines ection 2.3. Architecture tiers

communicate via a RESTful interface using JSON as markup language for data object exchange. The service web hosting and permanent data

synchronization of contents is manual, i.e. users have to push a button to initiate synchronization between the server and the client. To overcome some of the disadvantages

-creation, meaning that server always has the updated

to keep updated. The synchronization mechanism also uploads any ne in flight mode or without Internet access).

sage listing all the items

used in different scenarios. Here we briefly sketch the possible use of

ird-party services

ISBN: 978-972-8939-66-3 © 2012 IADIS

216

Meetings. Participants of a meeting can be asked to annotate a shared timeline by indicating their mood or writing down notes about their feelings or ideas. TimeLine is not intended to be a journal, for example to write meeting minutes. Rather, it should be used to write issues that are not necessarily related to the specific topics in the agenda, but more general about the interaction in the team. For example, it might be useful to note that a certain presentation could be improved or that a certain discussion has got too long or distressing. This information would normally not go into the minutes, but can be useful for the team to reflect for example on their communication and cooperation patterns or on the effectiveness of their meetings, with the aim to improve in future instances.

Field trips. A school class can use a shared timeline during a field trip to capture notes of different types and look at them later on to revisit their learning experience. This might help to identify, for example, events that have been particularly interesting, strategies that they have adopted to cooperate during the field trip, and ideas that are worth exploring further. The teacher can look back at the timeline to identify e.g. possible improvement to the scaffolding that is provided to students or moments that students have particularly enjoyed or disliked, and use this information to inform the planning of the next trip.

Development projects. Development projects, for example creating software, are normally involving teams of people with different roles and knowledge. In this case, a shared timeline might be used to record events that members feel are significant, personal impressions of the development, and ideas about how the process could be improved. After the project, TimeLine can be used to revisit the experience, as a stand-alone tool or as an additional source of data, in the context of structured project de-briefing/retrospective (Derby et al. 2006). Individuals might benefit from comparing the traces that they collected with the ones of colleagues to identify different perspectives on the project. Individual timelines might also help individuals re-think e.g., their contribution to the project and their reactions to problems.

4. EVALUATION

The application was evaluated in relation to the meeting scenario, during a three-day meeting of a large European project.

The meeting was attended by 40 persons and included long sessions with discussions and presentations, sessions in smaller groups and a guided tour of the science center in which the meeting took place. All participants were offered the possibility to use the applications on their mobile phones. Additionally, we made available 5 devices (4 mobile phones and one tablet). Before the meeting all the participants were sent an email message with information about the application, a short user guide, and instruction to download the application from the Android Market. All the participants were assigned to a group and a shared timeline was created.

At the meeting a short introduction to the system was provided, and the developers were available for technical help during the meeting. Participants could use TimeLine on the mobile phone to insert any type of supported data, but also to specify their mood using emoticons as well as using a third-party web application. The average mood was also visualized with the services described in Section 2.3. TimeLine was installed on 22 devices, including 10 different types of device from different brands and 4 different version of the operating system (Android 2.1; 2.2; 2.3; 2.3.3). The data collected during the evaluation includes observations and short interviews with the participants, the content of the timeline, and the log of the system.

Usability. Overall, the users were satisfied with the usability of the application, though some directions for improvement have been identified. It should be pointed out that the user experience considerably varied depending on the characteristics of the device. For example, users reported that the application was hard to use on devices with screens smaller than 3.7 inches, which we had used during the development. This is a general challenge to the development of mobile applications, which have to be adopted in a highly dynamic market. Users also lacked the possibility to visualize events in a timeline based on their status, for instance in order to identify more easily events to which new content has been added. Also, some users expressed that it should be easier to see which events belong to which user in a shared timeline.

Mobility. Users in this setting were not highly mobile. It was therefore not clear whether the usage of a mobile device for capturing and visualizing information was perceived as useful. However, users felt it was important to have the possibility to collect data with the application. Few desktop applications support pictures, videos and audio recording as seamlessly as mobile applications thanks to hardware components


217

available in most mobile phones. This is a strong advantage of using a mobile device for collecting data even when access to a desktop is available. When it comes to visualization, however, in cases like this when there is a shared space, ambient visualizations might be useful because they increase visibility of the timeline and provide a shared visualization of the information, increasing group awareness. Mobile devices might be appropriate for individual navigation after the event.

Usage. Users reported that they felt involved in the process of building the timeline, and that it was fun to see the events that other users shared each other, staying aware of what other users were doing or thinking about. Users added new events to the timeline, but also used the possibility to comment input from others, for example adding a comment to a picture or a smiley to an event. Emoticons were heavily used, with more than 1000 smileys (also including the ones sent in with the third-party web application). There may be different reasons for this. First, an emoticon is the easiest element to add to the timeline, since it is enough to select from 4 alternatives, emoticons are also commonly used in other computer applications (e.g. for instant messaging). Second, the mood was visualized in the room in different ways. This occasionally triggered a playful attitude, with people trying to change the general representation of the mood and in addition, and also put more focus on this type of data. Finally, the heavy use of emoticons might also reflect the perceived relevance of this type of information. However, given the data we have, we cannot make any final statement about this and further investigation is required. During the meeting, notes and pictures were also added to the timeline, but not video and audio.

If we look at the textual notes, we can see that they were used in different ways. In some cases they were used to report bugs in the application, for status updates (e.g. “I am now attending the technical meeting”); for quick exchange of messages; for noting down things that one find relevant. Though it is difficult to assess what might be useful for reflection and what not, it is clear that some notes were clearly intended to record information that might be useful to rethink the process and improve it, e.g.

“Sounds like it is a lot of criticism” “I think I used too much time for my slides, however, it was interesting” Investigating the usage of the application, we built a graph of the average mood for each day of the

meeting. (Figure 5 provides the graph for the first day.) The graph shows a number of peaks. In order to understand the graph, we overlaid events from the TimeLine application on the particular day, at interesting areas of the graph, e.g. decrease or increase in mood.

Figure 5. Mood change during the first day of meeting (highest line: valence; lowest arousal)

A first peak (positive feeling, but low energy) is around 13:30, when many started to feel the need for a break. After the lunch, a rise in the valence and arousal can be observed. In the same period we can also see a peak in number of events during an hour. Between 14:00 and 15:00, 8 events, with a total of 15 items were collected. This was the highest number of events and items in one hour during our evaluation. This can be

ISBN: 978-972-8939-66-3 © 2012 IADIS

218

explained by a guided tour to a nearby research facility. Another interesting decrease in valence and arousal can be seen starting at note N2, at approximately15:45. This note was added during the startup of a new session that eventually ended up in an important discussion of one of the main themes in the project. There are 4 events created during this session. Interestingly all the events are commenting the mood, not the discussion, or any specific events leading to the decreasing mood. The only event linking the mood to the discussion is event F4. But it only states that there is a connection between the mood and the current discussion, not explaining it. What we observed being there during this discussion was that the persons involved in the discussion were too engaged in the discussion, and did not have the time to create events or adding their mood using the tool. The persons contributing to the timeline and adding mood were the ones that didn’t play an active role during the discussion, and that might have felt a little bored as the session lasted over 2 hours without a break, and wanted to point this out by adding their mood and emphasizing the bad mood using the timeline.

5. IMPLICATIONS FOR DESIGN AND DEPLOYMENT

The evaluation confirmed that a timeline can help to capture information about a shared experience from different perspectives and it is easy to understand. Navigation within a timeline is also straightforward.

Multiple metaphors. A timeline is a simple and widely used metaphor for visualization. A shared timeline can be used to provide a team representation of a shared experience. Alternative metaphors should be considered and possibly integrated for getting different perspectives on the reflection data. For example, for work experiences characterized by a high degree of mobility it might be interesting to look at place as an alternative or complementary metaphor. The design challenge is to identify and support a suitable set of metaphors for visualization of reflection data, providing an easy switch from one to the other so that a user can re-visit a work experience looking from different standpoints. Multiple metaphors might also be useful to make sense of information and consider different types of information. For example, if we look at the average mood during the evaluation (Figure 5), it is difficult to make sense of it using only the information that is in the timeline. If we take into account that emotion is not only about valence and arousal but also has relational and situational aspects (Barrett et al. 2007), additional information about the situation is useful. By relating the timeline for instance to a process model, in this case simple information about steps in the meeting, it becomes easier to make sense of the information.

Capturing and comparing multiple perspectives on a shared experience. Being able to get multiple perspectives on a shared experience is critical, however our evaluation pointed out that capturing relevant perspectives might be challenging. As discussed in the previous section, during the meeting, at critical points, people with a critical role might not provide input because they are too busy. To address this challenge it is necessary to introduce adequate scaffolding mechanisms, but also provide easy modalities of input and, when relevant, connection with applications used for work that might automatically provide complementary data. In addition, during our evaluation users also pointed out the need for specific support to distinguish better and compare input from different users, especially one´s own vs. that of others. This challenge brings along issues connected to visualization, ownership, and privacy.

Tailoring to different contexts of usage. The timeline is a rather general metaphor for visualization that might be useful in a number of different situations, especially for reflecting on work practices that have a strong temporal element. However, a tailoring of the application might be needed. For example, the usage of photos to annotate the timeline could be problematic for nurses in a nursing home due to privacy constraints. Using the timeline metaphor but with a different interaction device might be more appropriate in some cases, e.g. electronic paper rather than a mobile device. In this way, the application would use a device with affordances more suitable to the specific scenario. The usage of ambient devices for visualizing information (e.g., the mood in Section 2.3) could prove to be an interesting approach for some working contexts. As we have experienced during the evaluation, the shared visualization might be used to provide a quick and non-intrusive overview of the mood in a group of users. Though the informational content is rather limited, the visualization can provide a feeling of connectedness and provoke awareness on different aspects of the collaborative effort. This approach might be particularly suitable in working environments where (1) workers share a physical place that can be enriched with ambient devices (keeping also the esthetical element in place); (2) there are a number of concerns to privacy that might limit the collection and visualization of


219

information and therefore where it might be more appropriate to provide limited information; and (3) workers have a regular cooperation that supports the emerging in time of a shared meaning for the device.

Scaffolding intended usage. TimeLine has been designed to be very flexible and it does not impose any requirement on the content that is put on the timeline as long as it can be conveyed through one the supported media. During the evaluation it was clear that this flexibility might be a source of problems because individual users might use the timeline in rather different ways. As users reported during the evaluation, they felt unsure about what type of information would be useful. This is also evident looking at the data that populated the timeline, as discussed in the previous section. Users also reported that it is easy to forget to provide input. The challenge is to identify adequate scaffolding mechanisms that can assure the collection of a coherent set of data, but allowing for multiple perspectives and flexibility of the tool for easy adoption.

Assuring reflective learning. TimeLine might be used to support reflection separately or as part of structured de-briefing and retrospective sessions. In the current version, the only support that is provided is in terms of navigation of the information along the timeline. It is up to the user to identify all relevant information. This assures a lightweight tool suitable to different modalities of reflection, counting on the personal knowledge of users about the experience to direct the navigation and selection of relevant elements in the timeline. The challenge is to identify support for assuring that the navigation of the timeline becomes a reflection session leading to learning, but without creating unnecessary constraints on users. In addition, at the deployment level, it might be necessary to define guidelines to integrate TimeLine in the context of structured reflection sessions.

6. CONCLUSION

In this paper we presented an application that allows capturing and sharing of information about an experience on a timeline. The information can be used to reflect on action and learn from experience. The application has been designed to be flexible and usable in different scenarios. The initial evaluation of the application confirmed the potential benefit of the timeline, but also points out challenges for future development and deployment.

As part of future work, we are planning to evaluate the timeline in different contexts of usage to verify its pedagogical value. We are also extending the design of the application to include scaffolding mechanisms to enhance the reflection session. Finally, we are planning to compare the usage of the timeline as a metaphor for visualizing information with respect to other metaphors, e.g. based on space or work processes.

ACKNOWLEDGEMENT

The work presented in this paper is co-funded by EU-ICT 7FP MIRROR project (http://www.mirror-project.eu) and NFR-VERDIKT 176841/SIO FABULA (http://research.idi.ntnu.no/teseo/). We thank the participants of the meeting during which the application was tested.

REFERENCES

Alonso, O., M. Gertz, et al. , 2009. Clustering and Exploring Search Results using Timeline Constructions. Proceedings of the 18th ACM conference on Information and knowledge management. Hong Kong, China, ACM Press, pp. 97-106.

Barrett, L. F., B. Mesquita, et al., 2007. The Experience of Emotion. Annual Review of Psychology. 58:31 pp. 373-403. Bennett, P., Fraser, M., Balaam, M., 2012. ChronoTape: Tangible Timelines For Family History" Proc. of the 6th

Tangible, Embedded and Embodied Interaction Conference (TEI), Kingston, Canada. Bohøj, M., N. G. Borchorst, et al., 2010. Timeline Collaboration. Proc. of the 2010 Annual Conference on Human

Factors in Computing Systems (CHI'10), Atlanta, GA, USA, ACM Press, pp. 523-532. Boud, D., R. Keogh, et al. , 1985. Reflection: Turning Experience into Learning, RoutledgeFalmer. Derby, E., D. Larsen, et al., 2006. Agile Retrospectives. Making Good Teams Great, Pragmatic Bookshelf.

ISBN: 978-972-8939-66-3 © 2012 IADIS

220

Glahn, C., Specht, M., & Koper, R., 2009. Perspective on Tag Clouds for Supporting Reflection in Self-organised Learning. S. Fischer, E. Maehle & R. Reischuk (Eds.), Informatik 2009, Im Focus das Leben, LNI P-154. Bonn, Germany: Gesellschaft für Informatik, pp. 1672-1679.

Kasi, V., et al., 2008. The post mortem paradox: a Delphi study of IT specialist perceptions. European Journal of Information Systems. 17: pp. 62-78.

Kristiansen, A. and A. Storlien, 2011. Enhancing reflection by collaboratively capturing experiences in a timeline, Master Thesis, Norwegian University of Science and Technology, Trondheim, Norway.

Krogstie, B. R., 2009. A model of retrospective reflection in project based learning utilizing historical data in collaborative tools. Proceedings of EC-TEL 2009, Nice, France, Springer.

Krogstie, B. R. and M. Divitini, 2009. Shared timeline and individual experience: Supporting retrospective reflection in student software engineering teams. Proceedings CSEE&T 2009, Hyderabad, India. IEEE Computer Society.

Mora, S., Boron, A. and Divitini M., to appear. CroMAR: Mobile augmented reality for supporting reflection on crowd management. International Journal of Mobile HCI, IGI-Global, to appear.

Mora, S., Rivera-Pelayo, V. and Müller, L., 2011. Supporting Mood Awareness in Collaborative Settings. Proc. 7th International Conference on Collaborative Computing: Networking, Applications and Work sharing; Orlando (USA), pp. 268-277.

Russell, J., 1980. A circumplex model of affect. Journal of personality and social psychology. (1980), 1161–1178. Schön, D., 1983. The Reflective Practitioner. Basic Books, Inc. Wongsubhasawat, K., J. A. G. Gomez, et al., 2011. LifeFlow: Visualizing an Overview of Event Sequences. Proc. of the

2011 Annual Conference on Human Factors in Computing Systems (CHI'11), Vancouver, BC, Canada, ACM Press, pp. 1747-1756.


221

LOCALEARN - A TOOL FOR EDUCATIONAL DISCOVERY IN THE LOCAL URBAN ENVIRONMENT

Liselott Brunnberg, Pelin Arslan and Federico Casalegno Mobile Experience Laboratory @ Massachusetts Institute of Technology

20 Ames Street, Cambridge, MA 02142

ABSTRACT

In this paper we present a learning tool for educational discovery in the local urban environment. Challenged by missions and guided by video templates on a mobile phone, students construct documentaries about topics within their local context, with the end goal of furthering their comprehension of a topic as it relates to their community. Through this exploration process, we aim to encourages civic engagement and foster a contextual, collaborative and constructive learning environment. The tool addresses the challenge to scaffold and control the learning process when education is moved out of the traditional class room setting. It further addresses the potential of using mobile media as a tool for educational reflection. We demonstrate the applicability of the tool by presenting an implementation aimed to teach the participants about global and local issues related to sustainable water use. Moreover, we will present a deployment of the implementation with a class of high school students in Italy and provide initial user feedback on the learning experience. The user feedback suggests that guided mobile video creation can be used as a powerful tool within contextual learning. Students, at the end of the use had gained a better understanding of their city’s and their own water usage, and felt better prepared to make sustainable decisions.

KEYWORDS

Contextual learning, design, mobile, narratives, video, sustainability

1. INTRODUCTION

As mobile devices with high-quality recording abilities proliferate, they are being increasingly utilized by young people to produce media content that is then uploaded, shared, and disseminated on social networks and other online distribution sites, such as Facebook, YouTube, Bambuser, Flickr etc. However, it has been observed that a gap exists between these informal learning activities, and media education in a formal educational environment (Bull et.al, 2008). The intellectual and creative process inherent in media creation lends itself well towards engaging students within learning experiences, especially those centered on locally relevant topics. By providing the learner with the tools to creatively construct content there is an opportunity to deepen the understanding of the topic. Or as Seymour Papert (1980) pointed out in his Constructionism theory, learning is most effective when the learner is given the opportunity to experience by doing and constructing a meaningful product. Another strength of using mobile devices within education is the possibility to learn in context. Hence, the education can be moved from a formalized class room setting to a physical context where the learning objective might make more sense. By learning in physical context a learner can easier relate information to their own personal frame of reference. However, when learning in a classroom, the teacher has full control over the learning process. The same degree of control does not apply when the students are by them self outside a formalized class-room setting. How to scaffold and moderate the learning process provides an important challenge within mobile and contextual learning (Frohberg, et.al., 2009). Consequently, an educational tool for mobile and contextual learning has to provide sufficient guidance such that the student makes sense of the leaning process and its goals.

In this paper we present a tool aimed to engage students in educational discovery through mobile video production. The tool promotes an explorative and contextualized learning approach in which students discover and explore assigned topics within their own local environment, such as their school, neighborhood, community and city. The tool provides support to scaffold and control the learning process by the means of

ISBN: 978-972-8939-66-3 © 2012 IADIS

222

assigned missions and templates for video recording. Apart from an introduction to the learning tool we will in this paper also present a use case that demonstrates how the concept of missions and video templates can enable and control a contextual, collaborative and constructive learning process. This use case is designed with the objective to educate teenagers on sustainable water use. By using mobile video as medium the students engage in a learning-process where the end product are set to be a documentary communicating the tought topic. Finally we will present the results from a three days workshop where a class of teenagers used the technology. During the workshop the students worked in groups, learning through various means such as conducting interviews, surveying questions to the public, and engaging in role-playing scenarios where they took the role as e.g. reporters, environmental activists, or private water company owners. This narrative exploration process taught the participants about global and local issues related to environmental impact of bottled water consumption and the predicted future of natural water resources. By exploring the topic in context, it contributed to an increased awareness and discovery of local matters, thus providing the students with a contextualized perspective on this global issue.

2. RELATED WORK

The work presented in this paper is above all related to the research area of mobile and contextual learning. Mobile learning is an extensive research field and a range of projects explore the prospect to incorporate the physical context into the learning experience. Several projects use for example the museum as physical context for mobile learning by providing the learners with an electronic guide (e.g. Bo, 2005; Proctor & Burton, 2004). Another emerging area makes use of the neighborhood as learning context. Paulo et al. (2008) explore the option to turn the mobile devices in to a networked measuring instrument. By taking the role as citizen scientists the learner can use the tool to investigate issues related to environmental sustainability by measuring for example air quality. The mobile technology support learning activities by measuring and visualizing the sensory data for the user.

At the same time as the above projects make interesting use of physical context within educational practice they don’t address the issue of control. It is here interesting to take a look at pervasive games designed for learning purposes. Pervasive games incorporate the player’s physical context into the learning experience and provide rules and goals to engage the user in the experience. Hence, it provides valuable insights on how to scaffold a learning experience in physical context where motivation and education are important factors. The aim of the pervasive game Power Agent is to motivate and educate teenagers towards energy conservation in the home (Gustafsson & Bang, 2008). The player is a secret energy agent with a mobile phone as his/her main tool. Through the mobile interface the player receives assignments to save the world from an energy crisis by saving energy in their own home. The game is connected to the household’s automatic electricity meter reading equipment via the cell network, and this setup makes it possible to use actual consumption data in the game. When players turn on and off electrical appliances in their homes they receive feedback on their actions within the game. Results from a deployment suggest that the game concept, and hence the use of phone generated assignments, was highly efficient in motivating and engaging the players and their families to change their daily energy consumption patterns during the game sessions. Also the game Mad City Mystery (Squire & Jan, 2007) takes a guided inquiry approach to learning within physical context. It is designed for Earth science students and through the course of the game, players talk to virtual characters to learn life histories and access documents describing chemicals, conduct simulated tests for PCBs, TCE, and mercury, and must piece together an argument about the cause of the death. Mad City Mystery also introduces another important factor, namely the design for communication and collaboration. As Schön (1983) points out, working together can improve the reflection on action. Consequently, collaboration among learners is important when learning in context. During the course of the Mad City Mystery game the students collaborate and communicate in groups by taking on different roles. By playing as doctors, environmental scientists, and government officials, they investigate the topic from different perspectives and collect different pieces of information to solve the mystery.

The projects presented above scaffold the learning process such that it enables guided and situated reflection, individually or in groups. However, the students are left without any meaningful product as result of their efforts. As earlier mentioned, by providing the learner with the tools to creatively construct content there is an opportunity to deepen the understanding of the topic. In our case we explore the use of mobile


223

video. Content construction of mobile video is earlier explored in the MoViE project (Tuomi & Multisilta, 2010). MoViE is a social mobile service that enables users to create video stories using their mobile phones. It was deployed with 8th and 9th grade students that used MoViE as a mobile video blogging research instrument to learn about Biology and Geography. The students first got to know the subject with the help of ordinary textbooks and the Internet, then they planned a manuscript for the mobile videos. They could use the MoViE application to upload videos, create remixes, watch videos, rate videos and reply to a video with their own video. The study shows that students became more active performers and participators in the classroom. Consequently, it indicates a positive use of mobile video as part of the education. However, the project does not explore the use of video as a tool for contextual learning. Neither does if explore the design challenge to scaffold the leaning process outside the formal class room setting.

We believe that by providing sufficient scaffolding of the learning process, mobile video creation can be used as a powerful tool to engage the student in a creative and collaborative learning experience in context. In the next sections we will present the learning tool and how it is design to guide and control the learning process and motivate the creation of a meaningful product.

3. THE LEARNING TOOL

The educational tool described in this paper enables a contextualized, collaborative and constructive learning experience that addresses the needs of students as well as teachers. It combines web and mobile applications to allow for geo-located video production and sharing. By using the mobile application on an Android phone the students can record geo-referenced video content that instantly can be shared with other students on a community website.

The tool addresses the challenge to scaffold the learning process when education is taking place outside the formal class-room setting by introducing the concepts of missions and video recording templates as learning formats. More precisely, the mobile application scaffolds and moderates the learning process by providing missions to complete as well as video templates that guide the students during each mission and structure the individual videos themselves. A video template is comprised of a set of “shots, where each shot consists of a direction and duration (see figure 1).

Figure 1. Screenshot of mobile phone: video template consisting of 8 shots

Figure 2. Students recording videos

The directions are displayed on the screen of the mobile device while a user is shooting a video, along with a progress bar indicating the time remaining of the shot. The duration can be infinite (∞), a maximum time (≤ n) or a set time, depending on the character of the displayed direction. As such, a video template act as an automatic editing tool and also give the ability to dictate creative aspects, such as camera angles, or guide the content of the video itself, giving instructions to students for how to fulfill certain roles or what topics to speak on. Hence, it functions as an instructive tool which assists the students not only in the learning process but also in the creation of a meaningful product through media production.

When the student has recorded all the shots of a template, the videos can be uploaded to the server by simply pressing a “Publish” button. Once published, the geo-located video clips become available on the web site and can be viewed on a map or played in a narrative sequence. The website provides for further reflection and education in the classroom setting, and also a means to share content to a greater audience.

In addition to an interface for content sharing the website also provides a customized interface for the administrators (e.g. teachers), allowing them to create missions and their associated templates. Consequently, it functions as a general learning platform that easily can be tailored to fit specific learning objectives (Giusti et.al, 2012). When the administrator creates or modifies missions and templates on the content management

ISBN: 978-972-8939-66-3 © 2012 IADIS

224

site they are automatically uploaded to the phones that are paired to the website and made avaliable in the mobile application. In the next section we will present an implemented use case which illustrate the applicability of the tool.

4. THE USE CASE

The use case was implemented for an educational workshop involving a class of high school students in Northern Italy. The workshop aimed to teach the students about global and local issues related to sustainable water use such as environmental impact of bottled water consumption and the predicted future of glaciers and other natural water resources (Brunnberg et al, 2011). Through their participation the students were involved in the creation of a video documentary centered on the subject matter. The students cooperated in groups of four to five persons, and conducted interviews, surveyed questions to the public, and participated in role-playing scenarios, where they took the role as reporters, environmental activists or private water company owners (figure 2). Through this creative and exploratory process, students studied the topic from a multiple perspectives: private versus public water, CO2 emission, climate change and melting glaciers as well as cultural value of water for the local community.

4.1 Missions

When opening the mobile application the students were presented with a list of seven missions, each dealing with diverse but interconnected aspects of sustaiable water use. Upon selecting a mission, an introductory video dealing with the subject was played and at the end of the video the student received an assignment. To complete the mission the students were not only required to investigate and solve the assignment, but also to record video content such that it composed a scene in the documentary. Consequently, when the group had completed all missions the produced documentary would be composed of seven interconnecting scenes presenting the topic based on the students investigations and their own interpretation and understanding of the matter.

Figure 3. Mission page Figure 4. Video recording templates

4.2 Video Templates

During a mission the students made use of video templates to accomplish their assigment. Video templates were meant to control the learning process by guiding the investigation and the creation of the video itself. According to Sharples et al. (2007) the level of control is an important challenge for any learning process. Learners are not homogenous, but individuals having different creative abilities and needs for guidance. Consequently, it is necessary to provide freedom for creativity while still providing guidance by scaffolding the activities. With this in mind we experimented with different types of templates that the students could choose from during a mission. When the students pressed the record button they were presented with a list of six video templates to choose from, one specific for the mission and five generic which applied to all


225

missions (see figure 3). Mission specific templates provided detailed step-by-step guidance of what to film. The generic templates were available within all missions and provide structured but only general directions for certain tasks, i.e. to conduct an interview, make a video montage, to record a Vox-pop (voice of the general public). The missions also included the option of a freestyle template, which provided no directions or time limits during the video recording. Depending on the mission and how a student choosed to approach it, different templates would work better than others; therefore, students were challenged to select a template that best corresponds to their conceptualization of the mission. Students could optionally make use several templates to compose more than one video to submit to a mission.

When the students had recorded all of the shots in the selected templates (that is, completed the mission), they could choose to uploaded the recorded videos to the server. Once uploaded, it became available on the website where all the video clips produced by a group of students could be viewed on the map or sequentially, forming a dynamically generated video documentary.

5. USER STUDY

5.1 Method and Setting

The implemented prototype was deployed and evaluated during an educational workshop with twenty participating students. The class was in the first of five years of high school at a professional school, where students were technically trained with either a mechanical or electrical focus. The students were all males, and fourteen years of age aside from a few who had been held back in school. The class’ teacher divided the students into four groups with one student in each group appointed as a leader. Each group received a mobile phone with the application installed.

The workshop was not officially integrated into the school curriculum, thus time available for its deployment was limited and took place during three school days in one week. During the first workshop day, the students were introduced to the project and received instruction on how to use the tool. After this two-hour introduction, students spent the remainder of the day working in their groups to accomplish missions. A researcher shadowed each group to observe and document group dynamics, activities, interactions, the students’ engagement or issues with the technology. The next workshop day began with a short class discussing their experiences and thoughts about the technology and program. After, the class viewed a film featuring a selection of videos created during the previous workshop day. The remainder of this second workshop day was also spent working in the assigned groups to accomplish missions. The final day was devoted to user feedback. The students first completed a post-experience questionnaire and then took part in focus group discussions. Additionally, the teacher was interviewed regarding the use and potential of the tool as part of the education. Due to the limited time frame, aspects of the concept and design could not be evaluated, such as interaction with the website or impact and results from extended use. However, the study provided valuable insights of the learning process and potential of the tool.

In the next section we will present results from the user study based on the observations, questionnaires, focus groups and feedback from the teacher.

5.2 Results

During the workshop the students were on their own without any guidance or directions from a teacher. Instead, the missions and video templates in the mobile application provided the main mechanism for guiding the students and controlling the learning process. Consequently, it were important that these control mechanisms were easy for the students to understand, were motivating to use and that they provided interesting and relevant content. The results from the study are in the subsequent text divided in three sections, i.e. learning in context, collaboration and the construction of a meaningful product.

5.2.1 Learning in Context

In order to experiment with different learning contexts the missions were taking place in varied settings. Some of the missions had students going around the town to record footage while other missions were carried

ISBN: 978-972-8939-66-3 © 2012 IADIS

226

out inside the classroom or on the campus. For the first scene in the documentary the students were taught about natural water resources in the

region, such as nearby glaciers, their provision of clean drinking water to the town and their role in the production of hydroelectric power. Their mission was to create a small video portrait of water where thy would show and tell us about its source, use and presence in the city. For this mission the teacher, along with a local expert on water and geography had selected a set of locations: old fountains for drinking and washing clothing, a channel transporting water from the mountain, and a hydroelectric plant. Consequently, each group was given a specific site to explore and film. One group by chance met a man and his elderly mother who were well informed about the old fountain they visited. The students conducted an interview and recorded video while the couple explained the fountain’s history, showing old pictures and reading old poetry about the fountain. This encounter made an excellent impression on the students and helped them to realize that there were many interesting things they did not know about their small town.

During the second and third missions the students were free to choose locations by themselves. The second mission was to investigate and explain water consumption in their town: did citizens prefer bottled or tap water? Consequently, all the groups were downtown speaking with local residents and visitors. Many of the students did Vox-pop's, that is, a series of short interviews in public space where each person is asked the same question and the aim is to get a variety of answers and opinions on any given subject. The third mission focused on water purity, asking students to investigate the quality of tap water in their town. One group conducted an interview with a local chef devoted to serving tap water in his restaurant. Another group conducted an interview with a local water activist, who they happened to meet when recording a vox-pop during the second mission. Another group surveyed people downtown asking them whether they felt tap or bottled water was cleaner, and discussed water purity regulations with a local police officer. The final group made a short role-play scenario around the facts listed on a bottled water label. For the fifth mission, the students came back to school for a water taste test. Each group received three samples of water: two from purchased bottles and one from the tap. Few of the students could discern the tap water sample, and many were surprised by the lack of perceptible difference. The following workshop day the students carried out missions six and seven. The local expert on water and geography was present during this session. For mission six, which concerned global warming and melting glaciers, the students received a small booklet that the expert had written as well as a map displaying the surrounding glaciers and their names. Students went outside for this mission, but remained on the school’s campus because of limited time; however, the snowcapped mountain range surrounding the town provided a perfect backdrop for the students’ footage when they were urged to present the local glaciers and their current situation. During the last mission, the students stayed inside the classroom and were expected to investigate, imagine, and report on the prospect of their town in 2050. The local expert was now available to answer questions or be interviewed by students. Several groups were inspired by the mission template to divide themselves into different roles (such as an activist, a private water company owner, a citizen, a politician, etc.) and perform a panel discussion.

The post-experience questionnaire revealed that 90% of the students felt that they generally understood the missions. Only one student marked negative on this question and one student did not answer. More detailed questions reveal how they perceived the individual missions. According to the results, the most interesting missions in terms of the subject matter and their learning were missions one and two, which received the most votes. For many of the students, these two missions were also the easiest to understand. The mission they indicated as most fun was above all mission two, which received half of the students’ votes.

The focus group discussions provide further information on mission preference. Both focus groups mentioned the first and the last missions as their favorites because they liked interviewing people and learning about the city (mission 1) and role-playing and discussion (mission 7). They said their least favorite missions were mission three and mission seven because they were “boring and hard to research and interview people about”. Mission three, which concerned water purity, was difficult for the students because the mission-specific template requested that students use a computer to research information, but computers and other researching tools were not available during this day. As a result, students had to be more creative, but with less guidance and lacking the content to comprehensively respond to the mission, some student groups floundered. Mission seven was challenging for many of the students. They had limited time, were confined to the school’s campus, and did not understand the mission content (CO2 emissions, global warming, and melting glaciers) as well as some of the earlier missions (water resources, bottled versus tap water, etc). Mission five, the taste test, was not particularly favorable or unfavorable to the students. One focus group mentioned that although the mission’s material was easily comprehensible and of some interest,


227

they preferred missions that took place outdoors and provided more opportunity for exploration. The questionnaire also revealed that most of the students believed they learned a lot about water during

the workshop. The focus groups provided further insights into what they learned. During these discussions, they claimed to have learned about:

Focus group 1 I) How fountains had developed in their town II) Glaciers and Carbon dioxide emission III) That their town has high quality tap water and that most residents prefer to drink it over bottled

water. Focus group 2 I) It is good to drink tap water and that glaciers are in danger II) How to conduct interviews III) How to use mobile phone to record video The focus groups further revealed that most of the students enjoyed learning about water within the

context of their city. They appreciated discovering where their water comes from and that their town has particularly high quality water. Above all, the students felt they learned most by conducting interviews with people in the area, discovering what the locals knew about water, and surveying water assumptions and preferences. The students believed their perception of water consumption and local resources changed and they from now on would avoid drinking bottled water. In the future, they would like to use the technology to learn more about other topics in their community, such as local history or pollution. It is also worth to notice that students that generally had a low level of focus when participating in class-room activities actively used the tool and engage in the workshop activities.

The teacher recommended that the tool should not be introduced as a topic by itself but rather be integrated in the general school agenda. In Italy the school agenda contain four to five big themes per year, such as renewable energies, science etc. By integrating it as an complementing tool within these themes would allow for a longer period of use and a better understanding of its actual potential.

5.2.2 Collaboration

The students were divided in groups of four to five persons. Based on our own observations and feedback from the teacher we can conclude that the size of the groups worked well. The missions usually triggered discussions within the groups. Not seldom we observed the students vividly discuss how to solve a task, what to film, what to say in front of the camera or who to interview. According to the teacher, the fact that they were forced to use the same device within the group created very good spirit in the classroom. The teacher particularly appreciated the fact that the students, by acting in separate groups, learn and experienced different things that they later could share with the rest of the class. He also appreciated that this experience could shared on the Internet and not just within the school.

The tool guided the students to take different roles, both implicitly and explicitly. Overall, one students always had to take the role as cameraman and one as the reporter. Occasionally, the templates themselves guided the students to take roles such as e.g. environmental activist, private company owner or citizen. We observed that the students actively discussed in the group how to divide the roles and they usually took turns to be in front of the camera. We observed great differences in how students handled this task, especially when acting as the reporter. Some participants were very comfortable and had an easier time improvising while others struggled with the role and often looked for precise instructions on what to say and how to act. The teacher explained that by taking on roles and perform in front of the camera the students overcome a lot of shyness and insecurities, which is very important. We also observed that taking on roles motivated the students to participate. Students that did not have a role sometimes ended up being passive and did not engage in the discussions.

5.2.3 Constructing a Meaningful Product

The teens enjoyed working with mobile phones as tools for learning, and they were proud of their ability to learn and utilize the technology. The results form the questionnaire show that the majority of the students found the mobile application easy to use. Sixteen of the twenty students marked that they were able to learn and fully understand its use. An important function of the tool is to give the students the opportunity to be creative and to construct a meaningful product as part of the learning process. The study reveals that it was

ISBN: 978-972-8939-66-3 © 2012 IADIS

228

inspiring for the students to have the ability to produce content and immediately see the result on the mobile device. According to the teacher the tool brought forward their creative side. They liked to be creative by setting up the scenes, organizing the roles in the group, and filming the videos in different ways. During the focus group the students mentioned that they got very motivated and wanted to produce something “cool”, because they knew it would be shown for the other students in the class.

Video templates were designed to guide the investigation and the creation of the video itself. When designing the templates we aimed to find solutions that targeted a varying need for creative freedom and guidelines. This need was also confirmed by the study. We could observe that some teens required step-by-step instructions while others preferred the freedom to improvise and discover by chance. During the focus groups we asked the students what templates they preferred to use during the video recording. Here, the test group was rather split. In one of the focus groups the students preferred the mission specific template to accomplish their missions. However, they also mentioned that in the last mission (where they were filming a panel discussion) it was more convenient to use the freestyle because they could discuss and film in a limitless time frame. In the other focus group only two students preferred the mission specific template. The rest of the group preferred more freedom when recording their videos, six of the students even mentioned that they the preferred to use the one shot freestyle template, which provides no structure at all.

Although some of the students mentioned that they used different camera angles, especially when being instructed by the shot directions on the screen the results indicate that the students did not quite comprehend the concept of creating a documentary with interconnected scenes, short video clips and varied camera angles. However, this is not surprising considering the short time frame they had to explore the technology. Nevertheless, the students were able to create interesting video content on the individual sub-topics. Consequently, the technology worked as a tool for learning and reflection also at a more simplistic level, allowing for multiple levels of engagement in the learning experience. We believe that an extra level of complexity, specifically having to think about the overall narrative and topic framework, will allow for greater reflection in a broader context will produce a more compelling end result.

5.2.4 Summary of Initial User Feedback

Our user study provides initial feedback on the use of the learning tool and how our implemented design managed to scaffold and guide contextual learning, collaboration and the construction of a meaningful product. We will here summaries the main findings of the user study:

• Using the mobile phone and digital media as part of the education was appreciated among the teenagers and they had no problem understanding the technique of using the tool.

• To scaffold the learning experience through the use of missions and video templates not only worked, but also motivated participants to explore the topic in their local environment, inspired collaboration and help the students to create an interesting result.

• It was clear that the teens enjoyed working in groups to collaboratively create video content, and enjoyed sharing their work with their classmates. Knowing that the result would be shown to the others incentivized their efforts to produce something special.

• In general, the students enjoyed being able to learn outside of the classroom and they claimed it made them want to try harder than when they sat in the classroom, listening to a professor.

• They liked learning about water in their own town and it helped them relate to the topic on a personal level. We noticed that their discoveries left a stronger impression the more they engaged with their local community. Chance encounters with knowledgeable locals made the greatest impression on the students. In these instances, students felt they had learned something special and were eager to share this experience with the others.

• The tool bridged a gap between different age groups in the community • Teens that usually had a low level of focus actively engaged in a motivated fashion. • Roles motivated the student to participate • It is important to provide video templates that support a varying need for creative freedom and

guidelines. • The limited time available for the workshop made it difficult to convey the concept of a narrative and

consequently the intention to construct a video documentary as product of the learning process. Despite, the individual video scenes turned out to be meaningful products by themselves


229

6. CONCLUSION

This paper contributes with insights on how to design for collaborative construction of narrative video content within a mobile and contextual learning environment. The result benefits the research field of mobile learning. We have presented a tool for enhancing learning through guided video creation. Students who partook in a 3-days workshop had the opportunity to use the tool to explore water within their local context. Although facets of the process and technology could be reworked to strengthen the experience, by the end of the workshop, students had gained a better understanding of their city’s and their own water usage. The tool illustrates how geo-referenced media has the potential to create strong links between people, places, and information. For future tests we would like to examine how the generated media can be used in the classroom for further reflection on the topic. While our implemented use case explored water and water resources, the program and technology could be applied to numerous topics to encourage learning and civic engagement in other ways.

ACKNOWLEDGEMENT

This research project is done within the Green Connected Home Alliance, between MIT Mobile Experience Lab and the Fondazione Bruno Kessler in Italy. We thank the Swedish Research Council for partly funding this research. We also thank our research partner the MTSN Museo tridentino di scienze naturali, and the School ENAIP Trentino, Italy.

REFERENCES

Bo, G., (2005). Mobilearn. Project Final Report, Mobilearn (IST-2001-37187). Brunnberg, L., et.al. (2011). Locast H2Flow: contextual learning through mobile video and guided documentary

production. In Proc. of the MobileHCI '11. ACM, New York, NY, USA, 105-108. Bull,G., Thompson,A., Searson,M., Garofalo,J., Park, J., Young, C., & Lee, J. (2008). Connecting informal and formal

learning: Experiences in the age of participatory media. Contemporary Issues in Technology and Teacher Education, 8(2).

Frohberg, D., Göth, C. and Schwabe, G. (2009), Mobile Learning projects – a critical analysis of the state of the art. Journal of Computer Assisted Learning, 25: 307–331.

Giusti, L., Pollini, A., Brunnberg, L., Casalegno, F., (2012). En Plein Air: a mobile learning approach for sustainability education in the wild. International Journal of Mobile HCI. In press.

Gustafsson, A. and Bang, M. (2008). Evaluation of a pervasive game for domestic energy engagement among teenagers. In Proceedings of the 2008 International Conference on Advances in Computer Entertainment Technology. ACM, New York, NY, USA, 232-239.

Papert, S. (1980). Mindstorms: Children, Computers, and Powerful Ideas. Basic Books, Inc., New York, NY, USA. Paulos, E., Honicky, R.J. and Hooker, B. (2008). Citizen Science: Enabling Participatory Urbanism, in Foth, M. (ed.)

Handbook of Research on Urban Informatics, IGI Global, Hershey, PA, 414-436. Proctor N. & Burton J. (2004) Tate modern multimedia tour pilots 2002–2003. mLearn2003: Learning with Mobile

Devices. Research and Development, Learning and Skills Development Agency, London. Schön D.A. (1983) The Reflective Practitioner: How Professionals Think in Action. Basic Book, NewYork. Sharples M., Taylor J. & Vavoula G. (2007) A theory of learning for the mobile age. In The Sage Handbook of Elearning Research, (eds R. Andrews & C. Haythornthwaite), pp. 221–247. Sage, London. Squire K.D. and Jan M. (2007). Mad City Mystery: Developing Scientific Argumentation Skills with a Place-based

Augmented Reality Game on Handheld Computers. Journal of Science Education and Technology, Vol. 16, No. 1, February 2007.

Tuomi, P., & Multisilta, J. (2010). MoViE: Experiences and attitudes—Learning with a mobile social video application. Digital Culture & Education, 2:2, 165-189.

ISBN: 978-972-8939-66-3 © 2012 IADIS

230

Short Papers

MORE WITH LESS VOCABULARY ACQUISITION THROUGH SMARTPHONE

APPS

Haymo Mitschian University of Kassel, School of Humanities, Department of German as a Foreign or Second Language

Kurt-Wolters-Straße 5, 34125 Kassel

ABSTRACT

The challenges in using smartphone apps to work on new vocabulary are not so much connected to technical features, but related to practical usage of didactic knowledge. Existing apps limit the diversity of learner activities in guiding them towards a more passive-receptive learning which is not self-determined, while teaching and learning theories are pushing for more active-productive learning behavior with a high degree of learner autonomy. Using a smartphone app that provides no content but only a functional framework will meet this didactical demands. Students are offered opportunities for autonomous, constructive, creative, incidental, collaborative, affective, and autobiographical learning, which brings them better learning outcomes, additionally more learning competence and more media literacy.

KEYWORDS

Vocabulary acquisition, learner autonomy, productive learning, learning with pictures.

1. MOBILE VOCABULARY

Notably in the field of computer-assisted language learning the available hardware and software is becoming increasingly powerful and sophisticated. The downsizing of computers to mobile phone dimensions had caused a major step forward and simplifications in software handling have opened up new ways of producing, processing and disseminating audio-visual media. These positive developments run the risk of being counterproductive when seen under the aspects of language teaching and learning theories. The more powerful the technology gets the less is left to be done by the students, limiting them to the role of comparatively passive recipients. This puts them in contrast to proven didactics and learning theory findings, stating that active-productive and self-driven learning activities lead to better results than passive-receptive ones inevitably predetermined by others. As seen in the past, successfully implemented innovations in the field of technology-enhanced learning had to match with the conditions of learning in order to support and not to dominate them (cf. Rösler 2007).

The options offered by the smartphone technology fit in an exceptionally favorable manner the needs that arise during the acquisition of new vocabulary. This applies not only to foreign language vocabulary learning, but also to the development and expansion of a vocabulary for special purposes, which is a crucial component of training courses in many fields. Sound knowledge in language didactics and educational psychology points out that new vocabulary is best taught and practiced in authentic learning environments and in the form of frequent, relatively short-termed repetitions. Mobile phones can be used as learning tools in places where the knowledge to be learned is to be applied in the future, and they open up new opportunities for learning in situations otherwise hardly suitable for such an activity. As powerful multi-media instruments they provide learning items in different ways, guiding to a diversity of learning techniques with positive effects on learning motivations. Additionally this feature comes along with a good tuning to different learning styles. In the mental lexicon mobile phones favor the establishment of unmediated connections between signifier and signified, in cases when the meaning of words is not transported via language but directly brought through images (cf. Schnotz 2005). Combined with the simplicity in creating


233

digital media in text, image or sound non-experts are able to produce their personal learning materials, thereby opening up a wide range of modes of learning that are valued by teaching and learning theory.

Investigating the numerous apps for vocabulary acquisition purposes offered by now, it turns out that in terms of productivity and self-determination of learning this potential still remains largely untapped. Methodologically, most of these applications are based on the principle of flashcards with matching learning items on a virtual front and back side. In a simple design there is the expression to be learned on one side of such a card and a translation, a description or sample usage on the other one. The acquisition of vocabulary by using index cards is generally regarded as a very effective method. Its strengths become clear through a comparison with word lists, self-written ones or printed sets. In fixed arrangements like this position effects and/or serial effects are likely to occur, connecting the items to be learned to irrelevant contexts and therefore leading to a kind of storage in the memory useless for later application. In case of position effects the items neighboring the new expression are remembered which only by chance will have a meaningful link to it. Serial effects make items at the beginning or towards the end of a learning sequence easier to be retrieved from memory. Both effects are to be avoided by the use of index cards permanently changing their serial locations within a learning list of items, giving room for the establishment of meaningful and therefore appropriate anchoring in memory.

2. STRENGTHS AND WEAKNESSES

A weak point of those software products that come along with all the new vocabulary is to be seen in a generally poor accordance to learning tasks in other learning processes taking part simultaneously, for example in classes or initiated by other learning materials. Moreover, manual or cognitive processes generated while producing personal flashcards may have supporting functions for a better storage in memory. They are suppressed by a ready-made tool as well. Compared to paper-based card files the strengths of digitized cards have to be seen in their simplicity in handling and stability as far as the internal organization of cards and information is concerned and, of course, in their "weightlessness" as a property which turns them into a convenient learning aid in the field. A special advantage of mobile vocabulary learning is the fact that mobile phones are carried along independently from any learning purpose. In this way they permit unplanned learning activities at places and on occasions otherwise unsuitable. The greatest benefits arise from the use of multimedia, for which media can be produced ever more easily. In foreign language learning software this turns out to be especially advantageous through the combination of written and spoken language, while in specialist learning environments the use of static or dynamic images may lead to better results. But also the threats derived from the increased performance of hard- and software are related to it.

Losses in terms of learning efficiency may be caused by the elimination of activities at first sight bothersome, such as looking up words in voluminous dictionaries or distractions during handwriting. This is because positive learning effects do occur not only during explicit learning activities such as securing understanding, practicing or memorization, but may come along with the preparation and processing of information for learning activities as well. A sometimes arduous search for a word in paper media may cause mental activities that contribute to a solid anchoring of learning items in memory. A more complex activity than manually pressing keys or touching a touch screen may initiate more intensive cognitive processes and applies more physical action to the learning process, something that had been promoted by Comenius as early as back in the 17th century (cf. Schaller 1973). Even if activities like that only prolong phases of searching in or producing of learning media, such actions may have a positive impact on learning because they extend the time of concentration on the target object. Handwriting recognition as a feature of up-to-date touchscreen devices may reopen more leeway at this point.

When producing flashcards on paper the size of the card sets the scope for the entries. If learning software is designed for user generated input the database working in the background may be responsible for some quantitative restrictions, or, when smartphone apps are involved, the capacity of the display will limit the amount of storable information. As a consequence many of the apps available right now impose strict limits regarding data volumes and data processing for learners’ input. So, for example, if not all writing systems are on hand for a Chinese student learning German, he might be handicapped in working with translations. Options to integrate self-made multimedia are often severely restricted or not provided at all in current products (cf. Mitschian 2010: 83).

ISBN: 978-972-8939-66-3 © 2012 IADIS

234

Language learning software which allows recording and storing of learner-produced language proves to be more openly constructed in this regard. In addition to given examples of intonation learners are able to record their own utterances in order to compare them to the provided ones. A reasonable extension of this feature would be the integration of a channel to import third-party recordings. Learners then would be able to listen to idiosyncratic pronunciations or get some training in understanding dialects or other nonstandard language varieties. In training units for language for special purposes some noises or other sound sequences may be important, which is for sure the case in musical training.

The use of visual media to support the learning of language proves to be less self-explanatory than the use of audio clips for this task. How exactly images support the acquisition of new vocabulary and its meaning is still widely unexplored. Paivio’s dual-coding theory for example, which has long been regarded as a key to understanding cognitive processing of pictures and words, has meanwhile lost most of its credibility (cf. Schnotz 2005). Comparatively well-known are the beneficial effects of visualizations in children’s learning for which by nature written reference material is only of limited use. The older learners are and the more experience they have with written information the more uncertain become the explanations of how visual aids support language learning.

So it is not surprising that in foreign language learning pictures as helpers in vocabulary acquisition are predominantly found with beginners where mainly words with a very concrete denotation are visualized. However, persistent learning problems often are not associated with those easily visualized concepts of content, but are more common when abstract meanings are involved for which comprehensible images, understandable by many, are hard to find. As a result images tend to be offered when they are of little use and they are missing when severe learning problems do occur.

3. LEARNING MORE WITH LESS TECHNOLOGY

The criticism outlined above focuses on two main issues: the inadequacy of the learning materials to meet the needs of learners or the requirements derived from the learning objects respectively and the limits to activities of learners with their negative effects on cognitive processing intensity. Both issues are to be met with a learning tool which provides only the framework for the upcoming learning tasks but waives all contents. A smartphone app organized in flashcard-mode and without any content at the beginning of the learning process completely fulfills this requirement. It consists only of flashcards that allocate open space for any kind of learning media on a front and a back side. The actual learning media, defined as the carriers of information, are created by the learners themselves in the course of learning processes.

All media are produced by the learner - in part under the guidance and with support by tutors – or personally derived from different sources. The learner’s own media productions are to be compiled on the smartphone, especially writings, photographs, audio and video recordings, or on a computer with high-performance internet connectivity and with expanded data processing options. Seen from a learning-theoretical and didactic point of view a tool with a configuration like this gives access to a variety of options:

• Multimedia learning - learning through written or spoken language, with static or dynamic images. Benefits:

o By combining images with target language expressions learning without recourse to another language becomes possible. This is inevitable especially in technical fields when there is no equivalent found in the language(s) commanded by the learner.

o Combinations of images with target-language expressions have the potential to generate even direct mental connections in the memory between signifier and signified as a precondition for effective language skills.

o Learning items, not or just poorly to be verbalized, can be included in the learning process by means of pictures or videos, for example, actions or just properties of things hard to describe.

o Learning aim shifts from written to spoken language are possible. o Adaptation to different learning styles through media preferences. o Learning activity variations by changing media. • Situational learning - learning at places of authentic language use. Benefits:


235

o The media for the flashcards are created in places and on occasions in which there is contact to the target language. This learning environment fits the item to be learned and promotes application-relevant cognitive processing.

o Learning exercises can be performed on these same places and also receive a high degree of authenticity.

o If necessary in appropriate situations, the learner’s own learning materials are at hand to be consulted. o During all events of situational learning incidental learning is promoted. • Learner activation, creative, autonomous, constructivist learning: the students receive no ready-made

learning materials determined by others which fit their individual learning needs more or less accurately, but create their own ones. Benefits:

o Active and productive learning has been shown to improve cognitive processing more than passive and receptive learning.

o Important learning processes take place as early as during the creation of learning materials. o Learning materials suit individual learning needs because they match the learner’s previous knowledge

and skills. Besides they offer opportunities to apply preferred learning techniques. o With appropriate training or other kinds of assistance learning skills could be broadened and new

learning techniques be achieved. o Creativity ensures individually composed flashcards bringing along a high degree of personal

involvement. • Affective, emotional and autobiographical learning: learning processes always involve the entire

personality. This is why new knowledge is not only connected in a proper logical manner with existing knowledge and thus secured, but also by widely uninfluenced rationally incomprehensible and mostly highly individual processes in the mental lexicon. The use of personally generated or at least self-selected items associated with the learning media supports all these types of incidental learning.

• Collaborative learning: the exchange via an Internet portal, set up as a contact point for users of the app, breaks through the isolation of individual learning. Learners with similar learning tasks make their ideas accessible to each other and receive appreciation for efforts in the design of learning media in case their ideas are valued by others.

The challenge connected to all these approaches is their applicability, not the technical features of the application. All components that are required already exist and are widely approved. In spite of all constraints that are always connected to didactic statements the arguments in favor are well grounded. Difficulties will arise to ensure the necessary level of acceptance among potential learners. Most students will be unable to cope with the task to gain sufficient expertise with all the options opened up by an app which offers nothing but blank index cards and some procedures to manage them. Experience has shown that detailed instructions supplied in the form of written systems do little to help overcome such an entry threshold. Therefore, there will be demand for specific training to make students familiar with the potential of a learning tool like that, maybe affecting their teachers as well. The reward for these efforts will not be limited to additional knowledge or gain of skills in the learning field, but an extension of the learning skills that will be useful for many learning tasks also is to be expected, as well as an increase in the general media competency, triggered by the productive use of the learning media.

REFERENCES

Mitschian, H. (2010). mLearning – die neue Welle? Mobiles Lernen für Deutsch als Fremdsprache. Kassel University Press, Kassel

Pavio, A. (1986). Mental Representations: A Dual Coding Approach. Oxford University Press, New York Rösler, D. (2007). E-Learning und Fremdsprachen – eine kritische Einführung. Stauffenburg Verlag, Tübingen Schaller, K. (1973). Comenius. Wissenschaftliche Buchgesellschaft, Darmstadt Schnotz, W. (2005). An Integrated Model of Text and Picture Comprehension. In: Mayer, R.E. (Ed.). The Cambridge

Handbook of Multimedia Learning. Cambridge University Press, Cambridge, 49-70

ISBN: 978-972-8939-66-3 © 2012 IADIS

236

ENHANCING SCIENTIFIC INQUIRY AND PRACTICING NEW LITERACIES SKILLS THROUGH ICTS AND

MOBILE DEVICES

Shiang-Kwei Wang, Hui-Yin Hsu and Lisa Runco New York Institute of Technology

P.O. Box, Northern Blvd, Old Westbury, NY, 11568-8000

ABSTRACT

New literacies have become an important set of knowledge and skills students need to participate fully into their civic life in a global era. The optimal way of cultivating these literacy skills lies in the successful integration of ICTs (information and communication technologies) and mobile devices into content area learning. This study is an exploratory case study to examine the feasibility of integrating new literacies into science classroom instruction. Three middle school science teachers implemented a learning module designed to incorporate new literacies and science literacy components. The results suggest that ICTs and mobile devices allow students to practice new literacies and scientific literacy, facilitate their cognitive tasks, and establish a sense of inquiry community. The paper will demonstrate the process to conduct scientific inquiry activity through the integration of ICTs and mobile devices.

KEYWORDS

New literacies, ICTs (information and communication technologies, mobile device, life science, exploratory case study

1. BACKGROUND OF THE STUDY

1.1 Inquiry-Based Science

Even though there has not been an agreement on the definition of inquiry (Barrow, 2006), educators agree that science teachers should adopt inquiry-based teaching to develop students’ skills of inquiry (Howes, Lim & Campos, 2009). Inquiry skills refer to the ability to identify scientifically testable questions that connect to real world problems, formulate a hypothesis, design an investigation plan, collect and analyze data, evaluate the hypothesis and draw conclusions to solve problems or generate alternative explanations (Lee, Linn, Varma & Liu, 2010; Khan, 2007). Educators recognize the importance to develop students’ inquiry skills and researchers have been advocating the shift towards more inquiry centered learning, but inquiry has not become a common practice in science classrooms (Crawford, 2007). Windschitl (2003) identified different forms of inquiry practices based on students’ levels of independence: confirmation activities (students follow a given procedure to confirm known scientific principles), structured inquiry (teacher provides a research question and procedure to allow students to investigate the answer), guided inquiry (teacher provides a research question but students decide on the procedure to investigate the answer), and open/independent inquiry (students develop their own research questions, design the procedure to investigate the answer). Open inquiry rarely occurs. It requires a great amount of time for teachers to nurture students’ independent inquiry skills because the procedure is complex and intellectually challenging; however it is an essential activity to facilitate students’ construction of knowledge and understanding of the nature of science (Germann, Haskins & Auls, 1996). Thus, our goal is to facilitate teachers to provide an open inquiry experience through the use of supporting technologies.


237

1.2 New Literacies Practices in Middle School Science Classrooms

Traditional literacy is defined as the ability to read, write, comprehend and communicate, and the term “new literacies” emerged to respond to the implications of literacy practices using digital technologies. Leu, Kinzer, Coiro and Cammack (2004) refers to new literacies as the ability to use ICTs (information and communication technologies) to “identify important questions, locate information, evaluate usefulness of the information, synthesize information to answer questions, and communicate the answers to others “(p. 1,572). The new literacies skills not only align with scientific literacy that support the inquiry process, but also are a set of knowledge and skills students need to possess to succeed in the global society (Scherz & Oren, 2006). Educators have been advocating the use of ICTs in K-12 classrooms, because they believe that allowing students to use the technologies they use in their daily life for academic work would positively affect their learning motivation and collaboration skills (Campbell, Wang, Hsu, Duffy & Wolf, 2010; Kim, Hannafin & Bryan, 2007; Solomon & Schrum, 2007). Even though students’ technology use outside of schools is prevalent, educators feel that schools have not been responding to students’ preferences and habits to use technology to consume and produce information (Li, 2007). Technology is accessible in most classrooms, but many teachers still lack the proper support and training to use it (Ertmer, 2005; Kumar, Rose & D’Silva, 2008), let alone to use it to practice students’ new literacies skills.

Previous research on using new literacies to support scientific literacy is scarce. Other ICT integration in science has been focusing on web use, especially for researching information (Kuiper & Volman, 2008). Activities limiting in researching information online or produce information using computers are not sufficient enough to support students’ independent inquiry task. Therefore, science educators need to explore the use of ICTs to enhance new literacies practices that support scientific inquiry.

To redesign the curriculum, we gathered a team consisting of a professor specializing in ICTs and mobile device integration, a professor specializing in new literacies, and a professor specializing in biology. After consulting with the three participant teachers on the available classroom resources, technology support, and how they typically teach the unit of human impact on the living environment, the team designed the module with five inquiry activities. Throughout the five activities, teachers first model the inquiry process, gradually releasing responsibility to the students, and then allow students to independently initiate the open inquiry process. In the process of applying new literacies to enhance scientific literacy, the mobile technology and ICTs play a vital role in supporting students’ research, and to evaluate information, collect and analyze data, and interpret and disseminate results (Table 1).

ISBN: 978-972-8939-66-3 © 2012 IADIS

238

Table 1. Inquiry activities to investigate how human decisions and activities affect aquatic living environment

Sequence Activity Description Pre-inquiry discussion Students brainstorm what factors affect water quality, and what factors are human caused. Teacher will

establish students’ background knowledge on water quality indicators. Activity 1: Students research information related to real-life problems

Students use search engines to find an article about water quality and its effects on a living organism. Students need to post the link of the article on the Edmodo class page and write a concluding statement that supports the explanations or arguments of the article. The article should be from a credible source, and the conclusion should be generated through scientific methods and convincing evidence. Each student needs to critique two other students’ projects.

Activity 2: Teachers model the research process

Teacher models research process. Teacher demonstrates the procedure of collecting data to answer a scientifically testable question. After activating students’ prior knowledge on two water quality indicators (temperature and dissolved oxygen (D.O.)), teacher identifies several research questions, uses a virtual laboratory book to document a hypothesis, uses a spreadsheet to log data collected from cyber resources (MySound, USGS), uses a chart to interpret data, examines if the hypothesis is accepted, and makes conclusions and/or alternative explanations. Teacher uses the laboratory book template to demonstrate how to document a research procedure. Sample research questions: • How do fluctuations in temperature affect D.O. levels in a specific body of water?

Activity 3: Students repeat the research (confirmation experience)

Students repeat the research process using the same variables. Students repeat the same procedure to answer the same research questions, focusing on different geographical locations. The procedure is to practice the use of ICTs and cyber resources, and test if the research question is repeatable. Students need to document the research process using a virtual laboratory book, and share their documentations with the class using Edmodo. Students need to critique two other students’ projects.

Activity 4: Teacher guides students through a research process (structured inquiry)

Teacher scaffolds and guides research process. Teacher works with students to identify research questions that can be answered using Probeware, then formulate a hypothesis. Teacher guides students to use a virtual laboratory book to document their research process. Teacher assists students in using Probeware to collect data, use a map to document the locations to examine water samples, and log data using a spreadsheet. Teacher facilitates students in the process of interpreting data, examining their hypothesis, and drawing conclusions. Students then share their research findings through Edmodo. Sample research questions: • What are the pH levels of each water sample? • What is the difference in pH levels collected from location A compared with location B?

Activity 5: Students independently initiate a research process (independent inquiry)

Students independently initiate the research process. Students identify a scientifically testable question, formulate a hypothesis, make a research plan, collect and analyze data, evaluate the hypothesis, and draw conclusions. Students share their research findings using Edmodo, and critique another two students’ projects. Sample research questions: • Is location A a healthy environment for aquatic life? • Is the pH level in location A related to its annual precipitation? • Is the pH level in location A related to its annual temperature?

Reflection and discussion Students reflect on how human activities affect water quality, how humans are intimately connected to their living environment, and make connections to real life examples.

2. THE THEORETICAL AND METHODOLOGICAL APPROACH

This initial phase of the research adopted the exploratory case study approach (Yin, 2009) for the following reasons: the term new literacies is newly emerged and has a small body of literature in science education; and research is needed to guide future research methods, data collection and analysis, and the assessment design in similar contexts. The purpose of the study was to answer two research questions: How feasible is it for teachers to integrate the identified ICTs, mobile devices and cyber resources to enhance new literacies and scientific literacy in middle school science classroom instruction? What are science teachers’ perception on using ICTs and mobile devices to cultivate students’ new literacies and scientific literacy using this module?

The study concerns participant teachers’ perception and experience of ICTs integration to facilitate new literacies and scientific literacy; therefore a phenomenological mode to the selection and analysis of data is adopted (Bogdan & Biklen, 2007). Teacher interviews provided their perception and experience of implementation; discussions with teachers during a training session helped us learn their understanding of new literacies and scientific inquiry; participant observation in the classrooms provided information regarding students’ reaction to the implementation and the difficulties of the ICTs and mobile device use; participant observation in the social networking group helped us learn how students interact among one another to establish the inquiry community; and the sample student artifacts provided the development of their new literacies and scientific literacy. The three participant teachers are middle school science teachers in an urban area, who have many years of science teaching experience. After several meetings and


239

observations, we determined that these teachers have a strong understanding of the subject they teach (living environment), but vary in their technology skills. One is technology savvy, one is comfortable with using technology but does not use it on a daily basis, and one has a fear of using technology in the classroom. Each teacher was provided a set of iPod Touch, a probeware, and an app that connects with the probeware.

The analysis of data aimed to understand teachers’ perception and experience of using ICTs and mobile devices to facilitate the development of new literacies that support scientific literacy. We conducted a thematic analysis (Miles & Huberman, 1994) to analyze interview and observation data. Teacher interviews provided their perception and experience of implementation; discussions with teachers during training session helped us learn their understanding of new literacies and scientific inquiry; participant observations in the classrooms provided information regarding students’ reaction to the implementation and the difficulties of the ICTs and mobile devices used; and participant observations in the social networking group helped us learn how students interact among one another to establish the inquiry community.

3. FINDINGS AND DISCUSSION

The classroom observations, interviews with teachers, participatory experience in the social networking tool, and students’ artifacts and interactions on a social networking tool provide answers to two research questions. (1) Feasibility of integrating the identified ICTs and cyber resources to enhance new literacies and scientific literacy in middle school science classroom instruction

The cyber resources identified provided rich and reliable data for students to conduct open inquiry. Students were highly motivated to play the role of scientists, using authentic data to answer their own research questions. The choice of ICTs used did affect the technology integration experience. The classroom observation showed that technology frustration only occurred when students forgot their cloud computing services accounts (e.g. Google). Students had limited training on the use of a spreadsheet tool in their previous learning experience; however all students could perform the tasks to use a spreadsheet to log data, create charts to observe the relationship between factors, and publish the spreadsheet and charts onto the social networking tool after they observed the teachers’ demonstration. Schools did not need to provide extra support to the teachers because the ICTs adopted were readily accessible, either through computer installed software, or cloud computing services. The painless technology adoption experience allows teachers to focus on the cognitive tasks, not technology issues. The greatest challenge of ICTs integration is distraction, which is a phenomenon discussed by previous studies (Fried, 2008; Levine, 2002). There were students abusing the flexibility teachers provided, looking for irrelevant information during class, or posting inappropriate comments on the social networking tool. Even though only a few students infrequently demonstrated these behaviors, it still caused distraction to the entire class.

(2) Advantages of integrating mobile devices to enhance new literacies and scientific literacy The mobile devices (iPod Touch and Probeware) enable teachers and students to collect real-time water

quality data in any selected locations. Teachers and students will not be confined to the physical space. iPod Touch and Probeware can be connected through blue tooth technology so wireless connection is not needed. The SparkVue app allows teachers and students to analyze data immediately after the data collection. The mobile devices make “anytime, anywhere” learning possible and students situated in an environment in which they can connect the scientific inquiry activity with their real life experience.

(3) Teachers’ perception on applying new literacies to support scientific inquiry While ICTs and cyber resources enhanced students’ scientific inquiry skills, new literacies skills were

also cultivated in the process. Throughout this module, students practiced information retrieval and evaluation skills in each of the inquiry processes. To identify a scientifically testable question, students needed to search for accurate information from reliable resources to develop research questions pertinent to the topic. When involved in the application and synthesis of scientific knowledge learned, such as using a virtual laboratory book template to develop a research plan and document their research process, and using a spreadsheet to process numerical data and charts, students practiced their information synthesizing skills. Students then practiced their collaboration and communication skills using a social networking tool to share their research findings. This module provides students with multimodal literacy practice, and allows teachers to examine students’ projects using multimodal formats of presentation.

ISBN: 978-972-8939-66-3 © 2012 IADIS

240

4. CONCLUSION

The study examined the feasibility to integrate ICTs and mobile devicse to enhance new literacies and support scientific literacy in middle school science classrooms, and reported the implementation process and the challenges of integration. We adopted the explorative case study approach to answer two research questions. The technology integration experience in science classroom instruction in this study emerged in the following formats: 1) both teachers and students experienced very little technology frustration, 2) students effectively conducted inquiry through the use of ICTs and cyber resources facilitated independent inquiry, and 3) students practiced new literacies skills through the use of ICTs. The evidence suggested that students experienced very little technology frustration because they were already comfortable with the use of technology. Cyber resources provided authentic and reliable data for students to investigate, and it confirmed the previous study result that students are better at interpreting findings of their experiments if they use real-time data collection and construct their own charts (Linn & Hsu, 2000).

REFERENCES

Barrow, L. B. (2006).A brief history of inquiry: From Dewey to standards. Journal of Science Teacher Education, 17(3), 265–278.

Howes, E. V., Lim, M., & Campos, J. (2009). Journeys into inquiry-based elementary science: Literacy practices, questioning, and empirical study. Science Education, 93(2), 189-217. doi: 10.1002/sce.20297.

Lee, H.-S., Linn, M. C., Varma, K., & Liu, O. L. (2010). How do technology-enhanced inquiry science units impact classroom learning? Journal of Research in Science Teaching, 47(1), 71-90. doi: 10.1002/tea.20304.

Khan, S. (2007). Model-based inquiries in chemistry. Science Education, 91(6), 877-905. doi: 10.1002/sce. Crawford, B. A. (2007). Learning to Teach Science as Inquiry in the Rough and Tumble of Practice. Journal of Research

in Science Teaching, 44(4), 613-642. doi: 10.1002/tea. Windschitl, M. (2003). Inquiry projects in science teacher education: What can investigative experiences reveal about

teacher thinking and eventual classroom practice? Science Education, 87(1), 112-143. doi: 10.1002/sce.10044. Germann, P. J., Haskins, S., & Auls, S. (1996). Analysis of Nine High School Biology Laboratory Manuals.pdf. Journal

of Research in Science Teaching, (5), 475-499. Leu, D. J., Kinzer, C. K., Coiro, J. L., & Cammack, D. W. (2004). Toward a theory of new literacies emerging from the

Internet and other communication technologies. In R. Ruddell and N. Unrau (Eds.), Theoretical models and processes of reading (5th ed.). Newark, DE: International Reading Association. Retrieved June 7, 2011 from http://www.reading.org/downloads/publications/books/bk502-54-Leu.pdf

Campbell, T., Wang, S.-K., Hsu, H.-Y., Duffy, A., & Wolf, P. (2010). Learning with web tools, simulations, and other technologies in science classrooms. Journal of Science Education & Technology, 19(5), 505-511.

Kim, M. C., Hannafin, M. J., & Bryan, L. A. (2007). Tools in science education : An emerging pedagogical framework for classroom practice. Science Education, 91(6), 1010-1030. doi: 10.1002/sce.

Solomon, G., & Schrum, L. (2007). Web 2.0: New tools, new schools. Washington, DC: International Society for Technology in Education.

Ertmer, P. A. (2005). Teacher pedagogical beliefs: The final frontier in our quest for technology integration? Educational Technology Research and Development, 53(4), 25–39

Kumar, N., Rose, R. C., & D’Silva, J. L. (2008) Teachers’ readiness to use technology in the classroom: An empirical study. European Journal of Scientific Research, 21(4), 603-616.

Kuiper, E. & Volman, M. (2008). The web as a source of information for students in K-12 education. In J. Coiro (Ed), Handbook of research on new literacies. New York, NY: Lawrence Erlbaum Associates.

Yin, R. (2009), Case study research: Design and methods, 4th ed., Thousand Oaks, Sage Publishing. Bogdan, R., & Biklen, S. K. (2007). Qualitative research for education: An introduction to theory and methods, 5th ed.

Boston: Allyn & Bacon. Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis. Thousand Oaks, CA: Sage. Fried, C. B. (2008). In-class laptop use and its effects on student learning. Computers & Education, 50(3), 906-914. Levine, L. E. (2002). Laptop classrooms present new teaching challenge. T.H.E. Journal, 30(5), 10 Linn, M.C., & Hsi, S. (2000). Computers, teachers, peers: Science learning partners. London: Lawrence Erlbaum

Associates.


241

ROLE OF NEEDS-ANALYSIS IN MOBILE LANGUAGE LEARNING CONTENT DEVELOPMENT

Yasemin Bayyurt and Nur Başak Karataş Boğaziçi University

Faculty of Education, Department of Foreign Language Education

ABSTRACT

Since the 1970s, language learning needs along learner-based lines have been of primary interest for many curriculum designers or language programme developers (Munby, 1978; Brown, 2009). The present paper seeks analysis of 85 tourism vocational high school students’ perceptions of needs for English language learning. It also addresses their ‘real’ wants and lacks substantiating on a theoretical framework by Dudley-Evans and St. John (1998). Through a multi-layered needs-analysis, it purports to create an appropriate and stimulating mobile language learning platform whereby their positive attitudes, language proficiency and technological literacy will be boosted in lieu of the traditional time-and-place constrained learning practices. Within the study, students’ internal subjective needs were determined by questionnaires while hotel managers/academics/teachers’ views on students’ objective needs were explored through semi-structured interviews. The results underscore that the students’ vocational language needs remarkably overshadow the other types of needs per se. Under these circumstances, the findings thrust the vitality of needs-analysis into the preparation of mobile language learning modules.

KEYWORDS

Needs-analysis, mobile learning, vocational language learning needs.

1. INTRODUCTION

Needs-analysis in second language education was pioneered in the 1960s as English for Specific Purposes instruction (ESP) gained momentum (Munby, 1978; Richards, 2001). It is worth noting at the outset that in the present study we adhere to the common term ‘needs analysis’, which can be confused with its interchangeable partner ‘needs assessment’ by some authors (Graves, 1996), because we believe that ‘analysis’ assigns value to the data obtained through ‘assessment’. The study thus relies on the argument that needs-analysis should be the backbone of any ESP course, as strongly argued by Hutchinson & Waters (1987) and Hamp-Lyons (2001).

Recent research into the language learning needs of diverse groups (e.g. Brown, 2009; Van Avermaet & Gysen, 2006; Long, 2005; Purpura & Graziano-King, 2004) illustrates that needs are learner- or group-specific, encompassing idiosyncratic dynamics. The current study examines the English language learning needs, wants, and lacks of tourism vocational high school 9th graders, based on the theoretical framework postulated by Dudley-Evans and St. John (1998).

Relating the inquiry area to both ‘Target Situation Analysis’ (TSA) introduced by Chambers (1980) and ‘Present Situation Analysis’ (PSA) posited by Robinson (1991), the study aims to suit the to-be-developed content of mobile learning platforms to a spectrum of learners’ needs. This mobile learning environment is the target product of an LdV Transfer of Innovation project entitled Mobile Learning at Risk Group, or MLARG in short. MLARG set out to incorporate Information and Communication Technologies (ICT) and Mobile Learning Technologies (MLT) into language teaching materials and methodology for young people (aged 14-17) with limited exposure to English, which puts the students’ future occupational status at stake. In order to achieve pre-set objectives such as the design of modules on mobile phones, access to innovative lifelong learning opportunities, and enhancement of transparency of competencies for vocational language development, resulting in ‘anywhere’, ‘anytime’, and ‘personalized’ language learning (Atwell, 2005;

ISBN: 978-972-8939-66-3 © 2012 IADIS

242

Kukulska-Hulme & Traxler, 2007; Kukulska-Hulme & Pettit, 2009; Valk, Rashid & Elder, 2010), this inclusive project urged for a needs-analysis to determine the target group’s peculiarities.

2. METHODOLOGY

A thorough needs analysis was conducted to identify the English language learning needs of tourism 9th graders as perceived from two poles, by adult professionals and by the students themselves. The initial semi-structured interviews were conducted with loosely pre-packaged sets of questions appropriate for the first group, and follow-up questionnaires were prepared to probe the intricately-framed topic of students’ needs for English language learning and for technology (Bayyurt & Tikac, forthcoming). The foremost reason for this two-stage needs-analysis was the fact that, distinct from the needs of regular English learners, vocational high school students’ needs arise from pressing professional needs, particularly the ability to transfer language knowledge to novel situations and to use acquired language skills in real life communication. (Kavalieuskiene & Uzpaliene, 2003).

2.1 Semi-structured Interviews

In qualitative research, semi-structured interviews are frequently preferred, presuming that they yield reliable data through an ‘interview guide’, which offers the informants freedom to express their views in their own terms. This type of interview was used here because no more than one chance to interview the respondents would be obtained, as advised by Bernard (1988). The researcher was able to tailor her questions to encourage meaningful two-way communication augmented by empathy, rapport, and trust, as highlighted by Glesne & Peshkin (1992). Interviews with the professionals—two hotel representatives, four English teachers at the pilot school, and two academics in the tourism department of a state university—were conducted in Turkish, their native language. The researcher went to their places of work, where they were comfortable exchanging ideas about the desired profile of vocational students in the tourism sector. In addition to questions intended to fill out their demographic profile, the four English teachers were asked programmatic questions such as the following:

• Do you think the time given to English language instruction is adequate? • What feedback do you get from hotel managers and employers? • What do you think about your course book, basic equipment, and technological resources? Do you have

an opportunity to use communicative activities or tasks? • Do you integrate technology into your teaching?

• Have you had any experience with ‘mobile learning’ or ‘e-learning?

2.2 Questionnaires

In the second phase of the needs-analysis, the students’ perceived needs were pinpointed by questionnaires devised to highlight any consistency among the students’ remarks. It should be stressed that the findings of the interviews with adult professionals helped to develop a comprehensive questionnaire to explore students’ English language needs. The questionnaire seeks information based on some commonly-known theoretical frameworks such as TSA (Target Situation Analysis), PSA (Present Situation Analysis), and LSA (Learning Situation Analysis), as well as other aspects pertaining to the model proposed by Dudley-Evans and St. John (1998).

The questionnaire, which was written in Turkish, the students’ native language, consisted of three sections: personal information, a five-point Likert scale, and one open-ended question: “As prospective employees in the tourism sector, please give your suggestions for improving the quality of English language education at your school so that it best fulfils your needs?” Given to 81 students (40 girls and 41 boys aged between 14-16), the questionnaire first elicited personal information such as gender, age, schooling, English language education, estimated proficiency levels rated by language skills. Then the students were asked to rate 20 items related to their language needs, using a scale of 1 (least important) to 5 (extremely important).


243

2.3 Results

The two primary data collection instruments in qualitative research according to the needs analysis model developed by Dudley-Evans & St John (1998), namely questionnaires and interviews, offered some insight into the students’ profile and language needs. First, the interviews with teachers suggested that six hours of English language education at the grade of 9 is not enough for fully-developed competence in all four skills. One teacher said, “There is no solution to this. There is not enough time to have it more than 6 hours. It’s a pity.” The teachers found it hard to accept the fact that students could barely speak English once they entered professional life, but “this is the best they can do with this limited range of facilities; we cannot blame them.” They were well aware of the employers’ concern about their employee’s need to communicate with people from various linguistic backgrounds: “The little chance of practising the language results in this inability to speak English fluently, effectively, and appropriately. That’s why they are mostly weak communicators, and that’s what the hotel managers perpetually complain about”.

All the teachers pointed out that the current trend to leave grammar out of instruction cannot be the remedy for the deficiencies. “We should give them the chance of using the language in ‘real world’, and grammar is definitely in this. How can you speak without it?” a teacher commented. Another teacher proposed integrating grammar into skills instruction; “Things would be better” if we could relate grammar to their prospective occupations by using field-appropriate texts.

The most commonly used technological device is the cassette player. It was acknowledged, however, that some “well-off” schools had started to use “technology-rooms”, with data-projectors, television, and so on. “It would make a lot of difference, if we could use videos or something all the time. But although we try to make up for it with what we have, there is not much we can do,” a teacher sighed.

Only 5 of the 81 students had attended a private primary school. All were exposed to English in primary school, for an average of six years. A majority (52 students) self-evaluated their English proficiency as intermediate, and only 9 considered themselves to be advanced. Of the language skills, speaking was rated the least developed (x̄ =2,88), whereas reading was rated the most developed skill. Even though their speaking skills needed to be improved, they perceived that it was the second most addressed skill by the teachers, which signals a discrepancy between the emphasis and the efficacy of instruction. The paramount set of data was gleaned from the five-point scale by boiling down 20 items into three broad categories, linguistic, vocational, and “other” (academic, cultural, etc.). There is likely to be some overlapping among the categories; however, these categories help to give a comprehensive picture of the analysis (see Table 1).

As indicated by the table, the average of every single item was first calculated and then the mean of each category was enumerated. Afterwards, the most important three needs in each category were tabulated in the table along with their individual means, standard deviations, and corresponding responses of importance. The table clearly demonstrates that vocational language needs are highest in hierarchical order (x̄ = 4.25). It accounts for the early awareness of the comparable importance of vocational language demands and implies that those demands should be seriously addressed in English lessons. The parameters of importance formulated in line with the mean scores also establish the greater influence of vocational language competence. It can be assumed that the limited time for vocational language instruction at 9th grade does not thwart its perceived importance.

The open-ended question evinced supplementary responses that are similar to the interview findings. Fifty-two per cent of the students suggested that the number of hours of English be increased; 23% proposed that speaking could be taught more effectively; and 12% recommended that lab sessions be added to the curriculum (meaning lessons in which students put what they learn into practice through small group communicative activities and Computer-Assisted Language Learning (CALL) materials). Together, when the questionnaires and interviews are taken in complement, it is noteworthy that they yield salient results in common. Thus these results can guide some worthy modifications to the curriculum of vocational high schools in Turkey, where the use of mobile phones claim to become a facilitating tool in support of English language learning.

ISBN: 978-972-8939-66-3 © 2012 IADIS

244

Table 1. Categorization of language needs by vocational high school students

Categories Items Mean Std.

Deviation Students’ responses

of importance To understand native speakers of English easily. 4.44 .94 Very important General language needs

To use the four basic skills of English (listening/ speaking/reading/ writing) effectively on a daily basis.

4.43 .94 Very important

To be able to use English grammatical rules and sentence patterns fluently.

4.06 1.11 Very important

To use English in the specific contexts such as restaurant, front desk, etc.

4.54 .79 Extremely important

Vocational language needs

To have a high position in tourism sector in future. 4.53 .72 Extremely important

To improve vocational vocabulary knowledge. 4.39 .78 Very important To prepare for English proficiency tests and

entrance exams in Turkey or abroad 4.01 1.14 Very important

Other: academic, cultural…

To participate in the exchange programs funded by the school or international organizations.


To be able to express the Turkish way of life and culture in English.


3. CONCLUSION

This paper has shown that needs-analysis ought to be the starting point for any research endeavour. A needs analysis can provide an accurate profile of a target group, thereby guiding the process of content development. There are plenty of studies emphasizing the description and analysis of students’ future needs in ESP settings (e.g. Hutchinson &Waters, 1987; Brown, 2009). They all agree that needs-analysis is to be regarded as an on-going procedure, reviewing students’ needs, wants, and lacks on a regular basis. The present study took the first step in exploring a disadvantaged group’s internal needs (by students themselves via questionnaires) and some external demands (by institutions, employers, and teachers via interviews) that can inform the development of a suitable mobile learning platform supplementary to the students’ in-class vocational English education. The main goals of m-learning are positive attitudes towards English, technological literacy, motivation to study ‘anywhere’ and ‘anytime’, and increased self-esteem that comes from feeling valued (Atwell, 2005; Kukulska-Hulme, 2006, 2011; Wishart, 2011). If guided by knowledge of the true learning needs of the students, MLARG materials will give rise to a revolution in vocational English language education in Turkey.

ACKNOWLEDGEMENT

This study was supported by European Commission Education and Training Lifelong Learning Leonardo da Vinci Transfer of Innovation Programme, “MLARG: M-Learning for young people at risk groups” Project (project number: 2009-TR1-LEO05-08674). We would like to thank the project member Saadet Tıkaç for conducting the earlier needs analysis interviews which constituted the basis of the needs analysis questionnaire and the mobile learning materials developed within the framework of this study. We would also like to thank the administrative staff, the English language teachers, and 9th and 10th grade students at Istanbul Etiler Tourism Vocational High School for their valuable contribution to the project.


245

REFERENCES

Atwell, J. (2005). A technology update and m-learning project summary. London: Learning and Skill Development Agency.

Bayyurt, Y. & Tikac, S. (forthcoming). Mobile Language Learning (MLL) in Vocational High Schools. In P. Broeder and M.J.W. Stokmans (Eds.) Proceedings of the 6th GET-IN Conference. Tilburg: Tilburg University Publications.

Bernard, H. (1988). Research Methods in Cultural Anthropology. Newbury Park, CA: Sage Publications. Brown, J. D. (2009). Foreign and second language needs analysis. In M. H. Long & C. J. Doughty (Eds.), The handbook

of language teaching (pp. 269-293). Oxford: Blackwell. Chambers, F. (1980). A re-evaluation of needs analysis. ESP Journal, 1(1), 25-33. Dickinson, L. (1991). Self-Instruction in Language Learning. Cambridge: Cambridge University Press. Dudley-Evans, T., & St John, M. J. (1998). Developments in English for specific purposes. Cambridge: Cambridge

University Press. Glesne, C., & Peshkin, A. (1992). Becoming Qualitative Researchers: An Introduction. White Plains, NY: Longman. Graves, K. (1996). Teachers as course developers. England: Cambridge University Press. Hamp-Lyons. (2001). English for academic purposes. In R. Carter and D. Nunan (Eds.), The Cambridge guide to

teaching English to speakers of other languages (pp. 126-130). Cambridge: Cambridge University Press. Hutchinson and Waters. (1987). English for specific purposes. New York: Cambridge University Kavaliauskiene, G. & Uzpaliene, D. (2003). Ongoing Needs Analysis as a Factor to Successful Language Learning.

Journal of Language and Learning, 1(1), 4-11. Kukulska-Hulme, A. (2006). Mobile language learning now and in the future. In P. Svensson (Ed.), Från vision till

praktik: Språkutbildning och Informationsteknik (From vision to practice: language learning and IT) (pp. 295–310). Sweden: Swedish Net University (Nätuniversitetet),.

Kukulska-Hulme, A., & Traxler, J. (2007). Designing for mobile and wireless learning. In H. Beetham & R. Sharpe (Eds.), Rethinking pedagogy for a digital age: Designing and delivering e-learning (pp. 180-192). London: Routledge.

Kukulska-Hulme, A. & Pettit, J. (2009). Practitioners as innovators: Emergent practice in personal mobile teaching, learning, work and leisure. In M. Ally (Ed.), Mobile Learning: transforming the delivery of education and training. Issues in Distance Education (pp. 135–155). Athabasca: Athabasca University Press.

Kukulska-Hulme, A. (2011). Lifelong language learning in a mobile age. Plenary speech presented at MLARG Final Conference, Istanbul, Turkey, 14 October.

Lett, J. A. (2005). Foreign language needs assessment in the US military. In M. H. Long (Eds.), Second language needs analysis (pp. 105-124). Cambridge: Cambridge University Press.

Long, M. H. (2005), Second language needs analysis. Cambridge: Cambridge University Press. Munby, J. (1978). Communicative syllabus design. Cambridge: Cambridge University Press. Purpura, J. E., & Graziano-King, J. (2004). Investigating the foreign language needs of professional school students in

international affairs: A case study. Working Papers in TESOL & Applied Linguistics, Teachers College, Columbia University, 4(1), 1-33. Retrieved from http://www.hawaii.edu/sls/uhwpesl/25(1)/Watanabe.pdf.

Richards, J. (2001). Curriculum development in language teaching. Cambridge: Cambridge University Press. Robinson, P. (1991). ESP today: A practitioner’s guide. New York: Prentice Hall. Valk, J.H., Rashid, A.T. And Elder, L. (2010). Using mobile phones to improve educational outcomes: an analysis of

evidence from asia. The International Review Of Research In Open And Distance Learning, Vol. 11, No. 1, Retrieved From: http://www.irrodl.org/index.php/irrodl/article/view/794/1487.

Van Avermaet, P., & Gysen, S. (2006). From needs to tasks: Language learning needs in a task-based approach. In K. Van den Branden (Eds.), Task-based language teaching in practice (pp. 17-46). Cambridge: Cambridge University Press.

Wishart, J. (2011). Research into teacher trainees and the way they can use mobile phones to support them in their teaching and learning. Plenary speech presented at MLARG Final Conference, Istanbul, Turkey, 14 October.

ISBN: 978-972-8939-66-3 © 2012 IADIS

246

MOBILE AUGMENTED REALITY APPS FOR TEACHING ETHICALLY SENSITIVE TOPICS IN MEDICINE

Urs-Vito Albrecht, Bernhard Häussermann, Herbert K. Matthies and Ute von Jan Hannover Medical School, P. L. Reichertz Institute for Medical Informatics

Carl-Neuberg-Str. 1, 30625 Hannover, Germany

ABSTRACT

In medical education, the use of eLearning content to support and improve teaching and learning has a long tradition. Since mobile devices are nowadays almost omnipresent, it is possible to seamlessly integrate the educational process into daily life when using mobile learning concepts. Augmented reality (AR) can significantly increase the attractiveness of mobile learning applications by adding a new level of experience for learners and thus improving the learning situation. In addition, AR applications allow students to gain experience in areas where ethical constraints may have to be placed on learning the subject in a real-life scenario. In this paper, an application following this concept, called mARble, will be presented. It offers an augmented reality blended learning environment for mobile phones. Currently, content for a course in basic forensics is available, and in a pilot study, medical students will be equipped with smart phones with a preinstalled version of mARble that gives them the opportunity to practice the recognition of certain wound patterns by overlaying these wound patterns on their own skin in real-time. The application also contains supplemental material in the form of multimedia and textual content as well as questions and tasks concerning the presented wound patterns to further enhance the learning experience. The main objective of the project is to generate synergy effects in the learning process by combining the best of modern mobile learning concepts with a traditional learning setting. By using innovative visualization techniques within the presented application, students are provided with the means to interact in a role-playing setting within their group, and a demanding, but fascinating learning environment can be created. The presented solution may also be of use for enhancing the learning process in other areas of medical expertise.

KEYWORDS

Mobile learning, augmented reality, medicine, ethics

1. INTRODUCTION

The traditional way of teaching medicine can be fittingly summarized in only six words using the credo “See one, do one, teach one”. There is no better access to a topic than to encounter the problem and watch the tutor working on the patient (see one), never a higher level of motivation than to participate in the action (do one) and to pass the knowledge on to the next (teach one). After years of studying and learning – mostly theoretical knowledge and only few practical skills – “Learning the job by doing the job” is a straightforward approach to learn the necessary skills in situations and environments that are always busy and demanding, like ER and OR, wards and ambulances. Dornan et al and Schmidt et al described positive learning results using realistic conditions in undergraduate medical students (Dornan T. et al., 2007 and Schmidt H.G. et al.,2007). Nevertheless, one important factor sometimes tends to be overlooked but should always be kept in mind when using this approach. If there is even a small chance of a negative influence on a patient’s physical or emotional well-being, this way of learning becomes unacceptable (e.g. Vozenilek, J. et. al 2004): There are many situations where ethical problems may arise when patients and real-life cases are presented to learners in the medical field. In some cases, it may be impossible to get a patient's consent to participate in the teaching process due to a potential or already sustained severe impairment of mental or physical health. Also, the bedside teaching must neither interfere with diagnostics and treatment nor worsen the situation or harm the patient in any way, even if the experience students could gain would be of great value for their later professional lives (Anders S. et. al, 2011).


247

Augmented reality may offer a solution to this dilemma: By blending information, e.g., images of the real world with virtual cases, it becomes possible to give students the opportunity to practice physical examination and interview techniques in a simulated setting, offering them an ideal and interactive alternative to a mere bedside teaching while staying within ethical boundaries. As an additional bonus, students are also allowed to experiment and make forgivable mistakes – which will be impossible at a later stage of their education or during their professional career.

2. METHODS

Teaching forensic medicine can serve as an example to illustrate all these issues. In the course of their studies, medical students have to learn about some of the basic aspects of forensics to be able to deal with what they might encounter in their future daily practice, since the ability to understand the basics of forensic medicine is a valuable asset for doctors which is recognized by the students as well (Anders, S. et. al, 2011). The basics they gain during their forensic training will later help them, e.g., to differentiate between a wound pattern that is more consistent with trauma due to assault or an everyday injury with a similar appearance. The students also learn about identifying possible signs of domestic violence or sexual child abuse. This knowledge is of great value when dealing with and treating traumatized patients, since these individuals will rarely admit the real cause of their injuries.

Over a period of two weeks, students at Hanover Medical School participate in a course about basic forensics that is presented the form of seminars and lectures. Traditionally, the course material mostly consists of anonymized images of victims with certain wound patterns. The physics leading to the depicted types of injuries are also described in detail. Students also attend a mandatory forensic postmortem medical examination and an autopsy in groups of eight students and one tutor to deepen their understanding of forensics.

Various problems may arise from this approach: On the one hand, the aforementioned ethical problems must be kept under consideration. Additionally, “quality control” may remain an issue since in reality no two cases are similar and there is no guarantee that it will be possible to present all findings deemed relevant by the teacher. Moreover, a number of students may at first experience a certain repugnance that may distract them from the presented case.

2.1 Mobile Augmented Reality

One possible solution to the mentioned problems can be the use of an approach based on augmented reality (AR) on a mobile device with use of overlaying the relevant findings and wound patterns on images of the learner's own body. Neither the concept of augmented reality nor of mobile learning is really new to medical education. Nevertheless, only the advances in mobile technologies over the past few years have made it possible to bring these two concepts together in user-friendly mobile applications that pose no barrier to potential users due to the high availability of mobile devices as well as their good usability and portability, thus opening up an “alluring option for teaching and learning” (Smith, 2010). As the Horizon Report from 2010 states, “the portability of mobile devices such as smart phones and their ability to connect to the Internet almost anywhere makes them ideal as a store of reference materials and learning experiences” (Johnson, L. et al, 2010).

ISBN: 978-972-8939-66-3 © 2012 IADIS

248

Figure 1. Paper marker on the skin detected and interpreted as a gunshot wound by the application on the iPhone® (live). On the right: iPhone® with a picture of the scene that was saved to the image gallery.

2.2 The Application

AR applications allow bridging the gap between the real, physical world and virtual reality by augmenting an acquired scene with additional, digital information of a complementary virtual world (Azuma, R., 1997). Various steps are necessary to successfully adapt a learning setting to be used with augmented reality. In an exemplary use case for teaching forensic medicine, these steps are integrated into a “mobile Augmented Reality blended learning environment (mARble)” running on a mobile device. For every wound pattern contained within the application, a distinct paper marker is available and can be placed within the physical scene, for example, on the learners forearm (Fig. 1).

Based on images of the scene that are acquired using the internal camera of the mobile device (e.g., an iPhone®), the installed app recognizes the marker and overlays the depiction of the corresponding finding, for example, as an entrance wound of a bullet (Fig. 1), in real-time. Links to supplemental multimedia and other content are also provided to enhance the learning experience. Related questions and tasks can also be triggered: Figure 2 shows the entire workflow: First, the marker corresponding to a bullet entrance wound is detected. In turn, this leads to a task to “define and describe the characteristics of an entrance wound”. Additional features include the possibility to document the learning process and to generate material for live (or later) presentations and discussions. All these images and videos generated while using the app can be saved in a personal gallery.


249

Figure 2. Exemplary use case: “Forensic Medicine”. The tutor chooses a marker from a predefined set and places it on the skin of a student to create a wound pattern the students should explore.

2.2.1 Navigating the Available Cases

Using the available features of the app, the user can comfortably navigate through the content (Fig. 3). All necessary controls can be easily accessed on the screen while the mixed image is shown. Snapshots of live situations may be acquired via a tap on the camera icon at the tab bar. These images can be later viewed by tapping the image gallery icon. When the lighting is sub-optimal, the phone’s flashlight can be turned on using the light bulb icon. The user may also determine the dimensions of a scanned object using the e-ruler function. The distance between the object and the phone’s camera is specified at the top of the screen.

Access to questions associated with the finding represented by the current marker is provided by tapping the question mark. The corresponding answers can be activated via the info-symbol. The user also gets feedback regarding his progress through a progress indicator displaying information about the absolute (numbers) and relative position (dots) of the currently displayed content with regard to the learning stack consisting of all cases available in the app. The user can return to the “live mode” by tapping the closing ×.

Figure 3. Application features in the live mode at the moment when the marker is detected (left). Additional functions become available when the user views questions, answers or attachments (right).

ISBN: 978-972-8939-66-3 © 2012 IADIS

250

2.2 Authoring Content Using XML

New content can be easily added by means of a comprehensive XML scheme, without even touching the core code of the application. Since no programming skills are necessary to expand the database of available cases, a tutor can comfortably add cases she finds interesting. This method also makes it possible to build up content databases for other medical specialties (e.g., dermatology) that might profit from the described approach of combining virtual information with data acquired from the real world.

2.3 Using mARble to Learn

A tutor can either replay real cases she encountered during her career or invent fictive cases by combining a number of different markers for the patterns of injuries corresponding to the cases. Thus, the tutor can easily vary details of the cases she presents to each group of students and also react to the questions that may surface during a course.

The standardized content contained in the app cannot only be used in the aforementioned group settings. An additional benefit of the highly versatile system is that students can also employ it for self-learning and revision of cases that were presented during the course, without the usual restrictions they usually encounter due to their packed schedules. Also, since learning with mARble requires active interaction by the students, e.g., by transforming them into learning objects while they study, they become more actively involved in the learning process and can thus easily gather personalized but shareable experiences, deepening their understanding of the subject.

3. CONCLUSION

mARble combines the best features from both worlds – traditional learning settings as well as augmented reality – and has the potential to significantly improve the learning process in medical education. A major point is that using an approach as presented in mARble, it is much easier to capture the attention of the students compared to the purely traditional way of teaching. This is partly achieved by the personal involvement of the students due to the highly interactive nature of the application. In contrast to web-based solutions for training external post-mortem examinations (Schmeling, A. et al., 2011), the students themselves become learning objects. In this way, they are better integrated into the learning process and can identify with what is being taught. This may possibly provoke emotions and an internal dialogue (inner student interaction). Interactions, i.e. discussions within the learning group (inter-student interaction) and with the tutor about the presented topics are well supported through the possibilities offered by mARble, e.g., via the documentation feature, which also adds to the learning experience. And although all available cases can be accessed in a very flexible way, the students are still lead on a structured path in order to cover all the required content.

The concept introduced by mARble alleviates any ethical problems that might arise when using real-life cases for basic forensic training while still giving students an opportunity to experience hands-on training that is close to reality. A complete replacement of real cases during medical training is impossible and is not the goal. Nevertheless, this can be left to advanced training, i.e. should students decide to go into the specialty of forensics later in their training, they will have to learn their job on real cases. mARble simply offers them a head start and increases their confidence via the experience the students can gain beforehand when employing the described AR approach for learning. This may lead to a more self confident demeanor once they start to work as doctors, and will in turn increase the confidence their patients will place in them, which is an integral part of a good patient-doctor relationship. This is especially important in a specialty such as forensics where cases are of a sensitive nature and ethical problems may easily arise.

The first preliminary results with a small number of users are encouraging. An in-depth evaluation of the project is currently being performed. Ongoing work is dedicated to integrating additional content for forensic training as well introducing mARble into the educational process of other areas of expertise.


251

ACKNOWLEDGEMENT

mARble has won the 2nd prize of the Mobile Learning Challenge 2011 of the International Association for Mobile Learning.

REFERENCES

Anders S., 2011. Teaching post-mortem external examination in undergraduate medical education-the formal and the informal curriculum. Forensic Sci Int. 2011 Jul 15;210(1-3):87-90. Epub 2011 Mar 3.

Azuma, R., 1997. Presence: A Survey of Augmented Reality. Teleoperators and Virtual Environments, 6, 4, 355-385. Dornan T., Boshuizen H., King N., Scherpbier A., 2007. Experience-based learning: a model linking the processes and

outcomes of medical students' workplace learning. Med Educ. 2007 Jan;41(1):84-91. Johnson, L. et al, 2010. The 2011 Horizon Report. The New Media Consortium, Austin, USA. Schmeling, A. et al, 2011. A web-based e-learning programme for training external post-mortem examination in

curricular medical education. International Journal of Legal Medicine Volume 125, Number 6, 857-861, DOI: 10.1007/s00414-011-0613-2.

Schmidt H.G., Rikers R.M., 2007. How expertise develops in medicine: knowledge encapsulation and illness script formation. Med Educ. 2007 Dec;41(12):1133-9. Epub 2007 Nov 13.

Smith M., 2010. Augmented Reality – Its Future in Education. http://www.publictechnology.net/sector/augmented-reality -its-future-education (last visited 28/10/2011).

Vozenilek, J. et al, 2004. See One, Do One, Teach One: Advanced Technology in Medical Education, Acad Emerg Med. 2004 Nov;11(11):1149-54.

ISBN: 978-972-8939-66-3 © 2012 IADIS

252

A SOCIAL SOFTWARE FOR MOBILE LEARNING

Tássia Serrão1, Sérgio Crespo C. S. Pinto1, Lucas M. Braz1 and Gisela Clunie2 1University of the Sinos Valley (UNISINOS), 950 Unisinos Ave, São Leopoldo-Brazil

2Technological University of Panama, Centenario Ave, Panama

ABSTRACT

The traditional teaching methods of the Learning Management Systems (or LMS) are rigid in nature and impose limitations on the teaching process. By having a closed pattern, these tools end up hurting the student, for preventing it from interacting with anyone who shares the same interests as him. As a result, the concepts of community, relationship and interaction between users are required to overcome these limitations. This paper proposes the development of an architecture for creating a social software that enables the use of online social networks automatically created for students through their mobile devices. Besides, this architecture has been created based on web services, what makes it possible the integration with MLEA (Mobile Learning Environment Adapter), an application that allows students to access Moodle through their mobile devices.

KEYWORDS

Social Networks, Software Architecture, Social Software.

1. INTRODUCTION

For many years, the studies of student/teacher interactions had been focused on the teacher. It had been studied how he should behave and all the responsibility in learning was attributed to him. Education was rigid with almost null participation of the students. Much time later there have been a few changes, but discussions related to the advances in educations are still common.

A current definition of learning is given by Chatti et al (2010). The authors claim that learning is like a network (they use the term LaaN - Learning as a Network) and highlight the connectivism between students, advocating that knowledge is inside the network. It says that learning begins individually by a student and later is concentrated in his Personal Knowledge Network (PKN). A PKN is comprised of a myriad of knowledge nodes which are the people who act together and help each other to view the connections in the network.

One of the main research goals to potentiate socializing among students is the use of social networks in the learning process. According to Wasserman and Faust (1994), a social network consists of finite set of actors and the relationships defined between them. Social networks have come to exist also on the Internet, being called Online Social Networks, and became popular with the rise of Web 2.0 and social network sites. This technological breakthrough has made the accessibility and involvement of social networks reach millions of people around the world. The evolution has been followed for integrating new technologies and experiences in social networks with formal education and in order to this happens education must take a new course, similar to Web, and become more open, dynamic and student centered (Chatti et al 2006).

Recent research indicates that interaction and collaboration between users are strengthened and improved through unification of educational environments and mobility, using new devices like smartphones, for creating mobile learning (Baloian and Galdames 2004). Thus, the potential of mobile Internet makes it easier to access resources from anywhere at any moment.

However, it is common to have computational models aimed at educational purposes that only transpose to virtual the technicist model of learning, in a similar way as students experience in regular classes. Such models prevent students to develop their social abilities because they focus on knowledge transmission in a hierarchical and passive way, where the student is seen as a mere container for the knowledge provided by teacher or machine.


253

Thus, this paper proposes the development of an architecture for a mobile social software that automatically creates online social networks for Moodle students. The networks can be viewed and articulated by the users from their mobile devices, enabling the creation of new communities, organized into topics. This way, students become much more connected with those who really matter, without geographic or time boundaries, potentiating interaction and learning between them.

Moreover, the social software is integrated with MLEA (Mobile Learning Environment Adapter), which is an international project, created in Panama, that aims to enable the access to Moodle resources through mobile devices (Crespo et al 2010). Such integration allows MLEA students to transparently create online social networks organized into communities with specific topics and formed by students from different instances of Moodle. Nevertheless, the social software can be used independently of MLEA.

This paper is organized as follows: Section 2 presents the concepts of online social networks applied to education; Section 3 shows some related works; Section 4 presents the proposed architecture and its integration with MLEA; and Section 5 presents some conclusions.

2. ONLINE SOCIAL NETWORKS IN EDUCATION

Online Social Networks (OSN) are a virtual representation of interaction between people, that is, a simulation of real social networks. These networks have gained more evidence with the popularization of social networking sites, becoming target of educators around the world. The success of these new ways of interaction, proved by the number of active users, have attracted the attention of some scholars in the field of education, such as Phillips et al (2011), who created a guide describing several ways of how to use Facebook for education, among which stands out the use of groups, online spaces of people who interact and share information with each other. The convenience relies on the information sharing, because when one member of a group posts a link or article, every member of that group is notified of the update. Moreover, Ratcham and Firpo (2011) propose the use of social networks technologies in classrooms as a way to improve learning through the creation and maintenance of virtual communities of practice.

Despite the benefits, there are educators against the use of social networks in education. Some argue the lack of privacy, as a huge personal exposure, since most people use social networking sites for entertainment and talk about issues related to family, friends and leisure. Another reason is related to intellectual property terms, which ensure all information discussed in the sites belong to its owner, removing any relationship to the institution that promoted this debate (Li and Liu 2009). Thus, it would be more interesting to add features of social networking to Moodle instead of integrate it with existing social networking sites.

3. RELATED WORKS

This Section presents some related works to the proposed subject. In this sense, it will be discussed works whose purpose is to promote a more interactive Moodle environment by adding social networking features to it.

Developed by Ben Werdmuller and David Tosh, Elgg is an open-source application for creating personal blogs and social networks that allows, among others, the sharing of text, photographs, music and videos (Canpbell et al 2005). The differential of this application is that it can be integrated with Moodle, forming a union called Megg (Moodle and Elgg) whose purpose, according to (MoodleDocs 2011), is to provide the student with an environment where they can create their own learning space connecting themselves with other students and forming online social networks. The integration module is available in (MoodleCore 2007).

Mahara is a system for creating e-portfolios that are articulated by online users. This system also provides a Weblog, a résumé builder and a social networks system, connecting users and creating online learning com-

munities. This system can be integrated with Moodle, being then called Mahoodle (Mahara 2011). Laydner (2007) presents the development of a module for Moodle, created at ITA (Technological

Institute of Aeronautics) that aims to add social network features to the Moodle environment. The idea of this module is to expand the profile of each user by adding tags to identify their specific interests. The user has the possibility to associate its profile to a set of tags, creating new ones and even browse through the users

ISBN: 978-972-8939-66-3 © 2012 IADIS

254

with a particular tag. This way, students with similar interests can join together more easily since they can maintain a list of users with their same interests.

The works presented so far have the same objectives of provide Moodle users with social networks capabilities. The proposed social software differentiates from them in the sense that it allows Moodle users to create their own social networks automatically and articulate these networks while using their mobile devices. Besides, it is integrated with Moodle forum, particular discussion. This is useful because a student that involves more people, since the networks created are not restricted to course.

4. ARCHITECTURE

The proposed architecture, shown in Figure 1, utilizes a client/server model, in which the cellphones play the role of client while the server side is represented by the environment where the Moodle instance and the proposed software are installed.

The main components of this architecture are:between clients and server. For each required functionality, there is a Web Service that must be invoked by the client passing the appropriate parameters; of the other modules in order to provide the desired functionality. This module works as a façade between the Web Services and the other modules; in order to find relevant information for the social software (name or profile picture). This module is fundamental to the automatic creation of the social netsome tag, it has to identify the discussions associated with this tag and the users who have participated in these discussions. Such users are considered candidates to join the social network being created, because they possibly have some interest in the subject of the network; for every function of constructing and articulating of the social networks. It takes the candidate users (output of the Module of Access) and decides which of them will indeedpreferences. The management of the networks, like adding or removing members, is also a responsibility of this module; Module of Persistence: relevant information, such as for example the networks created.

Figure 1. The architecture of the proposed social software.

Besides these modules, the proposed software contains a plugstudents to add tags to the discussions they create in the forums. These tags are understood as the interest of that particular discussion and consequently the interest of the users who have pinformation is stored in the application database to be used by the system while creating the social networks.

4.1 Automatic Construction of the Network

Since the main goal of this work is to automatically create social networks organized by communities, this Section aims to describe how this is done. Figure 2 shows an overall picture of this process and the following paragraph describes each step necessary to create a new network.

ar tag. This way, students with similar interests can join together more easily since they can maintain a list of users with their same interests.

The works presented so far have the same objectives of provide Moodle users with social networks . The proposed social software differentiates from them in the sense that it allows Moodle users to

create their own social networks automatically and articulate these networks while using their mobile Besides, it is integrated with Moodle forum, so that users can create or join social networks from a

particular discussion. This is useful because a student can continue that discussion in another environment that involves more people, since the networks created are not restricted to the boundaries o

The proposed architecture, shown in Figure 1, utilizes a client/server model, in which the cellphones play the role of client while the server side is represented by the environment where the Moodle instance and the

The main components of this architecture are: Web Services Layer: acts as the communication interface

between clients and server. For each required functionality, there is a Web Service that must be invoked by g the appropriate parameters; Module of Control: responsible for orchestrate the execution

of the other modules in order to provide the desired functionality. This module works as a façade between the Web Services and the other modules; Module of Access: has the role of perform queries on Moodle database in order to find relevant information for the social software (e.g. personal information of the users such as name or profile picture). This module is fundamental to the automatic creation of the social netsome tag, it has to identify the discussions associated with this tag and the users who have participated in these discussions. Such users are considered candidates to join the social network being created, because they

rest in the subject of the network; Module of Networks Construction: for every function of constructing and articulating of the social networks. It takes the candidate users (output of the Module of Access) and decides which of them will indeed join the network based on the users’ preferences. The management of the networks, like adding or removing members, is also a responsibility of

Module of Persistence: manages the application database, performing queries and storing formation, such as for example the networks created.

Figure 1. The architecture of the proposed social software.

Besides these modules, the proposed software contains a plug-in for Moodle that allows teachers and students to add tags to the discussions they create in the forums. These tags are understood as the interest of that particular discussion and consequently the interest of the users who have p

stored in the application database to be used by the system while creating the social networks.

Automatic Construction of the Networks

Since the main goal of this work is to automatically create social networks organized by communities, this aims to describe how this is done. Figure 2 shows an overall picture of this process and the following

paragraph describes each step necessary to create a new network.

ar tag. This way, students with similar interests can join together more easily since they can

The works presented so far have the same objectives of provide Moodle users with social networks . The proposed social software differentiates from them in the sense that it allows Moodle users to

create their own social networks automatically and articulate these networks while using their mobile so that users can create or join social networks from a

discussion in another environment the boundaries of a particular

The proposed architecture, shown in Figure 1, utilizes a client/server model, in which the cellphones play the role of client while the server side is represented by the environment where the Moodle instance and the

acts as the communication interface between clients and server. For each required functionality, there is a Web Service that must be invoked by

responsible for orchestrate the execution of the other modules in order to provide the desired functionality. This module works as a façade between the

as the role of perform queries on Moodle database personal information of the users such as

name or profile picture). This module is fundamental to the automatic creation of the social networks. Given some tag, it has to identify the discussions associated with this tag and the users who have participated in these discussions. Such users are considered candidates to join the social network being created, because they

le of Networks Construction: responsible for every function of constructing and articulating of the social networks. It takes the candidate users (output

join the network based on the users’ preferences. The management of the networks, like adding or removing members, is also a responsibility of

manages the application database, performing queries and storing

that allows teachers and students to add tags to the discussions they create in the forums. These tags are understood as the interest of that particular discussion and consequently the interest of the users who have participated in it. This

stored in the application database to be used by the system while creating the social networks.

Since the main goal of this work is to automatically create social networks organized by communities, this aims to describe how this is done. Figure 2 shows an overall picture of this process and the following


255

Figure 2. Automatic process of creation of the networks.

Initially, (i) the student, using a mobile device, requests the creation of a social network. At this moment,(ii) the client application invokes the Web Service responsible for it, passing the subject of the network, thatis, a tag. Then, (iii) this Web Service calls the Module of CoThe Module of Control (iv) invokes the Module of Access, which will query the Moodle database and returnthe users that might be interested in the subject of the network. Then, the Module of Control (v) invokModule of Networks Construction passing the candidate users. This module creates the required networkselecting the users who actually use MoodleModule of Control (vi) asks the Module Service that had started the process. The Web Service, in its turn, (viii) responds to the client application,who will present the user with the newly created network.

4.2 Integration of the Social Software with MLEA

The proposed social software can be integrated with MLEA, an application for Android devices that enables students and teacher to access Moodle resources through their cellphones and tablets. the users to: (i) log into one of the applications and use the features of the other one without the need of logging in again. When a user logs into MLEA, it automatically logs into Moodleadd tags to the discussion they create. This is necessary to keep the consistency with Moodle when the plugin is installed; (iii) create or join social networks from discussions in a forum. When a student does it, he/she can discuss that subject with others

The social software follows the pattern of the Android Dashbord project, whose guser a home screen that gives an overview of the features that tthis. The integration of the MLEAnetwork button passing the theme that he wants the network to be create, which in this example is about java, as shown in Figure 3 - b ). At thwho started the event will see in his screen the list of users who have interests similar to hiFigure 3 – c). The Android API supports the exchange of information betwefacilitating the development and making this change transparent to user

5. CONCLUSION

Figure 3. (a) Start screen of the social software; (b) MLEA screen used to begin the process of creating a social network; (c) List of users in

Figure 2. Automatic process of creation of the networks.

sing a mobile device, requests the creation of a social network. At this moment,(ii) the client application invokes the Web Service responsible for it, passing the subject of the network, thatis, a tag. Then, (iii) this Web Service calls the Module of Control, which will coordinate the other modules.The Module of Control (iv) invokes the Module of Access, which will query the Moodle database and returnthe users that might be interested in the subject of the network. Then, the Module of Control (v) invokModule of Networks Construction passing the candidate users. This module creates the required networkselecting the users who actually use Moodle-2-share, taking into account their preferences. Finally, theModule of Control (vi) asks the Module of Persistence to store the network and (vii) returns it to the WebService that had started the process. The Web Service, in its turn, (viii) responds to the client application,who will present the user with the newly created network.

the Social Software with MLEA

The proposed social software can be integrated with MLEA, an application for Android devices that enables students and teacher to access Moodle resources through their cellphones and tablets.

log into one of the applications and use the features of the other one without the need of logging in again. When a user logs into MLEA, it automatically logs into Moodle-2-share and vice

tags to the discussion they create. This is necessary to keep the consistency with Moodle when the plugcreate or join social networks from discussions in a forum. When a student does it, he/she

can discuss that subject with others different from those who had participated in the forum.The social software follows the pattern of the Android Dashbord project, whose g

home screen that gives an overview of the features that the system provides. The Figure MLEA with Moodle-2-Share happens when the user clicks the start social

network button passing the theme that he wants the network to be create, which in this example is about java, b ). At this time the application MLEA invokes Moodle-2-Share and the participant

who started the event will see in his screen the list of users who have interests similar to hiThe Android API supports the exchange of information between different applications,

ting the development and making this change transparent to user.

Figure 3. (a) Start screen of the social software; (b) MLEA screen used to begin the process of creating a social network; (c) List of users in the network with Java as subject.

sing a mobile device, requests the creation of a social network. At this moment, (ii) the client application invokes the Web Service responsible for it, passing the subject of the network, that

ntrol, which will coordinate the other modules. The Module of Control (iv) invokes the Module of Access, which will query the Moodle database and return the users that might be interested in the subject of the network. Then, the Module of Control (v) invokes the Module of Networks Construction passing the candidate users. This module creates the required network by

share, taking into account their preferences. Finally, the of Persistence to store the network and (vii) returns it to the Web

Service that had started the process. The Web Service, in its turn, (viii) responds to the client application,

The proposed social software can be integrated with MLEA, an application for Android devices that enables students and teacher to access Moodle resources through their cellphones and tablets. This integration allows

log into one of the applications and use the features of the other one without the need of share and vice-versa; (ii)

tags to the discussion they create. This is necessary to keep the consistency with Moodle when the plug-create or join social networks from discussions in a forum. When a student does it, he/she

different from those who had participated in the forum. The social software follows the pattern of the Android Dashbord project, whose goal is to provide to the

he system provides. The Figure 3 - a) shows Share happens when the user clicks the start social

network button passing the theme that he wants the network to be create, which in this example is about java, Share and the participant

who started the event will see in his screen the list of users who have interests similar to his, as shown in en different applications,

Figure 3. (a) Start screen of the social software; (b) MLEA screen used to begin the process of creating a social network;

ISBN: 978-972-8939-66-3 © 2012 IADIS

256

This paper aimed to present the development of a Mobile Social Software that enables the automatic construction and the articulation of online social networks to students and teachers from Moodle. The central idea is to integrate this social software with Mobile Learning Environment Adapter (MLEA) whose goal is to make Moodle accessible through mobile devices. This integration provides new ways of interaction and collaboration between students and teachers that access Moodle through these devices. In addition the proposed software can be used in distinct Moodle instances, from different institutions, and be configured to interact between them. This integration can lead to a gain of knowledge for each student and teacher involved, because it increases the opportunities for exchange of experiences with people who were previously unable to be part of his/her social network.

The main future work is to extent the proposed social software to allow the automatic construction of the social networks through the traditional Moodle, not only the mobile one, and the evaluation of the software with users in a real course, aiming to verify the increase of the interactions and the possible gain in learning through collaborative learning.

This work is funded by SENACYT (Secretaría Nacional de Ciencia, Tecnología e Innovación) as part of the Public Announcement for the Promotion of International Collaboration in R & D. The authors express their gratitude to SENACYT and the Technological University of Panama, in Panama, and the University of the Sinos Valley, in Porto Alegre, Brazil, for support the development of this project.

REFERENCES

Baloian, P. and Galdames, N., 2004. A Model for a Collaborative Recommender System for Multimedia Learning Material. In 10th International Workshop on Groupware. Heidelberg, Germany.

Campbell et al, 2005. Elgg a Personal Learning Landscape. In The Electronic Journal for English as a Second Language. Chatti, M. A. et al, 2010. Connectivism the Network Metaphor of Learning. In International Journal of Learning

Technology.

Chatti, M. A. et al, 2006. Mobile Web Services for Collaborative Learning. In Proceedings of the Fourth IEEE International Workshop on Wireless, Mobile and Ubiquitous Technology in Education.

Crespo, S. et al, 2010. MLEA – Uma Arquitetura Baseada em OWL para a Formação de Ambientes Móveis Flexíveis de Recomendação, Interação e Alarmes para Usuários de uma Plataforma EAD. In Proceedings of MoodleMoot, São Paulo, Brazil.

Laydner, L, 2007. Social Networking Features. http://tracker.moodle.org/browse/MDL-10169. Li, M. and Liu, Z., 2009. The Role of Online Social Networks in Students’ e-Learning Experiences. In Computational

Intelligence and Software Engineering, pp 1 - 4. Mahara, 2011. Moodle Mahara Integration. https://wiki.mahara.org/images/d/d5/Mahoodle.pdf. MoodleCore, 2007. Elgg Integration Block. http://moodle.org/mod/forum/discuss.php?d=83788. MoodleDocs, 2011. Elgg. http:/docs./moodle.org/20/en/Elgg. Philips, L. et al, 2011. Facebook for Educators. http://facebookforeducators.org. Ractham, P. and Firpo, 2011.Using Social Networking Technology to Enhance Learning in Higher Education: A Case

Study Using Facebook. In Proceedings of the 44th Hawaii International Conference on System Sciences Journal of Learning Technology, pp 1 – 10.

Wasserman, S. and Faust, K., 1994. Social Network Analysis: Methods and Applications. In Structural Analysis in the Social Sciences.


257

MOBILE LEARNING SYSTEM FOR EXPERIMENTS INVOLVING ELECTRONIC CIRCUIT MAKING USING A

TABLET PC

Atsushi Takemura Tokyo University of Agriculture and Technology

2-24-16, Naka-cho, Koganei-shi, Tokyo 184-8588, Japan

ABSTRACT

This paper proposes a novel mobile learning system for technical experiments involving electronic circuit making. To support circuit design and production, each student uses a portable computer (tablet PC) during the course of the experiments. In the proposed system, an analysis system that runs on a wireless network performs circuit recognition for the designed and constructed circuit’s image, which is transmitted from the user’s tablet PC. The analysis system can also translate the structure of the circuit into that of a general circuit description language (SPICE). This SPICE translation technique can indicate how the circuit works and can identify incorrect parts that may exist in the circuit. The proposed system is applicable to various circuit types and learning environments such as computer-aided circuit design and learning how to manufacture both virtual and real circuits. Therefore, this system has the advantage of allowing the user to choose a preferred educational support system on the basis of the required purpose or environment. The usefulness and effectiveness of the proposed system was evaluated by analyzing circuits made by 15 university students in an actual class.

KEYWORDS

Electronic circuit experiment, circuit design, circuit making, circuit translation, SPICE

1. INTRODUCTION

Knowledge of electronic circuit construction is important for education involving technical experiments. Therefore, the development of an educational support system for experiments involving circuit making is important. Recently, several such systems have been developed to improve students’ understanding of electronic circuits and their circuit-making ability (Gurkan, 2008; Oliver, 2009; Fitch, 2011). However, these conventional systems cannot cope with the wide variety of circuits designed by individual experimenters because they are based on all-purpose or ready-made learning tools. Moreover, the number of students is very large compared with the number of instructors, and it is therefore difficult to ensure individual instruction. Experiments performed in such environments may result in accidents such as electric shocks and fires. To overcome these disadvantages, I have proposed an educational support system for distance learning of experiments involving real circuit making (RCM) and virtual circuit making (VCM) (Takemura 2011). During the experiments, this system translates a designed circuit into a general circuit-description language (Simulation Program Integrated Circuit Emphasis: SPICE) (Rabaey) based on image processing techniques. This system can also simulate circuit behavior and inform the experimenter of the simulation result. Therefore, the experimenter can determine whether the circuit works correctly. This information is important for improving the experimental efficiency, and can prevent the occurrence of accidents. In this study, I improved this system and increased its applicability to various educational modes and media (e.g., mobile learning and virtual laboratories) for electronic circuits and experiments including circuit making such as circuit design, VCM, and RCM (cf., section 2.). An advantage of the proposed system is that a user can choose a preferred educational support system based on the required purpose or environment. The usefulness of the proposed system was evaluated by analyzing 15 circuits made by university students in an actual class.

ISBN: 978-972-8939-66-3 © 2012 IADIS

258

2. METHODOLOGY

Figure 1 illustrates the proposed educational support system. This study improves on the preceding e-learning system (Takemura, 2011) by making it usable for mobile learning (cf., 2.1 and 2.2). Each experimenter (student) designs his circuits using a tablet PC. The circuits made by the VCM system are transmitted to the remote analysis system via wireless internet. The analysis system can translate the circuit into SPICE. Automated circuit translation into SPICE enables simulation of the circuit operation, and individual users can observe the circuit behavior on their tablet PCs. Any differences that exist between the SPICE information for correct circuits and circuits made by an experimenter indicate the presence and location of incorrect parts in the circuit. This is an important step aimed at improving the efficiency and safety of circuit designing. In addition, the proposed system has the merit of being applicable to various educational modes for electronic circuits and experiments including circuit making such as circuit design, VCM, and RCM.

Figure 1. Schema of the proposed mobile learning system for experiments involving circuit making.

2.1 Mobile Learning System for Circuit Design and Virtual Circuit Making

The preceding VCM (Takemura, 2011) requires high resolution displays and software used exclusively for the processing of large amounts of data. Therefore, this system is not applicable to mobile learning. In this study, this system is improved so that an experimenter can use a general graphic editor that is usually provided in a tablet PC. To indicate the connections of circuit devices and wires on a virtual circuit, an experimenter is only required to draw colored lines on a template image (breadboard image) using the touch panel on the tablet PC. Each experimenter can download the breadboard image from the analysis system. The analysis system can differentiate between circuit devices and wiring based on the line colors that are defined by the experimenter. Images of the virtual circuit can be saved using a general file format (e.g., JPEG and BMP) and transmitted to the analysis system, together with information pertaining to the color-coding and device parameters (e.g., resistance, capacitance, and model names of ICs). The analysis system can translate the virtual circuit into SPICE without errors because circuit recognition is based on data that is related to the input of the virtually constructed circuit. Based on circuit recognition and translation, the analysis system notifies the experimenter of the circuit performance and whether or not there are incorrect parts in the circuit.


259

2.2 Mobile Learning System for Real Circuit Making

The analysis system in the previous e-learning system (Takemura, 2011) includes a CCD camera used for the acquisition of video data obtained from the circuit during the experiment. This video data is transmitted to an analysis system. Using moving image processing, the analysis system automatically recognizes sequential changes in circuit construction in real-time. However, experiments are disturbed when the computer is operated in order to obtain video data during the circuit making. To translate the produced circuits into SPICE without such disturbances, the proposed system uses only an image file that is obtained by a tablet PC after the completion of circuit making.

To realize the task of circuit recognition, the analysis system performs pattern matching between the virtually made circuit (developed using VCM) and the circuit made using RCM. This allows the user to differentiate between the layout of each device and the circuit wiring. The analysis system performs circuit recognition based on the information obtained from this approximate differentiation and the database of circuit devices, followed by an approximate recognition process. The combination of two recognition processes improves the accuracy of the circuit recognition and translation processes performed using a tablet PC, and decreases the computing cost for the circuit recognition.


The proposed system is evaluated by analyzing circuits designed and constructed by 15 experimenters (students) in an actual class at Tokyo University of Agriculture and Technology. Figure 2(a) shows the circuit diagram of the circuit (absolute value circuit) to be designed, and Fig. 2(b) shows the simulation of the circuit in Fig. 2(a) based on SPICE.

(a) (b)

Figure 2. Electronic circuit for circuit making experiment: (a) diagram of circuit to be designed and (b) circuit simulation of the circuit in Fig. 2(a) based on SPICE.

Figure 3 shows an example of the results obtained using a correct circuit, which was designed and constructed virtually by one of the students using the VCM system. Figure 3(a) shows the image of a breadboard that was downloaded from the analysis system. Fig. 3(b) shows the correct circuit that was drawn using the experimenter’s tablet PC. Figure 3(c) shows the result of circuit translation (into SPICE) obtained from the circuit shown in Fig. 3(b). Figure 3(d) shows an example of the simulation results obtained from the result of the SPICE translation. The result of the automated circuit translation was successful. Therefore, the simulation result coincided with the true behavior of the circuit shown in Fig. 2(b).

Figure 4(a) shows the circuit using the RCM system that is based on the same circuit that was designed and constructed virtually using the VCM system. As shown in Fig. 4(b), the analysis system automatically informs the experimenter of the incorrect parts. Figure 4(c) shows the corrected circuit. Fig. 4(d) shows the result of circuit translation (into SPICE) from the corrected circuit, while Figure 4(e) shows the circuit behavior based on circuit translation. The user can verify that the circuit behaves correctly by comparing with Fig. 3(d).

ISBN: 978-972-8939-66-3 © 2012 IADIS

260

The proposed system was evaluated by analyzing the circuits made by 15 students at Tokyo University of Agriculture and Technology. The following positive responses, which pertain to the usefulness and efficiency of the proposed system, were obtained from all the students:

• The proposed system, which can be used by an experimenter on a general tablet PC, is useful and effective because it does not require a large desktop computer and software used exclusively.

• The proposed systems is effective as a mobile learning tool because remote education of topics such as circuit designs and experiments involving circuit making is made possible wherever a wireless internet connection is available.

• Distance learning using the VCM system is effective for users lacking equipment for real circuit making (RCM) (e.g., laboratories, circuit components, and devices).

The proposed RCM system successfully differentiated between these circuit components, with the exception of model names of ICs, for which experimenters have to transmit to the analysis system using their tablet PCs. However, a few technical defects were observed:

• A more user-friendly user interface is required for the VCM system used for transmission of the information for retesting the device parameters and color-coding.

• Differentiation of model names of ICs was incomplete.

(a) (b)

(c) (d)

Figure 3. Results of a correct circuit made by a student using the VCM system: (a) breadboard image downloaded from the analysis system, (b) correct circuit made using a tablet PC, (c) circuit translation of the virtually made circuit in (b),

(d) circuit simulation of the incorrect circuit based on (c).

4. CONCLUSION

This paper proposed a novel mobile learning system for experiments involving circuit making. The proposed system has the advantage of allowing a user to use general graphic editors that are usually provided in a tablet PC. This system is applicable to various types of experiments that are performed in different environments such as computer-aided circuit design, VCM, and RCM. The usefulness and effectiveness of the system were verified by analyzing electronic circuits made by 15 students in a real university class. The following steps are necessary to practically realize the proposed system:

• A more advanced GUI is important to improve the user-friendliness of the experimenter’s system. • Applicability to larger scale circuits is important. • The usefulness of the proposed system must be validated by a larger number of experimenters.


261

(a) (b) (c)

(d) (e)

Figure 4. Circuit making results obtained using the RCM system: (a) incorrect circuit, (b) incorrect part on the circuit indicated by red line rectangles, (c) corrected circuit, (d) circuit translation into SPICE, and (e) circuit simulation of the

corrected circuit based on (c).

ACKNOWLEDGMENT

This work was supported in part by a Grant-in-Aid for Scientific Research (KAKENHI) 22500878 by the Japan Society for the Promotion of Science (JSPS).

REFERENCES

Gurkan D. et al., 2008. Remote laboratories for optical circuits, In IEEE Trans. Education, Vol. 51, No. 1, pp. 53-60. Oliver J.P. et al., 2009. Lab at Home: Hardware Kits for a Digital Design Lab, In IEEE Trans. Education, Vol. 52, No. 1,

pp. 46-51. Fitch A.L. et al., 2011. An Analog Computer for Electronic Engineering, In IEEE Trans. Education, Vol. 54, No.4,

pp.550-557. Rabaey J.M., The Spice Page, <URL: http://bwrc.eecs.berkeley.edu/Classes/IcBook/SPICE/> (accessed Nov. 25, 2011). Takemura A., 2011. E-learning system for experiments involving virtual and real electronic circuit making by using

network-based image processing technique, Proc. IADIS Conference e-Learning 2011, Rome, Italy, pp. 367-371.

ISBN: 978-972-8939-66-3 © 2012 IADIS

262

A MOBILE APPLICATION WITH EMBODIED MULTIMODAL INTERACTIONS FOR UNDERSTANDING

REPRESENTATIONS OF MOTION IN PHYSICS

Mattias Davidsson CeLeKT, Linnaeus University , 351 95 Växjö, Sweden

ABSTRACT

Current research in the Learning Sciences points out different methods and approaches to enhance and assist students in their learning and understanding of mathematical representations of the underlying physics of everyday situations. One of the aims of this paper is to address how mobile applications can be designed to support some of the pedagogical challenges associated with learners´ understanding of different graphical representations of motion – e.g. displacement as a function of time, velocity as a function of time, and how these couple to the actual motion, to each other, as well as to other mathematical representations of motion such as functions, equations and descriptive text. A prototype design is presented including a new type of application, or app, for mobile and in classroom use, using touch- and gesture based technology. One of the specific aims of this set of applications is to spur the learners exposure to, interaction with, as well as creation of multiple and multimodal representations of physical everyday phenomena involving motion, in a personal inquiry-based approach that could involve both informal as well as formal learning activities.

KEYWORDS

Multiple representations, physics education, embodied learning, e-learning, mobile learning, perceptual learning

1. INTRODUCTION

The explosion of the number of computers in Swedish schools, (Sverigekartan, 2011) where around 50% of the community schools now plan1-to-1 programs, and, as of late, the explosion in the number of touch based devices in the hands of (young) learners open up a new field for the design of touch based apps for education. In cognitive research the concepts of multimodal representations of complex concepts in science stress the importance of a multitude of senses to be involved in the learning process, and likewise when it comes to using different kinds of representations of mathematical abstractions of physical processes and events (Donovan & Bransford, 2005, Linn & Eylon, 2011).

Bridging the gap between the qualitative understanding and the ability to perform quantitative calculations (Skolverket, 2009) is essential for the high school students not to loose interest in the subject of physics, as is the ability to compete with other sources of knowledge and information in the ever growing media arena on its different platforms. We need to catch the attention of the new generation of learners. Introducing the pre-high school students, as well as high school students, to multiple representations, having them interact with- and manipulate these in an informal and preferably game-based perceptual learning setting could be one component towards achieving this goal. At the present moment the author’s opinion is that there is a lack of high quality applications dedicated to learning physics, and that there is a need and surge for it. Recently (mid October 2011) the Algodoo simulation software proved that there is a market for these types of applications, immediately jumping to the top grossing position in the Apple App store. This also implies that game like applications with an informal design and look that does not necessarily remind learners of school-work could be the way to go in terms of spreading this kind of application and hence their pedagogical content. So far studies like that of Kelly (2011) on the use of apps not specifically designed for physics studied also point in that direction.

The contribution of this paper is to present a prototype application specifically designed for learning physics using touch- and gesture based consumer technology. The application will aid learners in the


263

understanding of different graphical representations of motion, to see the connections between them, and the connections to the actual movement they represent. The learning experience includes embodied interactions involving several sensory modalities and the design and envisioned usage scenarios is based on sound theoretical argument and research as presented in the following section. The rest of the paper is organized as follows: First the theoretical background and justification is presented together with relevant related work. Then the prototype application is described in a typical pedagogical scenario setting and the paper is finished with a description of, and discussion about ongoing and future efforts.

2. THEORETICAL JUSTIFICATION AND RELATED WORK

In order to motivate how to match the availability and capability of the new types of touch- and gesture based personal devices with the suggestions from theory and recent studies, I will review a number of papers that have been identified as pointing to real possibilities in tackling the challenge of teaching young learners of today the meaning of abstract mathematical representations within physics.

In a recent paper, Anastopoulou, Sharples and Baber (2011) demonstrated the importance and power of getting the students and their bodies involved in the creation of representations of multiple modalities and types describing the mathematical concepts of motion such as speed, distance, time and velocity. Being able to produce and manipulate graphs e.g. showing the displacement and velocity of their hands moving as a function of time was shown to be significantly more effective when it comes to learning outcomes and understanding comparing pre- and post-tests with students that did not involve their own bodies in the learning but instead watched a teacher (the researcher) perform the same action. The background to the study by Anastopoulou, Sharples and Baber (2011) is the suggestion by Papert (1980) that using your own body to construct symbolic representations can aid students in their learning, a suggestion further stressed by Cox (1999). We propose to build on and spread this kind of learning activity in terms of first of all touch- and gesture based applications for tablets, smart-phones and digital whiteboards, but also for ordinary desktop computers. This is in line with the conclusions and suggestions from Anastopoulou, Sharples and Baber (2011) where they propose that “Providing students with personal multimodal technologies may help them to engage in learning science concepts”.

The usage of the new types of internet-connected touch based platforms also opens up the possibility to add more features as well as using other aspects of the hardware motivated by the same theoretical assumptions. One could for example add the possibility for the learner to reproduce a graph on a larger physical scale, letting the learner run or walk according to the description in a velocity-time graph, where the phone or tablet use the built in GPS functionality to map the speed, once again involving the student and their bodies in the construction/reproduction of abstract representations.

The second major work that the suggested approach and further development is based upon is the study presented by Kellman, Massey and Son (2009). The hypothesis is that the methods presented could increase the effect presented by Anastopoulou, Sharples and Baber (2011). Before receiving formal instructions on graphical representations of physical and other processes the learners in this study on perceptual learning were given the task to, in quick succession, guess and pair graphs with other representations such as equations and written text. The hope was that they, after many trials, would see the patterns and connections between the different representations and what they actually represent. This was indeed what was observed, as well as the ability of the subject students to pick up the more formal instructions and concepts of mathematical graphical representations easier, and for the knowledge taught with this inverted approach to stick longer, compared to the traditional one where the students are presented with formal education first and problems solving second. Similarly, the suggested design in this paper hypothetically would let the learners find and see the patterns and connections without the need of formal instructions.

There are already some efforts done and applications on the market, where some of the different aspects of touch capability, authentic and perceptual learning, multiple representations, ubiquity and mobility are addressed. One example is the Vernier Logger Pro desktop software and the quite recent Vernier iPad application (Vernier, 2011) where learners can film an object in motion, and from the film, using the iPads touch capability, extract graphical representations of the objects motion. Kelly (2011) have studied the use of publicly available game-like apps for iPod touch (most not especially made for physics studies) in middle school physics education and found a great deal of benefit e.g. from the standpoint of the students engagement level. A study carried out by Barab and colleagues (2007) further stresses the importance of

ISBN: 978-972-8939-66-3 © 2012 IADIS

264

engaging the learners in embodied participation. The application presented in this paper could then be part of the, by Barab et al. (2007), sought for multitude of embodied practices. Furthermore, major efforts on the hardware and research side like that of Texas Instruments (2011) build upon some of the ideas presented here. However, the aspects of embodiment - using multi-touch or body movement - affordance, and informal perceptual learning realized in one application have not (yet) come to the author’s attention. Neither does any of the above efforts include for the learners to generate and interact with the graphical representations directly using their own bodies with real-time multimodal feedback. Aiming for this sets the demands for the learning and functional requirements of the application described below.

3. MOBILE APPLICATION DESIGN

Based on the requirements as stated above, we rely on affordable consumer hardware and open platforms for developing a first generation application where the learner directly interact using their body and gets instant feedback in terms of graphical mathematical representations of their body-movements. The touch-based mobile application has been developed by the author using the processing language and is running on an Android platform. The Kinect application was developed using the Actionscript language with the Flash builder tool.

Figure 1. The prototype application in use (a). A screen shot showing motion graphs and suggested menu (b). The Kinect interface in use (c).

The first prototype illustrates the features of the most common graphical representations of motion by simply plotting the y-coordinate of the users moving finger, or in case of the Kinect version - the hand, on the right side of the display (see fig. 1a and 1c). As time passes the recently plotted coordinates are moved at a steady pace to the left, effectively producing a position, or displacement versus time graph (d-t) of the learners finger. The concurrent positions of the touching finger are also used to calculate and plot a velocity versus time graph (v-t), below the d-t graph (see fig. 1a and 1b). At the same time, an optional vector-representation of the finger/hand speed is plotted at the position of the finger. This simple setup could be used by practically anyone without any explanation of the rules needed or the physics involved. Thus the application could be placed in the hands of learners before formalizing the instructions on the physics and mathematics of movement, or it could be used in an exploratory fashion in the classroom with a flexible amount of guidance. The application could also be used in an informal setting outside school.

One typical question a learner is asked to answer concerning these types of graphs is what the slope of a d-t graph represents. Using the prototype it is evident that moving your hand slowly at a constant speed (see fig.1a), either towards or away from you, will result in a graph with a small constant inclination compared to when moving your finger at a faster speed (see fig.1b). Furthermore it is possible to examine and connect features of the two graphs in real time as you move your finger, or by pausing the application with a single touch. The learner could be asked to find out the properties of graphs when moving the finger at constant low or higher speed, with increasing or decreasing speed or other types of motion. The other way around the learner could also be asked to produce a d-t or v-t graph with a specific set of features, such as a v-t graph with no slope but of non-zero value, and try and find out what type of motion will produce it.

Using the app, the learners engage in embodied interactions with graphical representations by moving their hands, and produce visual representations in terms of graphs and vectors. To trigger a third modality, sound can be played while producing the graphs, where the frequency of the sound represents the speed of the finger. This feature could be turned on or off from the menu accessed by pausing the application with the tap of a finger. Another feature of importance to be activated from the menu, could be the possibility for the


265

learner to measure the slope of the d-t graph using two fingers to mark the region of interest in the graph and have the application calculate the velocity in that interval to be compared to the values of the v-t graph in the same interval. Several other features that could enhance the students’ engagement with the application and thus the exposure to multiple modalities and representations are discussed in the following section.

4. DISCUSSION AND FUTURE EFFORTS

In this paper we have explored the potentials and affordances offered by multi-touch and gesture based devices in relation to the design of mobile applications that may enable learners to interact in more intuitive embodied ways. The hope is for the learner to “feel” the movement embedded in different representations just by looking at them, and almost as learning to ride a bike be able to instinctively translate body movement into different graphical representations and vice versa. The prototype described in this paper is in the early stage of development and in the coming spring cosmetic work based on feedback from the early test phase in progress will be done. The GUI will be developed, and new as well as non-conventional types of graphical representations of the physics of motion will be added. Game based features, like those tested by Kellman et al. (2009) will be added, where learners will be asked to reproduce motions as represented by algebraic functions, by a presented v-t diagrams or representations in terms of text narratives. Similarly, using the built in GPS of mobile devices, the capability to produce, or be asked to reproduce graphs while walking or running will be implemented. Once again the learners body is involved in the production of different representations, but on a different scale. This feature will also be further explored using the Kinect interface, and all in all this will open up the possibilities for new innovative ways of embodiment in learning. Further on the aim is to evaluate the efficiency of the method both from the teacher perspective – how well does it integrate with the curriculum and already existing methods? – and from the learners perspective – can the increased learning effect presented in Anastopoulou (2011) be seen using the proposed method and hardware? We plan to introduce the app to a number of schools where tablets are being used in order to find out. Ideally using the same protocol as in Anastopoulou (2011) on the learners’ side, and using a more qualitative type of mixed method including surveys combined with in depth interviews on the teachers’ side.

REFERENCES

Anastopoulou, S. (2011). An evaluation of multimodal interactions with technology while learning science concepts. British Journal of Educational Technology Vol 42 No 2. ss. 266–290

Barab, S. (2007), Situationally embodied curriculum: Relating formalisms and contexts. Science Education, 91: 750–782. doi: 10.1002/sce.20217

Cox, R. (1999). Representation construction, externalised cognition and individual differences. Learning and instruction 9, ss. 343-363

Donovan M. S., Bransford J.D., (editors) (2005) How Students Learn: History, Mathematics, and Science in the Classroom. Whashington D.C., The national academies Press

Föreningen Datorn i Utbildningen (2011). Sverigekartan, http://www2.diu.se/framlar/egen-dator/ [2011-10-20] Kellman, P.J. (2009). Perceptual Learning Modules in Mathematics: Enhancing Students’ Pattern Recognition, Structure

Extraction, and Fluency. Topics in Cognitive Science, ss. 1–21 Kelly, A.M. (2011). Teaching Newton’s laws with the iPod Touch in conceptual physics. The Physics Teacher, 49(4),

202-205. Linn M.C., Eylon B.-S. (2011). Science learning and instruction: Taking advantage of technology to promote knowledge

integration. New York, NY: Routledge. Papert, S. (1980). Mindstorms: children, computers, and powerful ideas. New York: Basic Books. Texas Instruments (2011). Research on TI-Nspire™ Technology.

http://education.ti.com/educationportal/sites/US/nonProductMulti/research_nspire.html [2011-10-25] Vernier. (2011). Video Physics for iOS. http://www.vernier.com/products/software/video-physics/ [2011-10-19] Vogel, B. (2010), Integrating Mobile, Web and Sensory Technologies to Support Inquiry-Based Science Learning. The 6’th IEEE International Conference on Wireless, Mobile and Ubiquitous Technologies in Education. ss. 65-72 Skolverket. (2009). TIMSS Advanced 2008, Svenska gymnasieelevers kunskaper i avancerad matematik och fysik i ett

internationellt perspektiv. Report. Available: http://www.skolverket.se/publikationer?id=2291 [2011-10-17]

ISBN: 978-972-8939-66-3 © 2012 IADIS

266

YOUNG TURKISH LEARNERS’ FIRST ENCOUNTER WITH ENGLISH AS A FOREIGN LANGUAGE THROUGH

MOBILE DEVICES

Senem Yıldız Boğaziçi University

ABSTRACT

During this presentation, the process of designing and developing digital educational applications to introduce Turkish pre-school aged children with English as a foreign language through mobile devices such as smart phones and tablet computers and the preliminary findings of the investigation of the effectiveness of these applications on these learners’ language learning, specifically both receptive and expressive vocabulary acquisition, phonological awareness and listening comprehension skills will be discussed. Mobile devices, especially iPads are selected for this study as they provide an excellent platform for including activities that can activate both sides of the brain.

KEYWORDS

Mobile learning, english as a foreign language, young learners

1. LITERATURE REVIEW

1.1 Teaching Young Children

The benefits of learning a foreign language at an early age, especially on phonological awareness, listening comprehension and pronunciation, has been put forward by several research studies (Mechelli et al., 2004, Lightbown & Spada, 1994). Blondin et al. (1998) argue in the European Union’s recommendations that younger learners have an intuitive grasp of language and their ability to be more attuned to the phonological system of the target language make them more advantaged than older learners. They claim that “children are sensitive to the sounds and the rhythm of new languages and they enjoy copying new sounds and patterns of intonation” (as cites in Pinter, 2006). Learning a foreign language during preschool years has also positive influence on children’s physical, social and cognitive development. Multilingualism of children has been positively related to their skills about forming concepts, creativity, classification, reasoning and problem solving and it was observed that multilingualism increases language awareness and cognitive flexibility (Taylor-Ward, 2003; Bialystok, 2001; Foster and Reeves, 1989). In other words, learning a foreign language is considered to be an intellectual exercise. Furthermore, children who start becoming bilingual at preschool years were found to be more advantaged than their monolingual peers (Saunders, 1998).

The way children learn a second or foreign language differs from the way an older person learns languages. While older learners can approach language learning analytically and therefore can work on how a language is organized by studying the structures and rules, young learners approach a foreign language holistically (Pinter, 2006; Cameron, 2001). Language learning experience for children should be an enjoyable and stimulating experience with very frequent use of orally based actitivies; listening activities that include the recitation of songs and rhymes, and narration of short repetitive stories.

1.2 Role of Multimedia Environments in Learning

Multimedia environments by addressing both audio and visual senses tend to facilitate the procession of new information and increase retention. According to Paivio’s dual coding theory (1986), one of the most


267

prominent theories that explain learning in multimedia environments, new information is processed by two independently working channels. While one of these channels process verbal information like written texts or oral input, the other channel processes nonverbal information such as pictures, visuals and other nonverbal objects like sounds around us. These two channels functionally and structurally work independent from each other and yet support each other through symbolic systems that convene the same content. It was observed that when a learner codes new knowledge in both channels, retention of new knowledge later on increases (Mayer & Anderson, 1991; Paivio & Csapo, 1973) most probably because the learners find multiple ways to trace the information. When a learner restructures the new content both visually and nonvisually in his mind, meaningful learning occurs. And meaningful learning facilitates both the storage and recall of new information.

Another contribution of multimedia environments to learning is the control and interactivity features that they provide. In these environments, learners can access learning materials actively and whenever and however he/she wants rather than passively being exposed to these materials in a predetermined order. Having control over their learning processes help learners develop a more positive attitude towards learning.

It is known that the more there are media that cater to multiple senses of learners, the more effective the learning will be. Research shows that age is an important factor in the use of animations (Rieber, 1990). Children younger than 11 years old need more visual materials (animation, graphics, pictures etc.) than older ones. Adults can visualise orally presented texts in their minds better than children and therefore, it is more important to use visual materials when teaching young learners. It is observed that the visualization skill starts developing in children after the age of 9 and 10 (Sundberg, 1998).

Due to the above mentioned reasons, children may benefit from using multimedia environments when learning a foreign language more than adults. Digital books which can narrate individual words or whole texts, provide pronunciations, animated clues to word meanings, animate and label objects within stories and provide written definitions of words do help children understanding the story line, remembering the linguistic content in the stories better than story books with static pictures alone (Lewalter, 2003). It is argued that multimedia symbols, especially those that are in line with the storyline facilitate children understanding the story (Beck & McKeown, 2001). Similarly, zoom shots and other visual and audial effects draw learners’ attention to important visual details (Gibbons et al., 1986; Calvert et al., 1982). These features of multimedia environments provide scaffolding for children in choosing the content that facilitates the comprehension of stroyline (Greenfield et al., 1996; James, 1999; Kamil, Intrator, & Kim, 2000).

2. THE PRESENT STUDY

Majority of children who study at public schools in Turkey do not have a chance to be exposed to a foreign language before fourth grade. In other words, these children grow out of the early childhood age (0-8 years) defined as a critical age for language learning, especially in terms of phonological awareness, until they have a chance to meet a foreign language. However, children who do not have access to foreign languages at home or in their schools can be reached via appropriate language teaching materials that can be installed on mobile devices. Although a growing number of language teaching applications for tablet computers are being developed, the number of materials designed specifically for Turkish learners of English is exteremely limited. There are even less materials and applications for young Turkish learners of English.

The aim of this research project is to prepare educational applications to introduce pre-school aged children with English as a foreign language through mobile devices such as smart phones and tablet computers and investigate the effectiveness of these applications on their language learning, specifically both receptive and expressive vocabulary acquisition, phonological awareness and listening comprehension skills.

The first stage of the project includes designing and developing language teaching materials aiming at 4-6 year old children attending preschools in Turkey. These materials’ main aim is to introduce monolingual preschool children in Turkey with English as a foreign language for the first time in an engaging and motivating way, increase their phonological awareness and expose them to basic vocabulary. These materials are designed as iPad applications because these devices are light and portable and therefore easily accessible by children during the day at a variety of different places and under different conditions. Another advantage of tablet computers is their intuitive use, and touch screen interface which is easily operated by young children. These language teaching materials are designed to include texts, sounds, still and moving images

ISBN: 978-972-8939-66-3 © 2012 IADIS

268

and interactivity. All materials are bilingual (Turkish and English) and include written texts, narrations of texts by native speakers of the language, songs, rhymes, attracting and relevant visuals, animations, drag and drop interactivity, voice recording, playback of recorded sound, and immediate feedback features. Learners will be able to access the Turkish and English versions of the same content easily and quickly. Learners will be able to swipe through pages; they will be able to hear the pronunciation of an individual word (in both languages) by touching on words and objects on the screen, will be able to move around the objects on the screen using their fingertips, record their voice and then playback.

Cambridge English Young Learners syllabus is taken as a basis for the selection of target vocabulary and content. Applications allow learners to review new vocabulary along with images, animations and narrations. Short simple and yet interactive stories are used to contextualize the vocabulary and interactive games like puzzles, memory games, drag and drop items, sing-alongs where learners can record themselves follow the stories to reinforce vocabulary, listening comprehension and pronunciation. Motivating and encouraging immediate feedback will be provided.

The second stage of the project will start in February 2012. Two preschool classes in an instituion where mostly children from low socio economic class attend are selected. There is no formal English as a foreign language instruction provided in this instituion. Before the start of the study, these two classes will be randomly assigned as experimental and control classes. Typically, there are 10-12 children in each class. Around five iPads (without 3G feature to avoid the harmful effects) with the developed applications installed will be distributed to children in the experimental class. Children will also be able to take these devices home by taking turns. There will be no formal instruction of language in the experimental class but children will be encouraged to explore and the use the applications on iPads. In the control class, a language teacher will teach English as a foreign language using the same content for two to three hours a week for twelve weeks, without using mobile devices and technology. All the narrations, vocabulary pronunciations will be done by this teacher and interactive games will be played in the classroom. A linear syllabus will be followed during 12 weeks in control class.

At the beginning of the study, Peabody Picture Vocabulary Test (PPVT) will be administered to all children involved. The same test will be administered as a post test at the end of the 12 week period. In addition to PPVT, Expressive Vocabulary Test will also be given to learners as a post test. Listening comprehension and pronunciaton of children will be assesed by two native speaking English language teachers and Cambridge Listening Test.

During the study, the opinions and experiences of children, the teachers and the parents will also be recorded through inteviews and regular observations.

During the presentation, the materials design and development process, the transfer of materials into iPad applications and the preliminary findings of the actual data collection process shall be discussed.

REFERENCES

Beck, I. L., & McKeown, M. G. (2001). Text talks: Capturing the benefits of read-aloud experiences for young children. The Reading Teacher, 55, 10–20.

Bialystok, E. (2001). Bilingualism in development: Language, literacy and cognition. London: Cambridge University Press.

Blondin, C., Candelier, M., Edelenbos, P., Johnstone, A., Kubanek-German, A., & Taeschner, T. (1998). Foreign language in primary and preschool education: a review of recent reseeach within the European Union. London: CILT.

Cameron, L. (2001). Teaching languages to young learners. London: Cambridge University Press. Calvert, S. L., Huston, A. C., Watkins, B. A., & Wright, J. C. (1982). The relation between selective attention to

television forms and children’s comprehension of content. Child Development, 53, 601–610. Foster, K.M., & Reeves, C.K. (1989). FLES improves cognitive skills. FLES News, 2(3), 4. Gibbons, J., Anderson, D. R., Smith, R., Field, D. E., & Fischer, C. (1986). Young children’s recall and reconstruction of

audio and audiovisual narratives. Child Development, 57, 1014–1023. Greenfield, P. M., Camaioni, L., Ercolani, P., Weiss, L., Lauber, B. A., & Perucchini, P. (1996). Cognitive socialization

by computer games in two cultures: Inductive discovery or mastery of an iconic code? In I. E. Sigel (Series Ed.), P. M. Greenfield, & R. R. Cocking (Vol. Eds.), Advances, in applied developmental psychology: Interacting with video (Vol. 11, pp. 141–167). Norwood, NJ: Ablex.


269

James, R. (1999). Navigating CD-ROMs: An exploration of children reading interactive narratives. Children’s Literature in Education, 30, 47–63.

Kamil, M. L., Intrator, S. M., & Kim, H. S. (2000). The effects of other technologies on literacy and literacy learning. In M. L. Kamil, P. B. Mosenthal, P. D. Pearson, & R. Barr, (Eds.), Handbook of reading research (Vol. 3, pp. 771–788). Mahwah, NJ: Erlbaum.

Lewalter, D. (2003). Cognitive strategies for learning from static and dynamic visuals. Learning and Instruction, 13, 177–189.

Lightbown, P., & Spada, N. (1994). An innovative program for primary ESL in Quebec. TESOL Quarterly, 28(3), 563-579.

Mayer, R.E., & Anderson, R.B., (1991). Animations need narrations: An experimental test of a dual-coding hypothesis. Journal of Educational Psychology, 83, 484–490.

Mechelli, A., Crinion, J.T., Noppeney, U., O’Doherty. J., Ashburner. J., Frackowiak, R.S., & Price, C.J. (2004). Neurolinguistics: structural plasticity in the bilingual brain. Nature, 431, 757.

Paivio, A., & Csapo, K. (1973). Picture superiority in free recall: Imagery or dual coding? Cognitive Psychology, 5, 176-206.

Paivio, A. (1986). Mental representations: A dual coding approach. Oxford University Press: Oxford, England. Pinter, A. (2006). Teaching young language learners. Oxford University Press. Rieber, L.P. (1990). Using computer animated graphics in science instruction with children. Journal of Educational

Psychology, 82(1), 135-140. Saunders, C. M. (1998). The effect of the study of a foreign language in the elementary school on scores on the Iowa test

of basic skills and an analysis of student-participant attitudes and abilities. Athens, GA: University of Georgia. Sundberg, P. A., (1998). Animation in CALL: Learning to think in the fourth dimension. CALICO’98 Symposium, San

Diego, California. Taylor-Ward, C. (2003). The relationship between elementary foreign language students in grades three through five and

academic achievement on the Iowa test of basic skills (ITBS) and fourth grade Louisiana educational assessment program for the 21st century (LEAP 21) test. Baton Rouge: Louisiana State University, Department of Curriculum and Instruction.

ISBN: 978-972-8939-66-3 © 2012 IADIS

270

MOTIVATING LEARNING THROUGH MOBILE INTERACTION

Alexiei Dingli and Dylan Seychell University of Malta

ABSTRACT

The acquisition of any goal happens only with the correct dose of motivation instilled in the individual pursuing it. Mobile technology is at the same time providing us with different sensors and technology which allow us to measure valuable attributes around a person who is engaged in a learning experience. In this paper we will be studying what motivates an individual while finding methods on the mobile device which will reach this motivation. The socio-cultural background of the individual undergoing learning will also be brought into context by acting as one of the driving forces of the presented recommendation technique.

KEYWORDS

Motivation, Mobile Technology, Recommendations, Location Based Services, Cultural Background

1. INTRODUCTION

Recommender techniques have been used in various scenarios and they do indeed act as a learning opportunity for the users of such techniques. However, recommendations provided to users are normally used as a tool for overcoming the information overload problem [Wei et al, 2005]. We believe that in the context of m-learning, the information overload problem is an opportunity if filtered carefully. Motivation of learners takes place when one finds the key factors which motivate the individual in question. Nevertheless, not everyone is motivated by the same content and therefore recommender systems must be strategically set to find the correct factors by which to filter the available information depending on the receiver or learner.

This paper therefore proposes a recommendation approach based on 3 main factors: User Profiling, Mobile Metrics and User Cultural Background. Traditionally, recommender systems have been based on user profiling and different techniques which would filter content. These techniques will be explored in section 2.2 in this paper. The philosophy of this proposed recommendation technique is to motivate individuals who are pursuing knowledge through their mobile devices. The theory behind human motivation will be explored in section 2.1 which will also outline the key factors of motivation and approaches towards motivation. The socio-cultural context of the individual will then be taken in consideration in order to ensure that the content respects the individual and appeals to the quest in question.

This technique is based on a mobile environment which implies that the user is on the move and therefore not bound to one learning environment. This aspect is very important in the effort of motivating learning and the design of this technique will therefore be based on providing content based on the User background in his/her ‘geographical’ context. Feedback is important in the evaluation of the learning experience of individuals. Games are proposed in this technique in order to create a feedback interface between the learner and ‘teacher’ in order to ensure that the learner is following the designated learning trends.


271

2. BACKGROUND

2.1 Human Motivation

Various motivation theories assume that people are motivated if they are given an opportunity to reach a goal together with the right stimuli [Heller, 1998]. In other words, motivation deals with actions that determine how and why people initiate actions towards a goal while feeling involved in the activity leading to the said goal [Maslow, 1943]. The more motivated a person is in reaching a goal, the more persistent this person gets in the endeavor. Learning motivation is organized in two categories, Intrinsic and Extrinsic [Vallerand, 1993]. The intrinsic category includes factors within the individual which include personal motivation and drive towards the achievement of a reward. On the other hand, the extrinsic category includes external factors which include social pressure or a degree of punishment if a goal is not achieved. The latter may not necessarily be related to the task.

2.2 Mobile Recommender Systems

This technique aims at providing relevant content from the web to the user depending on his current location. The unvarying problem arising from this approach is that the web contains a very large amount of information that is by far more than what the user really needs [Wei et al, 2005]. This is known as the information overload problem. Throughout the years various efforts have been made in this field and recommender systems are now widely used in various areas such as e-commerce [Li et al, 2009] and content websites which need to guide viewers through videos, audio and other media [Wei et al, 2003].

In order to achieve this goal, different techniques have been developed in an effort to filter vast amounts of content. The Content-Based approach recommends content depending on the description of items being recommended [Wei et al, 2005] and therefore acting upon a similarity measure between the items. This is an objective filter since it does not depend on opinions. On the other hand, the Collaborative Filtering approach depends on the opinion and feedback of people. This is very efficient when it comes to recommending content which is difficult to compare due to the nature of the files [Li et al, 2009]. Examples of such content are video and audio files. Half way between these two approaches; one finds the Knowledge Based Filtering which refers to the class of filtering techniques which rely on rules. This approach is about getting to know the user and respective items and translate this information into a collection of statements [Berka and Poslnig, 2004]. A combination of Fuzzy and Boolean Logic is used in this approach in order to reduce the size of the final data set. The Hybrid approach then brings together the other filtering techniques in order to allow for systems to balance out subjective and objective judgments. This is a very good compromise since no approach solves all problems [Wei et al, 2003]. In practice, the hybrid approach would compute a final vector and then merge it with other collaborative ratings. These filtering techniques were enhanced with the developments in the field of mobile technology. Mobile devices improved recommender systems since they now allow for collection of situational information depending on the location of the user and thus the environment surrounding the same user [Huang and Webster, 2004]. This collection of information from extrinsic sources would therefore add more value to the final recommended set of items since it would improve relevance to the end user.

2.3 Cultural Background

When striving to motivate an individual, one has to bear in mind that motivation is at the end of the day boosted by personal attitude and other factors such as needs and interests. These attributes are controlled by the cultural background of the same individual which overarches human behavior in different situations. In this paper we are proposing an approach based on results of the World Values Survey (WVS) which is carried out in various countries around the world in an effort to measure a vast set of values while studying trends and variations in world values [Inglehart, 2009]. This survey investigates various aspects of values which vary from the measurement of the degree in trust in families or social groups to the degree of personal creativity. In the context of this survey, [Inglehart and Welzel, 2005] present the Inglehart-Welzel Cultural Map of the World which places countries on a set of axis categorized by a degree of Traditional/Secular

ISBN: 978-972-8939-66-3 © 2012 IADIS

272

values against their Survival and Self Expression Values. The placing does not therefore reflect the geographical location of the countries in question and it is a measurement of cultural proximity.

3. METHODOLOGY

In this paper we attempt to show the importance of side-factors which are required in order to ensure the relevance of content to the end user. In this paper we are proposing a technique which would be able to generate content and quests in relation to the user profile and background together with information from the environment where the activity is carried out. In order to tackle this problem, we propose that internal functions are organized in 3 layers. The outer layer represents the functions which are closest to the user while on the other hand, the inner-most layer represents the metrics which the mobile device captures from the geographical environment of the user. Recommender systems which are not housed in a mobile device normally focus on the User Layer features by getting to know the user, build his profile and update it according to the feedback given back through the application. The proposed technique does not deal directly with the mobile layer since, in practice, most mobile operating systems handle these metrics very well. In the middle layer we propose features which are relevant to the end user but utilize at the same time the metrics from the Mobile Device Layer.

Figure 1. The key processes of the proposed technique [Source: Authors]

Figure 1 shows the outcome of the conceptual layer discussed above. The system starts by reading information from the device and then using is as parameter for the quests and information requests. While the games and content is loaded, the user profile together with his cultural background is computed. The Cultural background can be computed through a multinomial logistic regression of the WVS given the user’s age gender and nationality. For a more precise reading, the user may be prompted with a set of questions which would return a better picture of the user’s values. The system would at the same time update its


273

information about its location from the web by making use of the mobile metrics and adapt content accordingly. Once this is completed, the system would launch the games with quests together with location based information and monitor the user activity. The last step of the system would be the collection of any feedback from the user which would be used to tune the system in the next use. More material and detail will be presented in future publications

4. EVALUATION

The concept proposed in this paper was initially evaluated with a survey in which 92 individuals of different age, gender and nationality answered the questionnaire. This survey investigated the user views of mobile recommendations systems in light of travelling. An encouraging 87% said that they will follow suggested provided by mobile devices and 48% of the respondents owned a smart-phone or a tablet. This shows an encouraging trend towards smart-phones since a research conducted by the authors in 2010 showed that only 40% owned a smart-phone. This survey also showed that 63% of the respondents would update information whenever requested and another 16% said that they require more information before inputting any information in their device.

5. CONCLUSION

This paper intends to explore this concept in its early stages. Ground research was conducted about the way users expect applications to function and to measure the trust of users in such devices. On the other hand the concept presented above presents a way of engaging users in a learning activity while striving to keep the goals clear since they act as a stronghold in human motivation. Implementation of this work commenced but to date, there are no sufficient results to completely prove this concept. Work on a simulation together with another survey with an implementation of this technique on a mobile device is underway and will yield clearer results in the near future.

REFERENCES

Berka, T. and Poslnig, M. (2004). Designing recommender systems for tourism. In The 11th International Conference on Information Technology in Travel and Tourism. Springer-Verlag Wien: Vienna. Cairo, Egypt.

Heller, R. (1998). Motivating People. Dorling Kindersley. Huang, W. and Webster, D. (2004). Enabling context-aware agents to understandsemantic resources on the wwwand the

semantic web. In Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence, WI’04, pages 138–144, Washington, DC, USA. IEEE Computer Society.

Inglehart, R. (2009). Values Change in the World. World Values Survey. Inglehart, R. and Welzel, C. (2005). Modernization, Cultural Change and Democracy. Cambridge University Press. Li, L.-H., Lee, F.-M., Chen, Y.-C., and Cheng, C.-Y. (2009). A multi-stage collaborative filtering approach for mobile

recommendation. In Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication, ICUIMC ’09, pages 88–97, New York, NY, USA. ACM.

Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50, 370-396. Vallerand, R. J. (1993). The Academic Motivation Scale: A Measure of Intrinsic, Extrinsic, and Amotivation in

Education. Educational and Psychological Measurement, 52, 4, 1003-17. Wei, Y. Z., Moreau, L., and Jennings, N. R. (2003). Recommender systems: a market-based design. In Proceedings of the

second international joint conference on Autonomous agents and multiagent systems, AAMAS ’03, pages 600–607, New York, NY, USA. ACM.

Wei, Y. Z., Moreau, L., and Jennings, N. R. (2005). A market-based approach to recommender systems. ACM Trans. Inf. Syst., 23:227–266.

ISBN: 978-972-8939-66-3 © 2012 IADIS

274

EFFECTS OF A TEST DELIVERY SYSTEM IN A BLENDED LEARNING ENVIRONMENT: A FOCUS ON THE

RELATIONSHIP BETWEEN ATTITUDE TOWARD TESTS, MOTIVATION FOR LEARNING, AND TEST SCORES

Takeshi Kitazawa and Masahiro Naga Tokyo Metropolitan University

ABSTRACT

This paper describes the effects of system whereby tests are delivered to students’ mobile phones in a blended learning environment. We employed the test delivery system along with the e-learning system. A teacher sent five tests, with questions pertaining to the course content, from the e-learning system to students’ mobile phones a few days after each lesson. We analyzed the relationship between their test approach/avoidance tendency, motivation for learning, which was determined by the time lapse between the sending and taking of the test and the test scores. We found that 37 students had a test approach tendency, 51 students had a test avoidance tendency, and 6 students had a neutral tendency. The average rate of test completion was 93.2%, which showed that almost all the students took the tests. The relationship between the students’ attitudes toward tests, motivation for learning, and test scores indicated that their attitude toward the tests delivered by this system, determined by the rate of test completion and time lapses between the sending and taking of the tests, did not depend on the students’ test approach/avoidance tendency. However, the average percentage of correct answers of the test approach tendency group was higher than that of the test avoidance tendency group.

KEYWORDS

m-learning, e-learning, blended learning, test approach-avoidance tendency, motivation for learning

1. INTRODUCTION

Many Japanese university students do not study outside of school hours. Therefore, to address this problem, teachers at Japanese universities should participate in faculty development (FD) programs in order to improve college classes. FD was mentioned in the 2008 report of the Japanese Ministry of Education, Culture, Sports, Science and Technology. In order to change students’ learning strategies, we adopted the blended learning approach at our university in 2009 (Kitazawa et al., 2008; Kitazawa et al., 2010). However, the problem still persists.

We focus on mobile learning (m-learning) as one of the learning strategies that can be employed outside of school hours because it facilitates an anytime, anywhere learning experience for the students (Yuen & Wang 2004). However, teachers have to scaffold students’ learning within the system so that at least a few students begin using the method. Therefore, we consider employing the test delivery system, in which tests are delivered to students’ mobile phones, along with the e-learning system.

This paper aims to evaluate the test delivery system along with the e-learning system in the blended learning environment.


275

2. METHODS

2.1 Information and Communication Technology Education Courses in Blended Learning Environments

Ninety-four students, who received mobile phones from T University in Tokyo, participated in this study. These students were enrolled in a lower-division information technology course. This elective course aimed at enabling students to acquire skills in computer statistics and database and Java programming. The course, with thirteen to fifteen 90-minute lessons, began in October 2011 and will end in January 2012.

This course employed an e-learning system, Blackboard Academic SuiteTM, that consisted of course materials, documents, task information, and task tools for submission.

2.2 The System of Delivering Tests to Mobile Phones through the e-learning System

The tests were delivered to the students’ mobile phones through the e-learning system. Figures 1 to 4 are screenshots of the system. First, the students logged into the system using their own IDs (Figure 1). Second, they selected the tests (Figure 2). Finally, they solved five problems and submitted their answers (Figure 3). Thereafter, they could check the results not only on the m-learning system but also on the e-learning system (Figure 4).

From October to November 2011, a teacher sent five tests from the system to the students’ mobile phones. The test comprised five questions pertaining to the course content and was sent a few days after each lesson.

2.3 Analysis

2.3.1 Students’ Attitude toward Tests

At the beginning of the sixth class, the students were administered a questionnaire that assessed their attitude toward the tests (Suzuki 2011). The questionnaire comprised 10 items (five regarding the test approach tendency and five regarding the test avoidance tendency). Students were asked to rate the items on a 7-point scale (1 = strongly disagree and 7 = strongly agree).

We categorized their test approach/avoidance tendency as follows: Students whose total rating of items regarding the test approach tendency were higher than that of the test avoidance tendency were defined as having a “test approach tendency.” Students whose total rating of items regarding the test approach tendency

Figure 1. Login screenshot Figure 2. Test selection Figure 3. Sample test Figure 4. Sample test result

ISBN: 978-972-8939-66-3 © 2012 IADIS

276

were lower than that of the test avoidance tendency were defined as having a “test avoidance tendency.” Students whose total rating of items regarding the test approach tendency were equal to that of the test avoidance tendency were defined as having a “neutral tendency.”

2.3.2 Motivation for Learning

To determine the student’s motivation for learning, we analyzed the rate at which the students completed the tests and the time lapses between the sending and taking of the tests. The time values were converted to serial ones in Microsoft Excel 2010. The averages of the rates at which the students completed the tests and the values were compared by test approach/avoidance tendency.

2.4.3 Test Scores

The students took 5 tests and answered a maximum of 25 questions. We analyzed their total test scores, which was determined by the percentage of questions answered correctly. The average of the percentage of correct answers were compared by test approach/avoidance tendency groups.

3. RESULTS

On analyzing the completed questionnaires, we found that the average rating by those with the test approach tendency was 20.33 and the average rating by those with the test avoidance tendency was 20.84; both averages were in the same range (table 1). We categorized the students’ test approach/avoidance tendency according to the definitions mentioned above. We found that 36 students had a test approach tendency, 51 students had a test avoidance tendency, and 6 students had a neutral tendency. The rate at which the tests were completed, time lapses between the sending and taking of the tests, and the percentage of correct answers were tested by using an ANOVA with the three test approach/avoidance tendency groups.

Table 2 shows the relationship between the attitude toward tests, motivation for learning, and test scores. The average rate of test completion was 93.2% (93.0% for those with the test approach tendency, 92.5% for those with the test avoidance tendency, and 100% for those with a neutral tendency). This result indicates that almost all students gave each test. The average time lapse was 6.04 (5.53 for the test approach tendency group, 6.47 for the test avoidance tendency group, and 5.58 for the neutral tendency group). The average percentage of correct answers was 72.4 (76.7% for the test approach tendency group, 69.7% for the test avoidance tendency group, and 69.3% for the neutral tendency group).

The ANOVA result showed that the percentage of correct answers differed significantly between the three groups (F (2, 88) = 2.99, p < .10). Therefore, Tukey’s multiple comparison test was used for further analysis. The result showed a significant difference in the tendency between the test approach tendency group and test avoidance tendency group (p < .10). Therefore, in this item, the test approach tendency group rated higher than the test avoidance tendency group.

Table 1. Result of the survey on the test approach/avoidance tendency

Test approach-avoidance tendency N Min. Max. Average SD1. I get motivated to study for tests. 94 1 7 5.10 1.612. I wish to get a higher score on tests than the others. 94 1 7 4.97 1.693. I enthusiastically try to compete with others in tests. 94 1 7 3.79 1.754. I like tests. 94 1 7 2.64 1.525. I want to determine my skill level by giving tests. 94 1 7 3.84 1.74

Total 94 5 33 20.33 6.296. I wish to avoid revealing my poor skills in tests. 94 1 7 3.44 1.827. I feel anxious about getting low scores on tests. 94 1 7 5.45 1.388. I dislike being compared with others on the basis of test scores. 94 1 7 3.16 1.609. I feel upset when there is a test. 94 1 7 4.93 1.67

10. I find studying more enjoyable if there are no tests. 94 1 7 3.87 1.77Total 94 8 33 20.84 4.98

Items

Test approach tendency

Test avoidance tendency


277

Table 2. Relationship between attitude toward tests, motivation for learning, and test scores

Items Categories N Average SDTest approach tendency 37 93.0% 0.20Test avoidance tendency 51 92.5% 0.23Neutral 6 100% 0Total 94 93.2% 0.21Test approach tendency 36 5.53 5.42Test avoidance tendency 49 6.47 6.79Neutral 6 5.58 3.56Total 91 6.04 6.08Test approach tendency 36 76.7% 0.10Test avoidance tendency 49 69.7% 0.16Neutral 6 69.3% 0.10Total 91 72.4% 0.14

† p<.10

Rate of test completion

Percentage of correct answers

Time lapse between the sending and taking of the tests

†

4. CONCLUSION

The purpose of this study was to evaluate a test delivery system, through which tests were delivered to students’ mobile phones, where it was used along with an e-learning system in a blended learning environment. From October to November 2011, a teacher sent five tests from the system to the students’ mobile phones. Each test had five questions pertaining to the course content and was sent a few days after each lesson. Ninety-four students gave the tests on their mobile phones. We analyzed the relationship between the student’s attitude toward tests, motivation for learning, and test scores.

The ANOVA results clearly indicate that the students’ motivation for learning was determined by the rate of test completion. The time lapses between the sending and taking of the tests did not depend on their test approach-avoidance tendency. However, the average percentage of the correct answers of the test approach tendency group was higher than that of the test avoidance tendency group.

We propose to conduct further study in this area by (1) increasing the time between the lesson and delivery of the test, (2) considering the number of test questions and the timing of the test delivery while conducting the analysis, and (3) studying the relationship between students’ academic achievement and their test results within this system.

ACKNOWLEDGEMENT

This study was supported by Grant-in-Aid for Young Scientists (B) No. 23700979 from the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and the Japan Society for the Promotion of Science (JSPS).

REFERENCES

Kitazawa, T., Nagai, M., and Ueno, J., (2008). Effects of e-Learning System in Blended Learning Environments: Exploring the Relationship between Motivational Beliefs and Self-Regulated Learning Strategies. In K. McFerrin et al. (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference 2008, pp. 2658-2664.

Kitazawa, T., Nagai, M., Ueno, J. (2010). Effects of feedback systems in blended learning environments: focus on Student satisfaction in Information Technology Education courses, Proceedings of the IADIS e-Learning 2010 (EL 2010) Conference, pp. 259-266.

Suzuki, M. (2011). How learning strategies are affected by the attitude toward tests: using competence as a moderator, Japanese Journal for Research on Testing, Vol.7, No.1, pp. 52-65 (in Japanese).

Yuen, S. & Wang, S. (2004). M-learning: Mobility in Learning. In J. Nall & R. Robson (Eds.), Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2004, pp. 2248-2252.

ISBN: 978-972-8939-66-3 © 2012 IADIS

278

READINESS OF TEACHERS TO IMPLEMENT OF MOBILE LEARNING AT EURASIAN NATIONAL UNIVERSITY

Daniyar Sapargaliyev Eurasian National University

5, Munaitpasov Street,010008, Astana, Kazakhstan

ABSTRACT

This paper introduces the results of survey among 50 teachers of Eurasian National University in Astana. The main aim of survey was to identify readiness of teachers to the introduction of mobile learning. Results of teachers’ survey were found that a mobile phone has sufficient technical capacity to use for training purposes. University teachers have good skills to work with mobile phone. In most cases, teachers have a positive attitude to the creation of mobile learning content. Teachers are interested in using mobile devices in the classroom. Teachers indicated that they ready to introduce mobile learning at Eurasian National University.

KEYWORDS

Mobile learning, readiness of teachers, Kazakhstan education, mobile devices

1. INTRODUCTION

Today many universities in Kazakhstan are trying to introduce advanced information systems and new platforms for development of distance learning. Many universities are trying to introduce the latest achievements in the field of e-learning. Last year Kazakhstan began active process of mobile learning’s implementation. However, most of this process depends on the financial capacity of higher education. Therefore, the first steps for the implementation of mobile learning undertaken in most cases by companies, but not only academic institutions.

For example, according to data of Ambient Insight Comprehensive Report, Kazakhstan became the first country in Eastern Europe that began introduced of Mobile Learning VAS (a Value-added Service). The first Mobile Learning VAS in Eastern Europe launched in Kazakhstan in February 2011 (Adkins, 2011). We assume that one of the first institutions that introduced the elements of mobile learning in Kazakhstan is The British Council.

The British Council have made a presentation of the mobile service “Phrase of the day”, with the use of which all subscribers will be able to learn English through SMS, using the materials of the British Council. The mobile service “Phrase of the day” represents one of products of the British Council to learn English, being developed for mobile phones and smart phones, aiming at giving access to users all over the world to educational resources of the British Council (KCell, 2011). Ministry of Education and Science has pilot projects on introduction of mobile learning at universities. It is dictated by the requirements of the new State Program for development of E-learning. Since 2011-2012 academic year will start a new project “SMS-diary” in Kazakhstan. Students and their parents will be able to access through SMS to get information from electronic databases of educational institutions about the current academic progress of students. Until the end of 2011 the information about the progress of students through SMS can get almost all the educational institutions. It is approximately about 2.5 million people (Nur, 2011). All universities are trying to provide Internet access for students. Eurasian National University in Astana is one of the first universities in Kazakhstan that organized the free wireless network in all campuses. This allows students and educators to use mobile devices for educational purposes at ENU. The other example of introducing of mobile learning we can see at Kazakh National University in Almaty.

The International seminar on the theme: “The introduction of mobile learning for teaching of a foreign language” has taken place in summer 2011 at Kazakh National University. The purpose of seminar was to


279

show the ways of innovative techniques in teaching of foreign languages. Teachers have studied the estimations of students’ achievements by using mobile learning technologies (Bekmurzayev, 2011). Unfortunately, we must recognize that the implementation of mobile learning in the universities of Kazakhstan in the early stages. Even with good technical conditions for the development of mobile learning, teachers are not rushing to use mobile devices in the classroom.

2. SURVEY AND RESULTS

This section describes the results of the survey. We have prepared a paper based questionnaire. This questionnaire included one closed-ended question and nine open-ended questions. We conducted a survey in an anonymous form.

2.1 Purpose

The purpose of this survey was to investigate teachers’ readiness to introduce of mobile learning at University. We tried to interview teachers in order to find out their opinion about mobile learning. In most cases, the successful implementation of mobile learning at universities depends on the attitude and commitment of teachers. In our study, we attempted to determine the technical and pedagogical conditions for the successful organization of mobile learning. For this aim, we have compiled a questionnaire for teachers for determine and reflect the readiness of educators to use mobile technology in teaching practice.

2.2 Participants

The participants in this survey were 50 teachers from 6 different faculties (31 female, 62%) at Eurasian National University in Astana. Teachers were in three different age groups (over 42-34%; from 31 to 41-36%; and under 31-30%) and they define four length of teaching experience (more than 10 years - 58%; from 5 to 10 years - 24%; from 1 to 5 years - 14%; under 1 year - 4%). The survey was made in the period 2-16 of September, 2011.

2.3 Mobile Devices of Teachers at ENU

In order to evaluate what types of mobile devices teachers use every day, they were asked to identify ones. The survey results indicate that teachers identified five types of mobile devices. According to the results, 100% of teachers use a mobile phone, 74% use a notebook or netbook, and 20% use a digital camera as everyday device. 16% use an e-reader (such as Amazon kindle, Sony reader) and only 4% use a Tablet PC (as iPad). It should be noted that the most frequently used device is a mobile phone (Figure 1).

Figure 1. Mobile devices of teachers

2.4 Identification of Technical Abilities of a Mobile Phone for Teaching

It was supposed that all of asked teachers use a mobile phone as main mobile device. We predicted this result on the stage of preparing our questionnaire. Therefore, we have focused on a mobile phone as the primary device for education practice. In order to examine the teachers’ technical abilities of using mobile phones in everyday life they were asked the following open-ended questions.

ISBN: 978-972-8939-66-3 © 2012 IADIS

280

(Q1) Time of using a mobile phone Teachers’ answers of Q1 indicate that the time when teachers use a mobile phone is not so different. The

majority of respondents (64%) answered that use mobile phone at any free time, 52% defined working hours. Only 8% used mobile phones during lunchtime, 6% used its before going to bed and 4% of respondents said that they use a mobile phone as needed (Figure 2).

(Q1) When you use your mobile phone frequently? (Q2) Where you use your mobile phone frequently?

Figure 2. Time of using a mobile phone Figure 3. Places of using a mobile phone

(Q2) Places of using a mobile phone Teachers’ responses to Q2 relating to where they use a mobile phone frequently. The most of teachers

(70%) answered that use mobile phone at home, 26% use it in public transport, 16% use this device in a lecture room, and 14% answered - at a bus stop. Equal results (10%) showed answers as standing in a queue and in public eating places. Also we were received 24% of response as “everywhere” (Figure 3).

(Q3) Mobile phone application using by teachers Teachers’ responses to Q3 relating to which software teachers use on a mobile phone. The majority of

teachers (64%) indicated that they did not use any application, 30% responded that they use mobile instant messenger, 14% used social networking apps. 10% of teachers answered that use video conferencing application Skype and 8% indicated micro-blogging Twitter. Only one teacher responded “dictionary” (Figure 4).

(Q3) Which application do you use on your mobile phone? (Q4) What type of wireless connection do you use on

your mobile phone?

Figure 4. Mobile phone application using by teachers

Figure 5. Types of mobile wireless connection using by teachers

(Q4) Types of mobile wireless connection using by teachers Teachers’ responses to Q4 relating to what type of mobile wireless connection teachers use. The results

show that 64% of teachers use Bluetooth, 26% use WIFI, and 24% did not use any wireless connection. Only 6% use IR port for data transmission (Figure 5).

(Q5) Different types of files appropriate for sharing of mobile learning content Teachers’ responses to Q5 relating to identifying the appropriate forms for mobile learning content. It was

important to know the opinions of teachers about types of digital files and formats and then we possibly could be find convenient forms for sending and receiving educational materials for mobile phones. We asked teachers about types of files that they had ever transferred from mobile phones to other one or a PC. According to 54% of teacher answered that it was a text file, 50% defined a photo file, 30% of teachers said that it was a video file, and 26% defined an audio file. 14% transferred an application and only 20% of teachers had never transferred any files from their mobile phone (Figure 6).


281

(Q5) What type of file do you transfer from your (Q6) Please define a problem of using your mobile phone? mobile phone to other one or to PC?

Figure 6. Different types of files appropriate for Figure 7. Main problems in using a mobile phone sharing of mobile learning content

(Q6) Main problems in using a mobile phone Teachers’ responses to Q6 relating to determining of main problems in using a mobile phone as a

teaching tool. Obviously that mobile phone is a device with different parameters and capabilities but also with many disadvantages. We asked teachers define main problems in using a mobile phone. More than half of teachers (54%) noted a small screen size, 40% answered that it is hard typing, 34% indicated a short battery life, and 30% of teachers indicated a slow Internet connection. 14% pointed out the difficulty in using a mobile phone and only 10% responded that they have not any problems in using a mobile phone (Figure 7).

(Q7) Quantity of teachers’ SMS per day Teachers’ responses to Q7 relating to identifying of quantity of teachers’ SMS per day. One of the most

accessible and popular mobile service in Kazakhstan is SMS. In our survey we consider SMS as one of primary way for delivering educational information. During the survey was founded that 64 % of respondents send from 1 to 5 SMS messages per day, 16% send less than 10 messages and 14% send more than 10 messages. And only 6% of teachers did not send any messages (Figure 8).

(Q7) How many SMS messages do you send daily? (Q8) What format is better to deliver learning information to a mobile phone of student?

Figure 8. Quantity of teachers’ SMS per day Figure 9. Appropriate formats for sharing of learning information

(Q7) Appropriate formats for sharing of learning information Teachers’ responses to Q8 relating to identifying of appropriate format for sharing of content with

students. According to data obtained 66 % of teachers supposed that the best format is a text, 44 percent of respondents asked that it is a video. The same amount (36%) of teachers assumed that an audio and SMS suitable for delivery of learning information, 24% responded that it is a presentation (as Power Point) and only one-fifth of respondents (20 percent) identified the MMS (Figure 9).

2.5 Teachers’ Opinions about Mobile Learning

Teachers were asked the following closed-ended question that was defined in eight different blocks (four positive answers and four negative ones).

(Q9) Teachers' attitudes toward creating of learning content for mobile devices Teachers’ responses to Q9 relating to indicate of teachers' attitudes toward creating of learning content for

students’ mobile devices. According to our survey approximately a half of teachers reacted positively, 46%

ISBN: 978-972-8939-66-3 © 2012 IADIS

282

teachers said: “this will help students to acquire learning information”, 40% of respondents answered: “yes, if this will not take much time”. Some teachers (16%) had pointed “yes, if this will be paid additionally”, and only 10% of teachers answered as “yes, this will be interesting for me” (Figure 10).

(Q9) Would you like to create learning content for mobile devices of students?

Figure 10. Positive attitudes toward creating of learning content

Figure 11. Negative attitudes toward creating of learning content

On the other hand we also identified negative reaction of teachers to creating of learning content. 10% of respondents noted that “this will not effective”, 6% of teachers said: “I don’t know how to create this”. Both results 4% of participants of survey answered: “this will not interesting for me” and “this will not needed for students” (Figure 11).

(Q10) Write your opinion, what does “mobile learning” mean? Finally, teachers were asked to provide a definition for mobile learning and to write their opinions. The

most of teachers’ responses to Q10 were not identified. Because 82% of teachers not responded on this question or they just wrote: “I do not know.” But some answers were noted and we choose the most encountered ones. For example, one teacher wrote, “This is one of distance learning types via mobile devices” and another wrote, “This is distance learning using mobile devices.” One teacher remarked, “Using different mobile tools in the learning process”. We also received follow answers: “Learning anywhere at any time”, “Using of mobile devices in learning”, “Learning using mobile technology”. One teacher notably mentioned that “this learning do not need any borders, regardless of conditions.”

3. CONCLUSION

This paper describes the survey that was made for identify of teachers’ readiness to implement of mobile learning. Summarizing the results of the survey, we can draw the following conclusions. Through open-ended questions, all of teachers specified mobile phone as main everyday mobile device. Teachers also reported that they use mobile phones mostly at home, everywhere and in public transport at any free time, and during working hours. In additional, teachers generally do not use any mobile applications (except a mobile instant messenger), and they mostly use Bluetooth and Wi-Fi for wireless connection. In most cases, a teacher sends between 1 and 5 SMS messages per day.

The main problem of using mobile phones as a teaching tool is a small screen size, hard typing. The best forms for delivery educational information to student's mobile phone are a text and video file.

Teachers have positive attitudes for create mobile learning content, because this probably helps students to acquire new learning information. Many teachers agreed to produce mobile content if it will not take much time. Although other teacher have negative attitudes for create mobile content, teachers argued that this process will not effective and many teacher did not know how create content for mobile devices.

Summing up the results of our study we should be noted that ENU has all necessary conditions and prerequisites for active development of mobile learning. The main participants of this process are the teachers who are generally willing to adopt mobile learning at University.


283

REFERENCES

Adkins, S., 2011. The Worldwide Market for Mobile Learning Products and Services: 2010-2015 Forecast and Analysis. [online] Available at http://www.ambientinsight.com/Resources/Documents/Ambient-Insight-2010-2015-Worldwide-Mobile-Learning-Market-Forecast-Executive-Overview.pdf/ (Accessed 8 October 2011).

KCell, 2011. British Council and Kcell have launched the mobile service for learning English. [online] http://www.kcell.kz/en/?l=press&p=display&idx=325/ (Accessed 11 September 2011).

Nur., 2011. Universities of Kazakhstan will introduce SMS-diaries. [online] (Accessed 6 September 2011). Bekmurzayev, B., 2011. The introduction of mobile learning for teaching of a foreign language. [online] Available at

http://www.inform.kz/rus/article/2400007 (Accessed 14 September 2011).

ISBN: 978-972-8939-66-3 © 2012 IADIS

284

PRAGMATIC PODCASTING: FACILITATING PODCASTING IN DEVELOPING HEIs

Raymond Mugwanya1, Gary Marsden1 and John Traxler2 1HPI Research School in ICT4D, Department of Computer Science

University of Cape Town, Rondebosch # 7700, South Africa 2The Learning Lab, School of Computing and Information Technology

University of Wolverhampton, TF2 9NT, United Kingdom

ABSTRACT

MLCAT is a desktop content authoring application that is used to record lectures and presentations for educational purposes. It does not only record the audio of the speaker but also their Power Point presentation. It is able to record, encode and save the presentation in various formats. The result is one synchronized multimedia video that can be played back on a variety of feature phones. Apple has a big success with the release of podcasting solutions, iPod series and accessories. They enable the user to carry around music and videos, play them back while on a bus or even use it as a digital multimedia library. These products have been trialled and used in Higher Education Institutions (HEIs) in the developed world. Developing world HEIs such as those in Africa have limited diffusion of these technologies due to their relative high cost; infrastructural limitations, technical skills shortages; digital divides and cultural and socio-economic issues. This paper describes a pragmatic podcasting approach and how instructors can author and supply the learner with mobile-ready lecture recordings in order to enable mobile learning “anytime – anywhere”. Our solution has been implemented and is being made available for lecturers and students to examine and evaluate. The feedback will be analyzed and enhancements to the system proposed.

KEYWORDS

E-Learning, Podcasting, M-Learning, HEIs, Mobile Education.

1. INTRODUCTION

The growth of podcasting since its incarnation in 2004 has been phenomenal and has become an innovative way of broadcasting information on a range of subjects, from news-based items to comedy sketches (Dale, 2007). Within an educational context, podcasting offers innovative and creative opportunities for academics to further support learning. Podcasting refers to “a form of mobile learning in which audio or video content, available on the internet or some server can be downloaded onto a computer then transferred to mobile devices for consumption” (Evans, 2008). The other variant i.e. video podcast is a term used for the online delivery of video on demand via Atom or real simple syndication (RSS) enclosures facilitating the automatic download of new content as it becomes available.

From a web server, a video podcast can be distributed as a file or as a stream. This subscription model is ideal in Western HEIs with fast and reliable internet connections. Therefore, in developing HEIs, the emphasis is on the authoring and end user access with no stress on subscription models as put forward by other researchers (Malan, 2007 & Lee et al., 2009).

Ultimately, access to the video podcasts in advance gives the user the ability to play the video podcasts off-line and on a number of devices, particularly cell phones – mainly prevalent in developing HEIs (ITU, 2011). In addition, podcasts can be watched many times and shared amongst different users reducing bandwidth costs. Developing, publishing and integrating podcasts in teaching practice does not necessarily have to be exhaustive, complex, require expensive software or highly skilled and advanced system users. Therefore, this paper focuses on the emerging requirement of empowering instructors to author mobile content for educational purposes in developing HEIs. We introduce our novel approach of Pragmatic Podcasting - a fully automated generation of video podcasts through an exploration and transformation of authentically recorded lectures and presentations into mobile multimedia learning objects of high quality.


285

These learning objects can be played back on cell phones in order for the learner to access nearly everywhere and off-line. The remainder of this paper is organized as follows; we start in section two with related work, an overview of pragmatic podcasting in section three; describe some preliminary deployment results in section four; and finally conclusions and future work in section five.

2. RELATED WORK

Mugwanya & Marsden (2010) reveal that majority of tools published for authoring mobile educational content report on their use in developed HEIs. These tools may not be easily adapted to developing HEIs due to the varying social, economic and cultural environments. This is evident from the low adoption of some e-learning tools such as Blackboard and WebCT in various African HEIs. In addition, there are limited uses of podcasting within developing HEIs with a few undertaken by enthusiastic faculty. Typically, faculty do not use any standard architecture or model for podcasting but instead have their own piecemeal improvisations e.g. the use of Podcast Producer Server at the University of Cape Town on a trial basis, OpenEyA (http://www.openeya.org/), Tele-task (Wolf et al., 2007) and Adobe tools. These tools are normally costly, general purpose and not developed within developing (ICT4D) contexts. As a result, they do not necessarily adequately address users’ needs; are often complex and difficult to use.

In other works, Ketterl et al. (2006) describe the use of VirtPresenter - a PowerPoint based lecture recording system currently integrated into Stud.IP - a Learning Management System. It creates web enabled presentations for further adaptation to mobile devices. Gannod et al. (2008) report on the use of Profcast for capturing Microsoft Power Point and Apple Keynote presentations with voiceovers; Snapz for capturing full motion presentations of software use (e.g. a screen cast); iMovie for capturing full motion talking head lectures; iWeb for deploying the podcasts onto a standard web server and Black Board for storage, grade book and assessment management. Many of the applications use a variety of applications to deliver the end product and require accessibility to computers or high-end mobile devices whose ownership is limited in the developing world. The implementations described are problematic and are not sustainable since tooling may require that lecture theatres have integrated infrastructure common in developed HEIs. To the best of our knowledge, despite the reported successes for many of the tools presented above, there is a gap in the literature on designing podcasting systems for developing HEIs. Moreover, utilizing tools such as mobile devices already in the possession of students and relieving the pressure on HEI infrastructure through the use of a simple, easy to use desktop application may save academics valuable time, effort and resources. Hence, we present our pragmatic podcasting approach that is being trialled at developing HEIs. We begin by describing the approach and then provide some preliminary deployment findings.

3. PRAGMATIC PODCASTING

Producing and publishing a podcast oftentimes involves a series of people and/or technical skills to operate a video camera (in case of video podcasts – “vodcasts”), to record sound, to edit recorded material, to encode material to a podcast format, to develop XML feeds, and to publish material on a web server. Only a very limited amount of instructors have all these technical skills and access to the required equipment, and thus this way of podcasting may be unrealistic, too time-consuming, or too expensive. Therefore, our pragmatic approach offers support for instructors and students to develop podcasts themselves using easy-to-use authoring and access tools respectively. The sections that follow describe our podcasting approach, exemplify how a podcast can be authored using a simple low-tech setup, and discuss its integration in teaching practice.

3.1 Technical Setup

The setup of our podcasting system has three components i.e. the authoring component, hosting component (the Snap&Grab system (Maunder et al., 2008) and a LMS) and access component (using feature phones and laptop/desktop computers). Figure 1 below illustrates the architectural setup.

ISBN: 978-972-8939-66-3 © 2012 IADIS

286

Figure 1. MLCAT Setup

The setup is based on a system developed using the .NET environment as it offers the ability to develop extensions or add-ins for Microsoft Office applications.

In particular, we design interface ribbons onto which click events are developed to offer varying functionality such as recording, encoding, previewing, pausing and saving recordings in different formats. The back-end systems that host the recordings are a LMS and the Snap&Grab system. Users can access podcasts using the network provided on campus via the LMS or through Bluetooth via the Snap&Grab system.

3.2 Authoring

In our pragmatic approach, the authoring of the podcasts is done by the instructors themselves using MLCAT interface and a headset. The authoring takes its starting point in the material of an existing presentation or lecture. Most instructors prepare digital slideshows like PowerPoint presentations as an integral part of their lectures. MLCAT allows the instructor to record and pause audio, navigate the presentation and later on encode the presentation and audio into a high quality video in a variety of formats i.e. MPEG-4, AVI, MPEG and 3GPP.

3.3 Publishing

Once the podcasts have been created, they may be uploaded to the Snap&Grab system and a Learning Management system (see figure 1). The LMS is accessible to both students and lecturers through the HEIs network. The Snap&Grab system consists of four basic components namely; a large situated display, Bluetooth access point, server machine and the client device (a Bluetooth enabled camera-phone). The Snap&Grab system allows a user to select and download media packages in our case lecture recordings (a collection of various OBEX items) by photographing a visual download key (an image on the display which we replaced with A4 size paper posters) and sending that photo to the Snap&Grab system via Bluetooth. The submitted photo is then processed and compared to the key images currently on display. If a match is detected the media package (or lecture recordings) associated with key image is sent back to the user’s device.


287

4. PILOT DEPLOYMENT AT TSIBA

4.1 System Deployment

In order to deploy the system at TSiBA (http://www.tsiba.org.za/), we were in close contact with a technology champion – The Executive Director who introduced us to three lecturers willing to take part in our trial. The three lecturers teach undergraduate courses in business namely; Strategic management, a foundations course in economics and applied financial management. At this point our goal was not to impose on them how we wanted our tool to be used but to find out interesting ways in which they would appropriate it and later on identify opportunities for further design. Informal Interactions with the lectures provided rich qualitative data revealing interesting results as described under four key themes below. Our assumption was that lecturers would record entire lectures as the MLCAT requirements arose from the unsuccessful adoption of Podcast Producer, OpenEyA and the use of pre-installed recording software on the Mac books and Windows machines i.e. (iMovie), Windows Moviemaker respectively. Participants were trained on how to use the MLCAT system (using the researcher’s laptop) after which they were given an opportunity to make test recordings. Two of the participants had their own laptops onto which the system was installed whereas the other utilized a computer in the library currently used by a part-time student librarian. This computer required the researcher to have administrative rights (in order to install software); housed some of the librarian’s applications and thus had reservations about installation of additional software. We then resorted to installing the application on a laptop that was provided by the systems administrator at TSiBA. The results from the informal qualitative interviews are as summarized under the following four themes:

Themes Notes Do recording when it suits me/in my free time

“ […] it would be useful to install on my work computer so that when there are no people around, I can try to get this thing going but to make this thing happen, I would have to find a place that is quiet or to use this […]”

Breaking down content into smaller chunks

“ […] identify hypothetically 50 key lessons for the course. These lessons also appear in the course text books and other resources and create say 50 clips of the same material for students to reference [….]”

Integrating assembling content into the application ecology

“[…] in finance, we use Excel quite a lot…we can have it in excel and paste it into Power Point. Easier to use excel because i can change numbers i.e. what happens if the profit in year 2 was not 300 but 400? How does it affect our average, standard deviation, coefficient of returns? How will the analyst/ Investor perceive this investment? [...] one can achieve that by replicating this in Power Point [….]”

Privacy “ […] I do not want them to see me in the recording […] ” thus validating our initial assumption that recoding the presenter may not be necessary

4.1.1 Student Survey Summary

The survey sample was self selecting as we focused on students who were undertaking courses taught by our participants. The purpose of this informal survey was to get an idea of who the students were, the devices they interact with, their knowledge of digital lectures and any challenges they currently face. As a result, we interviewed 26 students who were undertaking the foundation economics course with no incentive for participation. A snapshot of the questions asked and responses are presented below.

ISBN: 978-972-8939-66-3 © 2012 IADIS

288

What technologies do you own?

Flash drives, a few Personal computers, two with no technology at all and the 22 owning a cell phone as their only technological device.

Which Cell Phone Brands do you own?

Nokia Express music 53C, Nokia C3, black berry curve 2GB, Sony Eriksson 4GB, nokia Music express 5130C, Samsung star, Samsung E250, Samsung B3210, E250i, Vodafone 543, BlackBerry curve 8520 4GB, Sony Ericsson W 395, Nokia 5230.

Which technology do you use at Home?

The most dominant technology used at home is the cell phone which validates the existence of a high mobile phone penetration in the developing world. Some instances of usage of Television, Digital Video Disk (DVD) and personal computers were reported to be used at home.

How do you access digital lectures?

A personal computer at School (through download from Moodle - LMS), School network, Khan Academy (http://www.khanacademy.org/), Cami Maths (http://www.camiweb.com/), Internet/online, Maths lessons Online, You Tube, personal computer and download it to external hard drive.

What are the Challenges during access?

“ […] takes long to respond, internet is offline, slow network sometimes, cannot ask questions directly, slow internet, scarcity of personal computers, do not have a personal computer, mobile cannot read office documents, Difficult to download work and software on campus and home is not the same [….]”

How would you like podcast lectures presented/delivered to you?

Visual, video, via cell phone, Bluetooth – for sharing, audio and slide shows, available anytime you logon, sms, e-mail, Phone or any other way possible other than MXit (http://mxit.com/), Face book because I would rarely do anything, via Bluetooth every after lecture. Fun and not long, clear and straight to the point e.g. You Tube videos.

What is your understanding of digital lectures?

- Lectures that take place on a PC like Khan Academy - Lectures we have using computers and projectors - Being lectured in the video way – using You Tube and Khan Academy


Our preliminary experiences with podcasting show that it is feasible and fruitful to employ a pragmatic approach to podcasting at a developing HEI. Using easy-to-use software tools for authoring, it is possible for instructors to develop podcasts themselves. The approach is not geared to develop “professionally” produced recordings, but rather short presentation and video podcasts. In this paper, we have introduced our pragmatic approach, detailed how lecturers would appropriate it. Our initial assumption that the system was directed towards lengthy recorded lectures was quashed. Instead, there is a potential for short videos – such as demonstrations, summaries of course sections, presentations, model descriptions, solutions to frequently asked questions and topics that call for visual representation.

The pedagogical idea behind short introductory videos is to provide them as resources for students’ problem-oriented work and revision. The short introductory videos are in many cases easy to author using our pragmatic solution. The technical solution, both with regards to authoring tools, LMS and situated display – is in every way cheap and easy to administer and support. The described solution meets many of the podcast needs of the HEIs despite there being room for refinements. Future work will explore extended user evaluations and prototype improvements.

ACKNOWLEDGEMENT

Our sincere thanks go to the Hasso Plattner Institute for funding this research.


289

REFERENCES

Dale .C (2007): Strategies for Using Podcasting to Support Student learning; Journal of Hospitality, Leisure and Tourism; Vol. 6. No. 1[online at:] www.hlst.heacademy.ac.uk/johlste {accessed}October 2011.

Evans .C (2008): The effectiveness of m-learning in the form of podcast revision lectures in higher education. Computers and Education. 50, 2 (February 2008), pp 491-498.

Gannod, G. C., Burge, J. E., & Helmick, M. T. (2008). Using the Inverted Classroom to Teach Software Engineering. In the Proceedings of ICSE 2008, pp. 777-786. Ketterl, M., Mertens, R., Morisse, K. (2006): Alternative Content Distribution Channels for Mobile Devices. In: Hug, T.,

Lindner, M., Bruck, P.A. (Eds.), Micromedia & e-Learning 2.0: Gaining the Big Picture. Proceedings of Microlearning Conference 2006, Innsbruck (Austria), pp. 119 - 130, Innsbruck University Press, 2006.

Lee M. J. W., Millar .C and Newnham .L (2009): Podcasting syndication services and university students: Why don't they subscribe? The Internet and Higher Education Volume 12, Issue 1, January 2009, pp. 53-59. Research, Reflections and Innovations in Integrating ICT in Education 123

Lee, J. (2001), Education for Technology Readiness: Prospects for Developing Countries. Journal of Human Development vol. 2, 1 pp 115 - 151.

Malan D. J (2007): Podcasting computer science E-1. In Proceedings of the 38th SIGCSE technical symposium on Computer science education (SIGCSE'07). ACM, New York, NY, USA, 389-393. [online at:] http://doi.acm.org/10.1145/1227310.1227446 {accessed} October 2011.

Maunder A. J, Marsden .G and Harper .R (2008). SnapAndGrab: accessing and sharing contextual

multi-media content using Bluetooth enabled camera phones and large situated displays. In CHI '08 extended abstracts on Human factors in computing systems (CHI EA '08). ACM, New York.

Mugwanya, R. and Marsden, G. (2010): Mobile Learning Content Authoring Tools: A Systematic Review: In the proceedings of the 1st conference on E-Infrastructures and E-Services on Developing Countries, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Maputo, Published by Springer Berlin Heidelberg, pg. 20-31.

Sife .A. S., Lwoga .E .T and Sanga .C (2007): Technology C. New technologies for teaching and learning: Challenges for higher learning institutions in developing countries. Journal of Education 3, 2 pp 57-67.

The ITU Facts and Figures (2011): http://www.itu.int/ITU-D/ict/facts/2011/index.html {accessed} October 2011. Vavoula, G., Meek, J. Sharples, M., Lonsdale, P. & Rudman, P. (2006): A lifecycle approach to evaluating MyArtSpace.

In Hsi, S., Kinshuk, Chan, T., Sampson, D. (eds) Proc. 4th Int. Workshop of Wireless, Mobile and Ubiquitous Technologies in Education (WMUTE 2006 ), Nov 16-17, Athens, Greece. IEEE Computer Society, pp. 18-22

Wolf, K., Linckels, S., & Meinel, C. (2007). Teleteaching Anywhere Solution Kit (tele-TASK) Goes Mobile. In Proceedings of the 35th Annual ACM SIGUCCS Conference on User Services, pp. 366–371. ACM, New York.

ISBN: 978-972-8939-66-3 © 2012 IADIS

290

RECOMMENDER SYSTEM FOR COMBINATION OF LEARNING ELEMENTS IN MOBILE ENVIRONMENT

Fayrouz Soualah-Alila, Florence Mendes, Christophe Cruz and Christophe Nicolle LE2I, UMR CNRS 5158

University of Bourgogne, Dijon, France

ABSTRACT

This paper presents an ongoing research about the development of a new recommender system dedicated to m-learning. This system is an extension of content based recommender system proposals. It’s made of three levels architecture: 1/ a domain model describing the knowledge of teaching, 2/ a user model defining learner’s profile and learning’s context, 3/ an adaptation model containing rules and metaheuristics, which aims at combining learning modules. Our system takes into account the spatio-temporal context of the learners, the evolution of learner’s profile and the dynamic adaptation of modules during the learning process in a mobile environment. The result of the recommendation is one of the best combinations of pieces of training according to mobility constraints of learners and of the know-how of teachers.

KEYWORDS

Recommender system, m-learning, ontology, metaheuristics, spatiotemporal context, learner’s profile.

1. INTRODUCTION

Due to the rapid growth of information technology and communications, the learning methods are evolving. Now, the great challenge of e-learning companies is to bridge the gap between the static e-learning and the mobile learning (or m-learning).

The m-learning features are numerous but can be focused on these three mains: flexibility, accessibility and informality. The flexibility is the ability of the system to access freely the learning training without constraints in time and space. The accessibility is the ability of the system to find any piece of information about the learning training independently from the initial organization of this learning. The informality is the ability of the system to develop a process of learning beyond the original path of learning defined by the teacher. The development of a system respecting these features is a difficult task.

(Quinn, 2000) considers that m-learning refers to all learning using smart phones. (Geddes, 2004) presents m-learning as “the acquisition of all knowledge and skill using mobile technologies, regardless of place or time, causing a change in behavior." In this definition, three main elements are important: the association of knowledge and skill, the definition of a spatio-temporal context of learning and the change in the behavior of learners.

According to this observation, this paper presents an ongoing research about the development of a new recommender system dedicated to m-learning. This system is an extension of content based recommender system proposals. It’s made of a static part representing both knowledge of the teachers and profile and context of learners, and a behavioral part containing rules and metaheuristics, which aim at combining learning modules. Our system takes into account the spatio-temporal context of learners, the evolution of learner’s profile and the dynamic adaptation of modules during the learning process in a mobile environment.

The rest of this paper is articulated in three parts. The first part presents a background of the recommender system domain. The second part presents our proposal and more specifically our architecture. The third part focuses on the combinatory problems of m-learning domains, and the last part concludes this paper.


291

2. RECOMMENDER SYSTEM BACKGROUND

Recommender systems are based on adaptive hypermedia systems (AH) developed during the end of the 90’s. E-learning was considered as the first application of adaptive hypermedia systems. In the e-learning domain, most of the existing proposals are based on a set of layers (Cristea & de Mooij, 2003) which are closed to the AH architectures. A consensus of proposals described a basic set of three layers made of the domain model, the user model and the adaptation model. The domain model describes knowledge of the domain. The user model represents all the information characterizing the user. It is used by algorithms contained in the adaptation model in order to extract, transform and combine information from the domain model. Derived from adaptive hypermedia systems, the architecture of the recommender systems is closed to these set of layers.

A recommender system can provide personalized recommendations into a specific space of knowledge. Derived from the work of (Khairil Imra & Nor Aniz, 2009), figure 1 summarizes the various strategies of recommendation in the e-learning domain. The two main types of recommender systems are collaborative filtering or content-based filtering (Adomavicius & Tuzhilin, 2005), (Lousame & Sanchez, 2009).

Figure 1. E-learning recommendation strategies

On the one hand, recommendations by collaborative filtering are calculated on how users use the system. The system recommends pieces of training, called items, which have been already selected by other users in the past. This system is limited to e-learning applications. To be build, the recommendation depends on other users. This system requires a period before being efficient.

On the other hand, content-based recommender system analyses the resources or descriptions of these resources to determine which resources are likely to be useful or interesting for a given user. These systems are attractive in the e-learning domain because the recommendation can start directly after system’s deployment. Anyway, it needs an initial time of parameterization. These systems require an indexation of resources and a definition of relationships between system’s resources. These processes of indexing and binding on resources are generally driven by ontology (Stojanovic & al, 2001). Ontology is an abstract representation of knowledge independent from physical implementation of resources (Gruber, 1991). Nevertheless, in a mobile environment, the main gap is the modeling of the context of learning. This context may be defined by spatio-temporal constraints (where and when) but also, by personal or environmental constraints such as “the weather”, “into a plane”, “at home with children”, “the heterogeneity of skill levels of the learners”, etc. These last constraints require a semantic modeling of user’s profile. Moreover, in m-learning, the teacher ability to build specific teaching is hindered by the complexity of different learning’s circumstances in mobility.

We argue that m-learning systems are content-based recommender systems, which need to be improved to take into account the learning context and the learner profile. This will be done by improving the user model with semantic modeling of learner profile and learning context, and with the improvement of the adaption mechanisms. This will be done by a dynamic process combining pieces of training course according to profiles and contexts of learning.

Input Recommendation Output

-learner's activities/access history -learners rating -item attributes

-Collaborative filtering(CF) -Content-based filtering(CB) -Others: Item, Metadata, Rule-based expert system…

-related items/documents -related links -learning activities -courseware module

ISBN: 978-972-8939-66-3 © 2012 IADIS

292

3. A

This sin thre

Thdescridescriontoloexampsystemconnestandacontex

Thmetahcontex

Wcompspatioand ucoursecontexmobilanoth

Threcommetahhave combdescri

APPROAC

section describee main parts:he model domiption is struciption of eachogy are definple: switch thm, we use theected to the leaard relational xts. These twohe adaptation heuristics resoxt (for examp

When a learnerleted by cont

o-temporal infser constrainte. Next, metahxt. Finally, a le device. If ter, adapting thhis approach i

mmender systeheuristic specito define theining items, iption of the m

CH

bes our appro: domain modmain containsctured as an oh piece of traned accordinghe teaching oue Sesame midarning repositdatabases. Tho elements aremodel contai

olve the comle, geolocalisa

Fig

r uses our sytext informatioformation, ands, logical ruleheuristics are proposal of cothe context che learning wiis derived fromem dedicated ifically adaptee optimizationaccording to

metaheuristic u

ach and mainldel, adaptation the semanticntology dedic

aining accordi to learning utput flow froddleware as atory containinhe user model e modeled intoins both rules

mbination probation of the le

gure 2. M-learn

ystem, he hason send by thd the user can es run through

used to find tourse (made ohanges duringith the new com the Tourismto the comb

ed to the optin problem of

constraints dused in our ap

ly the architecn model and usc description cated to m-leang to the teacgoals of teacom audio to ta triple-store,g the physicalcontains the d

o an ontologys and metaheublem of itemearner) and the

ning recommend

s to define itshe mobile devspecify some

h the ontology the best combof a combinatg the learning

onstraints. mKM project bination of toimization probf m-learning,defined in thepproach is pres

cture of our syser model. of knowledge

arning. This Oching descriphers and answtext if the leato store the cl data of learndefinition of p store in Sesamuristics. Rule

ms, according e profile inform

der system arch

s profile or lovice and come constraints o

to identify anbination of thetion of elemeng, the system

(Picot-Clémeourism offers. blem in the towhich consise profile and sented in the n

ystem. This ar

e describing lOWL ontologyption. The conwers to const

arner can’t hecorrespondingning module. Tprofiles and deme. s model the sto the constr

mation of the

hitecture

oad an existinmpleted by theof the environmnd extract pertese elements ants) is sent to

m can directly

ente, 2011), wThe Tourism

ourism domaists on the bui

the context next section.

rchitecture is a

learning mody contains thencepts and lintraints of mo

ear the speechg ontology. ThThis repositoryefinition of th

skill of the teraints describlearner.

ng one. This e user (the moment). From thtinent pieces oaccording to pthe learner th

y switch an el

which aims to mKM project in. In our appilding of a trpart of our s

articulated

dules. This e semantic nks in this bility (for

h). In our his part is y could be

he possible

eacher and bed in the

profile is obile send his profile of training profile and hrough the lement by

develop a defines a

proach, we raining by system. A


293

4. M-LEARNING AND METAHEURISTICS

Validate training independently from the heterogeneity of the learner (profile and context) is the major goal of an m-learning’s recommender system.

The validation of training is subject to various business rules. They define how the different items constituting the training must be selected and combined. Each item of training is defined by a subject, a context of use (mode, duration), a type (lectures, exercises, practical work) and precedence constraints that define the possible positioning of the item relative to others. For example, some training’s component modules can be followed by an entirely independent way, while some modules require other modules as a prerequisite. Similarly, for each new concept to learn, it will be more suitable to have taken over an item of type “course” before selecting an item of type “exercise."

The platform of m-learning proposes an optimized panel of training items corresponding to the current profile of the learner. This optimization bridges the gap between the learner and the teaching. It reduces the cost and the duration of the training. Furthermore, it maximizes the gain skills and makes the teaching relevant to the training material.

For this, an evolutionary scheduling of items and an evaluation of the benefits of different proposals is needed. From this, a combinatorial optimization problem can be identified. This problem can be reduced to a multi-objective difficult scheduling problem. Such problems cannot be resolved by an exact method, because of the exponential growth in complexity depending on the size of the problem; we propose to use an approximation solution method of metaheuristic type, which will ensure the achievement of a solution in a reasonable time. The metaheuristics used must be adapted to take advantage of rules described in static layer of the system. We, therefore, wish to link the semantic modeling techniques in the offer of training and user profile with powerful algorithms derived from combinatorial optimization, to provide a recommendation system that maximizes the availability of m-learning.

5. CONCLUSION

In this paper, we present a recommender system applied to the field of m-learning. The idea is to combine technologies of Semantic Web, adaptive hypermedia systems and combinatorial optimization algorithms to help users to access easily to learning modules on their mobiles. This system is made of a static part representing both the knowledge of teachers and the profile and context of the learners, and a behavioral part containing rules and metaheuristics. Our approach allows the teacher to represent his how-know using rules and ontology. Next, in a mobility environment, it allows to take into account the constraints of the environment and the constraints of the user with the definition of profiles and contexts. Finally, the metaheuristic part of our proposal makes it possible a dynamic combination of pieces of training according to these constraints. This specific architecture gives to our system flexibility, accessibility and informality features.

This work is partially supported by the CrossKnowledge Company. We are working on the modeling of the ontology, and the connection of the existing training courses contained in the databases of the company. In parallel, we are studying the impact of this approach on user behaviors in learning context.

REFERENCES

Adomavicius G. and Tuzhilin A., 2005. Incorporating contextual information in recommender systems using a multidimensional approach. ACM Transactions on Information Systems, Vol. 23, No. 1, pp 103–145.

Burke R., 2007. Hybrid web recommender systems. In The adaptive Web. pp 377-408. Cristea, A. and De Mooij, A., 2003. LAOS: Layered WWW AHS Authoring Model and their corresponding Algebraic

Operators. In WWW 2003 Conference. Budapest, Hungary. Geddes S., 2004. Mobile learning in the 21st century: Benefit for learners. The knowledge tree, 6. Gruber R., 1991. Toward Principles for the Design of Ontologies Used for Knowledge Sharing. International Journal of

Human-Computer Studies.

ISBN: 978-972-8939-66-3 © 2012 IADIS

294

Khairil Imra, B.-G. and Nor Aniz, A., 2009. Building an E-Learning Recommender System using Vector Space Model and Good Learners Average Rating. In Ninth IEEE International Conference on Advanced Learning Technologies. Riga, Latvia.

Lousame F. and Sanchez E., 2009. A Taxonomy of Collaborative-Based Recommender Systems. Web Personalization in Intelligent Environments, pp 81–117.

Picot-Clémente, R., Cruz C. and Nicolle C., 2011. A Semantic-based Recommender System Using A Simulated Annealing Algorithm. In SEMAPRO 2010, The Fourth international Conference on Advances in Semantic Processing. Florence, Italy.

Picot-Clémente, R., Mendes, F., Cruz, C. and Nicolle, C., 2012. TOURISM-KM, A variant of MMKP applied to the tourism domain, In 1st International Conference on Operations Research and Enterprise Systems (ICORES 2012). Vilamoura, Algarve, Portugal.

Quinn, C., 2000. M-Learning: Mobile, Wireless, In-Your-Pocket Learning. LiNE Zine. Fall. In We Need an Educationally Relevant Definition of Mobile Learning.

Stojanovic L., Staab S., and Studer R., 2001. eLearning based on the Semantic Web. In WebNet2001-World Conference on the WWW and Internet. Orlando, Florida.


295

A NOVEL APPROACH TO THE APPLICATION OF SEMANTIC WEB TECHNOLOGIES TO STUDENT

CENTRED LEARNING

Ghislain Maurice Norbert Isabwe; Frank Reichert and Morgan Konnestad University of Agder

ABSTRACT

This paper addresses student centred learning in mobile environments. The challenges of student centred learning implementation are the requirements to provide learning resources/services according to the needs of individual students and adaptability to dynamically changing student contexts. The concept of student centred learning places the student at the centre of teaching and learning, and the student has more responsibility and ownership of his/her learning. This paper proposes the application of semantic technologies to create a mobile learning context model in order to support the student centred learning environments. A context-aware mobile learning ontology is presented, together with rules that are applied for reasoning on learning resources/services which would be considered by the student. The paper provides learning scenarios with rule based reasoning, and suggests a student centred learning service architecture.

KEYWORDS

Context-awareness, Mobile Learning, Semantics, Ontology.

1. INTRODUCTION

The quest for excellence in education has driven research efforts both in pedagogical models and educational technology over many years. Recently, it was argued that future teaching and learning will embrace new technology enabled constructivist learning concepts, including the use of mobile technology to improve the students’ engagement in the learning process (Isabwe et al., 2011). In this context, the student is active and the emphasis is put on what the student does in order to acquire knowledge or skills. This will involve a high level of student’s choice in education and customization of learning to suit different individuals.

In the late 90’s, Hannafin et al. (Hannafin and Land, 1997) discussed technology-enhanced student centred learning environments, with the identification of their foundations and assumptions. Through a review and a critical analysis of such environments, the authors noted the potential to address individuals’ learning interests, and enhance the learners’ thinking ability as well as their understanding. On the other hand however, the implementation of technology supported student centred learning environments, involves complex processes in terms of pedagogic conceptual adaptation and optimization of adopted technology tools.

Our approach capitalizes on students’ ability to make choices on what they want to learn, how they prefer to learn it and their context information such as the location, time and the activity among others. The aim is to assist the students in making their choices while being encouraged to identify their needs, to explore the available learning opportunities, to reason and to learn what they believe is necessary and meaningful.

This paper presents in section 2 an overview of related work, comprising of a literature review of context-aware mobile learning. In section 3, a context-aware mobile learning ontology is discussed and, in section 4, a semantic web rules language is used for rule based reasoning on scenarios of student centred learning. The last section is a conclusion with future directions.

ISBN: 978-972-8939-66-3 © 2012 IADIS

296

2. CONTEXT-AWARE MOBILE LEARNING

Mobile learning, a modern concept of using mobile technology in teaching and learning, has seen an increasing interest among educators and researchers. Context-aware mobile learning is of special interest because of the context dimension which is defined as “any information that can be used to characterize the situation of an entity (Dey, 2001)”; and the awareness as used in context-aware systems, whereby the awareness stands for the use of “context to provide relevant information and/or services to the user, where relevancy depends on the user’s task” (Dey, 2001).

Lehsten et al. (Lehsten et al., 2010) proposed an extension of Learning Management Systems to provide personalized mobile learning services. It is suggested that using mobile device features like positioning, acceleration sensors, or the camera, the user’s intentions are detected. Then, based on the knowledge of user’s location and timetable, helpful and interesting university services are offered, such as the location-sensitive lecture streaming, guiding the way to books recommended by the lecturer in the library, campus navigation, accessing optimized lecture notes for mobile devices and using ubiquitous features of the whole university computing infrastructure. It is noted that, in this work, context information was only limited to time and location.

Furthermore, another study considered user perceptions and preferences for a context-aware personalized mobile learning application (Yau and Joy, 2010). The authors carried out an interview study of individual mobile learning preferences comprising of the location of study, noise or distraction levels in a location and the time of the day. The typical locations of study were sorted into study-dedicated areas, home areas, cafes and transport facilities. It was mentioned that preferred locations are related to factors affecting student concentration levels such as noise, busyness of the environment, temperature, light and layout of the room, motivation, time of the day and urgency of the task. The authors argue that current location, noise level, and time of day can be detected to determine appropriate learning materials for a student profile (preferred location of study, preferred noise level and preferred time of day). That study does not provide details of how appropriate learning materials are defined.

In a separate study, Moore et al. (Moore et al., 2009) discussed the effective creation and implementation of an individual profile, termed as context. They defined two general types of context: a static context (customisation) in which the user is actively involved in making the profile and, a dynamic context (personalisation) whereby the system detects, analyses and reacts dynamically to the user’s behavior. Subsequent to user profile creation, context matching and processing was carried out in order to enable an effective use of contextual information. Through a scenario based evaluation and simulation, context matching and context processing rules were tested out using semantic web technologies. Context matching may prove difficult if there are highly dynamic context factors as well as possibilities to encounter anomalous or ambiguous contexts.

Context in mobile learning can be modeled using the ontology, which is a specification of a concept. The ontology is used to present and organize a learner’s context and, a context-aware mobile learning model can be constructed based on ontology and case-based reasoning approach.

In the next sections, we present our approach to context-aware mobile learning. The novelty of our approach resides in the combination of mobile technology aspects for user profile building and the user’s ability to supply context information as well as the selection of learning resources. Here the focus is put on reasoning on the student’s context and learning style in order to suggest to him/her the learning resources/services.

3. CONTEXT-AWARE MOBILE LEARNING ONTOLOGY

Mobile learning can play an important role in enabling student centred learning. A student can choose his/her preferred learning style and, given today’s mobile devices capabilities, some of the student’s context information such as time, location and activity can be detected and used for learning purposes. Furthermore, the student can be involved in manual creation of his/her profile using a mobile device.

Figure 1 illustrates a context-aware mobile learning ontology that was developed with Protégé (SCBIR’, 2011) Web Ontology Language (OWL) editor. Generally, the ontology, as a specification of a domain concept, explicitly describes the context elements and defines the relationships between the entities in terms


297

of object properties and data properties. OWL offers the capability to create four ontology components: (i) concepts, (ii) instances, (iii) relations and (iv) axioms. In this work, we suggest 5 main concepts to describe a context-aware mobile learning domain.

Figure 1. Context-aware mobile learning ontology

1. Courses: This is a class with subclasses representing the specific courses that are offered. Course classes such as ‘IKT709’ will also have ‘instances’ to represent courses that are offered during a particular academic year or semester.

2. Person: This is a class whose individual entities represent the students. It helps to collect individual students’ data such as names and contact addresses.

3. Context: a student context is comprised of his/her current activity and location. a. Activity : Three main sets of activities are defined as follows:

i. Working: All activities directly related to the studies. These can include tasks such as working on an assignment, laboratory work or group study. Such activities can take place both during the official study time or any other time when the student works on his/her own initiative. This kind of context information can be collected onto the ontology through customisation. ii. Travelling: Any activities that involve moving from a point in space to another. This context

information helps to determine appropriate formats of learning materials; for example, due to safety reasons, we would not expect a student to be able to read course notes while riding a bike. iii. Resting: All activities during which the student is not supposed to be studying. These include activities such as sleeping, socializing with friends and sporting just to name a few. We assume that these activities take place during the student’s free time, which is out of official studying hours. Therefore, the context aware mobile learning system should only suggest such learning activities that are not compulsory and might not disrupt the student’s right to rest. For instance, it would not be necessarily appreciated if a student was to receive an alarm message while he/she is sleeping.

b. Location: We have defined two main sets of locations: i. MobileDynamicLocation: This is defined as a set of locations where a student can be while

travelling. We consider that a student can be on a bus, in a car, on a foot path, on a train or a plane. It is noted that although the list may not be exhaustive, it gives a good indication of possible mobile locations. ii. FixedLocation: This is a complement set to the previous one (MobileDynamicLocation). It

comprises of locations in which the student is not moving in space, with consideration to both indoor and outdoor environments. For instance, the indoor locations can be subclassified into public and private areas.

In addition to the activity and location, we have considered four learning styles with reference to Kolb’s learning styles (Kolb, 1984). Using a self-descriptive inventory, Kolb measured differences in learning styles and he identified four most significant learning styles. It is noted that, in this paper, we have appended each learning style with the word ‘Style’ for the sake of consistency in the naming of “learning concept”:

4. LearningStyle: i. DivergerStyle: This style refers to a way of knowledge development through a combination of

Concrete Experience (feeling) and Reflective Observation (watching) of the environment around

ISBN: 978-972-8939-66-3 © 2012 IADIS

298

the student. Students in this category dispose of strong imaginative abilities, and they are capable of discerning concrete situations from a multitude of viewpoints and ideas. ii. ConvergerStyle: Students with this learning style prove to have dominant Abstract

Conceptualisation (thinking) and Active Experimentation (doing) learning abilities. iii. AssimilatorStyle: The learning is achieved through thinking (Abstract Conceptualisation) and watching (Reflective Observation). Students with this learning style are said to be capable of inductive reasoning as well as model and theory creation. iv. AccommodatorStyle: This learning style is marked by the strengths in Concrete Experience and Active Experimentation. Students who fall in this category are those who are more involved in doing things, making new plans and experiments as well as taking part in new experiences.

5. Resources: The resources describe services and learning materials that can be offered to the student. For instance, the system can deliver messaging services such as alerts and announcements in addition to providing podcasts and lecture videos. Reading materials are also another form of resources that can be offered in this context.

4. RULE BASED REASONING FOR A STUDENT CENTRED LEARNING ENVIRONMENT

In order to implement a student-centered learning environment, each student’s profile is collected into the ontology. Profile elements consist of a student bio-data, course of study, context, and learning style.

Figure 2 shows the ontology’s entities and relationships that are used for reasoning on the learning resources/ services offered to different students. Given the student’s activity at a given time, location, learning style, and the course of study; the student can be offered learning resources (services) accordingly. These services include the provision of course materials in the form of documents (reading materials) and podcasts (here called VideoCast/ AudioCast), as well as a messaging service (PhoneService) for alerts and announcements. Using the Semantic Web Rules Language (SWRL), rules are written so that a reasoner can infer the learning resources that will be offered to a given student. The logic behind the reasoning is that the student should be allowed to choose whether he/she would like to have access only to those resources according to the context and learning style or to have access to an extended list with priorities of resources following predefined rules.

Figure 2. Rule-based reasoning for a student centred learning

In order to illustrate the rule based reasoning, in the next subsection, we present 4 scenarios showing how the student can be offered learning resources. The scenarios are built on the context information presented in the ontology given above, the learning styles as well as the courses of study. As a proof of concept, the scenarios were implemented using OWL DL and SWRL in Protégé.

4.1 Student Centred Learning Scenarios

Annie is a student who has enrolled on an English course. Her learning style was predefined as a “Diverger”, and she is at the moment working (individual study) at home. Annie’s learning style was set manually (customization) and her activity and location information are being dynamically collected by a mobile device


299

(personalization) onto the ontology. Annie should be given access to learning resources that are appropriate to her current profile and, she should be able to make choices as to have access to a wider range of materials (less profile related restrictions). Therefore, four rules are added on the ontology to make that possible. Rule number one is first applied in response to Annie’s profile (context and learning style), and then Annie is given an option to choose her preferences on additional learning materials. The implementation of the rule based reasoning is achieved with JESS rule engine (Sandia, 2008).

• Rule 1. Access to resources restricted to the student’s context and learning style: Person(?P)^ Course(?C) ^ hasCourse(?P;?C) ^ hasResources(?C;?R) ^ hasActivity(?P;?A) ^ hasLocation(?P;?L) ^ canAccessResources(?A;?R) ^ hasLearningStyle(?P;?l) ^ makeUseO f Resources(?l;?R) ^ canUseResources(?L;?R) �hasAccess(?P;?R)

Subsequent to the reasoning on this rule, the rule engine has inferred that Annie can have access to an English course Videocast (lecture video). This is based on her learning style, which suggests that she can learn by watching a video, her activity which is studying and the home as a ‘private area location’. The ‘studying’ activity can access ’VideoCast’ resources and the ‘private area location’ can use the ’VideoCast’ resources as well. The same rule also had first to check on Annie’s course of study in order to return English learning resources.

In addition to the inferences from rule number 1, using the available OWL APIs; there is a possibility to generate a request for Annie to trigger the reasoning on the rules number 2 to 4 so that she can have access to an extended range of learning resource as presented in the next rule scenarios.

• Rule 2. Access to resources relevant to the student’s course of study and learning style: Person(?P) ^ Course(?C) ^ hasCourse(?P;?C) ^ hasResources(?C;?R) ^ hasLearningStyle(?P;?l) ^ makeUseO f Resources(?l;?R) �hasAccess(?P;?R)

• Rule 3. Access to all resources relevant to the student’s course of study: Person(?P) ^ Course(?C) ^ hasCourse(?P;?C) ^ hasResources(?C;?R) �hasAccess(?P;?R)

• Rule 4. Access to resources from all courses related to the student’s course of study: Person(?P) ^ Course(?C) ^ hasCourse(?P;?C) ^ hasResources(?C;?R) ^ isRelatedTo(?C;?T) ^ hasResources(?T;?Z) �hasAccess(?P;?R) ^ hasAccess(?P;?Z)

4.2 Student Centred Learning Environment

A student centred learning environment can be enabled through the integration of ontology based mobile learning context model and a learning management system (LMS).

Figure 3 presents a student centred learning service architecture, consisting of an enhanced LMS which handles the ontology storage, processing and reasoning together with a mobile device which handles the context data collection as well as learning resources delivery. Our approach proposes to make use of Protégé OWL API (Application programming interface) in order to define the interactions between the ontology and the existing LMS which can host the learning resources on one hand. On the other hand, using the mobile operating system API, a mobile application can be defined to push context data into the ontology. Subsequently, a rule engine will reason on the context data so that new (updated) instances of learning resources can be generated and exported into the ontology. Once the ontology is updated, the mobile application should retrieve appropriate learning resources from the LMS.

Figure 3. Student centred learning service architecture.

• Learning /Content Management System

• Ontology storage & Processing

• Rule based reasoning • Context collection

• Mobile servicesContext data

Learning resources /Services

Internet

ISBN: 978-972-8939-66-3 © 2012 IADIS

300

5. CONCLUSION AND FUTURE DIRECTIONS

Student centred learning as opposed to teacher centred learning not only places the student at the centre of the learning process but also seeks to improve the learning efficiency through active learning. This requires the consideration of the student’s profile and the student’s ability to control their learning. The student profile can be established and regularly updated both manually and automatically using the sensors embedded in mobile devices.

With the knowledge of students’ context information, personalized services can be offered to the students. Students are involved in this mobile learning model both in building their profile on which the reasoning on learning resources is done, and choosing the resources that they want to use for learning. This paper discussed the development of a mobile learning ontology, and a rule based reasoning for efficient implementation of student centred learning environments.

Our implementation has considered OWL DL together with SWRL, and it has enabled access to learning resources according to both the student’s profile (context and learning style) as well as the student’s choice of learning resources. Since this work has proved the viability of semantic web technologies for student centred learning, future work will consider additional aspects of learning such as students’ understanding levels and learning performance for advanced reasoning on learning resources and services.

REFERENCES

Dey, A. K., 2001. Understanding and using context. Personal and Ubiquitous Computing, Vol. 5, No.1, pp.4–7. Hannafin, M. J. and Land, S. M., 1997. The foundations and assumptions of technology-enhanced student-centered

learning environments. Instructional Science, Vol. 25, No.3, pp.167–202. Isabwe, G. M. N., Oysaed, H., and Reichert, F.,2011. Future concepts for university teaching and learning. Proceedings

of IADIS International conference Mobile Learning. Avila, Spain, pp. 307 – 309. Kolb, D. A., 1984. Experiential learning: experience as the source of learning and development. Prentice Hall,

Englewood Cliffs, NJ, USA. Lehsten, P., Zender, R., Lucke, U., and Tavangarian, D., 2010. A service-oriented approach towards context-aware

mobile learning management systems. Proceedings of the 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops). Mannheim, Germany, pp. 268–273.

Moore, P., Hu, B., Jackson, M., and Wan, J.,2009. Intelligent context for personalized mobile learning. Proceedings of International Conference on Complex, Intelligent and Software Intensive Systems. Fukuoka, Japan, pp. 247–254.

Sandia National Laboratories, (2008). Jess rule engine. Available on http://www.jessrules.com. Accessed on 16/01/2012. Stanford Center for Biomedical Informatics Research - SCFBIR, 2011. Protégé-OWL editor. Available on

http://protege.stanford.edu/overview/protege-owl.html. Accessed on 16/01/2012.

Yau, J. Y. K. and Joy, M. (2010). A context-aware personalized m-learning application based on mlearning preferences. Proceedings of the 6th IEEE International Conference on Wireless, Mobile, and Ubiquitous Technologies in Education, Kaohsiung, Taiwan, pp. 11–18.


301

MBCLICK - AN ELECTRONIC VOTING SYSTEM THAT RETURNS INDIVIDUAL FEEDBACK

Geoff Rubner School of Electrical and Electronic Engineering, University of Manchester,

Oxford Road, Manchester M13 9PL UK

ABSTRACT

mbclick is a new electronic voting system that emphasizes the return of individual feedback. It uses students’ own mobile phones, and works with both ‘smart’ and ordinary types. It is web-based, thereby removing the need to install any dedicated application software to make it work. It is easy to learn and use, and integrates with Microsoft PowerPoint. mbclick does away with the need to purchase and distribute traditional handheld clickers, freeing the institution and the teacher from the associated overheads. The system has been successfully trialed at the University of Manchester.

KEYWORDS

mbclick electronic voting system mobile phones individual feedback

1. INTRODUCTION

Active learning approaches in the classroom have long been recognized as a means of promoting student engagement and understanding. Interaction between teacher and student can enrich the learning environment, facilitating students to participate actively in the learning process. For the teacher, the design of formative assessment activities is motivated by wanting to increase students’ desire to learn, to engage in self-evaluation and self-assessment, and, in varying degrees, to take control of their own learning.

The work of Nicol and Macfarlane-Dick [1] brought fresh perspectives to formative assessment and feedback processes, and articulated sets of principles considered integral to good assessment design. A selected subset of these principles, and relevant to this discussion, are listed below:

• engage students actively in learning • facilitate opportunities for self-assessment and reflection • deliver high-quality feedback that helps students self-correct • provide opportunities for feedback dialogue, both peer-peer and teacher-student • provide opportunities to act on feedback • engage students in deep, not just shallow, learning Within the context of the classroom/lecture theatre, an Electronic Voting System (EVS) can be used to

help design assessment activities that include all of the above. Such systems, also known as Audience Response Systems, Classroom Communication Systems, or clickers, directly introduce dialogue and interactivity between teacher and student, and been extensively described and researched [2][3][4]. With such systems, the term ‘feedback’ is variously used to describe the feedback provided by the system to the teacher, and that given by the teacher to the student. The focus of this discussion is on the feedback supplied by the teacher.

Experienced practitioners of these systems know that they are of value in quickly determining students’ understanding of the topics being taught. In reviewing the students’ responses to the questions set, the teacher is able to examine how the students have understood the material presented. This allows the teacher to adjust their presentation accordingly and provide feedback. The quality of the feedback provided by the teacher is a critical area for the use of an EVS. For the student, the feedback takes on value once it has been internalized and understood. It can then be used to evaluate their comprehension of the topic under consideration, leading

ISBN: 978-972-8939-66-3 © 2012 IADIS

302

to a deeper understanding. Studies have shown that the feedback provided by the teacher in such settings can be a very effective pedagogical strategy for enhancing student understanding and performance [5][6][7].

2. FEEDBACK WITHIN EVS SYSTEMS

EVS systems work essentially by allowing a teacher to present questions –typically multiple choice- each with a small number of response options- to the students, who respond with handsets distributed to them in advance. The results are then displayed on an overhead chart. Commercial EVS systems often integrate with commonly-used presentation software e.g. Microsoft PowerPoint and are popular in various institutions [8].

With an EVS the classic interaction between teacher and students can be visualized as a simple cycle consisting of the presentation of questions, gathering the responses, and then providing feedback to the student. The feedback imparted to the student by the teacher is typically verbal or written. Its main purpose is to correct any misunderstandings on the part of the student (or re-affirm correct understanding), and help develop the student’s own skills of evaluation and judgement. Usually, however, where the class size is such that it is difficult to give individual attention, the feedback is imparted to the whole class, rather than the individual student. In this respect while current EVS systems are valuable in providing information quickly to the teacher about the level of understanding in the classroom, they are not generally designed to ensure that feedback is targeted at, and delivered to, the student in an individual way.

3. PRACTICALITIES OF USING EVS SYSTEMS

The components of an EVS typically include a handset per student, a receiver, and software installed on the teacher’s computer. Handsets are distributed to students either at the start of the lecture and collected in again at the end, or, students may be expected to buy the handset or lease one from the institution, and bring them to class. They are usually simple devices and it does not take students long to become familiar with their use.

For an EVS to be used effectively however, the questions presented must be relevant, addressing those concepts vital to the subject, and leading to deep learning. It can take time for a teacher to learn how to design sessions that include good-quality questions, and a teacher must be well-prepared to ensure that the expected outcomes are achieved. In comparison with delivering the traditional didactic lecture, where little technology other than presentation software is used, a lot more is demanded from a teacher who decides to use an EVS. Particularly relevant are skills relating to strong and confident classroom management.

The clickers provided by EVS systems tend to be proprietary devices, either radio frequency–based, or infra red-based, where the receiver is in the form of a dongle that is plugged into the teacher’s laptop computer. From the student perspective a clicker is yet another device that has to be carried around, in addition to their own mobile phone. The ownership of mobile phones amongst students is frequently reported as being close to 100%, and with the emergence of wifi-enabled ‘smart’ phones owners have the equivalent of a powerful computer in their pocket with full internet connectivity. The idea that students could use their own phone as a clicker when participating in an EVS has not gone unnoticed. Some EVS vendors have extended their systems to work with mobiles, allowing a student to participate via web access, SMS, or both [9]. Some educational institutions have independently experimented with systems that use mobile phone and other portable wireless internet-connected devices, where one motivation has been to minimize usage costs to both the student and institution. See, for example, mInteract from the University of Technology, Sydney [10], and W.I.L.D. from the School of Arts and New Media, University of Hull [11].

4. THE MBCLICK SYSTEM

It is apparent that increasing numbers of students want to use their phones to access educational materials and this is certainly true of students at Manchester [12]. mbclick is an EVS that is aligned with these aims, but works with any mobile phone, not just smart-phones. Any device that is capable of being connected to the internet will also work, so laptops can be used, for example.


303

It is innovative in that it is designed around the return of feedback that is targeted to the student in a personalized way. This is possible because the students are known to the system via a one-time registration process carried out at the start of the teaching calendar. The feedback returned typically explains why the student’s response was correct or not and is included by the teacher at the time the question is created. Feedback can typically also include other information, for example links to further learning activities, or materials on the institution’s Virtual Learning Environment. A system diagram is shown in Figure 1.

Figure 1. mbclick System Diagram

Questions are presented in class either with a web browser or PowerPoint. Students respond either with a browser running on a laptop/notebook computer, or their smart-phone (browser or app), or via SMS if using an ordinary phone. The system includes a database that stores the results for each session held. Surveys can also be conducted using the system. In common with other EVS systems the sets of data collected are informative and can be viewed in a number of different ways.

For example, the diagram in Figure 2 shows a chart of the percentage of questions answered correctly for each of eight sessions from an undergraduate course in Java Programming, presented in the School of Electrical and Electronic Engineering at the University of Manchester, during February-April 2011:

Figure 2. Percentage of questions answered correctly for eight sessions

The results for individual questions presented during each session are also recorded and charted. Furthermore, because each individual’s responses are also stored, an individual student’s performance can be tracked across multiple sessions, as shown in Figure 3:

Figure 3. Percentage of questions answered correctly by a student for sessions attended (note –not all were attended).

ISBN: 978-972-8939-66-3 © 2012 IADIS

304

Such data can be valuable to a teacher when reviewing the design and delivery of lectures and other course materials, particularly the student response data: an individual that is having difficulties with specific parts of the course can be readily identified. Sessions can be archived for comparison say, with successive runs of the course. The data is available in chart form as above, or downloadable in csv format.

5. CREATION OF QUESTIONS AND FEEDBACK

To create questions a teacher will first login and access course units that he/she teaches. Typically multiple-choice questions are created that are text-only, or if required, a mixture of text and images. Questions can have single or multiple answers, and feedback is created for each possible answer option. The feedback is usually a short piece of text explaining why the choice is correct/incorrect, and can also include links to further course materials, or further questions, for example. The feedback is returned to the students’ phone and also sent by email to them at the end of the session. An example taken from a question about programming from the Java course is shown in Figure 4:

Figure 4. Example of feedback returned explaining why the selected option (option 2 in this case) is incorrect and illustrating which is the correct response.

The feedback returned to the student corresponds to the option chosen (option 2 in the above example), and explains why that option is incorrect. The correct answer is also shown (marked by a tick). Such feedback adds value to the session and can be stored in any way the student chooses to organize it. Later, the student can login to the system and review all the session questions and see the feedback associated with each of the answer options, not just the ones chosen. Access to the system is entirely web-based, and designed to be easy to use. A teacher requires no more than a few minutes to learn enough to be able to start creating questions with feedback.

6. TRIALS AND RESULTS

A number of trials were held during 2010/11 with groups of up to 300 staff and students, at events in selected Schools across the University. Attendees were asked to complete questionnaires in which they were asked several questions. To summarise, the analysis of the responses gathered showed that 90% of the respondents liked the mbclick system, 61% preferred to use a web browser rather than SMS, and 89% of the academic staff who responded would consider using mobile phones instead of clickers in their teaching in future [13].

The experience gained in using the system with this one course was extremely valuable. The data collected helped determine which students had difficulties with different areas of the course, and to what extent. It was also helpful in designing better quality questions and feedback to improve their understanding and knowledge of the subject. Students were enthusiastic about the sessions. The following are a sample of comments obtained from questionnaires completed at the end of sessions: “good to get instant feedback”, “help keeps me alert”, “allowed me to interact with the lecturer and stay awake”, “interact with the lecturer with privacy”, “points out flaws in my knowledge”, “personalize the lecture”, “instant feedback very useful”.

From the trials there emerged a number of issues to do with both classroom management and the technology, whose importance quickly became apparent. The system relies on a wireless infrastructure that provides good WiFi and 3G/GSM coverage, but of course not all locations guarantee this. The bandwidth requirements ultimately depend on the class size. In tests, the requirements for each user were found to be


305

quite modest: typically 4kB of data are sent or received in responding to each text-based question. In a group of say, 100 users, demand would be expected to peak during the polling window. In the worst case this would result in a demand of approximately 3Mb/s. At the University of Manchester wireless access points that are deployed in or near classrooms, are multiple-antenna, supporting 802.11 a/b/g/n, and easily meet the bandwidth requirements. A further consideration is to ensure that authentication timeouts due to inactivity are extended to cover the time of the session.

7. SUMMARY

mbclick provides the basic functionality one would expect of an EVS but goes further in that it returns individual feedback to the student, direct to their mobile phone/device. This feature alone is of high value because it provides the teacher with an automated way to deliver high-quality feedback that helps students self-correct and engage in deep learning. It also provides a detailed record of students’ responses, so that a profile of individual performance can be built up. For the student, having detailed feedback sent to their phone makes it feel personalized and individual. An evaluation study of the mbclick system is currently under way in a selected number of schools within the University of Manchester.

ACKNOWLEDGMENTS

The author would like to thank the University of Manchester Teaching and Learning Support Office and the Faculty of Engineering and Physical Science for providing funding for the mbclick project.

REFERENCES

[1] http://tltt.strath.ac.uk/REAP/public/Resources/ DN_SHE_Final.pdf (accessed: June 2011) [2] Kennedy, G.E. & Cuts, QI (2005) “The association between student’s use of an electronic voting system and their

learning outcomes.” Journal of Computer Assisted Learning, 21, 260-268. [3] Bruff, D (2009) “Teaching with classroom response systems: creating active learning environments.” San Francisco

Jossey-Bass [4] Fies, C. & Marshall J, (2006). “Classroom Response Systems : a review of the literature.” Journal of Science

Education and Technology, 15(1), 101-109. [5] Beatty, I (2004). “Transforming student learning with classroom communication systems.”

http://net.educause.edu/ir/library/pdf/ERB0403.pdf (accessed: August 2011) [6] Draper, S.W. & Brown M.I. (2004) “Increasing interactivity in lectures using an electronic voting system”.

http://www.psy.gla.ac.uk/~steve/evs/papers/draperbrown.pdf (accessed: September 2011) [7] Nicol, D. J. (2006). “Increasing success in first year courses: assessment re-design, self-regulation and learning

technologies”. Paper presented at ASCILITE Conference, Sydney, Dec 3-6, 2006 [8] See for example TurningPoint and eInstruction: (http://www.turningtechnologies.co.uk)

(http://www.einstruction.com) (accessed: September 2011) [9] TurningTechnologies Responseware:

http://www.turningtechnologies.com/studentresponsesystems/mobiledistancelearning/higheredresponseware/ accessed: September 2011) See also Poll Everywhere: http://www.polleverywhere.com/ (accessed: September 2011)

[10] Laurel Evelyn Dyson, Andrew Litchfield, Elaine Lawrence, Ryszard Raban and Peter Leijdekkers “Advancing the m-learning research agenda for active,experiential learning: Four case studies”, Australasian Journal of Educational Technology 2009, 25(2), 250-267.

[11] Mundy, D.P and Proctor, J, “Getting W.I.L.D in the Classroom”, 3rd Practice Based and Practitioner Research Conference, Bergen, Norway, November 26th - 28th, 2008.

[12] http://www.campus.manchester.ac.uk/tlso/ newsbulletins/mle/ (accessed: June 2011) [13] Rubner, G., Internal TESS report, Faculty of EPS, University of Manchester, 2010.

ISBN: 978-972-8939-66-3 © 2012 IADIS

306

HEALTH CARE EDUCATION SYSTEM FOR MOBILE DEVICES

Toshiyuki Maeda1, Yuki Ando2, Yae Fukushige3, Mayumi Yamamoto4 and Takayuki Asada5 1Hannan University, Japan

2Osaka University, Japan 3Otaru University of Commerce, Japan

4Gifu University, Japan 5Ritsumeikan University, Japan

ABSTRACT

This paper addresses a health care education system in communication with mobile devices such as mobile phone, tablet computer, and so on. We introduce a Web/mail interface application system for health care support at a university. We focused on anti-obesity using mobile phones as client terminals, and discuss effects through experimental field tests.

KEYWORDS

Health care education, Mobile communication, Web/mail application, Anti-obesitys

1. INTRODUCTION

Health is essential for human being to live a happy and pleasant life. We need to sustain the motivation to keep healthy habits for good quality of life (QoL). However, the number of people who claim their health problems is increasing. One of the reasons is that their life styles are getting variations, which include irregular life cycle and increase of stress. That implies many people have some health problem caused from lack of normal nutrition or activity, even though they have high health consciousness.

We focus on anti-obesity treatment for students in a university, as obesity is shown to decrease QoL as increasing risks of future chronic diseases and their complications[1]. It is reported, furthermore, that eating action and feelings of fullness or emptiness are less related for obese people[2]. [3] addresses that university students who have high health consciousness make good health action. Furthermore, health problems for aged people emerge more likely, and that means they actually seem to have some problems. We believe people should raise health consciousness in younger ages for preventing health problem. Overweight may not only causes into health disorder, but also affects future life style, and so it is very important to care for weight. We focus on health care education as preventing health disorder of student youth and improving “health literacy.”

We thus believe regular life cycle is essentially important for obese people to be healthy, and some ICTs (Information and Communication Tools) help that. We aim to support health care using mobile communication systems (MCSs), which are getting more and more important for our everyday life as a mobile device is already a must item, not only for business but also private time.

In this paper, we explain our health care education system for university students and later describe the proposal of Web/mail interface application. We then express experimental results in a university and discuss those.

2. RELATED WORKS

So far, there are some researches for health care support systems. [4] researches and develops health care system in universities using Web and mobile system. [5] studies calories management for health care support using mobile phone applications. Above systems, however, have problems for our targets as below;


307

• System complexity for various carriers, • Lack of health consciousness for nutrition, and • Lack of communication between students and health office. System complexity for various carriers causes from Japan-specific matters. In Japan, there are some

carriers, and each of those has many equipment types and no compatibilities for contents service. For that reason, we have to pay tremendous cost if we support all equipment. We thus introduce a generic mail-based communication system that can be used by almost all mobile devices such as mobile phone, tablet computer, and so on.

We expect so called “Recording diet method” effect by sending plain-text e-mails written by students themselves. The method is to lead dietary effect for users by recording their daily meal data, and then reinforcing consciousness of caloric intake. In Japan, “Recording diet method” is one of popular diet methods. For instance, [6] researches a recording system of caloric intake by taking and saving each meal image. [7] develops a Web-based “Recording diet method” system and examines field tests. This system expects to improve casual human communication by forcing students to describe health management data and to send mails.

For our purpose, it is important not only to communicate, but also to give some incentives by e-mails as “push” media for stimulating “health consciousness.” We therefore introduce Web/mail interface[8]. Furthermore, our system supports not only mobile phone terminals but also other equipment (PC, PDA, and so on) which can send/receive mails, and that means the system offers various approaches for each device. We can operate the system only by normal mails, and that means users should not learn additionally how to use, and so the system can be regarded as easy-to-use, lightweight, and generic.

3. HEALTH CARE SUPPORT

Our main objectives for health care support system are below two; • preventing health disorder, and • improving health literacy of students. Hence we have several concrete targets for students [9]; • understanding their own situation objectively, • learning preferable behaviors for preventing overweight, • enabling to set their tangible goals, • keeping the knowledge for practical use, • continuing to behave for preventing overweight, • reducing BMI (Body Mass Index), and • understanding necessity of self-management. We thus propose health care system regarding to the conventional system as follows. • The system must be improved health care education, • The system is used in everyday life, and • The system supports continual communication. Table 1 shows system requirement for health care education in a university. Note that “Conditional” is

used for filtering, such as, students with no attendance for last 3 times, students with no reply for last 3 questionnaires, and so on.

Table 1. Health care system requirement.

All Attended Conditional* Attendance Registration ○ Short Examination ○ ○ Questionnaire ○ ○ ○ Notice delivery ○ △ ○

ISBN: 978-972-8939-66-3 © 2012 IADIS

308

4. SYSTEM ARCHITECTURE AND EXPERIMENT RESULTS

Our system is designed and developed as follows (see Figure 1); • E-mail text-based communication independent with sorts of terminals, • Based on mail-communication system and approved various communications by one-stop account, and • Users’ availability for checking their own data which is reflected by every day’s reply data.

Figure 1. System flow

We had researched for above health consciousness by our system. On that system, users send e-mails with caloric intake and amount of physical exercise to a medical office every day, and the data are stored in a database on a server. Medical office staffs advise each user adequately using the database. The system is e-mail based communication system, and then all of users (not only students but medical staffs) communicate to each other by only e-mails.

In this paper, “Mail application” denotes an application where sending mails from users to a server is treated as input and replies from the server to corresponding users are as output, and repeating this interaction (round-trip) makes a unit of communication for the application system.

The features of this system concept are to collect, accumulate, proceed and distribute information anytime and anywhere using mobile phone at low cost. We proposed our system in a broad range of applications in the health care field. We apply this system in changing the lifestyle habits for students through diet and exercise monitoring with university nurses.

We have had field tests as three experimental trials. The first and most important part is daily questionnaire for students’ food intake, physical activity, and lifestyle habits. The questionnaire is sent and received through the questionnaire function using mobile e-mail every day. The second part is provision of information via message distribution function. The third part is individualized instruction message to a student when the health nurse deemed it necessary. Through the field tests, we have got following results:

• Subjects are 31 students (20 male, 11 female), and among them, 17 subjects reduce weights (-0.47 ±4.47 kg, averagely).


309

• We examine for the period from April until July in 2009. Among 31 subjects, 11 have continued for that period (Group A), and 20 abandoned before July (Group B).

• The variation of Group A is -2.89 ± 4.27 kg (t-test: p=0.028), and Group B +0.86 ± 3.87 kg (t-test: p=0.172), and so only Group A is statistically significant for reducing weight (p < 0.05).

Though this trial has not achieved so remarkable effects on students’ lifestyle habits, this trial has also revealed some problems: one of negative results is the low motivation of students, which is suggested in the return rate of daily questionnaire, which tends to decline. We regard the low motivation as caused mainly two reasons. One of the reasons seems the attitude of students, as many students have not realized the necessity of changing lifestyle habits, and there are no rewards for this trial. Another seems to be as input burden, where there may be intrinsic problems using mobile phone as interface, where the average numbers of input characters is around 60.

5. CONCLUDING REMARK

We introduce a health care education system using mobile device at a university, especially focused on anti-obesity, and discuss our implementation and some experimental results. For the time being qualitative and/or quantitative evaluation is not examined enough and so we believe we must do any other examination for that, and some in progress.

ACKNOWLEDGEMENT

Medical Office at Hannan University supported part of this research, especially preceding a field test. The authors greatly appreciate the support.

REFERENCES

[1] M. E. J. Lean, T. S. Han, and J. C. Seidell. Impairment of Health and Quality of Life Using New US Federal Guidelines for the Identification of Obesity. Archives of Internal Medicine, 159:837–843, 1999.

[2] B. Barkeling, N. A. King, E. Näslund, and J. E. Blundell. Characterization of obese individuals who claim to detect no relationship between their eating pattern and sensations of hunger or fullness. International Journal of Obesity, 31:435–439, 2007.

[3] K. Fujisawa and S. Watanabe. The Investigation of Health Consciousness and Behavior of Students: A Case of Certain Humanities Students at a Private University. Bulletin of Institute of Health and Sports Sciences, University of Tsukuba (in Japanese), pages 81–89, 2004.

[4] W. Y. Jen. Mobile Healthcare Services in School-Based Health Center. International Journal of Medical Informatics, 78:425–434, 2009.

[5] C. C. Tsai, G. Lee, F. Raab, G. J. Norman, T. Sohn, W. G. Griswold, and K. Patrick. Usability and Feasibility of PmEB: A Mobile Phone Application for Monitoring Real Time Caloric Balance. Mobile Network Application, 12:173–184, 2007.

[6] K. Kitamura, T. Yamasaki, and K. Aizawa. Food Logging and Processing: Analysis of Food Image. Journal of The Institute of Image Information and Television Engineers (In Japanese), 63(3):376–379, 2009.

[7] S. Karikome and A. Fujii. Analyzing Diet and Access Logs in A Dietary Habit Support System. In DEIM Forum 2010, page A4, 2010.

[8] T. Maeda, T. Okamoto, Y. Fukushige, and T. Asada. Mobile Application Framework for Health Care Education. In Proceedings of 7th Annual IEEE Consumer Communications & Networking Conference, pages (in CD–ROM), Las Vegas (NV, USA), 2010.

[9] T. Maeda, T. Okamoto, Y. Fukushige, and T. Asada. Mobile Communication System for Health Education. In Proceedings of World Conference on Educational Multimedia, Hypermedia & Telecommunications (ED-MEDIA 2009), pages 1156–1161, Honolulu (HI, USA), 2009.

ISBN: 978-972-8939-66-3 © 2012 IADIS

310

M-LEARNING 2.0: THE POTENTIAL AND CHALLENGES OF COLLABORATIVE MOBILE LEARNIG IN

PARTICIPATORY CURRICULUM DEVELOPMENT

Ilona Buchem1, Thom Cochrane2, Averill Gordon2, Helen Keegan3 and Mar Camacho4 1Beuth University of Applied Sciences Berlin , Luxemburger Str. 10, D-13353 Berlin, Germany

2AUT University, 55 Wellesley Street East, Auckland 1010, New Zealand 3Salford University, MediaCityUK, Salford Quays, M50 2HE, UK

4Universitat Rovira i Virgili, Ctra. de Valls s/n 43007 Tarragona, Spain

ABSTRACT

This paper explores the potential and challenges of collaborative mobile learning as a foundation for participatory curriculum development based on preliminary findings from a pilot phase of the iCollaborate project, which is an international collaboration project between university students and lecturers in four different countries. The project builds upon a heutagogical approach to m-learning integration (Cochrane & Rhodes, 2011) and serendipitous learning in social media (Buchem, 2011). The iCollaborate project incorporates international collaboration between groups of students in Germany (sociology of technology students in Berlin), Spain (educational technology students in Tarragona), UK (design students in Sheffield and Salford) and New Zealand (architecture students in Auckland) where participating lecturers have established partnerships aimed at exploring the potential of integration of collaborative m-learning in higher education. The focus of the project is on pedagogical strategies for cross-boundary, collaborative uses of mobile web for learning through the development of personal learning networks and user generated content. The paper reflects upon the potential and challenges related to international collaboration based on the application of mobile web 2.0 tools.

KEYWORDS

m-learning, mobile web 2.0, collaboration, participatory curriculum development, ePortfolio

1. INTRODUCTION

Collaborative learning scenarios are not new, however due to recent technological developments, mobile collaboration as a technology-enhanced process of remote communication in learning networks has just emerged as a promising approach for enhancing cross-boundary participation with new opportunities of peer-to-peer learning and teacher facilitation. From the perspective of participatory culture, mobile collaboration can play an important role in shaping curricula in higher education. This especially applies to new forms of affiliations (memberships in different networks and communities), expressions (production of new creative forms and user generated content), collaborative problem-solving (working together in groups to develop new knowledge) and circulations (shaping the flow of media in mobile web) (Jenkins, 2006). Mobile web 2.0 applications provide a technological basis that can both inspire and support these new forms of peer interaction. However, there is still a need for a pedagogical conceptualization of the application of mobile web 2.0 tools to support teaching and learning processes in formal settings, such as higher education.

The iCollaborate project aims to explore and clarify what strategies and mechanisms can be effective to support student collaboration and at the same time participation in decision-making about teaching and learning supported by mobile web applications. By granting autonomy for participating individuals and educational institutional as well as encouraging the exploration of possible applications of mobile web for collaboration, the iCollaborate project enables an open environment supporting curriculum innovation as a continuous learning process. This paper extends the current discussion on mobile learning and participatory curriculum development by presenting key learning points from field-based experience in 2011.


311

2. FRAMEWORK OF COLLABORATIVE MOBILE LEARNING

The collaborative mobile learning in the iCollaborate project has a serendipitous and emergent character. Serendipitous learning emphasizes the role of dynamic, unfiltered information coming from one’s social network combined with intellectual readiness for discovering seemingly unrelated connections and meanings (Buchem, 2011). Emergent learning is closely related to heutagogy in the sense of student-directed, negotiated learning in open contexts (Cochrane & Rhodes, 2011). Both serendipitous and emergent learning are applied to enhance spontaneous, low-threshold participation of students with different competency levels and cultural backgrounds rather than imposing full, rigid curricula impeding student engagement.

These approaches are founded upon social learning theory and frameworks, which inform the choice of technologies that support the different types of interaction within the project. Following the principles of social constructivist pedagogies based on Vygotsky’s (1978) argument that any learning is a social process, collaborative mobile learning in the iCollaborate project aims at enabling students to develop creative, critical thinking, and collaborative skills, rather than focusing upon fixed course content. Based on the concept of Communities of Practice by Lave and Wenger (1991), the project encourages students to find common interests and explore issues within a particular theme and context, at the same time acknowledging legitimate peripheral participation and enhancing learning through gradually bringing students into an active role and full participation in the community. The process of moving from a position of peripheral participation to full participation within a community of practice involves sustained activity and requires time for the ontological shifts necessary for learning something new (Cochrane, 2010). The sustained engagement of a community of practice, including students and lecturers, creates a supportive framework for cultivating participant ontological shifts: Lecturers reconceptualise their roles from content experts to facilitators of student-generated content and student-generated learning contexts; Students reconceptualise their roles from passive receptors of knowledge to active participants generating content and context within authentic learning environments and in this way negotiating and co-creating curricula.

Mobile learning is about ubiquitous social connectivity, instant information access, and enhancing how we view the world through digital augmentation (Cook, 2010). Aligning mobile web 2.0 tools with the learning goals, students and lecturers team together and engage in a number of different activities, such as microblogging or mobile video streaming, in this way creating working partnerships and intercultural experiences. Student groups from each participating country form a community of practice, share their own mobile generated content and gather feedback from other groups. Thus each local community of practice is augmented by a larger virtual community of practice. The project activities comprise:

• Collaborative teaching and project mapping through Skype, Google Plus Hangout, Google Docs • Videocasted remote presentations from lecturers and students shared via YouTube, • Microblogging on Twitter for communication and sharing of ideas and resources, • Lecturer and student blogs for recording project progress and peer commenting, • Student ePortfolios with reflections on the learning processes and digital identities, • Mobile student-generated media such as geo-tagged images shared via Flickr or Picasaweb, • Student-generated presentations (Prezi), augmented reality (Layer) and digital story-telling (Storify), • Mobile surveys shared by lecturers and students related to the use of mobile technologies, • Collecting and sharing resources in wikis, such as collections of tested mobile web 2.0 tools.

3. DESIGN OF PARTICIPATORY CURRICULUM DEVELOPMENT

Innovations in curriculum development become more likely if participants enjoy a certain degree of autonomy and the curriculum development is decentralized (Taylor, 2004). The resultant artifacts produced in the process of the mobile collaboration become boundary objects enhancing coordination and interaction between the local physical communities. The artifacts as boundary objects (e.g. pictures, videos, digital stories, wiki-entries) convey a common identity of each group and of all groups as a community (Star, 2010). These artifacts are less structured and easily adaptable to specific contexts. Creating, re-using and re-purposing artifacts as boundary objects are key to participatory curriculum design in the iCollaborate project.

ISBN: 978-972-8939-66-3 © 2012 IADIS

312

The iCollaborate project recognizes the importance of student engagement in the curriculum development process. Engaging students in negotiation of learning aims, processes and outcomes as well as in decision-making about the curriculum increase the ownership of learning and enhance participation. Creating working partnerships between lecturers and students across different universities in different countries enables building functional linkages across local communities. In this way both the content of the curriculum and the processes of teaching and learning may be related to global needs and practices in using mobile web for learning. These strategies require a dedicated engagement by lecturers and students in curriculum creation and negotiation process. This process has led both to good practice and to some less successful or less sustainable practices. Therefore it becomes crucial for the participants of the project to reflect upon these practices and evaluate their value added to the learning and teaching process. This ongoing reflection and evaluation of pedagogical practices is supported by means of student and lecturer blogging, student ePortfolios, survey and evaluations as well as ongoing sharing of experiences and development of new strategies in synchronous web-meetings. Besides a number of potential benefits, some initial challenges of mobile collaboration with the aim of participatory curriculum development are presented below.

4. POTENTIAL AND CHALLENGES OF MOBILE COLLABORATION

Building a core community of practice membership from the participating lecturers over a period of almost six months prior to the implementation of the project with their respective students has built up not only a toolkit for use, but also built significant trust among the lecturers. The serendipitous nature of mobile web 2.0 tools has also been illustrated by the brokering of the project across groups spanning four countries. Based on the field-experience in 2011 the key potentials of collaborative mobile learning that have been identified relate to changed educational practice, both on part of the lecturers and the students, such as:

• User-generated content (e.g. wiki-entries, video-casts, curated-collections) that can be reused, repurposed and remixed in other formal and informal learning/teaching scenarios (Downes, 2008) ,

• Students engaging in the process of deeper learning rather than surface learning due to intensive communication, collaborative problem solving , peer-feedback and reflection (Biggs, 1999),

• Raising awareness in participating institutions of the possibilities for connecting learners from different levels and disciplines through the use of mobile web 2.0 technologies, particularly focusing on the potential for cross-disciplinary connections (Balsamo, 2011).

The challenges of mobile collaboration described here are based on observations, survey and evaluations conducted in 2011 within and across local communities participating in the iCollaborate project. The following aspects were especially critical in the initial phase of the project:

• Diversity of perspectives, experiences, mobile devices and platforms (iOS, Android), • Language barriers and different course- and country-specific educational strategies, • Concerns about data security and sharing personal information via mobile web tools, • Enabling synchronous interaction due to different time zones. Owing to engagement of lecturers and students in mobile collaboration and development of the common

curriculum, an initial work plan has been agreed specifying learning/teaching activities and mobile web 2.0 tools. This plan has been continuously adjusted, recognising the emergent nature of collaboration and the changing needs and competencies of participants. Some key challenges encountered at a later stage include:

• Conflicting semester schedules - end of some courses, while other courses are still running, which impedes sustainable facilitation and self-regulated development of student groups,

• Recognition of a need to allow students time for generating content and thus difficulties in scheduling interactions and feedback phases,

• High level of facilitation needed to address the process-oriented approach and the need to develop skills and abilities to support participatory curriculum development.

• Encouraging students to value their participation and become active in the community of practice in order to acquire their knowledge.


313

5. CONCLUSION

The paper outlines the strategies, benefits and challenges of mobile, international collaboration in higher education enabled by mobile web 2.0 tools and aiming at participatory curriculum development. This has been an emergent process and project, as the participants have personally appropriated and modeled the use of mobile web 2.0 tools in the facilitation and sustaining of a mobile community of practice. In the process of negotiating and developing curricula, lecturers and students have experimented with the collaborative affordances of various mobile tools. The different applications of mobile web 2.0 have been reflected in blogs, ePortfolios and wikis as well as evaluated by means of mobile surveys, field observations and online questionnaires. The project attempts to bridge learning contexts beyond the local formal and informal learning contexts into international collaboration. One of the keys to making this collaboration successful will be the brokering of disperse local communities of practice into an overarching, international community. The reified activities of each local community will form artifacts that will be used to afford this international brokering: for example the introductory YouTube videos, student blogs, and Twitter streams. These mobile web 2.0 tools have become social and mobile enablers of international collaboration within this project. The establishment of international partnerships presents an exciting opportunity for future collaboration. The project forms a catalyst for introducing pedagogical transformation from teacher-centric curricula to participatory curriculum development together with students. The outcomes of the field-phase in 2011 form the basis of further research on mobile collaboration and participatory curriculum development.

REFERENCES

Balsamo, A., 2011. Designing Culture: The Technological Imagination at Work. Durham, NC: Duke University Press. Biggs, J., 1999. What the Student Does: Teaching for Enhanced Learning. Higher Education Research & Development,

Vol. 18, No. l, pp. 57-75 Buchem, I., 2011. Serendipitous learning: Recognizing and fostering the potential of microblogging. Form@re 201, Vol.

74, No 3, pp. 3-10. Cochrane, T., 2010. An mlearning Journey: Mobile Web 2.0 Critical Success Factors. In M. Montebello, V. Camilleri, &

A. Dingli, eds. Development. University of Malta, pp. 167-174 Cochrane, T. and Rhodes, D., 2011. iArchi[tech]ture: Heutagogical Approaches to Education Facilitated by Mlearning

Integration. Proceedings of the International Conference on Information and Communication Technologies in Education ICICTE 2011. Rhodes, Greece, pp. 112-121.

Cook, J., 2010. Mobile Phones as Mediating Tools Within Augmented Contexts for Development. International Journal of Mobile and Blended Learning, Vol. 2, No. 1, p.1-10.

Downes, S., 2008. E-Learning 2.0. eLearn Magazine. Available at: http://www.elearnmag.org/subpage.cfm?section=articles&article=29-1.

Lave, J. and Wenger, E., 1991. Situated Learning: Legitimate peripheral participation. Cambridge University Press, Cambridge, USA.

Leigh Star, S., 2010. This is Not a Boundary Object: Reflections on the Origin of a Concept. Science Technology And Human Values, 35(5), p.601-617.

Jenkins, H., 2006. Confronting the Challenges of Participatory Culture: Media Education for the 21st Century. Program, Vol. 21, No. 1, p.129.

Star, S. L. (2010). This Not a Boundary Object: Reflections on the Origin of a Concept. Science, Technology, & Human Values, 35(5), 601-617.

Taylor, P., 2004. How can participatory processes of curriculum development impact on the quality of teaching and learning in developing countries? Background paper prepared for the Education for All Global Monitoring Report 2005, UNESCO document.

Vygotsky, L., 1978. Mind in Society. Harvard University Press, Cambridge, USA.

ISBN: 978-972-8939-66-3 © 2012 IADIS

314

MODELING OF MOBILE LEARNING

Mahmoud Mohanna and Laurence Capus Department of Computer Science and Software Engineering - Université Laval

Quebéc, Canada

ABSTRACT

Mobile learning is a special case of distance learning, which in turn is considered as a technological evolution of the conventional learning. This paper proposes a doctoral research project aims to construct a comprehensive model of mobile learning. Research questions and objectives are discussed. CommonKADS methodology accompanied with its model suite is introduced and explained why it has been chosen to guide the modeling process. Research plan is identified including work done so far and next research steps.

KEYWORDS

Mobile learning, CommonKADS, modeling

1. INTRODUCTION

As a result of the mobile era and the explosion in the growth of mobile communications, Mobile learning (will be referred to it as m-learning in the rest of document) plays a growing role in the field of education. However, this fast growing type of learning faces many social, pedagogical and technical problems.

To date, m-learning has no strict definition and no worldwide standard. Consequently, mobile technology is not perfectly utilized in the field of education and the possible gains that could be obtained from the employment of this fast growing technology have not been recognized yet. Accordingly, researchers have lot to do in order to bridge the gap between the actual situation of m-learning and what potentially could be achieved due to its distinct features and capabilities.

This document presents briefly a doctoral research project in the mentioned track. Our research aims at modelling the m-learning processes to provide a deep understanding of m-learning process in order to help the following researcher and developers in the same field.

In the next section, we first briefly discuss m-learning special characteristics as well as its pedagogical and technical challenges. In section 3, we define m-learning associated problems which motivate our research. Section 4 states the research objectives and section 5 discusses briefly the CommonKADS methodology which is utilized to achieve the research objectives and why we have chosen it. In section 6, we illustrate what is done so far as well as next research steps.

2. CHARACTERISTICS OF M-LEARNING

M-learning is a new type of learning based on mobile technology where students can follow up their education anywhere, anytime, and any form using their mobile devices. These devices must respond to students requests and provide them with all required information effectively. Moreover, they should provide interactive communications between all sides of the learning process: students, instructors, and education administrators.

M-learning is simply defined as the ability to obtain or provide educational content on personal pocket devices such as Tablets, PDAs, smartphones and mobile phones [4]. It is agreed that m-learning requires further development in terms of both technology and pedagogy to meet its potential expectations.


315

2.1 M-learning Pedagogic Characteristics

M-learning offers three specials pedagogical advantages in the three learning experiences; individual, social, and contextual as follows [2]:

1. Constructive (Individual): M-learning provides the possibility to combine learning with moving, field education with ICT (Information and Communication Technologies). It can also provide the individual services according to student’s needs and his individual learning style.

2. Collaborative (Social): M-learning offers the opportunity to create a community of students will be beneficial to other students’ experiences and this can be done by good utilisation of communication tools provided by the mobile technology.

3. Situated (Contextual): M-learning provides support for context-aware learning. This is a great advantage of m-learning as the activities of the student and his surroundings are central and effective in determining learning objectives and educational contents.

2.2 M-learning Technical Characteristics

Using of mobile devices provides some features which have large effect on the learning process driven by mobile learning. The following technical factors result in the unique and special nature of m-learning and should be taken in concern during the design and the development of any m-learning process [4]:

1. Mobility: As longs as the learner is covered by the telecommunication network, he/she has access to the learning material anytime and anywhere within the coverage area.

2. Real time: M-learning is a real time learning method as it allows the learner a continuous and instantaneous access to the learning material.

3. Virtualization: Mobile device with cameras allows the instructors to create virtual classrooms. In addition, the ability of performing video calls provides high degree interactivity and interrelationships between the learners and their instructors.

4. Bit-Sized: As the traffic of the telecommunication networks has a great effect on the interconnection between different parties of m-learning, the educational content should be relatively short and comprehensive.

2.3 M-learning Limitations

Despite of its great offered pedagogical capabilities, m-learning has considerable defects and pedagogical drawbacks that cannot be neglected such as:

1. Lack of face-to-face interaction: In the traditional classroom, people can get to know each other and develop contacts and it is simple for them to access instructors to ask questions and receive guidance. The lack of face-to-face interaction and mentoring might make mobile learning very tough.

2. Lack of learning motivation: Mobile phones are designed for communicating with the other people, not for learning purposes. Therefore, many people would lack the psychological motivation needed to use consistently mobile phone in learning.

3. Lack of convenient learning environment: The mobility feature of m-learning has its drawback; that is surrounding environment may negatively influence the gain of the learning process or even interrupts it, this effect can be considered unavoidable.

Furthermore, there are also some technical limitations that impede the growth and the acceptance of m-learning such as the cost of service utilisation, small screens and low resolutions, input limitations, limited battery life, internet access limitations, standard and compatibility problems, and security challenges [5].

3. RESEARCH QUESTION

As a new research area, mobile learning is in its infancy, it is considered as a raw area for research. Consequently, a lot of work should be done to put the mobile learning in the right position which it deserves according to its distinct features and capabilities.

ISBN: 978-972-8939-66-3 © 2012 IADIS

316

Most of trials and case studies of m-learning currently applied now are individual and separate cases [6]. It is obvious that there are no global standard or clear guide lines to be followed to construct a complete and integrated mobile learning process.

The main problems related to the development of m-learning systems are summarized in the following points:

1. There no formulation of mobile learning and no standard ruling it. 2. M-learning could not completely replace the e-learning as a result of its pedagogical and technical

limitations explained earlier, and the low degree of acceptance and awareness of its capabilities. 3. The roles of different actors involved in learning process based on m-learning (educators, learning

administrators, and the learners) are not clearly defined. 4. M-learning currently does not represent more than a complementary part of an educational course

which can be easily displaced or removed without a considerable effect on the learning process. In others cases it is used to deliver a very small and simple learning material.

5. The contribution of m-learning in the learning process is not clear, in other words; there is no clear answer to the following question: “To what extent mobile learning can represent an added value to the learning process and play an essential part in it?”.

Consequently, the main research question which collects all the previously mentioned problems in one statement can be defined as:

“How to formulate a complete learning process depends basically on the mobile technology including the definition of the roles of all involved agents?”

4. RESEARCH OBJECTIVES

The main objective of our research is to provide a complete and satisfactory answer for the mentioned research question. More precisely, the research objective is to: “Propose a complete and generic model for a learning process based mainly on the mobile technology profiting entirely its capabilities and benefits provided by it”

This objective could be divided into specific sub-objectives as follows: 1. The first trigger of our research is to clearly define all components of the m-learning process. 2. Our research aims at providing a strict definition of m-learning tasks as well as all actors who carry out

these tasks. 3. The final proposed model should be applicable and generic enough to be feasible in different domains

from the lowest to the highest education levels and for vast variations of learning applications. 4. The proposed model should minimize as much as the impacts of m-learning limitations discussed

earlier. 5. It is essential to achieve the maximum profitability from the expected evolutions and advances in

mobile devices and telecommunication technology.

5. RESEARCH METHODOLOGY

CommonKADS (Common Knowledge Analysis and Design System) [1] is a comprehensive methodology for development of knowledge based systems covers the whole knowledge based process including knowledge analysis and engineering as well as system design and implementation introducing the knowledge-oriented methods and techniques for organizational analysis.

CommonKADS is the product of a series international research and application projects on knowledge engineering since 1983. It was developed by a number of industry-university consortia. At that time, there was little interest in such methodological issues, but nowadays it is in use worldwide by many companies and institutions.


317

5.1 Methodological Pyramid

A methodology such as CommonKADS like any other software development approach has a set of elements. These elements are represented in the form of a pyramid which is called the methodological pyramid. This pyramid is shown and explained briefly by figure 1.

Figure 1. Building blocks of methodological pyramid [1]

The CommonKADS process can be summarized in following steps: 1. Organizational analysis. 2. Business process analysis. 3. Knowledge elicitation. 4. Knowledge capture. 5. Knowledge modeling. 6. System development. 7. System test.

5.2 CommonKADS Model Suite

The core of CommonKADS methodology consists of three groups of models; these models are the answers of three basic classes of questions related to the system under examination (as described in figure 2), these questions are:

1. Why: why a knowledge base system is considered a solution for the mentioned problem? 2. What: what is the nature and structure of the knowledge involved, and the corresponding

communication? 3. How: how the knowledge will be implemented in a computer system?

Figure 2. CommonKADS model suite [1]

Now, we will represent a quick overview for each element of the CommonKADS model set illustrated in figure 1:

1. Organization Model: The organization model supports the analysis of the major features of an organization to discover the problems and the opportunities of knowledge systems and establish their feasibility.

2. Task Model: The task model analyzes the global task layout, its inputs and outputs, preconditions and performance criteria, in addition to needed resources and competences.

ISBN: 978-972-8939-66-3 © 2012 IADIS

318

3. Agent Model: Agents are the executers of tasks. An agent can be human, an information system, or any other entity can be carry out a task. The agent model describes the characteristics of agents, their competences, their authorities and constraints.

4. Knowledge Model: The knowledge model is to explicate in detail the types and structures of knowledge used to perform a task. It provides an implementation-independent description of the different knowledge components in a way which is understandable by humans.

5. Communication Model: The communication model represents the communicative transactions between the agents involved in the different tasks, it is also provided in an implementation-independent way.

6. Design Model: The previous models constitute the requirements and specifications of the knowledge system. The design model provides the technical system specifications based on the determined requirements. These technical specifications include the implementation platform, software modules, representational constructs, and computational mechanisms.

5.3 Why CommonKADS?

CommonKADS provides us the ability to deeply define all parts and actors of the business process, i.e. such a comprehensive solution we look for. The three context models describe the m-learning process related context: educational institution providing m-learning services, tasks carried out along the mentioned process, and agents who are responsible for carrying out these tasks. Concept modeling stage consolidates context knowledge and prepares for the development phase (artefact model) of m-learning pilot application. It is important to mention that it is not mandatory to construct all models included in CommonKADS model suite; this is an additional advantage of such methodology.

6. DISCUSSION AND RESEARCH STEPS

Our research started with deep literature review, it is important here to note that it is crucial to review the literature on regular basis to keep track with rapid evolutions in telecommunication technologies.

So far, the context modeling phase is complete. Concept modeling (knowledge and communication) takes place in the first half of 2012. Afterwards, a pilot application would be developed (design model), tested, and applied to a real distance learning course in autumn 2012. The applied pilot application will be evaluated through several methods such as:

1. Self monitoring. 2. Feedback from students through questionnaires and individual interviews. 3. Comparing students’ performance and their test results with such of the same course in class. A complete text and official PhD defense would be ready by the beginnings of 2013.

REFERENCES

[1] Schreiber, G. et al, 1999.Knowledge Engineering and Management: The CommonKADS Methodology. The MIT Press, Cambridge, Massachusetts, USA.

[2] Ryu, H., and Parsons, D, 2009. Innovative Mobile Learning: Techniques and Technology. Information Science Reference, Hershey, New York, USA.

[3] Laouris, Y. and Eteokleous, N., 2005. We need an educationally relevant definition of Mobile learning. Proceedings of the 4th World Conference on Mobile Learning, Cape Town, South Africa, pp. 290-294.

[4] Traxler, J., 2005. Defining Mobile learning, Proceedings of International Conference Mobile Learning IADIS ‘05, Qawra, Malta.

[5] Shudong, W. and Higgins, M., 2005. Limitations of Mobile Phone Learning, Proceedings of IEEE International Workshop on Wireless and Mobile Technologies in Education, Tokushima, Japan.

[6] Finkelstein, J., Wood, J., Cha, E., 2010. Introducing a Blackberry eLearning Platform for Interactive Hypertension Education, Second International Conference on Mobile, Hybrid, and On-Line Learning, Washington, DC, USA, pp. 77-81.


319

MOBILE WEB2.0 FOR WORKPLACE INFORMAL LEARNING: CASE STUDY IN CHINA

Gu Jia, Daniel Churchill and Mark King Faculty of Education

The University of Hong Kong

ABSTRACT

This study will investigate how mobile Web 2.0 technologies support employees in the process of informal learning during work-related engagements in foreign investment enterprises (FIEs) in china. A multiple-case study will be conducted, with five participants chosen from different FIEs. This new way of learning is believed to benefit both individual employees as well as corporations in developing learning organizations. The study also enriches the research literature on mobile learning and adult learning in the workplace.

KEYWORDS

Mobile Web 2.0, informal learning, workplace

1. PURPOSE OF THE STUDY

Being characterized as more flexible and self-regulated, informal learning takes up the majority of workplace learning (Cross, 2003), and is benefitting from the boom in information technologies. Nowadays employees often turn to the Internet to find information and solutions to problems they face in the workplace. Web 2.0 tools such a blogs, wikis, community bookmarking and social networking are creating opportunities not only for the rapid gathering of information, but also for learning. Emerging mobile technologies add a new dimension and multiple possibilities to these processes. However, their use in the context of the workplace has not been extensively explored and relevant recommendations are lacking, especially in the Chinese context. This study explores how Mobile Web 2.0 technologies assist employees in their work-related informal learning activities. Five cases are selected for an in-depth study of their practices and adoption of mobile Web 2.0 tools over a prolonged period of time.

2. INFORMAL LEARNING IN THE WORKPLACE

Formally taught skills are increasingly being found to be impractical in the modern workplace, as a result of growing competition and fast-paced industrial development. Having the capacity to improve on and adapt current knowledge in order to accomplish new tasks therefore becomes essential. Along with the universal trend in establishing a learning society, a learning organization and a learning community, organizations are encouraging their employees to learn at work and work to learn. Compared with the bureaucratic State-owned Enterprises in China, Foreign Investment Enterprises (FIEs) mostly adopt a business model which emphasizes the importance of continuous learning as a strategy for achieving goals and improving performance. The learning and improved knowledge of employees is thought to lead to higher work efficiency and continuous “personal mastery” (Senge, 1990). Learning in the organization is seen as key to maintaining competitiveness and dealing with the emergent demands of the marketplace.

Eraut (2004) has pointed out that the majority of learning that occurs in the workplace is informal, and involves a combination of learning from others and from personal experience. The term ‘informal learning’ is used to describe learning without formally organized content and learning that happens outside of formally organized settings (Sefton-Green, 2004). Some scholars have even narrowed the context of informal learning

ISBN: 978-972-8939-66-3 © 2012 IADIS

320

into the workplace (Dale and Bell, 1999, McGivney, 1999). Informal learning occurs in context of an employee’s attempt to deal with emerging problems in the workplace. Chatti, Jarke and Specht (2010) have emphasized that effective and efficient learning is supposed to be individualized, personalized and learner-controlled. Mobile and Web 2.0 technologies are creating new opportunities for people to conduct these kinds of learning activities.

3. MOBILE WEB 2.0 FOR LEARNING

Today’s mobile device mainly refers to fully compact handheld equipment (Keegan, 2004) with functions including high-speed wireless connectivity, multimedia access, webpage readability, GPS, and so on. Constructed as a place where people meet, read and write (O'Reilly, 2007), Web 2.0 is a new way of using the Internet as a platform for interactive information sharing and collaboration on the World Wide Web, and has been integrated into mobile devices recently. Mobile devices with high-speed internet access allow users to blog, chat, podcast, and social network whilst on the move, which has lead to the emergence of a new term---mobile Web 2.0 (Jaokar and Fish, 2006).

Numerous studies have investigated the applications and impact of mobile technologies in education. A review of three journals (Computers & Education, British Journal of Educational Technology, and Educational Technology Research and Development) published between 2004 and 2010 reveals limited numbers of publications identifying mobile learning projects. Frohberg, Göth and Schwabe’s (2009) overview of 102 mobile learning projects out of 1469 publications in several leading journals and conferences in the area is considered to be more systematic and informative. A total of 170 publications on mobile learning were mostly designed for young students and adolescents. Only 15 articles targeted adult learners beyond the formal classroom (see Table 1). In addition, few of these projects were carried out in the context of the workplace. Thus, exploring workplace learning using mobile technologies is required to fill the gap in the research area.

Table 1. Mobile learning projects published between 2004 and 2010

Journal Total articles

Mobile learning articles (total 170)

Mobile learning in workplace

Computers & Education 1303 53

15

British Journal of Educational Technology

590 13

Educational Technology Research and Development

286 2

Frohberg, Göth and Schwabe’s analysis (2009)

102

Web 2.0 technologies have gained increasing attention in the field of education as well. The frequently adopted applications thus far include blogs, wikis, podcasts, social networking and tagging, just to name a few. Basically, there are five general features of web 2.0 technologies: information sharing, communication, collaboration, social presence, and flexibility (Hsu, 2007). In fact, almost all web 2.0 services can be accessed via modern wireless mobile devices, which have resulted in some new enhanced features. Table 2 describes the educational uses of mobile devices and Web 2.0 technologies gained from existing literature, together with the generalized enhanced features of mobile Web 2.0 that could potentially be applied to learning.


321

Table 2. Educational uses of mobile devices

Educational uses of mobile devices Educational uses of Web

2.0 Patten, Sánchez, &

Tangney (2006) Churchill & Churchill

(2008) Song (2009) Hsu (2007)

a) Administration b) Referential c) Interactive applications d) Microworld e) Data collection f) Location awareness g) Collaboration

a) Multimedia access b) Connectivity tool c) Capture tool d) Representation tool h) Analytical tool

a) Resource access b) Communication c) Resource collection d) Scheduling e) Representation f) Construction g) Resource sharing h) Location-awareness i) Analytical tool e) Productivity

a) Information sharing b) Communication c) Collaboration d) Social presence e) Flexibility

Enhanced features of mobile Web 2.0 in education Anytime & anywhere resource access; Capture & recording; Connectivity; Collaboration; Analytical & administration tool; Location awareness; Customized mobile client

Back in 1970s, Knowles (1975) has described five steps involved in the process of self-directed learning: to diagnose their learning need, to formulate learning goal, to identify resources for learning, to select and carry out learning strategies, and to estimate learning outcomes. Knowles’ contribution has been valued highly in the area of informal learning as well. With the flexible and personalized mobile Web 2.0 technologies, learners in the workplace are able to set their own learning goals, and use their mobile devices to find resources, communicate, share their interests, as well as record their learning progress in a highly flexible informal learning environment. Workplace learners, mostly informal learners, also deserve attention from researchers in this area. This study will contribute to the field of informal learning with mobile Web 2.0 technologies, especially targeting adult learners in the workplace.

4. METHODOLOGY AND EXPECTED OUTCOMES

This study will be conducted with five participants to investigate how mobile Web 2.0 technologies support employees’ informal learning in the context of FIES in mainland China. A 6-month qualitative multiple-case study will be adopted, guided by a phenomenological research method. Qualitative research methods provide the framework for a holistic view of the phenomenon (Merriam, 1988). Case study is an empirical inquiry that investigates a contemporary phenomenon within its real-life context, while multiple-case study offers a deeper understanding of complex phenomena as well as strengthened validity and reliability (Yin, 2003). The long interview is the major approach to gather data on the research topic in the phenomenological investigation (Moustakas, 1994). At the beginning of the case studies, a semi-structured interview will be conducted to understand participants’ current informal learning situations during their daily work activities, as well as whether and how they use mobile Web 2.0 technologies as learning tools. After the first interview and preliminary data analysis, there will be a workshop to introduce participants to recommended mobile Web 2.0 technologies that could be used to support their learning in the workplace. In order to learn collaboratively, a microblog site will be set up as an online community for participants to share information and interact with each other. The next step is to let participants explore various Web 2.0 applications on their mobile devices to assist their work-related assignments. Participants will also be requested to upload a weekly reflection on the microblog site via audio recording. The instrument of data collection will include participants’ artifacts, i.e., mobile screen shots of a particular Web 2.0 application, retrospective communication (online discussions), microblog observations, and field notes. At the end of the study, a second semi-structured interview will be conducted to understand any change in each participant’s status and

ISBN: 978-972-8939-66-3 © 2012 IADIS

322

attitude towards mobile Web 2.0-supported workplace informal learning, as well as to develop recommendations for empirical practices and further research in the area.

The study is expected to inspire both employees and organizations in terms of workplace learning practices. First of all, employees in FIEs in China are able to take advantage of their own mobile devices to improve themselves in order to stay competitive. Further, organizations shall look into the value of such relatively new learning approaches to corporation performance. The proposed solution tends to help organizations develop a more vibrant corporate culture, which arguably leads to better performance and increased productivity. This is also in line with establishing a learning organization (Senge, 1990). In addition, this study will enrich both mobile leaning and adult learning. As previously mentioned, less attention is currently given to adult’s informal learning in the workplace with mobile and Web 2.0 technologies, compared with learning in formal classroom settings. The study fills this research gap by investigating employee’s adoption of mobile Web 2.0 technologies in a self-directed manner to solve problems in daily work-related assignments. Most workplace learning research to date has been carried out from the perspective of the corporation, rather than that of employees themselves. This study evaluates the individual employee’s needs for professional development and utilizes existing technologies to propose an informal way of workplace learning and knowledge sharing.

5. CONCLUSION

This article describes the preliminary stage of an ongoing study of mobile Web 2.0 supported workplace informal learning by reviewing current literature on educational uses of mobile and Web 2.0 technologies. The main study will be carried out in early 2012. Given that the focus is on evaluating each participant’s informal leaning activity, the researcher will not put too much control. However, some intervention will be required to guide the process.

REFERENCES

CHATTI, M. A., JARKE, M. & SPECHT, M. 2010. The 3P Learning Model. Educational Technology & Society, 13, 74-85.

CHURCHILL, D. & CHURCHILL, N. 2008. Educational affordances of PDAs: a study of a teacher's exploration of this technology. Computers & Education, 50, 1439-1450.

CROSS, J. 2003. Informal Learning-the other 80% [Online]. Internet Time Group. Available: http://www.internettime.com/Learning/The%20Other%2080%25.htm [Accessed].

DALE, M. & BELL, J. 1999. Informal learning in the workplace. DfEE Research Report London: Department for Education and Employment.

ERAUT, M. 2004. Informal learning in the workplace. Studies in Continuing Education, 26, 247-273. FROHBERG, D., G TH, C. & SCHWABE, G. 2009. Mobile Learning projects – a critical analysis of the state of the art.

Journal of Computer Assisted Learning, 25, 307-331. HSU, J. 2007. Innovative Technologies for education and Learning: education and Knowledge-oriented applications of

blogs, Wikis, podcasts, and more. International Journal of Information and Communication Technology Education, 3, 70-89.

JAOKAR, A. & FISH, T. 2006. Mobile Web 2.0: The innovator's guide to developing and marketing next generation wireless/mobile applications, futuretext.

KEEGAN, D. Year. Mobile learning: the next generation of learning. In: 18th AAOU conference, Quality education for all - New missions and challenges facing Open Universities, 2004 Shanghai TV University, China. 95-98.

KNOWLES, M. S. 1975. Self-Directed Learning. A guide for learners and teachers, Englewood Cliffs, Prentice Hall/Cambridge.

MCGIVNEY, V. 1999. Informal Learning in the Community: A Trigger for Change and Development. Leicester: NIACE.

MERRIAM, S. B. 1988. Case study research in education: A qualitative approach, San Francisco, Jossey-Bass. MOUSTAKAS, C. 1994. Phenomenological research methods, Newbury Park, CA, Sage.


323

O'REILLY, T. 2007. What is Web 2.0: Design patterns and business models for the next generation of software. Communications and Strategies, 65, 17.

PATTEN, B., ARNEDILLO S NCHEZ, I. & TANGNEY, B. 2006. Designing collaborative, constructionist and contextual applications for handheld devices. Computers & Education, 46, 294-308.

SEFTON-GREEN, J. 2004. Literature review in informal learning with technology outside school. Bristol: Futurelab. SENGE, P. M. 1990. The fifth discipline: the art and practice of the learning organization, New York,

Doubleday/Currency. SONG, Y. 2009. Educational uses of PDAs (Personal Digital Assistants): Undergraduate student experiences. PhD, The

University of Hong Kong. YIN, R. K. 2003. Applications of case study research, Sage Publications, Inc.

ISBN: 978-972-8939-66-3 © 2012 IADIS

324

A WIRELESS ARCHITECTURE FOR ASSISTIVE MOBILE LEARNING ENVIRONMENTS

Catherine Marinagi1 and Christos Skourlas2 1Department of Logistics, T.E.I. of Chalkis , GR-32200, Thiva, Greece

2Department of Informatics, T.E.I. of Athens, GR-12210, Athens, Greece

ABSTRACT

This paper presents a wireless distributed architecture for Personalized Educational Learning Environments – PELE used for supporting students with disabilities and learning difficulties and the collaboration of these environments. The architecture aims at enabling accessibility for Deaf (D) and Hard-of-Hearing (HH) students as well as dyslexic students. Devices that support mobile learning, such as Personal Digital Assistants (PDAs) are integrated in educational scenarios to support educational activities, such as giving lectures in the mainstream class, attending classes, or working in the laboratory, participating in assessments and participating in exams. We present and discuss how wireless networks, personalization techniques, and mobile learning form an attractive and helpful framework for supporting specific categories of students with disabilities and learning difficulties. Some utilization scenarios (use cases) are also given to demonstrate the various types of teaching and personalized services provided by the architecture.

KEYWORDS

Wireless learning system, personalized learning, assistive learning, mobile learning

1. INTRODUCTION

Students with disabilities and learning difficulties can be greatly benefited by appropriate Information and Communication Technological tools. Students with the cognitive disability of dyslexia, and Deaf and Hard-of-Hearing (D-HH) students constitute learning groups that we mainly concern in this paper.

Universal Design or “Design for All” aims at using products, services and systems by people of all ages and abilities. In learning, universal design mainly guides the development of flexible learning environments that accommodate individual learning differences. It can also be seen as an effort to provide instruction and learning strategies and also increase the awareness and the motivation of faculty to use these strategies in mainstreamed classes (Skourlas et al., 2009).

E-learning and mobile learning (mLearning) can be both considered important components of the blended learning paradigm, where face-to-face learning is combined with distance learning. E-learning tools include e-tutoring tools, self-evaluation tools and, also, lecture notes, instructions for study, multimedia lessons and other accompanying educational material. Chat, forum, voice and video conference are also used for distance communication between learners and instructors. MLearning can be seen not only as a component of distance learning realized at anywhere and anytime through mobile devices, but also as a mode of learning, which can be applied in classroom (Chen, G. et al, 2008), mainly, for students with disabilities.

Advances in mobile devices, such as smart phones, portables, WebPad, Tablet PCs or PDAs make them suitable for assistive environments. Mobile devices are appropriate for motor impaired students, since they are light and easy to handle. Visual impaired learners can use text to speech software. Deaf learners and dyslexic learners can take advantages of the rich visual content of mobile devices (Vinci and Cucchi, 2007). Case studies presented in (JISCTechDis, 2012), illustrate the different kind of benefits that disabled students have been experienced using mobile devices for learning. A lot of challenges though, emerge from any effort to integrate these devices in educational scenarios to support people with disabilities For example, wireless infrastructures in the educational context are characterized by rapid changes in their topology. Students and teachers move around the campus and various activities must be supported, e.g. giving lectures in the


325

mainstream class, attending in classes, working in the laboratory, participating in exams etc. (Skourlas et al., 2009).

Mobile devices have successfully been used for testing, without significant differences in the results obtained from web-based assessment (Romero et al., 2009). However, educational information is highly sensitive in the case of examinations and assessments using PDAs, enrolments, accessing grades, etc. Therefore we have to design our applications in order to demand less processing and network bandwidth resources, without though decreasing our privacy requirements (Skourlas et al., 2009; Vassis et al., 2009). Moreover the new networking paradigm that emerged with the appearance of wireless computing can boost the performance of systems in which they get applied (Belsis et al., 2008).

This work presents the architecture of a wireless distributed system for Personalized Educational Learning Environments – PELE for supporting students with disabilities and learning difficulties. In particular, the system design aims at enabling accessibility for Deaf (D) and Hard-of-Hearing (HH) students as well as dyslexic students. The proposed framework has been implemented for including D-HH and dyslexic students to mainstream class in Technological Educational Institute of Athens, Greece.

Previous work that has been reported includes a brief description of the architecture of Personalized Educational Learning Environments (PELE) and some experimental results from a first evaluation of the system (Marinagi et al., 2010, 2011). In particular, personalized self-assessment tests were offered to Deaf and Hard of Hearing (D-HH) students, to evaluate the understanding of educational material (Kaburlazos et al., 2008).

The remainder of the paper is organized as follows: Section 2 describes the requirements of a framework for a wireless PELE architecture and presents the usage of a PELE architecture. Some utilization scenarios) are given to demonstrate the types of services offered by the architecture. In Section 3, the evaluation of the PELE pilot implementation is presented. Finally, conclusions are given and future activities are discussed.

2. A PERSONALIZED LEARNING ENVIRONMENTS' ARCHITECTURE - UTILIZATION SCENARIOS AND TYPES OF SERVICES OFFERED

The main requirements for a wireless PELE architecture are the following: 1) Access control management For specific sensitive activities, e.g. examinations in the laboratory, administrative services, it is essential

to manage access rights and enforce access control based on roles; for flexibility and simplicity we have used the Role Based Access Control Model - RBAC. This is a standardised model which allows the assignment of permissions to resources according to the role that the user is granted to. For example, all students are granted similar permissions (Access specific resources).

Another issue is to prevent information disclosure; for this requirement, encryption is the solution. Due to the fact that the devices have limited capabilities, a shared key approach has been used (Skourlas et al., 2009); each device has a key installed, which will be used to communicate with the server, which identifies all the shared keys for the participating devices. This ensures a minimization of resource consuming since the battery lifetime and CPU usage are limited for mobile devices.

2) Distributed management It is not infrequent that a node looses connectivity while attempting to connect with the server; on the

other hand, nodes on the residing area may also be identified and act as a mediator in order the transmitted information to reach its destination. This can be done using advanced algorithms, which allow the nodes in the network to act collectively as a distributed server (Malatras et al., 2005). The idea behind that approach is the following: each device with its neighbouring devices, participate in the ad-hoc network; all together the devices act collectively as one server. Some nodes take a specific role to monitor the retaining of communication and act as leader nodes, or members of the Connected Dominating Set (CDS).

3) Integration of the IT infrastructures Finally, the proposed architecture must provide the integration of the IT infrastructures between learning

domains or units, as well as the improvement of the collaboration of the learning environment with other ones.

ISBN: 978-972-8939-66-3 © 2012 IADIS

326

In the following we shall present and discuss the types of services, offered by the architecture, using various system utilization scenarios (use cases). First, simple representative use cases will be given in order to clarify things and also outline specific technical requirements:

A deaf student within the mainstream class s/he attends or in her/his place wants to access some basic notes regarding the teacher’s presentation or a previous learning unit stored in the multimedia database e.g. a PowerPoint presentation and the related notes. The student sends a request from her/his PDA to retrieve the data from the database. Since the requested resource is not a critical one, only the permissions of the requester are evaluated against the local policy and no encryption is used.

In the case of examinations or assignments, when a request is sent to the server, in order to authorize or not the request, the server needs to identify the learner’s identity as well as to evaluate the permissions which have been granted to the learner for the specific activity. It requests a validation of the learner’s id. This can be done using public key encryption techniques.

The proposed architecture offers and supports various types of the services. An organizational scheme for supporting teaching and personalized services is depicted in Figure 1. It consists of a wireless network which spans along the campus, and in specific consists of different subnets which communicate.

Figure 1. Organizational scheme for supporting teaching and personalized services including the mainstream class, and

parallel, “assistive” classes, the personalization server, and the database server for multimedia information and educational material.

Figure 1 illustrates a scalable, distributed architecture which can support various learning environments and domains. The mainstream class in Figure 1, illustrates the use of the wireless infrastructure offered to students with disabilities and learning difficulties. Two categories of students are concerned here: dyslexic and D-HH students. Two important actors appear: teacher and teacher assistant. Multimedia presentations of the teacher are shown on the interactive whiteboard and everything written on it can be saved. Assistant does not know SL, but can have chat communication with D-HH students for question – answering, during the lecture. Another interesting actor that plays a complementary role is a hearing notes’ taker. S/he takes notes apart from the existence of the interactive whiteboard, which saves presentations and written text by the teacher.. The dyslexic and D-HH students use mobile devices, such as PDAs, WebPad, Tablet PCs or laptops.


327

The dyslexic students can adapt user interface to watch presentations on their device according to their needs. They have, both, the choice to access more information and multimedia material locally or accessing other servers out of the classroom. In the initial stage students fill forms with personal details, for the personalized access to the multimedia information and documents and for the adaptation of the interface according to their needs. Privacy of all these personal details is ensured. Α parallel, “assistive” class is also illustrated in Figure 1,. Here, the interpreter plays the key role, since

there are no teaching assistant and notes’ taker. Hearing volunteers and hearing students are included. All the presentation and the related discussion are recorded for future study. Therefore, teaching in this case is based on bilingual presentations. We have also done successful experiments to establish communication between the mainstream class and parallel classes, and communication between two parallel classes when there is only one interpreter. Therefore, the organizational scheme depicted in Figure 1 can support bilingual teaching, synchronous e-learning and m-learning, and communication.

Figure 1 also illustrates the establishment of a scalable environment including three servers (personalization server, communication server, and database server) and multimedia database of lessons, documents, bibliography. Therefore, the scheme offers the possibility of asynchronous distance learning and personalized access to distributed databases of educational documents and information. Teacher can use this possibility to add material: documents, assignments, small projects, examination’ tests, results, etc. Personalized services to students are supported through the personalized server and the whole scheme ensures the privacy of the personal details. Data related to the usage of the system (the personalized service) can be used to dynamically change user models (profiles).

3. EVALUATION OF THE PELE PILOT IMPLEMENTATION

Our pedagogical and teaching activities were part of a continuous twelve years program (1999-10) hosted at the Technological Educational Institute of Athens. During this period, fifty seven (57) D-HH students out of sixty nine (69) ones, from nineteen (19) different departments of the TEI of Athens, have used services, mainly translation in the SL, offered by the program.

More precisely our activities were related to a three years experiment (six semesters) in the Department of Informatics (Skourlas, 2010). In this framework, translation into SL was offered (more than 150 hours per semester for seven D-HH students) for various courses. Parallel classes were organized for specific courses: Databases I & II, Introduction to Programming (Pascal language), Programming (C language), Numerical Analysis and Introduction to Informatics.

In this framework, an expert with good knowledge of the SL, two teachers and three teaching assistants of the Department of Informatics, three students - volunteers, and seven D-HH students worked in special parallel classes three times per week and they participated in a weekly meeting. The seven D-HH students also attended lessons in the mainstream classes. It is worth mentioning that one of the teaching assistants is a Deaf graduate of the Department of Informatics. There is a new program funded in order to create a new integrated system for supporting D-HH active students, in the class, the laboratory, etc. To cover further needs, we organize the participation of volunteers, interpreters and notes’ takers, and the enrollment, in the same modules, of as many as possible D-HH students. Nineteen (19) Dyslexic people are also active students of the department of Informatics. Our aim is to support them through m-learning in the mainstream class, and offer them, on an asynchronous basis, teaching and study material through an interface adaptive to their needs.

Table 1 displays the seven D-HH students of the Department of Informatics and the courses offered. Each course includes theory and laboratory part. ‘T’ value in table 1, means that the student passed the theory part and ‘L’ value means that the student passed the laboratory part. The D-HH students that participate in the mainstream classes and the parallel classes are enrolled in different semesters. Greek SL is the first language for one student and the preferred language for other six students. Another D-HH student of the department has denied his participation in the parallel classes and in the weekly meetings organized by the expert.

ISBN: 978-972-8939-66-3 © 2012 IADIS

328

Table 1. D-HH students and courses offered in parallel classes. C: C programming, P: Pascal Programming, DB1: Database I, DB2: Database II, Num. Analysis: Numerical Analysis, Intro: Introduction to Informatics

D-HH Students C P DB1 DB2 Num. Anal. Intro First year enrollment J.Z. - T+L T+L T+L T+L L 2006 V-K.B. L T+L T+L T+L L L 2007 E.T. L T+L T+L T+L - L 2007 K.R. T+L T+L T+L T+L T+L T+L 2008 T.B. L T+L T+L - T+L L 2009 M.S. - - - - - - 2010 S.L - - - - - - 2010

Table 2 displays a comparative self assessment of D-HH and hearing students. In the first group 25 hearing students were included and in the second group seven D-HH students were included. For each group two experiments were conducted based on Adaptive Self-Evaluation (ASE) and Self-Evaluation (SE) (Kaburlasos, et al, 2008). The columns ASE and SE of the table display the average mark calculated for the two groups. The columns ASE-success and SE-success display the number of the students that were successful (mark greater than or equal to 5) for each group. The multiple-choice tests were the same for the students. Some oral explanations were given to the hearing students and the same explanations were translated in Sign Language. The group of the D-HH students was attended a preparatory lecture.

Table 2. Comparative evaluation based on the self-assessment of two student groups: Hearing students (group A) and D-HH students (group B). Course: Introduction to Informatics

Groups of Students ASE SE ASE - Success SE – Success Hearing 4.8/10 5.1/10 14/25 15/25 D-HH 4.4/10 4.7/10 5/7 5/7

We use assistive technology, and especially mobile learning, for the establishment of the communication between learner and teacher, and the involvement of the students in teaching and learning process, mainly, in the mainstream class. We also establish parallel “assistive” classes for students of special needs. At the same time, we organize and operate synchronous distance / face-to-face question-answering. Working Communication languages are written language; text is provided through adaptable interface for Dyslexic people and through SL for D-HH students.

A major problem encountered is that D-HH students miss important information during presentations because they must choose whether to watch the interpreter or the instructor or the projected screen (slide). To face this problem, we include the slides, instructions, videos in SL, etc, into the syllabi and arrange parallel, “assistive” classes and meetings so that the D-HH students can study before the presentation and afterwards. In this way, we can achieve the important goal of the inclusion of normal students in the parallel, “assistive” class which is dedicated to D-HH students.

4. CONCLUSIONS AND FUTURE WORK

In this paper we focused on the design of Personalized Educational Learning Environments (PELE), which enable students of Higher Education with disabilities and learning difficulties to attend mainstream classes. We concerned with the learners’ requirements mainly in the case of dyslexic, D-HH students. We presented a wireless distributed architecture for Personalized Educational Learning Environments and the collaboration of these environments. This includes a scheme of servers including wireless infrastructure, personalized, multimedia based and educational course material. The proposed architecture supports experimental services for dyslexic and D-HH students. Devices that support mLearning, such as Personal Digital Assistants (PDAs) are integrated in educational scenarios to support educational activities.

We have seen the importance of the multimedia educational material as a vehicle for increasing the interest, and helping the study of D-HH students, and, also, improving communication between students and teachers. Useful multimedia material includes aims and scope of courses, instructions for study, video recording of lectures, presentation and translation into SL (for D-HH) or use of text-to-speech, examples, visualization of critical concepts, etc.


329

We come to the general conclusion that wireless networks and PDAs form an attractive and helpful framework for supporting D-HH students. We also concluded that bilingual teaching in the mainstream class is possible but that it has its price.

Future research should focus on the further integration of the various components (servers, etc) and the establishment of services for Dyslexic and D-HH students of other departments. We intend to examine other user (learner) categories; we also intend to establish a framework not only for dyslexic people and persons with hearing disabilities, but also for people with other disabilities e.g. problems of vision. In addition we intend to perform a further analysis aimed at facilitating other groups with specific characteristics and needs e.g. working students, rejected students in specific courses.

In the future integrated system, we shall also try to specify and apply innovative features, focusing on: automatic adaptation of the document presentation when a change in the user profile takes place, analysis of text, taking into account the profile of the student and suggestions (based on the user’s profile and learners’ performance) for ‘further reading’ and / or exercises that will help the student.

ACKNOWLEDGEMENT

This research has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: Archimedes III Investing in knowledge society through the European Social Fund.

REFERENCES

Belsis, P. et al, 2008. Exploiting Distance Learning Methods and Multimedia-enhanced instructional content to support IT Curricula in Greek Technological Educational Institutes. Proceedings of the 6th International Networked Learning Conference (NLC08). Thessaloniki, Greece.

Chen, G. et al, 2008. Ubiquitous learning website: Scaffold learners by mobile devices with information-aware techniques. Computers & Education ,Vol. 50, Issue: 1, pp. 77-90.

JISC TechDis, 2008. GoMobile! Maximising the potential of mobile technologies for learners with disabilities, http://www.jisctechdis.ac.uk/assets/Documents/goingdigital/Go_Mobile.pdf

Kaburlasos, VG. et al, 2008. Personalized multi-student improvement based on Bayesian cybernetics. Computers & Education, Vol. 51, No. 4, pp. 1430-1449.

Malatras, A. et al, 2005. Secure and Distributed Knowledge Management in Pervasive Environments. IEEE International Conference on Pervasive Services: conference proceedings, ed V Kalogeraki, pp. 79-87.

Marinagi, C. et al, 2010. Α learning system for the adaptive evaluation of Deaf and Hard–of–Hearing students. Proceedings of the 5th International Scientific Conference eRA-5. Athens, Greece, pp. 540-545.

Marinagi, C. et al, 2011. Personalized self-assessment for Deaf and Hard–of–Hearing students. International Journal on Integrated Information Management. Vol. 01, Issue 01.

Romero C., et al, 2009. Using Mobile and Web-based Computerized Tests to Evaluate University Students, Computer Applications in Engineering Education Journal, vol. 9999, Published online in Wiley InterScience, 2009, DOI 10.1002/cae.20242.

Skourlas, C. et al, 2009. A Wireless Distributed Framework for Supporting Assistive Learning Environments. The workshop Assistive Healthcare & Educational Technologies for special target groups: conference proceedings. ACM Press, Corfu, Greece.

Skourlas, C., 2010. Inclusion of students with disabilities and learning difficulties at the Technological Educational Institute of Athens. The 7th International Conference on Higher Education & Disability, July 20-23, Innsbruck, Austria.

Vassis, D. et al, 2009. End to end secure communication in ad-hoc assistive medical environments using secure paths. 1st Workshop on Privacy and Security in Pervasive e-Health and Assistive Environments. Corfu, Greece.

Vinci M. L., and Cucchi, D., 2007. Possibilities of application of e-tools in education: mobile learning, Proc. Conf. on ICT for Language Learning, Florence, Italy.

ISBN: 978-972-8939-66-3 © 2012 IADIS

330

AN INTERACTIVE MOBILE LEARNING SYSTEM FOR ENHANCING LEARNING IN HIGHER EDUCATION

Olutayo Boyinbode1, Antoine Bagula1 and Dick Ng’ambi2

University of Cape Town, South Africa

1Department of Computer Science, University of Cape Town, South Africa

2Centre for Educational Technology, University of Cape Town, South Africa

ABSTRACT

Most higher education in South Africa adopt English language as a medium of instruction, which made it difficult for students who speak and write English as a second or third language to cope with the face-to-face lectures. Face-to-face lectures lack persistence and when students fail to understand the lectures during the once off face-to-face sessions, there is no opportunity to playback the lecture. Recording lectures with Opencast Matterhorn and making these available to these students as a supplementary resource to the face-to-face lecture has potential to alleviate this problem. Accessing the Video or Audio of opencast recorded lectures (ORL) on students’ mobile devices anywhere and at any time after face-to-face lecture could enhance student understanding of lectures and improve learning. This paper describes the architecture and design of an Interactive Opencast Mobile learning that enhances learning in higher education.

KEYWORDS

Opencast, Mobile learning, Mobile devices, Video, Audio, Face to Face Lecture

1. INTRODUCTION

With the tremendous growth and advancements in mobile and wireless technologies such as Smart Phones, iPads, Tablets, Wi-Fi, GPS, 3G; mobile learning has come into focus (Woukeu et al 2005). This proposed Interactive Opencast mobile learning has the potential of activating an educational shift from a formal, classroom-based and teacher-centred approach towards an informal, interactive and learner-centred approach where learning happens anywhere and at anytime.

We propose an Interactive Opencast Mobile Learning Framework (OMLF) where students of University of Cape Town (UCT), South Africa, that have difficulty coping with the face-to-face lectures can watch or download opencast recorded lectures (ORL) to their mobile devices while on campus where they have free access to Internet and learn while on the move. We have been able to develop a mobile application (figure 3) where students can view their recorded lectures on their mobile devices at anywhere and anytime. The short coming of this system is that students cannot post a comment on the ORL as they watch it, there is need to navigate to another page, which disrupts the interaction with the ORL. The ORL also cannot be downloaded.

In this proposed interactive mobile learning (figure 2), students can watch the video or listen to the audio of the ORL and also download it. The comments can be posted while watching the video. The strength of interaction in this system lies in the collaboration between students and students, students and lectures. The students post comments after watching the ORL; these comments help weak students to understand the lectures. This form of interaction is beneficial to students having limited access to the lecturer after the face-to-face lecture. The ability to see the comments of other students on the ORL in different official languages of South Africa i.e Afrikaans, Zulu, and Xhosa will also enhance student learning.

2. OPENCAST MATTERHORN

Opencast Matterhorn is a free, open-source, platform for supporting the management of educational audio and video content and has the affordance to improve the efficiency and production of recorded lectures than


331

traditional podcasting. Most institutions of higher education produce a huge number of lecture recordings which are stored in an archive; opencast allows access to this storage when needed. Podcast works with a variety of tools and programs to produce and distribute content while Opencast Matterhorn offers all the relevant functionalities as an integrated whole. This reduces the amount of manual work needed to shepherd media objects across various sub-systems, thus increasing productivity and reliability (Ketterl et al 2010). Opencast Matterhorn also provides the educational community with a rich media platform for educational research, both technological and pedagogical. Higher education students can be reached in more ways, through plugging into the right learning context (e.g. LMS), or access through mobile devices hence increasing interaction, universal access and improved discoverability.

Opencast Matterhorn aims to make lecture capture affordable for institutions whether an institution is just starting an academic podcasting program, or wanting to integrate with existing infrastructure for those institution who have already invested in a lecture recording program. Opencast Matterhorn includes the following features1 (Ketterl etal, 2010):

• Administrative tools: tools for scheduling automated recordings, manually uploading files, and managing metadata, captioning and processing functions

• Integration with recording devices in the classroom for managing automated capture • Processing and encoding service: services that prepare and package the media files according to

configurable specifications • Distribution: local streaming and download servers and configuration capability for distribution to

channels such as YouTube, iTunes or a campus course or content management system. The feed distribution channel provides an easy endpoint for integration with any third party system wanting to connect to Matterhorn. The implementation of the service is straight forward, copying the distribution media files to local download and/or streaming servers and creating an rss and/or atom feed out of the static metadata of the media package

• Rich media user interface for learners to engage with content, including slide preview, content-based search and captioning

3. MOBILE LEARNING

Mobile Learning (M-learning) also called nomadic learning has influenced and enhances the benefit of e-learning, accessing learning contents and making available personalized learning anywhere and anytime (Ketterl et al 2006).

Many definitions of M-learning exist in literature. Geddes (2004) defines mobile learning as ‘the acquisition of any knowledge and skill through using mobile technology, anywhere, anytime that results in an alteration in behavior’. Some other authors (Quinn, 2000; Keegan, 2002) place more emphasis on the mobile devices and the mobility of the user. These authors viewed m-learning as occurring in informal learning settings.

4. DESIGN OF AN INTERACTIVE MOBILE OPENCAST

There is need to capture and record lectures using Opencast for continuity and persistence outside the traditional classroom which lack persistency. Opencast Matterhorn provides a way of automatically capturing and recording lectures in higher education hence making lectures persistent. Pilots are currently being run at the Faculty of Health Sciences, University of Cape Town. Our view is that when students download (ORL) to their mobile devices, the pedagogical potential of Opencast Matterhorn would be realised as most students own mobile devices.

Apart from students having difficulties in face-to-face lectures due to language barrier, there is need for part-time students who are always on the move to have a mobile version of the Opencast; examples of such students are mothers having to wait in the doctor’s waiting room for hours and students working as salesmen

1www.opencastproject.org

ISBN: 978-972-8939-66-3 © 2012 IADIS

332

spending a lot of time driving from one customer to another either on train, bus or in their own car (Becking et al (2004)).

We have built an Opencast mobile application (figure3) which can be viewed on mobile devices by students. Students can watch and listen to the ORL on their mobile devices. For students that are shy to ask questions during the face-to-face lectures (Lee et al 2007), this mobile Opencast encourages participation and collaboration among students using blogs. The major short coming of this application is the inflexibility of the interactive mode. Students have to navigate to another page to post the comments after watching the ORL and cannot download the ORL. We are proposing an interactive opencast mobile learning, an improvement on this existing application. In this design (figure 2) the students can post their comments while watching the video in different languages. There is also a download option. Figure 1 describes the architecture of the interactive opencast mobile learning. In this architecture:

• Mobile devices provide interfacing to the application. • Host web site provides the fields to access data (ORL) for the application on the mobile device. • Administrator authorizes the upload and download of ORL from the host site.

Figure 1. Architecture of an Interactive Opencast Mobile Learning

Figure 2. Prototype design of the Interactive Mobile Opencast


333

Figure 3. A Mobile User interface to Opencast

5. CONCLUSION

This interactive Opencast Mobile learning seeks to enhance learning in higher education. In this work we have been able to improve on our existing mobile opencast application that supplements the face-to-face lectures. This application will run on different mobile devices of student and allow collaboration between students that are good and weak in understanding English language. Students will also have seamless access to recorded lectures anywhere and anytime on their mobile devices to watch at their convenience. This mobile application supplements the traditional face-to-face lecture and not substitutes it. The next phase of this work is to implement and evaluate this application at University of Cape Town (UCT), South Africa.

REFERENCES

Becking, D., Betermieux, S., Bomsdorf, B., Feldmann, B., Heuel, E., langer, P., Schlageter, G., (2004). Didactic profiling: supporting the mobile learner. In: World Conference on E-learning in Corporate, Government, Health and Higher Education. Association for the Advancement of Computers in Education, pp. 1760–1767.

Geddes, S. (2004). Mobile learning in the 21st century: benefit for learners, The Knowledge Tree: An e-Journal of Learning Innovation.

Keegan, D. (2002). The future of learning: from eLearning to mLearning (Hagan, FernUniversität). Ketterl, M.; Mertens, R.; Morisse, K. (2006). Vornberger,O. Studying with Mobile Devices: Workflow and Tools for

Automatic Content Distribution, ED-Media, World Conference on Educational Multimedia, Hypermedia & Telecommunications, Orlando, USA, 26-30 June 2006, pp. 2082-2088.

Ketterl, M., Schulte, O., Hochman (2010). “Opencast Matterhorn: A community-driven Open Source software project for producing, managing, and distributing academic video”, International Journal of Interactive Technology

Lee, M., Chan, A. (2007). Pervasive, lifestyle-integrated mobile learning for distance learners: An analysis and unexpected results from a podcasting study. Open Learning: The Journal of Open and Distance Learning, 22(3), pp. 201-218.

Quinn, C. (2000). mLearning: mobile, wireless, in-your-pocket learning. Woukeu, A., Millard, D., Tao, F., & Davis, H. (2005). Challenges for semantic grid-based mobile learning Proceedings

for the IEEE SITIS Conference.

ISBN: 978-972-8939-66-3 © 2012 IADIS

334

EXPLORING MOBILE AND CONTEXTUAL LEARNING WITH GGULIVRR

Hiram Bollaert and Philippe Possemiers Artesis University College Antwerp

Bouwmeestersstraat3, 2000 Antwerp, Belgium

ABSTRACT

Today’s society assumes its members to be skilled for the 21st century, to have an attitude of lifelong learning while it is constantly and ever faster changing. Optimizing the learning process of today’s society members, motivating these learners into active participation in education is the quest of the present learning communities (Scott, 2003). This project envisions the creation of mobile and contextual games based on a social constructivist view. The described concept demonstrates how all community members, no matter their culture, discipline, social group or age, can be engaged in the creative construction of learning material. The resulting serious games invite to interact with the learning context. The focus of the project lies on the creative implementation of technology to effectively facilitate and enable communication and collaboration. The aim of the concept is to induce a new social weave and to entice society members, through the use and creation of mobile games, into practicing and enhancing their 21st century skills.

KEYWORDS

Mobile gaming, contextual learning, social constructivism

1. INTRODUCTION

1.1 21st Century Skills

The new demands on today’s learning communities is to prepare learners for the 21st century, to provide them with skills regarding cross-cultural understanding, critical thinking, communication, self-direction, technology, teamwork and creativity. A learning community that is creative in the implementation and use of ICT in general, and Virtual Learning Communities (VLEs) in particular, is required to truly engage, activate and challenge learners, to assist, sustain and effectively facilitate education using limited resources (Bollaert, 2011).

1.2 Social Constructivism

Envisioning the evolution towards a learning community that engages every member to cohere and collaborate this project is based on a social constructivist view empowering learners to construct for others to learn. The challenge is to evoke and stimulate cross-cultural, cross-age and cross-disciplinary collaboration in creating and using attractive interactive learning objects, a costly and time-consuming task.

1.3 Mobile Technology

To facilitate the active participation of the learner who wants to combine this with his/her other five lives, the VLE and its content needs to be pervasive (Scott, 2003). The use of mobile technology implies the ubiquity of the VLE. With current cell phone market targeting faster multimedia mobiles and the price-drop of data transfer through mobile networks, also enriched and interactive learning content becomes available everywhere at all times.


335

1.4 Serious Gaming

Learning should imply fun. Therefore, this project includes serious gaming. Games induce engagement, involvement and fun whereas ‘serious’ indicates the informal learning through playing the game. The same informal learning process occurs when one collaborates in the creative process of building a new game.

1.5 Mixed Realities

Bringing the game in a contextual setting makes contextual learning possible. Through the use of intelligent tags, Radio Frequency Identification (RFID), Near Field Communication (NFC) or even two dimensional barcodes like Quick Response codes (QR), objects in the real world are linked with their virtual double. This mixed reality transforms rich learning content into a rich learning context (Benford, 2005). As indoor or outdoor locations become interactive environments, learning content is virtually layered upon these locations and accessible through a game. The visitor is challenged into a game, becoming immersed in an informal learning process, where contextual content is passed on to the player through interaction.

2. BODY OF PAPER

The search for a project format in which participants are enabled to work on their 21st century skills in a social constructivist setting, holistically combining the principles of serious gaming, contextual learning and mixed realities, resulted in project GGULIVRR, Generic Game for Ubiquitous Learning in Interacting Virtual and Real Realities (Bollaert, 2010).

2.1 Structure

The GGULIVRR software suite exist of three parts: the game-player, the game-cloud and the game-editor. The game-player is a cross-platform mobile client, handling the gaming, following the thread of the

game. The software translates the readings of the tags, communicates with the database, responds to input from the user and delivers multimedia content.

The game-cloud is a web-service controlling several underlying systems. The user management system deals with the user accounts and their profiles.The built-in scoring system keeps track of the gaming so users can review and compare their gaming results. A rating system promotes the best games and the best players to the top of the list. The content management system takes care of the multimedia game resources. The game-cloud also includes communication and collaboration tools like messaging and forums.

The game-editor incorporates a set of tools enabling non-technical skilled users to create, edit and author new games.

As GGULIVRR thrives on user generated content, the used software should be open-source empowering users to enhance and improve its functionality.

2.1.1 Generic Game

The game combines game rules with actions, identifications of tangible and tagged objects and virtual multimedia content. The generic structure of the game, using simple code (a mark-up language), enables non-technical skilled users to write new game stories with conditional rules. The infrastructure of the game editor and the scripting language should be extensible allowing more technically skilled users to add suitable functionality.

2.1.2 Interacting Virtual and Real Realities

The key feature of the game is to enable interaction between the user/player and objects in his/her proximity, indoors or outdoors through the use of intelligent tags. Reading the tag fixed on an object triggers the game-player, positions the user and generates a communication with the database. In response the user receives multimedia information about his context.

ISBN: 978-972-8939-66-3 © 2012 IADIS

336

Using tags is preferable to global positioning systems (GPS), as the positioning is accurate, immediate and realizable indoors or in bad climatological circumstances.

2.1.3 Ubiquitous Learning

As the acronym of the project indicates the goal is to persuade people into exploring new places and to get immersed in the context. The pervasiveness of the GGULIVRR game plunges the user in an informal learning process initiated through the challenge of the game. The context-aware environment provides the user with adaptive content, depending of the users actions and the game rules. The learning material is embedded in the game story.

2.2 Community

Although similar development projects can be found, this projects’ uniqueness lies in the engagement to induce interdisciplinary, inter-social and intercultural communication and collaboration.

Evidently there is the virtual community of users and builders who share and comment on game experiences and assemble in the development of new games.

GGULIVRR offers also a project format empowering local people to unlock contextual content with minimal technical threshold. To realize a new game this group of people is bound to connect with others for resources. Permission must be granted to install the intelligent tags, people willing to bring in their expertise must be found and learning content has to be aggregated and digitalized. Creating a new GGULIVRR game attracts and influences a larger community of people.

Developing and implementing technology in a creative way effectively facilitates and enables communication and collaboration. The aim of the concept is to induce a new social weave and to entice society members, through the use and creation of mobile games, to practice and enhance their 21st century skills.

2.3 Scenario

The following scenario illustrates the theoretical description of GGULIVRR in four parts. The first part tells a story of two people choosing a GGULIVRR game in a specific location. The second part sketches how the game was created. The third part briefly illustrates the rich context and the fourth part shows a specific function of the networked game-clouds.

“Noticing the GGULIVRR logo while I was passing by the Zoo of Berlin I decided to skip a few hours of conference presentations to check out which games I could play. The next day I touched the GGULIVRR logo at the entrance of the zoo with my smartphone and was immediately welcomed by the voice of Knut through my earplug. While a list of choices appeared on the screen of my device, Knut welcomes me and talks about the several GGULIVRR games available at the zoo. Knut concludes by proposing me to engage in “Saving the lions”, a game in which one must use clues hidden in the architectural and historical elements of the buildings of the zoo to help saving the animals. This game is based on the destructive events during the Second World War where amongst some other animals two lions were saved. This proposal results from my earlier playing a similar game ‘Ming’s legacy” at the Zoo of London. In this game one needs to persuade the twelve pandas (by giving them virtual tidbits) into explaining how Ming boosted propaganda during the Second World War”.

Only a year ago several students of very different disciplines worked together for the creation of this game. Also the touristic department of the zoo and some retired historians collaborated in creating, collecting and assembling the content for this game. As GGULIVRR is a generic system it took the students of applied informatics little time to figure out all the different ways to imbed interactivity into the game. They even created new functionality. Art students provided the images used in the game. They searched for old pictures of the zoo and its inhabitants, digitized them and made them more vivid. They also succeeded in getting some famous voices in front of the microphone. In this way several characters in this game, Knut and one cranky lion, received their voices. Languages students translates material into English and lower grade students worked together with the maintenance services to install the RFID tags all around the zoo.

GGULIVRR uses a mix of the real reality with a virtual one. During the game, players use their mobile devices to hear recordings, to watch pictures or movies and to interact. The mobile devices enable the user


337

through touching intelligent tags to experience virtual information. After touching the tag of an old house, the user can (for example) see how this building looked like 200 years ago and hear the voice of the architect.

As ratings on the GGULIVRR website show, “Saving the Lions” is clearly a popular game in Berlin. And there appears to be a competition with a game in the Zoo of Antwerp.

2.4 Technology

To implement a game system as proposed in this paper, we use several open-source techniques. Taking into account the fact that two operating systems (iOS and Android) dominate the mobile ecosystem and the fact that we want to minimize development time, we would like to propose a generic system to eliminate the need for designing two user interfaces. Also, to enhance the responsiveness and robustness of the game system we want to propose techniques to make sure that the absence of an internet connection does not hinder the game.

The game system consists of two components. A web-service and master database that contains all information for the game (user accounts, multimedia files, tag information, scores, rules, ...). And a mobile client and local database. This client replicates the master database information, presents the game UI and multimedia files and interprets the game rules.

For the first component and for the local client database, we have chosen Apache CouchDB (The Apache Software Foundation, 2011). This new database application is a noSQL (Wikipedia, 2012), scheme-less, document-oriented database that exposes all operations through a RESTful web-service (Wikipedia, 2012). The format of the records is JSON (Wikipedia, 2012). The database also has strong support for replication and last but not least can be run on iOS as well as Android.

By using CouchDB, we get following important advantages. Through the replication features, we can transparently sync the latest game information with the CouchDB instance on the mobile device. Once the information is synced, the game can be played without an internet connection since everything now resides in the database instance on the mobile device (Couchbase, 2012). All values posted by the user can be aggregated in a JSON document and replicated to the master database once an internet connection is available. Network latencies are eliminated since all information comes from the local database. And there is no need to write a separate web-service layer, since CouchDB has a built-in webservice API.

For the second component, we have developed a framework in iOS and Android that uses HTML as mark-up language for the user interface. In iOS there is a UI component called UIWebView, while Android has WebView. Both components act like a full-fledged browser with support for all mime types and even a built-in Javascript engine. This way, plain HTML can transparently function as the UI. In the database, the HTML snippets are stored inside JSON documents together with their attachments. These attachments can be anything a browser understands (pictures, sounds, movie clips, etc...).

The use of HTML has following advantages: - Interface design only has to be done once for all platforms. - The game designer does not have to know anything about special UI features on iOS or Android. - The game designer does not have to have special technical skills, UI development can be done in a

simple HTML editor. - Other platforms can be supported in the future. - Through the use of HTML forms, the application posts everything to the REST API of the local

CouchDB instance. This way, generic JSON documents can be generated with all the values that the user has filled in.

- Style sheets can change the look and feel and even the behavior of the UI quickly and efficiently. - The mobile client makes use of QR codes to steer actions. The name of the JSON document to process

at that location is stored in the QR code. When the client reads the code, the HTML and attachments are retrieved from the JSON document and

shown in the UI of the mobile device. We are using the open-source ZBar library (Sourceforge, 2012), available on iOS and Android for reading the QR codes.

ISBN: 978-972-8939-66-3 © 2012 IADIS

338

3. CONCLUSION

GGULIVRR is still a concept, although a proof of concept exists on iOS as well as Android. Due to all kind of factors development is evolving slow.

With the concept as seed, scenario thinking has generated several small challenges that have been studied by students and lecturers of different disciplines. The results, varying from infographics and websites, game design for contextual learning, to specific code for mobile platforms, have already inspired others to change curricula or to generate new applications.

As such the GGULIVRR concept gives us the opportunity to explore mobile and contextual learning, allowing us to advance the mission and vision of our educational programmes.

REFERENCES

Websites Couchbase, 2012, http://www.couchbase.com/products-and-services/mobile-couchbase Sourceforge, 2012, http://zbar.sourceforge.net/ The Apache Software Foundation, 2011, http://couchdb.apache.org/ Wikipedia, 2012, http://en.wikipedia.org/wiki/NoSQL Wikipedia, 2012, http://en.wikipedia.org/wiki/Representational_state_transfer Wikipedia, 2012, http://en.wikipedia.org/wiki/JSON Conference papers Benford, S., et al, 2005, Bridging the physical and digital in pervasive gaming, Communications of the ACM, vol. 48, no.

3, pp. 54–57 Bollaert, H, 2010, Holistic Embedding of Interaction Generating Learning Objects, Journal of Education, Informatics,

and Cybernetics, Available at http://www.journaleic.com/article/view/8050 Bollaert, H, et al, 2011 Fireflies on the campus:’I glow! Enlighten me!’, Online Educa Book of Abstracts, Berlin,

Germany, pp 180-181 Scott, G. (2003), Effective Change Management in Higher Education, EDUCAUSE, Available at

http://net.educause.edu/ir/library/pdf/ERM0363.pdf


339

Reflection Papers

MOBILE LEARNING AND ITS APPLICATION IN JAVA PROGRAMMING LANGUAGE COURSE

Jianhua Wang1 and Long Zhang2 1College of Computer Science and Information Engineering, Harbin Normal University

Harbin 150025, Heilongjiang, China 2School of Computer Science and Technology, Harbin Institute of Technology

Harbin 150001, Heilongjiang, China

ABSTRACT

With the fast development of mobile computing, Mobile Learning which makes anyone to learn in anytime and anywhere by any methods of learning, gains more attention and has been used widely. After studying the nature of Mobile Learning and its main application models, this paper combined with the current teaching in higher school, leads Mobile Learning to the teaching of a specialized course, Java Programming Language. Then a Short Message Service Based Mobile Learning System (SMS-Based MLS) is built, and the related curriculum content resources are well designed. At the end, the application models and practical results of Mobile Learning in Java Programming Language course is discussed.

KEYWORDS

Mobile Learning; Short Message Service; Curriculum Content Resources; Java Programming Language

1. INTRODUCTION

Statistics released by Ministry of Industry and Information Technology show that up to February 2009, China's mobile phone users reached 660 million, and more than 100 million mobile Internet users. This tells us that, with the development of mobile technology, mobile equipment price reduction and performance improvement, Mobile Learning based on the wireless communication technology already has a mature soil in China, and it has inestimable application potential and huge market in the field of education and training. Mobile Learning will be triggered at any moment, and gradually entered the mainstream view of public(X. Ni et al, 2009).

In a broad sense, Mobile Learning refers to the learning activity with the help of mobile devices. The mobile devices comprise a mobile phone, electronic dictionary, Mp3 player, pocket dictionary and so on. From the perspective of educational technology, Mobile Learning relies on the mature wireless mobile network, Internet, and multimedia technology, and helps students and teachers to achieve the interactive teaching activities and the exchange of information, in the fields of education, science and technology(G. Zhao et al, 2005). Mobile Learning allows anyone, at any time, any place to carry on the independent study, and thus contributes to the realization of life-long education and a learning society.

2. THE APPLICATION MODES OF MOBILE LEARNING

According to the development trends of Mobile Learning, the application of Mobile Learning is mainly divided into two categories: Online Mobile Learning Mode (OMLM) and Storage Based Mobile Learning Mode (SMLM). OMLM mainly relies on the mobile network, and freely access the Internet Education resources. The resource access is affected by mobile equipments and mobile communication network, and also restricted by mobile communication network and Internet communication protocol. The present mobile communication protocol mainly has two forms: one is for the short message; the other is the connected online (real-time communication). So OMLM can be divided into two patterns: short message based OMLM (SMOMLM) and connection based OMLM (COMLM). SMOMLM has low operation cost, generally


343

supported equipment and many other advantages, and mainly used in the learning activities and learning services that can communications with less data and simple text description. COMLM can direct accesses to teaching servers using mobile learning terminal, and then browses, queries and interacts with the learning resources. It mainly used in the learning activities with rich pictures, sounds, animations and other multimedia information materials. At present, domestic and foreign has launched the WAP, GPRS, 3G, wireless LAN and other connection based data services. It is worth mentioning that, 3G technology will make Mobile Learning unprecedented change in convenience and service quality, and ensure high quality teaching activities. SMLM stores e-book, multimedia courseware and other digital content in a portable or mobile device, and then learners can perform a learning activity whenever and wherever possible. SMLM is similar to the traditional sense of "mobile" in the process of learning. As can be seen, OMLM emphasizes real-time and interactive learning using wireless communication technology, and SMLM is a ubiquitous and practical learning ways.

From the above analysis we can see that, different forms of Mobile Learning have their characteristics. From the development perspective, OMLM will become the main direction of the development of distance education in the future (J. Walcott, 2001).

However, there are still many new problems concerning Mobile Learning in our country. Though the popularity of the new technology provides a wider scope for the development of Mobile Learning, yet there isn’t a practical and wide-used Mobile Learning System in existence because of many factors, including the variety of the mobile equipment and its functions, the limited capability, the small screen size, the low storage capacity, and the high cost of communication in China (J. Fu et al, 2009).

Short message service is the most popular means of mobile communication in china. It has many advantages, such as high capability of adaptation, easy operation, promptness and convenience, security, low cost, and separate sending. It is very fitful for the fragment learning in the mobile situations. So SMOMLM will be the best solution to Mobile Learning in China, which can be widely used.

Based on the detailed research on Mobile Learning and short message communication service, we designed the structure and function of a Short Message Service Based Mobile Learning System (SMS-based MLS) and then built it by means of Java. It consists of six main functional modules: Student spatial module, teacher spatial module, administrator spatial module, short message monitor module, short message intelligent processing module and short message sending module. The Student spatial module is an interactive interface between students and the system, and provides the students' role support. Teacher spatial module is an interactive interface between teachers and the system, and provides the teachers' role support. Administrator spatial module mainly completes the educational administration management and system maintenance work. Short message monitor module is used for monitoring whether a short information arrival. If any, it immediately notices the short message intelligent processing module for processing. Short message intelligent processing function module will distribute and process all kinds of short messages. Short message sending function module is used to send single or mass short message. The users of the system need only to interact with the first three modules, and the rest three modules provide the corresponding services for the first three modules and invoked by the first three modules. The six modules all deal with the backstage database to store, update and search data.

3. CURRICULUM CONTENT RESOURCES CONSTRUCTION

In order to lead Mobile Learning to the teaching of a specialized course, Java Programming Language, we need to distinguish, integrate and redone the existing curriculum content resources for Mobile Learning. According to different learning contents with different types of learning resources, to adapt them to different terminal, so as to use them more effectively applied to students in Mobile Learning to meet the diverse needs of the learners, and to provide convenience condition for learning activities.

The learning resources in the course of Java Programming Language are mainly divided into three categories: one is various teaching documentations, such as curriculum specification, syllabus, plan, experiment, test instructions and so on; two is various learning resources, such as PPT courseware, multimedia courseware, course recording, audio/video resources; three is various assistance information, such as essential knowledge of the chapters, expand learning materials, task library of curriculum design, case library of program design, library of examination questions.

ISBN: 978-972-8939-66-3 © 2012 IADIS

344

We can provide various mobile learning resources for learners through the following way, and then effectively carry out Mobile Learning:

(1) Relating to course message, real-time guidance information, stage submission deadline, examination arrangement information and other information, teachers can directly push the information to the learner's mobile phone through short message sending function in the teaching space module. This can facilitate learners to timely access to key information, prepared in advance, so as to avoid the delay of assignment submission, examinations and other important learning activity because of busy work and other reasons. Of course, learners can also query these information by sending a short message instruction.

(2) All kinds of learning resources of the course can be realized through a variety of Mobile Learning Mode. On one hand, we organize the teaching content according to the hierarchical mode of chapter-section- knowledge, and arrange learning objectives, key, difficulty, learning guidance, reference information for each chapter and each section, and briefly summarize the core content and the number of the test subject for each knowledge point. Learners can get these learning message whenever and wherever possible, review the important knowledge, and test the learning effect. On the other hand, we can provide the course documents, picture sequences (generated from the PPT courseware), audio/video recordings, suitable for a variety of mobile learning devices, and meeting the needs of learners with different learning needs and learning habit. For example, the learner can download these resources to a mobile terminal, such as mobile phone, electronic dictionaries, MP3 players and so on through our teaching website. When they are outside of the classroom, or waiting for a bus, it is available through the mobile terminal to browse these teaching documents, pictures, audio/video tutorial sequences and so on. They can enjoy the easy and convenient of Mobile Learning, and does not need to assume high mobile communication costs.

(3) It is the most important for Mobile Learning to communicate in real time. Using the SMS-Based MLS, the students in question, can get timely and effective help of the teacher and other students. It is obvious to improve the learners' learning enthusiasm.

4. EXPERIMENTS AND THE RESULTS

To study the effectiveness of Mobile Learning, we select one class from three classes in the same grade of the same specialty to develop the Mobile Learning through using the SMS-Based MLS and related mobile curriculum content resources. The experiment time lasts the whole semester. The final mean examination grades of three classes were 85.03 points, 76.26 points, 77.14 points, and it is obvious that the students in the class which developed Mobile Learning have a great improvement of learning quality and efficiency.

In addition, through the analysis of the three questionnaire surveys during the Mobile Learning, we got some valuable conclusions, expect to everyone in the future mobile learning practice to have the certain reference significance.

(1) Learners known very little about the Mobile Learning before the implementation, and about 96% of the learners is first heard the concept of "Mobile Learning", but they generally showed great interest to the kind of learning pattern, and very willing to participate it. But when asked whether using the mobile phone, Mp3 players, mobile device to download the learning materials, there are 65% learners that have used. Thus, most of the students have been naturally or half unconsciously the experience of Mobile Learning. While Mobile Learning are mostly foreign language courses, almost not the professional courses.

(2) In the whole process of Mobile Learning, the main way to study for learners is still to download the audio/video resources, image sequences, documents to mobile phone, Mp3 media player for learning, and the use of short message is very small percentage. The main reason is the resources, such as the audio/video resources, image sequences and so on, can access convenient, own abundant information, do not need to spend any communication costs. Therefore, audio, video, pictures, documents are the most important mobile learning resources. And Mobile Learning based on the short message, not only communication costs is high, but the information contained is not rich, thus is not frequently used by students.

(3) Learners gradually send/receive the short message for information access, as well as the exchange of information. Through the SMS-Based MLS, learners can study knowledge whenever and wherever possible, communicate and exchange with teachers or other students, and get teachers guidance and help. Learners are very willing to use the SMS-Based MLS.


345

(4) The effect of Mobile Learning is generally recognized, 96% learners think that Mobile Learning is a supplement of classroom teaching, 87% learners think that Mobile Learning can help them get better grades. Its reason mainly has the following several aspects: (a) learners using the Mobile Learning is very curious, the pursuit of the form more than the connotation, therefore, Mobile Learning better stimulates their learning enthusiasm. (b) learners can download from the Internet and enrich the learning content, can obtain the more knowledge outside the classroom. So, they can get a more profound understanding of course knowledge, and learning effect is better. (c) learners can use all the idle time, such as waiting cars, walking, with the need of learning whenever and wherever possible. This is simple and convenient, and many a little make a mickle. (d) learners basically can get the teacher very timely guidance, when they are in the extracurricular program design, or curriculum design. This is generally welcomed by the learners.

5. CONCLUSION

Mobile Learning, in even greater extent breakthrough of the restrictions in time and space, makes anyone to learn in anytime and anywhere by any methods of learning, and is the future of learning. International Distance Education Authority, the Irish education technology expert Desmond Keegan, believed that the success distance education technology, is not those are suitable for teaching characteristics, but those have achieved widespread popularity(D. Keegan, 2004). Thus, with the rapid development and universal application of wireless communications technology, Mobile Learning will have a wide application prospect, will certainly to the mainstream way of learning. At the same time, we are also hope that, more and more colleges and universities teachers can develop Mobile Learning in their teaching practice, and Mobile Learning can play a greater role in higher education reform.

ACKNOWLEDGEMENT

This study is supported by the science and technology project of the Education Department of Heilongjiang Province (11541093), and the advanced research project of Harbin Normal University (10XYG-07).

REFERENCES

D. Keegan, 2004. The future of learning: From eLearning to mLearning. http://learning.ericsson.net/mlearning2/project_one/index.html.

G. Zhao et al, 2005. Learning Resource Adaptation and Delivery Framework for Mobile Learning. Proc. of 35th Frontiers in Education Conference, pp. 19-22 .

J. Walcott, 2001. An investigation into the use of mobile computing devices as Tools for Supporting Learning and Workplace Activities. Proc. of the 5th Human Centered Technology Postgraduate Workshop, pp. 265-268.

J. Fu et al, 2009. The theoretical and practical study on mobile learning in the past decade. China Educational Technology, Vol. 7, pp 36-41 (In Chinese) .

R. Wang, 2006. Mobile learning system research. Master's degree thesis, East China Normal University, Shanghai (In Chinese).

X. Ni et al, 2009. The development trends of mobile learning. China Educational Technology, Vol. 7, pp 1-5 (In Chinese)

ISBN: 978-972-8939-66-3 © 2012 IADIS

346

MOBILE DEVICE TRENDS AND THEIR IMPLICATIONS FOR MOBILE LEARNING AT HIGHER EDUCATION

INSTITUTIONS

Dr. Daniel J. Guhr and Grace A. Gair The Illuminate Consulting Group

P.O. Box 262, San Carlos, CA 94070

ABSTRACT

The market for mobile devices is evolving quickly, bringing with it both new technologies as well as increased expectations for mobile device performance and content. For higher education institutions that want to enable learning on mobile devices, these changes in technology and expectations will have a significant impact on mLearning strategies. Drawing from current market data and forecasts, this paper provides an outlook on trends in the mobile device and applications market as well as perspectives on how the growth and changes of this market will impact higher education institutions.

KEYWORDS

Mobile Devices, Higher Education, Mobile Learning.

1. INTRODUCTION

The market for mobile devices – tablet computers, smart phones, e-Readers, etc. – is changing and growing rapidly, bringing with it new devices, new standards and new expectations about mobile capabilities. For higher education institutions that want to enable learning on mobile devices, these changes will continue to have a significant impact on these efforts.

Given the consumerization of mobile technology over the last decade, the generation of students now entering higher education possesses high expectations toward mobile device functionality and content. Combined with the rapidly changing mobile technology market, students’ high expectations present a significant challenge for institutions in creating and deploying content which has a broad reach but meets users’ conceptions of quality and performance.

This paper examines the current forecasts and trends in mobile devices, operating systems and applications in order to highlight the fragmentation and rapid dynamics of the market. The final section provides perspectives for higher education institutions which will, as the proliferation of mobile devices continues to increase across campuses, need to strategically address issues of mobility in order to meet the expectations of 21st century learners.

2. MOBILE DEVICE TRENDS

2.1 Tablet Market

While tablets are relatively new to the mobile market, they have quickly moved from a niche product into a mainstream consumer good. According to the technology forecaster Gartner, the global purchasing of tablets jumped from 17.6 million units in 2010 to a projected 64 million in 2011. This number is expected to reach 326 million units in 2015.

In terms of devices, Apple’s iPad has been and is projected to remain the leader in tablet sales through


347

2014, during which time it is anticipated to hold more than 50 percent of the market share. The decline in iOS market share over the next three years will be caused by the growth of Android as well as the entry of other competitors like Microsoft.

Forecasts in spring 2011, which put Android as a growing competitor for Apple in 2011, were revised in the fall with a less optimistic outlook – a 28% decrease from original projections. The adoption rate of Android tablets, for the time being, has been slower than expected, according to an analysis by Canaccord Genuity (Epstein, 2011). This trend will likely be subject to change as the Android OS runs on a large variety of tablets from different manufacturers.

While their market share is anticipated to remain low, with no individual competitor at more than 5 percent, other platforms have and are projected to enter the market. In fall 2011, Amazon released Kindle Fire and Sony released Tablet S, both which run on Android. Several companies including Samsung, HP, Dell, and Nokia are planning to release Windows 8 tablets during the latter half of 2012, which is slated to increase Microsoft’s OS market share significantly (Newman, 2011; Albanesius, 2011).

Given that the tablet market is still in its infancy, the certainty of market forecasts is somewhat unclear. HP’s Touch Pad, for example, was expected as a substantial market competitor but was discontinued about a month after its release. While there is a relatively significant amount of volatility in the market, forecasts by Gartner show, however, that it is highly likely iOS and Android will combine to dominate the tablet OS market over the next few years. Nevertheless, given the various diversity which will continue to exist in the market, education institutions will need to be prepared for a fragmented tablet OS landscape with at least four different platforms (iOS, Android, QNX, and Microsoft).

2.2 Smartphone Market

By 2015, the average selling price of all open OS devices (i.e. every OS with a published software development kit and application program kit) is predicted to be at USD 300 or less, establishing smartphones as the mainstream mobile phone (Wilcox, 2011). The relative affordability of smartphones will contribute to the growth of the global installed base of smartphones, projected to top one billion units by the end of 2012.

Android devices will, according to Gartner, continue to dominate the smartphone market and grow to a share of 49 percent by 2015, up from 23 percent in 2010. Google’s platform will be followed by Microsoft’s Windows Phone OS, which is forecasted to increase its market share from 5 percent in 2010 to 20 percent by 2015.

Apple’s iOS will account for 20 percent, and BlackBerry producer RIM’s market share will stand at 17 percent. Nokia’s Symbian platform is projected to drop from its 2010 market leader position with 38 percent to 0.1 percent in 2015 given Nokia’s decision in February 2011 to switch its OS to the Windows Phone 7. Therefore, similar to the tablet market, the smartphone OS landscape is predicted to remain fragmented with four dominant platforms (Android, Microsoft, iOS and RIM).

The Gartner forecasts might also underestimate Samsung’s OS Bada, which it includes in the category “other OS.” In Q3 2011, despite the success of the Samsung Galaxy which runs on Android, Samsung’s push of Bada Smartphones sold more than 2.5 million devices – in contrast to Window’s phone which sold 1.7 million devices during Q1-Q3 in 2011. If Samsung prioritized the production of Bada smartphones over Android devices, Bada might become a direct rival for the Windows Phone OS, despite the introduction of Nokia’s new Windows devices (Ahonen & Moore, 2011b).

2.3 e-Reader Market

According to the market researcher Juniper, e-Reader shipments are projected to reach 67 million by 2016 – nearly tripling the number for 2011 (25 million in total). According to the research firm IDC, Amazon led the e-Reader market in Q3 of 2011 with a 51.5 percent market share, with Barnes and Noble following at 21.2 percent. The e-Reader market is stratified into two segments: On the one hand, there are dedicated e-Readers, of which some are marketed by eBook vendors, such as Barnes & Noble, Amazon, or Google. On the other hand, eBooks are also read on high-performing Tablet PCs, notably with apps from Kindle, Barnes & Noble, Google, and Apple (iOS only). According to a 2011 Pew research study, 12 percent of the US population possesses an e-Reader and 8 percent a Tablet. Only 3 percent own both devices (Purcell, 2011).

ISBN: 978-972-8939-66-3 © 2012 IADIS

348

Over time, tablets and e-Readers are likely to converge into one device. Apart from weight and considerable price differences, the main advantage of dedicated (black and white) e-Readers over tablets is that the translucent e-ink display does not fatigue the user’s eyes and can be read in direct sunlight. Display technology that combines both color and e-ink is already in the industry’s development pipeline. Apple, for example, has secured a patent for a hybrid screen for its devices, which lets the user switch between the color (LCD or OLED) display and e-ink (Foresam, 2011).

2.4 Mobile Platform Standard Trends: Apps vs. Web

According to a US study by Flurry Analytics in June 2010, users were spending 21 more minutes a day browsing the mobile web than using applications. This behavioral pattern has changed with the increasing success of apps. In June 2011, users spent on average 74 minutes per day mobile browsing, and 81 minutes per day using applications (Toefl, 2011). Apps have become a major part of mobile user behavior which is reflected in the change in the number of apps downloaded per day from major stores like Apple – 18.4 million in Q3 2010 to 33.3 million in Q3 2011.

Despite apps’ success for individual users who are free to select from apps which are designed for their specific device, institutions that want to accommodate learners on their own devices face a number of issues. Programming, customizing and updating apps for multiple devices and OS according to the different screen-sizes, resolutions, orientation (landscape or portrait), color graphics and video/audio formats can be time consuming, costly, and subject to different security and reliability issues.

As a consequence, education institutions are increasingly shifting their attention from apps to browser-based platforms that can be accessed on any type of handheld device. New development platforms such as the UCLA Mobile Web Framework and the Kuali Foundation Mobility Enterprise are facilitating the development of mobile websites and allow for a decentralized and bottom-up development of mobile learning capacities (Keller, 2011).

One major problem for the development of mobile content on browser-based platforms has been the contentious issue of Adobe Flash for mobile, which has not been supported on iOS. In November 2011, however, Adobe announced that it would cease the development of its Flash mobile browser plug-in. It is anticipated that the new browser programming language HTML5 will begin to fill some of the gap left by Adobe Flash while helping to overcome some of the issues with OS fragmentation.

HTML5 supports non-proprietary audio and video standards, and allows for the creation of engaging, multimedia-rich content that can be fully integrated with mobile devices. One of the largest problems with moving to web-based platforms is users’ high expectations derived from experiences with native apps – those apps built for a specific platform. Key technologies like JavaScript and Node.js, however, are helping to enable a more natural look and feel like that of native apps.

The maturation of HTML5 over the next few years will push to establish the web as a viable cross-device alternative to apps, likely shifting current usage patterns. This means that education institutions will be able to provide mobile learning programs which do not require students to have a certain OS and mobile device as students will be able to directly access any learning content with their device of choice (mobile or non-mobile), without the need to pre-install apps.

3. OUTLOOK

As the above overview of trends and forecasts demonstrate, while the mobile device market continues to change and evolve, the overall shift towards mobile is clear. For higher education institutions, the growth of mobile technology and its rapid adoption in the consumer market is already impacting campus culture, and will only increase in the coming years. The following perspectives seek to highlight that enabling mLearning is a significant but crucial challenge for higher education institutions that want to provide a learning experience that meets the growing expectations of 21st century learners.

Mobile devices are, by definition, a significantly different user experience than traditional desktop and laptop computers. Thus learning on mobile devices is a significantly different user experience, particularly with regards to the amount of information that can be absorbed from the mobile device at any one time. The porting over of content from existing classroom- and desktop/laptop-based, materials to mobile can cause


349

significant alignment issues not only in terms of resolution and readability, but also in terms of the effectiveness of content transmission.

Secondly, although some convergence is expected, fragmentation – device, manufacturer, operating system, etc – will continue to be a key characteristic of the mobile market. Unfortunately, when it comes to institutional support for learning on mobile devices, there will likely not be a device or platform panacea. The fragmentation of both devices and operating systems will ultimately force higher education institutions to make certain choices about mobility: Institutions that choose to focus too narrowly on any one device or platform may miss opportunities to reach a broad audience, provide learners with the best possible mLearning experiences, or find themselves flat-footed when the market presents a new opportunity.

Despite these limitations, however, mobile devices present unparalleled learning opportunities through not only the capabilities they offer – mainstream features such as cameras, microphones, recording devices and up-and-coming technologies like Near Field Communication (NFC), Augmented Reality (AR), etc. – but also through their ability to tap into learning streams anywhere and anytime through Wi-Fi and data connectivity. As these capabilities continue to grow in both reach and scope, the possibilities for mLearning from both the institution and student will continue to broaden.

REFERENCES

Albanesius, C., 2011. Will HP revive the TouchPad? probably not, PC Magazine, [Online]. Available at: http://www.pcmag.com/article2/0,2817,2395459,00.asp.us [Accessed 16 November 2011].

Ahonen, T. & Moore, A., 2011a. Bloodbath update: smartphone market at end of June (before Q2 results). [Online] Communities Dominate Brands. Available at: http://communities-dominate.blogs.com/brands/2011/07/bloodbath-update-smartphone-market-at-end-of-june-before-the-q2-results.html [Accessed 31 July 2011].

Ahonen, T. & Moore, A., 2011b. Now what’s Microsoft’s play in mobile? Mostly missed opportunities. [Online] Communities Dominate Brands. Available at: http://communities-dominate.blogs.com/brands/2011/07/now-whats-microsofts-play-in-mobile-mostly-missed-opportunities.html [Accessed 31 July 2011].

Epstein, Z., 2011. Android users buy the iPad over Google-powered tablets. [Online] BGR. Available at http://www.bgr.com/2011/07/11/android-users-buy-the-ipad-over-google-powered-tablets/#utm_source=feedburner &utm_medium=twitter&utm_campaign=Feed%3A+TheBoyGeniusReport+%28BGR+|+Boy+Genius+Report%29&utm_content=Netvibes [Accessed 27 July 2011].

Foresam, C., 2011. Apple exploring hybrid e-ink/LCD display for iDevice, [Online] Ars Technica. Available at http://arstechnica.com/apple/news/2011/04/apple-exploring-hybrid-e-inklcd-display-for-idevices.ars [Accessed 27 July 2011].

Keller, J., 2011. As mobile devices multiply, some colleges turn away from building campus apps, The Chronicle of Higher Education, Available at: http://chronicle.com/article/As-Mobile-Devices-Multiply/128060 [Accessed 28 July 2011].

Levy-Even, Y., 2011. HTML5 – Opportunities for mobile devices, Learning Solutions Magazine, [Online] Available at: http://www.learningsolutionsmag.com/articles/681/html5--opportunities-for-mobile-devices [Accessed 30 July 2011].

Newman, J., 2011. Samsung Windows 8 tablet coming in second half of 2012, PC World, [Online] Available at: http://www.pcworld.com/article/243470/samsung_windows_8_tablet_coming_in_second_half_of_2012.htm [November 15 2011].

Purcell, K., 2011. E-reader Ownership doubles in six months. [Online] Pew Research. Available at: http://pewresearch.org/pubs/2039/e-reader-ownership-doubles-tablet-adoption-grows-more-slowly [Accessed 30 July 2011].

Tofel, K., 2011. Sorry HTML 5, mobile apps are used more than the web. [Online] Gigaom. Available at: http://gigaom.com/mobile/sorry-html-5-mobile-apps-are-used-more-than-the-web/?utm_source=twitter&utm_medium=twitterfeed [Accessed 31 July 2011].

Wilcox, J., 2011. You can't trust Gartner's smartphone OS forecast, or any other. [Online] BetaNews. Available at: www.betanews.com/joewilcox/article/You-cant-trust-Gartners-smartphone-OS-forecast-or-an-other/1302193051 [Accessed 28 July 2011].

ISBN: 978-972-8939-66-3 © 2012 IADIS

350

NEW ACCESS TO MOBILE TECHNOLOGY AS AN EMERGING LEARNING POTENTIAL

András Benedek and György Molnár Budapest University of Technology and Economics H-1117 Budapest, Magyar Tudósok Boulevard 2.

ABSTRACT

The paper deals with the application of brain-computer interfaces improving the learning potential of the increasingly complex tools of mobile communication. The application possibilities of this technology were tested primarily by an application developed for disabled people making possible the reception of mobile calls. The results can be presented by a mobile phone of Windows Mobil 6.5 operation system, capable of receiving phone calls by human EEG (Electroencephalography) brainwaves. The application can create new possibilities of learning. The target-oriented applications developed during the research activity were tested and measured. The experiments have proved that the new ICT tools not only expand human activity but also increase the individual learning potential for disabled people by providing new access to learning.

KEYWORDS

Access to learning, mobile communication, platform for mLearning, new learning potential

1. INTRODUCTION

The paper focuses on a technological aspect of mobile communication affecting the future of learning. This implies the provision of learning potentials for disabled people by extending the limits of learning. It was examined how mobile communication influences instruction (Nyíri K., Katz. J.) mainly focusing on the instructional- and learning development experiments of mLearning (Hug T., Pachler N.). The goal was to utilize the properties of the new generation of mobile communication tools for the extension of the possibilities of learning. Our technical approach implied focusing on the problem of learning-oriented application of brain control, that is, EEG-based human thought management. The application possibilities of this technology were investigated by a target-oriented application of our own development making it possible for disabled persons to answer mobile calls. The EEG signal is a complex periodic curve of several components, dominated by waves of relatively great amplitude, in the range of 8-12 in a quiet state. The goal of our research was to develop a communication platform suitable for control, accepting and rejecting mobile phone calls by monitoring human brain activity and investigating electric and magnetic signals of neural operation. Such an information technology platform can lead to the formation of a new social practice by creating new possibilities of learning.

2. BODY OF PAPER

2.1 Proceedings

It is necessary to point out Castells’ suggestion – as the starting point of our researches – significantly influencing our way of thinking after the millennium. Analyzing the relationships of informatics and social networks in his revolutionary work, Castells supposes that access to IT services will significantly improve parallel with the social status. Levinson’s book should also be mentioned with respect to the synthesis of social effects. It might be stated that the development is of similar scale as the quality improvement of


351

physical tool-related human mobility: at the turn of the millennium evolved human mobility based on new virtual momentums. Our research work is related to the complex research program of the Hungarian Academy of Sciences analyzing the social impacts of mobile communication. New tools are thought not only to broaden human activity by opening up the “space”, but also influence our acquisition, share and generation of knowledge. Providing the possibility of mobile communication on a daily basis for disadvantaged people is essential for the expansion of learning. Brain-computer interface (BCI) researches, developments focus on the improvement of impaired hearing, seeing, moving. The application of this technology were investigated primarily by means of using a test application receiving mobile calls especially developed for disabled people. The provision of disadvantaged people with mobile communication tools implies communication possibilities never experienced before.

2.2 Technical Background and Developments

Our developments are based on the principle that action and inhibitory activities form an EEG curve strengthening each other’s effect by means of the neurons. Since the condition of the formation of an EEG sign is the fact that numerous little electric changes strengthen each other. The electrodes necessary for the perception of the signals of the human brain are placed on the hairy skin of the scalp, these electrodes being of little resistance. The method of two different voltage leads are in most cases applied, the bipolar or the uni- or monopolar one. The voltage difference between neighboring points is measured in the first solution, while the difference from a so called nil point or reference point is measured in the second solution. The nil point electrode should be placed somewhere where the potential is not affected by any brain activity. Normally, the earlobes are used. The bipolar solution is generally used for clinical or diagnostic examinations. The application of the monopolar solution is more often used for research purposes. This solution provides a general picture of brain activity and this is more appropriate for research and testing. The greatest advantage of the monopolar solution is that the nil point makes it possible to compare the signals. However, it lacks an ideal nil point. The bipolar solution is more appropriate for local analysis, as neighboring areas can be compared. It was supposed that the noise occurring in the EEG signals can be estimated and decreased by means of using adaptive and non-adaptive filtering techniques. The frequency range of brain waves used in EEG is below 100 Hz (below 30 Hz in most applications). The disturbing signals occurring above this frequency range can be filtered by means of a simple filter permitting signals below the specific range to pass. When forming the test environment, it was vital to provide a good contact with the skin in order that the EEG signals could be measured appropriately. From this viewpoint the foreheads are optimal. EEG equipment is required capable of data transmission with a mobile phone. Naturally, wireless data transmission should be used. The regular wireless data transmission modes are first the Bluetooth, secondly the WIFI data connection for connecting external tools supported by mobile phones.

Magnetoencephalography and functional magnetic resonance imaging (fMRI) procedures were successfully applied in addition to EEG signal processing. BCI suitable for real time control can be realized on the base of blood flow characteristics by means of functional magnetic resonance imaging. The Computational Neuroscience Laboratory of the Kyoto-based Advanced Telecommunications Research Institute was able to reconstruct 10x10 pixel black and white pictures imagined by the test person by means of functional magnetic resonance imaging. The EEG system uses an ultra low consumption ASIC (Application Specific Integrated Circuit) circuit suitable for the measurement of EEG signals, characterized by common mode suppression (120dB) and a low noise level (60nV/sqrt(Hz). The Application Specific Integrated Circuit also contains low consumption ADC (Analog Digital Converter, 11 bites) and connections used for calibration and electrode resistance measurement, all these by consuming 200µW. The integrated EEG measurement system contains a law consumption microcontroller and a wireless transmission unit.

The reception of the data transmissed by the MindSet EEG headset on mobile phones can be realized after the procession of the EEG signals. The MindSet EEG headset is based on ThinkGear technology used in all NeuroSky products, which makes the perception of the wearer’s brain waves possible. It includes a sensor attached to the forehead and reference points located on the earphones / earlobes, as well as a built-in circuit to process the measured data. All the calculations / measurements of both the brain waves and the eSense evaluator (Attention and Meditation) are carried out by the ThinkGear chip. The EEG signals processed by the chip are sent to the Bluetooth unit in the MindSet EEG headset (see Figure 1) and are transformed into a serial communication protocol, to be received and processed by a Bluetooth adapter.

ISBN: 978-972-8939-66-3 © 2012 IADIS

352

Figure 1. The target environment of the development. Source: own figure

ESense is the patent algorithm of NeuroSky for the characterization of mental state. The unprocessed brain wave signals are amplified by means of the NeuroSky ThinkGear technology, then, the background noise and the electric noises caused by muscle movements are removed for the calculation of the eSense. ESense measurement is one mode of showing how effectively preoccupied the user is (similar to concentration). It can be stated that attention/concentration can be controlled through visual/imagined concentration. 144 evaluable measurements were performed, which is below the elemental minimum (164). So the reliability of the measurements is a bit lower than the planned significance level of 95% and the relative error of 10%. 7 men (58%) and 6 women (42%) were tested. 31% of the data come from young, 27% from middle-aged, and 42% of them from elder persons. The 46% of the tests were performed in the morning, and 54% in the afternoon. The accuracy and representativity is below the expected taking the number and the composition of the measurements into consideration, but sufficient. The results can be refined by further measurements.

The success rate of the tested activity among the above conditions was 0.72. The confidence interval of 95% is located in the range of 0.65-0.8. Not taking into account the data of 5% most differing from the average, the average success rate is 0.75. The series of measurements implied 10 tests. This way it was examined whether the repetition has any effect in the short run. Our preconception was that the success rate would decrease proportionately with the number of the measurements due to the test persons’ growing tiredness. This supposition proved to be false, as the 0.127 value of the correlation coefficient (0.128) of the number of the measurement and the successfulness shows.

Growing tiredness and getting more practiced are found to contradictorily affect the tests. The first ten tests seem to be ”relatively even”. These are confirmed by the tertiary trend curve. (See Figure 2)

Figure 2. The distribution of the success of measurements. Source: own figure

The research results can be presented on a mobile phone of Windows mobile 6.5 operation system, whose function in the research was to accept calls by means of EEG brain waves. This needed the following:

• Forming, measuring, processing EEG signals, and the mathematical background of processing EEG signals

• Brain computer interfaces, and Mobile EEG equipment


353

• MindSet EEG headset, controlling incoming calls on MindSet EEG headset-based mobile phones • Test, results By the described applications it is possible to realize human brain control by cheaper, more easily

available tools instead of the expensive and complex EEG Equipment. The accuracy of brain wave control can be improved by increasing the number of sensors, to be realized by means of using a several-sensor mobile EEG headset. The methods of EEG-based control needs further improving. By means of the qualitative measurements it was possible to show the operation of a mobile phone controlled by EEG waves, with 0.72 probability. The repetitions, distances, day parts, temperatures, gender and age do not influence the results.

2.3 Experiments and Results

When selecting the EEG tool, the main viewpoint was that it should be capable of wireless communication in accordance with the standard applied in the case of mobile phones, that is, it should be capable of regular Bluetooth or WIFI 802.11 transmission. Secondly, it should be capable of traditional telephone speakerphone headset functions by means of Bluetooth connection. As, mobile headsets parameters were also important, such as comfortable wearing, easy putting on, simple use, or the use of dry electrodes, the Mindset EEG headset manufactured by NeuroSky was selected. The EEG headset performed the transmission of both the measured „raw” and the processed data by means of the Bluetooth connection, which include attention/concentration figures as well to be used during mobile phone control. The MendSet-based communication needed a Bluetooth-able tool. The MindSet transmisses data processed by the ThinGear through a regular Bluetooth series port profile (SPP) in the form of a series data flow, coded in packages applied by the ThinkGear.

3. CONCLUSION

The new ICT applications can make access to learning easier. Our experiments have proved that the latest ICT tools increase individual learning potentials in addition to expanding human activity by providing new access to learning for disabled people. The main focus was the application possibilities of brain control, the learning-oriented application of EEG-based thought-management by using a test application developed for disabled people, which makes the reception of mobile calls possible. New possibilities of learning can be created for a significant population.

REFERENCES

Castells, Manuel (1998, second edition, 2000). End of Millennium, The Information Age: Economy, Society and Culture Vol. III. Cambridge, MA; Oxford, UK: Blackwell. ISBN 978-0631221395

Norbert Pachler, John Cook, Ben Bachmair, Appropriation of mobile Cultural resources for learning International Journal of Mobile and Blended Learning, 2(1), 1-21, January-March 2010

Mobile Understanding: The Epistemology of Ubiquitous Communication ed. by Kristóf Nyíri, Vienna: Passagen Verlag, 2006

György Molnár: Flashes or steady light? Or the potentials of developing networked learning, In: Miguel Baptista Nunes, Maggie McPherson (ed.): Proceedings of the IADIS International Conference e Learning, IADIS international conference E-learning 2011, Volume II. Rome, Italy, july 20-23, 2011, ISBN: 978-972-8939-38-0, pp. 405-408.

György Molnár - András Benedek: The empirical analysis of a web 2.0-based learning platform, In: Constantin Paleologu, Constandinos Mavromoustakis, Marius Minea (ed.): ICCGI 2011, The Sixth International Multi-Conference on Computing in the Global Information Technology, Luxembourg, June 19-24, 2011., ISBN: 978-1-61208-008-6, pp. 56-62.

ISBN: 978-972-8939-66-3 © 2012 IADIS

354

MOLEDIWO – MOBILE LEARNING SYSTEM FOR DISABLED PEOPLE AT WORKPLACE

Benjamin Tannert1, Saeed Zare2 and Michael Lund1 1TZI, University of Bremen

2International Education, University of Rostock

ABSTRACT

Usage of mobile technology is growing rapidly, and it affects other technologies by bringing in new innovation and approaches. Mobile learning can be seen as a bridge between higher level of abstracted knowledge and practical experiences, which supports the adaptation in a learning process. Our approach is a mobile learning application for people with cognitive impairments at their workplace to help them to learn and keep back in mind the work-steps they have to do. For these people it is important to learn at the place they have to work, as their ability to abstract something is very low or not existent. For their personal development it is important to become more and more autonomous in learning and working. This implies a specific support of their autonomous actions. Furthermore it is significant to keep the used speech in a low level to prevent overwhelming the users. There are hardly applications comparable for this target group in this area, thus we think that it is an interesting area of research in that we could develop new research results. The application will be useable on mobile devices so the users can interact with it at the places they need the information. It will try to adjust itself to the abilities and the mood of the user. This enables to support them by their autonomous actions. Results of this research will be developed by empirical studies in cooperation with a shelter workshop.

KEYWORDS

People with Cognitive Disabilities, Sheltered Workshop, Workplace, Inclusive Design, Adaptive Systems.

1. INTRODUCTION

The domain of learning context for people with cognitive impairments is a big challenge for digital media in education. We try to observe how these people can be assisted by a mobile learning application to learn and keep in mind the steps they have to do at the workplace. Through empirical studies we will work out in detail in what way mobile learning is more helpful for this target group then traditional ways.

People with cognitive impairments need a lot of help during their learning intervals. Due to their limited ability to abstract explained work-steps and recall of learned steps they need a personalized and adaptable way to learn new work-steps and to strength recall. Explanations have to be repeated many times until they will be able to memorize it. Also the illustrations have to be done adapted to their current cognitive status and with simple speech, so the users won’t be overloaded in learning. Because of the differences between people with cognitive disabilities explanations in many different levels are needed.

For this target group there are rarely comparable applications that are in use. There is also only a little number of researchers that are involved in new approaches for people with these special needs. Our approach is based on bringing direct specific support to their workplaces to fulfill their tasks. With the aid of the running application on mobile devices, the people will be able to learn new tasks directly more autonomous at the position where they need it. This solves the problem of the target group to abstract new work-steps and helps to bind the learning matter with the machine or the materials they have to interact with. Furthermore they will be able to recall work steps by getting personalized descriptions provided by the application. Because of users different abilities and learning behaviors, the software has to adjust itself for each user. For people with cognitive disabilities the emotional status direct the attention and enable them to be focused on the steps that should be performed or distract them. When they are distracted the danger of working accidents rises. In order to cover this problem, we will conceptualize a system that can detect the emotional status according the discrepancies towards personalized parameters of interactions.


355

In cooperation with a sheltered workshop for disabled people, we will enforce this research approach. By persist tests with the employees of this workshop during the developing process, we will gain a lot of feedback to adapt and improve our concepts and models. In addition, the supervisors of the workshop will support us with their special knowledge about the behavior, emotional constitution and abilities of people with special needs.

The contribution of this paper is to explore and discuss how mobile learning can be used for people with cognitive disabilities to foster their autonomy and enable them to run a more independent life. The application should be able to identify the mood of the user by using speech recognition also to adapt the level of the learning material to the actual mood. In this study we give a short overview about our research process. Afterwards we describe the implementation model and the developed application. Besides this, specifics in the realization and limitations can be emphasized which should have a high focus during the whole research process.

2. MOLEDIWO

2.1 Related Work

In a preliminary work for our actual approach, and from one side, we made a vast literature review on current systems based on digital media for this target group. From the other side, we developed “Intelligent Mobile Learning Interaction System (IMLIS)”, a personalized mobile learning system for people with mental abilities at school. We researched and analyzed the abilities to personalize the provided learning material for each user. Different workshops have been held for observing and estimating their abilities for using mobile devices. In this way we could get a better impression from their activities with mobile technology.

2.2 The System

People with cognitive impairments need special ways to learn new things and keep them in mind. Especially at their workplace, there is necessity that they can recall their working steps in mind to fulfill the work without become injured or to avoid inappropriate actions. For these people it is hard to learn new tasks because they are not able to abstract the work process and therefore a special explanation right at their machine or their workstation is needed. Another characteristic of this target group is their difficulty in staying focused. Often small things can distract them from their work-task. Also the ability to stay focused or other abilities differ, according to their emotional status and their health constitution. Some psychological research results for people with cognitive disabilities indicate a relation between the sound quality of voice and emotional status. Because of this our technology will respect this indication. Learning-Material must be provided in a specific representation for mentally disabled people, because of their cognitive impairments they often become overwhelmed, loose motivation or get distracted.

2.2.1 Implementation of the Approach

For this context, we developed a conceptual design based on several empirical studies run during the last two years. In cooperation with a sheltered workshop, and during workshops, we observed how people with cognitive impairments could handle with mobile technology and audiovisual instructions. The aim was to describe the steps and structuring methods that could support them for performing their work tasks. Combining the outcome of our observations with the characteristics given by experts from inclusive didactics and their supervisors we understood that complex actions has to be reduced and restructured. The information is split up into small actions that will build story units planed and organized from the advisors through interactive storyboards. The next important need for our target group is to give instruction embedded in the work task they do at present. Dependent to the personal profile the information is provided and represented in a fitting way. This information will be prepared and processed by the system in small steps as so-called learning nuggets.

The control of the application should focus on interactions based on simple speech. This will avoid the difficulties that the users may have with reading and writing. In this way, they can control the application by

ISBN: 978-972-8939-66-3 © 2012 IADIS

356

using their voice (either simple sound combination or short well defined words). They can swap between explanations by saying something like “next” or “previous” and get the corresponding illustrations. These explanations will be made available through a visual as well as an audio channel.

2.2.2 The System Architecture and Interaction Pattern

The architecture of the system consists of two main components. The first is the learning management system with all the stored learning material. The second is a client application running on several mobile devices. The planned technology for the mobile devices is smartphones. The learning management system is built by a database in core and several connected modular applications. The structure is predefined for extension by additional modules. With the registration a profile will be created. In this profile individual characteristics of each user with descriptions on behavioral patterns are stored. These patterns describe the individual variation of interactions and feedbacks for each registered user. The starting profile is created by the supervisors and during the use it gets updated according observed or traced reactions and behaviors of the user. In order to analyze this information, criteria’s had been implemented as rules in a decision engine. A second module provides a complex application for speech recognition with focus on sound variation of human voice. Here the differences in voice are analyzed in order to reveal current emotional status. For example dynamic, sound level and tone pitch are important to identify indicators for the current emotional status. But now the system has to tackle with specific problems. The problem that arrives with the voice is the specific, individual expression varied to individual ability of articulation. If one user has a loud voice the system should respect this. As a result of this predefined sentences have to be verbalized by the user in different dynamic and sound level during the registration. The most challenging part is the main module that carries the audio-visual tutorials. For the creation of these tutorials a specific sub application is needed. This application consists of intelligent storyboard templates. This storyboard templates guide the supervisor to implement a specific performed description of a work task in a simple and visual comprehensive logic. This implies three steps with three well defined clarifications. The first step is called “context”, the second “action” and the third “test of success”. In the first step a long shot describes the context and needed initial situation. Here orientation is provided. In the second step the action is shown in detail in a tempo according personal profile and emotional status. The third step presents how to test whether the action had been successful or not. All these instructions can be coupled with an audio comment. The implementation of our system is not finished yet and by further tests the model might be adapted.

2.2.3 Catch the Mood

A new approach in developing learning software is to integrate the identification of the actual mood of the user. The perception of this diagnose will allow the software to individualize and personalize the displayed learning material in relation to it. This will give a higher personalization, which is very important for people with special needs as their abilities fluctuate dependent by their situation. In traditional face-to-face learning, the personalization is always considered by the teachers in the background of the learning process. Thus the lack of personalization in digital media should be in some way compensating.

The recognition will be made by two feedbacks of the user. Firstly their interactions are traced and analyzed according a stored personal profile. Secondly the system is analyzing the spoken words of the user. By the pronunciation of their instruction, the application will be able to cognize how they feel during they use it, and how should the user be behaved for the next steps. For this we will implement sound patterns for different emotional status. With the first use of the system the supervisor has to run a specialized test to evaluate the individual patterns. With respect to the emotional status and the personal profile of each user, the application will be able to prepare the learning material for the user according to their current cognitive status.

2.2.4 Limitations

Although the speech recognition is in many areas really good and helpful, it is a new approach to extract the feeling and emotional conditions of somebody out of the spoken words and let this result flow into further action. The reliability and the correctness of this have to be evaluated during our research process. Furthermore it has to be tested in which scope disabled people are able to create parts of the learning material by their own.


357

From the other side, we clearly state that the mobile learning solutions or generally learning based on digital media cannot be replaced with face-to-face learning. They just can be an alternative for a face-to-face learning in the situations that the live instructor cannot participate in the learning process.

3. CONCLUSION

In this paper we presented a new approach to support people with cognitive impairments in learning at workplace based on mobile technology. We try to raise their autonomy and protect them from injuries by providing them the ability to check their next work-steps directly at their workplace. In workshops, we observe the target group in different views and cleared that they have not the skill to abstract things, as they need, as well as special learning material that guides them step by step through their work.

Mobile devices can enhance the motivation of learning and can be used as a catalyzer for improving their learning and work performance. The communicative functionalities and social self-determined mobile activities will be a challenge for our future work. As this approach is an ongoing research process, we cannot give some conclusive results yet. At the current state of our research, this will contribute to an ongoing discussion on computer-aided support for people with disabilities and on the discussion of personalized learning applications.

ACKNOWLEDGEMENT

We would like to thank the “Digital Media in Education” group at University of Bremen, especially Prof. Dr. Heidi Schelhowe for their valuable comments and advises. Also special thanks to research group “Computer Architecture” at University of Rostock for their support.

REFERENCES

Zare, Saeed.: Personalization in Mobile Learning for People with Special Needs. HCII2011. Universal Access in Human-Computer Interaction. Orlando, Florida, USA. (2011)

Zare, Saeed.: Intelligent Mobile Interaction: A Personalized Learning System for People with Mental Disabilities. “IMLIS”. Doctoral Thesis. Digital Media in Education Research Group. University of Bremen, Germany. (2010)

Krannich, Dennis., Zare, Saeed.: Concept and Design of a Mobile Learning Support System for Mentally Disabled People at Workplace. The International Conference on E-Learning in the Workplace - ICELW. ISBN: 978-0-615-29514-5. New York, USA. (2009)

J. Traxler, “Learning in a Mobile Age”, International Journal of Mobile and Blended Learning, Vol. 1, 2008. V. Suta, L. Suta, M. Vasile, “Study on the ICT Application in the Didactic Activity of Children with Mental Deficiency”,

ICT in Education: Reflections and Perspectives, Bucharest, June 14-16, 2007. H.J. Pitsch, “How does a trainer working with the mentally disabled differ from any other teacher or trainer? : Agora

XII. Training for mentally disabled people and their trainers. Permitting the mentally disabled a genuine and appropriate exercise of their rights.” Cedefop Hrsg.: Thessaloniki, 5-6 July 2001. pp. 127-140. Luxembourg : Office for Official Publications of the European Communities 2003.

ISBN: 978-972-8939-66-3 © 2012 IADIS

358

MAKING (MORE) PEDAGOGICAL SENSE OF TWITTER WITH A NEWLY DEVELOPED TRACKING DEVICE AND PRIORITISED DISCUSSION POINTS: THE STORY OF A

COLLABORATIVE TWITTER IMPROVEMENT PROJECT

Thomas Menkhoff1, Gabriel Yee Qi Ming2 and Magnus Lars Bengtsson3 1Practice Associate Professor of Organizational Behavior and Human Resources

Lee Kong Chian School of Business - Singapore Management University 50 Stamford Road #05-01, Singapore 178899

2School of Information Systems - Singapore Management University 80 Stamford Road, Singapore 178902

3Manager, Learning Systems and Technologies Integrated Information Technology Services - Singapore Management University

70 Stamford Rd. #05-22, Singapore 178901

ABSTRACT

In this paper, we share experiences made in developing a new Twitter application in the context of a Knowledge Management course taught at the Singapore Management University (SMU) aimed at enabling students to post and view pedagogically important tweets in an organized manner for easy (re-)use and participatory discussion. Additional application features developed by the team include an analysis tool which can help instructors to assess and grade the participation level of students. The project is both innovative and interesting for several reasons: (i) it showcases the pedagogical power of tweeting in the classroom; (ii) it successfully evolved as a collaborative project across two disciplines, namely between a School of Business management instructor, five students from the School of Information Systems (SIS) and SIS mentors and (iii) it helped to resolve actual tweeting challenges which occurred in class during tweeting experiments such as ‘getting lost in a sea of tweets’ or the lack of conversation tracking. Qualitative feedback from undergraduate students who took part in the tweeting activities and the progress of the application development project suggests that the use of twitter as a discussion platform during class has a positive impact on learning and that the newly developed twitter application is value added.

KEYWORDS

Twitter, higher education, collaborative Twitter application project, Singapore

1. INTRODUCTION

In this paper, we share experiences made in developing a Twitter application in the context of a Knowledge Management course at the Singapore Management University (SMU) aimed at enabling students to post and view tweets in an organized manner for easy (re-)use and participatory discussion. Twitter is an online social networking service and micro blogging service that enables its users to send and read text based posts of up to 140 characters, known as “tweets”. Twitter is widely used by netizens around the world, with over 300 million users as of 2011 generating over an average of 1 billion tweets per week and handling over 1.6 billion search queries per day. Twitter allows its users to post tweets via different devices such as laptops, desktop PCs or mobile phones. SMU instructors can make full use of the university’s hi-tech seminar rooms which are equipped with two screens: one to project slides, and the other to enable students to post tweets. Initially, the instructor was concerned that students would be distracted from following lesson contents because they were encouraged to text while in class. But we have learned through experience that such class chats enhance learning effectiveness and the depth of class discussions. In the following, we will discuss two research questions: 1. How can new educational technologies such as Twitter enrich the learning experience of Gen Y


359

students in institutions of higher learning? 2. What are the key challenges when it comes to implementing tweeting initiatives in the classroom and how can our new twitter application tackle them?

1.1 Method and Application Context

Methodologically this study is embedded in the tradition of interpretative case study and exploratory research (Eisenhardt 1989; Stebbins 2001) based on the analysis of relevant literature, discussions with course participants, colleagues and mobile learning experts as well as observations during students’ mobile learning activities. We develop several implicit evaluative arguments about the practice of twitter in higher education which will be useful in future, more quantitative and theory-driven research on using tweeting in the context of mobile learning (Cook et al. 2006; Lundin et al. 2010) based on explicit hypotheses.

The authors began experimenting with tweets in undergraduate courses on Knowledge Management in 2010. SMU’s students are quite familiar with social media tools such as wikis, blogs and podcasts. To tap into Twitter as a classroom tool, however, is still a novum at SMU. Being rather unfamiliar with Twitter himself, the instructor (Thomas Menkhoff) enlisted the support of a colleague from the university’s Integrated Information Technology Services (IITS) unit (Magnus L. Bengtsson) and a IT-savvy Teaching Assistant (Gabriel Yee Qi Ming) to help to create an account with Twitter and to kick start the tweeting activities in class. Students were encouraged to make use of their laptops and/or other hand-held devices such as mobile phones in class aimed at enriching class discussions through tweeting. Once students realized that their professor really wanted them to message during class time, they began contributing ideas and posting subject matter-related comments on the screen for all to see. Twitter helps students who are a bit shy and introvert to send (tweet) questions onto the screen which can then be answered by others. Trial runs in our classes have shown that using twitter as a discussion platform during class has a positive impact as this approach yielded a high(er) participation rate, especially among the less active students. Tweeting in class allows the instructor ‘to read students’ minds’ and to check whether they have successfully internalized concepts and are able to appreciate related practical applications in business or not. Sometimes students are bored. By looking at the tweets on screen, the instructor gets an idea about what is really going on in class. Trial runs in our classes have shown that using twitter as a discussion platform during class has a positive impact as this approach yielded a high(er) participation rate, especially among the less active students.

Students were rewarded for their pioneering and anonymous tweeting works with a certain percentage of their class participation grade. Whether graded or not, pilots conducted by the authors indicate that the use of social media can promote interaction among students and instructor as well as learning among peers. General observations made during students’ tweeting activities in class include:

• Gen Y students are quick in leveraging on the twitter platform. • Tweets are used to cheer presenting student groups on which is good for the overall motivational

climate in the classroom. • Evaluative tweet comments about other presenters and the subject matter covered by the instructor are

quickly forthcoming and very frank. • Tweeting allows absent students (e.g. due to sickness) to participate in class discussions and

commentary flows. • Students use twitter to raise new issues and content-related questions to be addressed in class. • Students use twitter to contribute valuable content-related knowledge to course and thereby enrich the

learning process. Still, there are some teething problems like the danger of ‘cognitive overload’ when the instructor is

simultaneously looking at the tweets stream on the screen in the classroom and listening to verbal contributions from class participants. Another challenge is tweetiquette as students are not always familiar with the guidelines for proper tweets such as the use of discretion, avoiding using profanity or the need to restraint from overutilising Twitter notes.

In a recent discussion with students about their twitter experiences, one student remarked: “I think that it is making the class distracting as people are busy tweeting and no one is listening to the presentation in some sense. Eventually some tweets are still chosen to be discussed in class, which makes tweeting a little redundant… The whole list of tweets becomes too long to be read …” The comment suggests that it is important to have “a system” in place which allows students to track tweet discussions easily (and without technical glitches) and which helps the class to rank order the numerous discussion points raised by students

ISBN: 978-972-8939-66-3 © 2012 IADIS

360

in order to focus on what is really meaningful. This insight prompted the development of a new Twitter application in collaboration with colleagues and 4th year students from SMU’s School of Information Systems (SIS). The latter regularly undertake such projects as part of their final year project assignments. In the following, we summarize the objectives, features and expected benefits of the application.

2. IMPROVING CLASSROOM TWEETING WITH A NEWLY DEVELOPED (TWITTER) APPLICATION: RATIONALE AND EXPECTED BENEFITS

While our tweeting pilots have produced overall positive results so far in terms of engagement and learning, using the Twitter website to discuss course topics while class is in session has one main drawback. As Twitter needs to handle high volume of requests and to store large volume of tweets, Twitter implemented a policy according to which it only displays tweets from the past one week. This means that on-going discussions on Twitter ‘disappear in cyberspace’ so to speak as tweets are being removed from the server. By tapping on Twitter’s popularity and service, we are in the process of developing an application to further enhance its effectiveness for teaching and learning purposes.

The objective of our new application is to develop a web site for mobile and computer web browsers that will provide students with an alternative avenue to participate in class discussions through the use of micro blogging. The idea is to enable them to login into a “forum” via their Twitter accounts so that they can post to twitter and view tweets in a more organized manner, participating in discussions through the use of the forum. Since tweets which are older than a week can no longer be searched, the forum has the added advantage (function) of archiving all tweets for easy viewing. Additional value added features include the provision of analytical tools to help educators to determine and grade students’ participation levels.

Figure 1. Screenshot of a Selected Application Feature Enabling Students to ‘Upgrade’ Popular Tweets into Discussion Points

Taking the limitations of twitter into consideration, the team created a portal where users have to register by entering their respective school email and the course that he/she wishes to register for. Once that has been done, the user receives an email with a link to access the twitter portal. Once the user gets into the login page,


361

he/she will be prompted to enter their Course ID and course section. The user will then be directed to the main page of the portal with its live feed, popular tweets and discussion points.

As far as the live feed is concerned, students are able to contribute and participate actively during class time with regards to the topic discussed at that point of time in the form of tweets or post URLs. They can also upload images if they wish. The tweets that are displayed in the live feed are based on a specific hashtag that the instructor has set to be used for that particular class discussion. Hence, the tweets can be external tweets as well. By using the same hashtag, a person outside the class can tweet, too, and his/her tweet would appear in the live feed as well. This enables a richer learning experience for students because external comments and discussion points can lead to a livelier and interesting internal debate.

For each tweet put up on the live chat, students are able to nominate it as a popular tweet (see Fig. 1) in order to bring attention to it. This feature prevents interesting tweets from getting lost in the live feed. If many students find this tweet interesting, they can vote for it (see Fig above). If the tweet hits a certain number of votes within a certain time frame, it gets posted to the discussion points (see Fig. 1) section where students can comment/reply to it and view it as a structured discussion thread. The reason for developing such as voting system (see Fig. 1) is to ensure that students discuss only those tweets that a significant number of learners find interesting or discussion worthy. This gives the educator an insight into the general interests of the class, allowing him/her to let the discussion revolve around significant topics.

Additional features for Instructors and TAs (Settings) The instructor and teaching assistant (TA) can be given additional rights to control settings timer and

display settings to optimize the in-class tweeting experience in line with their individual requirements. Setting options provided for instructor / TAs includes: 1. Customise Hashtag: Allows the instructor or TA to change the pre-generated hashtag to one that is

shorter or specific to the class.

2. Assign TA: Enables the instructor to assign a TA for the tweeting session.

3. Set Discussion Count: The purpose is to control the maximum number of discussion points which will be displayed to students. If the number of discussion points exceeds the respective limit, the less active discussion points will be removed from the display.

4. Set Voting Limit: Enables the user to control the minimum number of votes required for a ‘nominated tweet’ to become a discussion point.

5. Set Popular Vote Time Out: Allows teaching personnel to control the number of minutes a popular tweet has to gather enough votes to become a discussion point. If the nominated tweet does not receive the minimum number of votes, it reverts back to being a normal tweet.

6. Set Crawler Time: Helps to control the frequency at which the crawler will retrieve and then store tweets from Twitter.

7. Export Tweet Data: Enables the instructor or the TA to retrieve the data for the tweeting session in Microsoft Excel. The data can either be raw tweet data, lists of popular and nominated tweets, discussion points, or analysis results of the respective tweeting session.

The in-class discussion tool is scalable as it can be replicated in any course and section in the university.

3. CONCLUSIONS

Both face-to-face and online classroom discourses have been recognized as important to enhance the educational experience of students and their learning curve (Junco et al. 2011). While representative studies about the effectiveness of tweeting in higher education are still rare, we argue based on our own data and prior pedagogical research (Menkhoff et al. 2011) that such tools are useful in the context of mobile learning for the following reasons: (i) they supplement blended learning approaches and help students to create meaningful, contextual learning outcomes in relation to pedagogical objectives if they are used selectively and with relevant pedagogical objectives in mind; (ii) they enable students to engage in meaningful, collaborative learning and to tackle existing competency gaps either individually or in a team with the help of their peers; (iii) they motivate class participants to tweet any question they might have about the respective subject matter which can then be immediately addressed by the instructor and (iv) they support students’ engagement and assurance of learning as they appeal to Gen Y’s technological knowhow and learning culture.

ISBN: 978-972-8939-66-3 © 2012 IADIS

362

The new Twitter application project described above is instrumental is resolving the following problems with tweeting in class:

Lack of Automation Although an easily implementable feature, one of the more frustrating features of using Twitter.com is

that it does not enable the immediate display of new Tweets. External intervention by manually ‘refreshing’ that page is needed to simulate a continuous display of new Tweets. Our newly developed application addresses this issue by creating a true ‘live’ feed.

Lack of Conversation Tracking With Twitter in class still being a novelty, active discussions (when they get started) can result in large

numbers of tweets being generated within a short period of time. Losing good quality questions or inputs within the deluge of exchange is a fairly common occurrence as new tweets push the old tweets down the display list even before they get their fair share of airtime. The new application addresses this by having the ability to mark specific tweets as conversation starters / discussion points so that students can post directly to them. These conversation starters / discussion points will be separated from the main live feed to increase prominence and can be generated either via automatic responses by students (via a pre-set value for re-tweets or replies) or manual inclusion by instructors or teaching assistants.

Lack of User Statistics One of the toughest tasks during our Twitter experiments was to sift through the tweets that were posted

and to identify students who contributed meaningfully or started good discussions. Previously, tweets had to be captured (within 24-48 hours before they were automatically deleted by Twitter) and painstakingly analyzed tweet-by-tweet. Our Twitter application will reduce that through collaboration with SMU’s Living Analytics Research Centre at the School of Information Systems (SIS) aimed at analyzing Twitter feeds to produce user statistics that can help to identify contribution rates and to ascertain the influence over other Tweets within the same feed.

While there might be some initial resistance amongst students or instructors in utilizing our newly developed portal application, we strongly believe that once users are familiar with the new application and its features that it will prove to be a very useful tool in engaging (tweeting) students in class discussions and beyond.

REFERENCES

Arnold, N. & Paulus, T. (2010). “Using a Social Networking Site for Experiential Learning: Appropriating, Lurking, Modelling and Community Building.” Internet and Higher Education, 13(4), 188-196.

Ebner, M., Lienhardt, C., Rohs, M. and Meyer, I. (2010). “Microblogs in Higher Education – A Chance to Facilitate Informal and Process-oriented Learning?”, Computers & Education, 55(1), 92-100.

Eisenhardt, K.M. (1989). Building Theories from Case Study Research. Academy of Management Review, 14, 532-550. Junco, R., Heiberger, G. & Loken, E. (2011). “The Effect of Twitter on College Student Engagement and Grades”.

Journal of Computer Assisted Learning, 27, 119-132. Klein, H. K. & Myers, M. D. (1999). A Set of Principles for Conducting and Evaluating Interpretive Field Studies in

Information Systems. MIS Quarterly, 23: 67-94. McCarthy, J. (2010). “Blended Learning Environments: Using Social Networking Sites to Enhance the First Year

Experience.” Australasian Journal of Educational Technology, 26(6), 729-740. Menkhoff, T., Thang, T.Y., Chay, Y.W. and Wong, Y.K. (2011). “Using Web-Based ICT in Learning: A Case Study of a

Knowledge Management Programme”, The Journal of Information and Knowledge Management Systems, Vol. 41, No. 2, pp. 132-151.

Miles, M. B. & Huberman, M. A. (1994). Qualitative Data Analysis (2nd edition). Beverly Hills, CA: Sage. Naaman, M., Becker, H. & Gravano, L. (2011). “Hip and Trendy: Characterizing Emerging Trends on Twitter”. Journal

of the American Society for Information Science and Technology, 62(5), 902-918. Saeed, N., Yun, N. & Sinnappan, S. (2009). “Emerging Web Technologies in Higher Education: A Case of Incorporating

Blogs, Podcasts and Social Bookmarks in a Web Programming Course based on Students’ Learning Styles and Technology Preferences.” Journal of Educational Technology & Society, 12(4), 98-109.

Stake, R. (1995). The Art of Case Research. Newbury Park, CA: Sage. Stebbins, R. (2001). Exploratory Research in the Social Sciences. Thousand Oaks: Sage Publications. Wankel, C. (2009). “Management Education Using Social Media.” Organization Management Journal, 6(4), 251-262.


363

Posters

A PROPOSAL FOR USING VIRTUALIZATION TECHNOLOGY IN MOBILE LEARNING

Carlos Oliveira Instituto Federal de Educação, Ciência e Tecnologia (IFRJ)

Rio de Janeiro, Brazil

ABSTRACT

Every year many students need to stay out of classes, for days or even weeks. Most of them, due to unexpected situations such as illness or pregnancy. In this paper we present a proposal that aims to provide a way to keep in touch teachers and students that are temporarily out of classes. This proposal consists in the use of the virtualization technology to create an environment in which teachers can deliver the content presented in class to the absent student. To achieve this goal, it is used a virtual machine, termed “virtual desktop” in this work, that contains an operating system, the material presented in class and the applications the student needs to perform tasks proposed by teachers.

KEYWORDS

Virtualization; Virtual desktop.

1. INTRODUCTION

In this paper we present a proposal that aims to provide a way to keep in touch teachers and students that are temporarily out of classes. This proposal consists in the use of the virtualization technology to create an environment in which teachers can deliver the content presented in class to the absent student. Virtualization is an area that has been in existence since 1960s and has achieved renewed interest from the research community in the last years. Virtualization technologies provide several important features that make it a very powerful tool to be used across a wide range of applications, including mobile computing [Susanta Nanda and Tzi-cker Chiueh, 2005]. In a non-virtualized system, one instance of the operating system supports one or more application programs. In a virtualized environment, a single physical computer runs software that abstracts the physical computer’s resources so that they may be shared between multiple “virtual machines”.

Each virtual machine may be running a different operating system from all of the other virtual machines on the physical machine. A crash or other program error on any of the virtual machines leaves all of the other virtual machines unaffected. Our goal is to use a virtual machine, termed “virtual desktop” in this work, that contains an operating system, files containing the material presented in class, and the applications the student needs to perform tasks proposed by teachers. This virtual desktop is remotely accessed by the student that uses it to learn the content presented in classes and to perform tasks proposed by teachers. Teachers also access the virtual desktop to deliver content to the student and to evaluate the tasks performed by the student.

2. BACKGROUND AND PROPOSAL

Virtualization technology has achieved renewed interest in the last years. Several Virtual Machine Monitors (VMMs), also known as hypervisors, like VirtualBox [Oracle, 2011] and VMware [Edward L. Haletky, 2008] have been developed to support server virtualization. They act as a layer between the virtual machine and the actual hardware. Each virtual machine (VM) is subject to management operations such as creation, deletion, and migration between physical machines, as well as run-time resource allocation.


367

In this context, a Virtual Desktop is a VM containing an operating system and applications like it would be in a non-virtualized desktop. However, the virtualized desktop is stored on a remote server rather than locally. Thus, when users work from their local machine, all of the applications, processes, and data used are kept on the remote server. This allows users to run operating system and execute applications from PCs, laptops, netbooks, tablets, smartphones and even dumb “thin clients” which exceed the user hardware's ability to run. The client device may use an entirely different hardware architecture from that used by the projected desktop environment, and may also be based upon an entirely different operating system.

Our proposal is a virtualized environment, presented in Figure 1, to support Virtual Desktops. In this environment, each student has a virtual desktop that is updated by teachers with course material and tasks to be executed by the student. The virtual desktop also contains the applications the student needs to execute the tasks after study the material course. At the moment the student is absent, he uses a remote client device to access the virtual desktop. Thus, the client device only displays the virtual desktop. All modifications take place in the virtual desktop, allowing teachers to periodically access the virtual desktop to manage student’s studies. In this environment, each student has a virtual desktop. Our idea is to implement a website in which the student logs in, using a student ID and password, when he wants to access the virtual desktop. The website then starts the student’s virtual desktop and retrieves the IP address the student will use to access his virtual desktop. Teachers have privileges to access all students’ virtual desktops.

It is assumed a constant network or Internet connection to the server where the virtual desktop is running. This might not be a problem since most users have fast Internet connections. If the Internet connection is a problem, would be interest to provide a Client-hosted model in which the virtual desktop runs in the local system, reducing the network bandwidth consumption. There are other modes to access a virtual desktop e.g., by using Remote Synchronization. In this mode, the virtual desktop is copied to a local system, where it may run without requiring a network connection. A disadvantage is that the local system needs to run a hypervisor. Thus, we prefer the model in which the virtual desktop remotely accessed by the student, requiring no modifications to the local system, facilitating the use of the virtual desktop.

3. RELATED WORK

Moodle [Moodle, 2011] is an open source software that aims to help educators to create virtual learning environments. Many institutions use it as a platform to conduct fully online courses, while some use it simply to augment face-to-face courses. Moodle also provides activity modules (such as forums, databases and wikis) and allows users (teachers and students) to send messages to each other.

Aiming to allow the access to applications used by students and their professors, authors in [Cameron Seay and Gary Tucker, 2010] use software images installed onto blade servers. They use virtualization technology as a key component of the way applications are deployed and used. Thus, users access the applications remotely not on their local computers, allowing them to use the software they need when they need it.

Authors in [Michael Kozuch and Mahadev Satyanarayanan, 2002] use virtual machine technology and distributed file system to permit users to access anytime/anywhere a virtual machine, containing an operating system and user applications, by using different physical machines. To allow this mobile computing, their work require from the user to install a client and a server software to allow the file system to be mapped between server and clients. The main differ of our proposal is that the virtual desktop runs in a server and is accessed remotely, avoiding any installation on the user’s physical machine.

In response to the growing number of teachers using Skype to help their students learn, it was created Skype in the classroom [Skype, 2011]. Skype in the classroom brings a community of people and information in which teachers can browse through a members-only directory to find teachers who can offer them help, or whom they might be able to help. Once teachers find someone they’d like to connect with, they can add that person as a Skype contact. Several teachers are also using Skype videoconferencing for teaching, like presented in [The Chronicle of higher education, 2011]. For these teachers, the virtual desktop would help giving a support for delivering to the student the tools he needs to perform proposed tasks.

ISBN: 978-972-8939-66-3 © 2012 IADIS

368

Figure 1. Relationship among Teachers, Students and Virtual Desktop


It was presented in this work a proposal that aims to take advantage of the virtual machine technology to provide an environment targeted to permit students that are temporarily out of school to keep in touch with teachers. Our goal is not to provide an environment for online courses or substitute the student-teacher interaction. Our goal is to provide a way to keep the absent student in touch with teachers, since the student has an Internet connection to access the virtual desktop. We plan to use cloud computing technology to implement a solution that allow users to access virtual desktops, allocating them (i.e., starting and shutting down) on demand. Thus, we are currently evaluating Eucalyptus [Eucalyptus Systems, 2011] to help the implementation of the proposed system. In a next step, after the implementation, we are going to carry out experiments in the system, that is, we are going to provide virtual desktops to students who are out of school because of illness or pregnancy.

REFERENCES

Moodle, 2011. Welcome to the Moodle community!. http://moodle.org/ Cameron Seay and Gary Tucker, 2010. Virtual computing initiative at a small public university. Communications of the

ACM, Vol. 53, No. 3, pp. 75-83. Michael Kozuch and Mahadev Satyanarayanan, 2002. Internet Suspend/Resume. Proceedings of the Fourth IEEE

Workshop on Mobile Computing Systems and Applications. Washington, DC, USA, pp. 40--. Eucalyptus Systems, 2011. Eucalyptus Open Source. http://www.eucalyptus.com/ Susanta Nanda and Tzi-cker Chiueh, 2005. A Survey on Virtualization Technologies. Technical Report.

http://www.ecsl.cs.sunysb.edu/tr/TR179.pdf Skype, 2011. Skype in the classroom. http://education.skype.com/ The Chronicle of higher education, 2011. Absent Students Want to Attend Traditional Classes via Webcam.

http://chronicle.com/article/New-Question-for-Professors-/126073/ Edward L. Haletky, 2008. VMware ESX Server in the Enterprise: Planning and Securing Virtualization Servers. Prentice

Hall, New Jersey, USA. Oracle, 2011. Welcome to VirtualBox.org!. https://www.virtualbox.org/


369

INTRASUBJECT RELATIONS BEING THE BASIS OF PHYSICAL CONTENTS WITH MOBILE LEARNING

Dr. Ped. Sc. Prof. T. Gnitetskaya, Ph. D. docent E. Ivanova, master E. Karnauhova and Ph. D. docent L. Dubovaya

8, Suhanova str., phys. dep., Far Eastern Federal University, Vladivostok, Rus, Fed. 690650

ABSTRACT

Intensive development of wireless mobile technologies has caused a natural tendency to use mobile devices in the learning process. Alongside with communication convenience, there are some problems as well: newly trained teachers as well as newly presented teaching material are required. It is particularly important in learning physics. Before developing a new style of mobile learning, it is necessary to investigate its psychological and theoretical sides. This article represents a scientific explanation of a new, mobile technologies-adequate approach to structuring and systemizing of teaching materials by the example of physics.

KEYWORDS

Mobile learning, intrasubject relations, semantic structure.

1. INTERACTION

Recently a lot of attention in conferences and researcher’s discussions has been paid to the questions of introduction of mobile learning into the educational environment. A constantly growing number of universities and schools is starting to use mobile technologies within alternative methods of learning academic subjects. It is unquestionable that the use of mobile wireless technologies for the educational purposes has a pragmatic basis. Teaching information is transferred quickly, it may be sent and received at any convenient time and in large amounts. Moreover, the information accompanied by Internet address links, is essentially extended if a mobile device is enabled with WiFi. However, availability of the information does not guarantee its successful learning. It is known that reading of texts from fairly small monitors of mobile devices is rather complicated due to rapid eyes fatigability. Besides, material study often requires going back to the axiom or the value definition in order to understand the meaning of the text containing in another file. This is a serious problem faced by students and schoolchildren who learn physics, chemistry, mathematics and other exact sciences. "Jumps" from file to file lead to the concentration of attention over the search process rather than over the contents. This may result in formation of skills of superficial understanding of academic tasks. In this case the main objective of the education is lost, which is an achievement of a high level of quality of the education.

At the same time, one must appreciate the abovementioned communicative advantages of mobile wireless devices and the fact that every student and schoolboy has at least one such a device. Besides, there are multipurpose smartphones enabled with multimedia translation and display, extended opportunities of wireless connection and mobile devices with larger displays available for today.

In other words, there is a need to research the mobile technologies-adequate ways of systemizing, structuring and representation of the teaching material. This is particularly important if to use mobile devices in learning physics.

ISBN: 978-972-8939-66-3 © 2012 IADIS

370

2. RESEARCH

2.1 Psychological Criteria of Learning Process Efficiency

The problem of adequacy of the way of teaching material representation to technologies used in teaching originates in students’ psychology. Back in the middle of the last century famous psychologist established that “grouping of material during its memorizing is a conversion of the information arriving for long storage”. In other words, it is not the quantity of the information that is subjectively reflected but the conditions created for conversion of this information. We need to use this rule today. Therefore, picking up ways of training that creates optimum conditions for learning and mastering the teaching information, plays a key role in ensuring learning efficiency. According to the researches of a group of Russian psychologists (Zinchenko P. edc., 2010; Kozlovski S., 2000)), human memory has huge reserves which are not completely used in relation to both rational ways of memorizing and a volume of the information being memorized, opportunities to retain and operatively use it. Psychologists have come to the conclusion that if all these opportunities are not completely used in learning, then the reasons should be probably sought for in specifics of organization of the learning process itself. The first and the basic reason is a lack of students’ own activity organization during learning. The formulated conclusion caused a deep research of psychological regularities of the educational process. As a result, the factors of the learning process efficiency were determined.

The first factor was revealed during study of the regularities of knowledge acquisition. According to researches, knowledge is successfully acquired when the student masters purposeful actions (competencies – author’s note) which disclose the contents of this knowledge.

The second important factor of the learning efficiency is considered to be an expressed dependence of stability of the involuntarily memorizing knowledge on the inclusion degree of the purposeful action whichled to its memorizing into a system of other actions. It means that in the learning process it is necessary to form not separate, private, isolated actions, but rather their system in which each of the earlier, previously formed actions becomes a way to perform the following one. Thus, it is necessary to develop a system of academic tasks, that is to organize the material structure so that formation of the necessary system of actions with this material would be ensured. The psychological principle ensuring organization of such a structure, is that the contents which are the purpose of action in one task, should be included into a subsequent one as a way or a part of ways to solve it.

This article discusses the way of implementation of the psychological principle (the second factor of the learning efficiency) in the context of use of mobile devices during learning physics at any educational levels. The above stated psychological principle concerns a substantive area of learning physics and it is offered to consider it from the point of view of intrasubject relations in a physics course (Gnitetskaya T., 2004).

2.2 Method of Semantic Structures

The authors suggest to implement the psychological principle by considering learning as a process of carrying information from one academic task to another using intra- and intersubject relations disclosed in a teaching material [1]. Intrasubject connection provides transfer of the teaching information from a course structure element in which the object of connection is formed (for example, Lorentz force) to that element of structure in which it is used. The offered approach ensures the representing of any teaching information as semantic structures reflecting the intrasubject connections in a paragraph or a theme material. The semantic structure of a paragraph represents a semantic network which elements are physics concepts or any natural phenomena. Let’s consider a method of training material representation using the semantic structures by example of A.V. Peryshkin physics course for the eighth form pupils in a general education school [4]. A basis of the semantic structure method is in structuring of a teaching material (section, theme, concept which is included in such theme) subject to subsequent representation of the structure in form of column and calculation of the information contained in this structure. The teaching information transferred from one paragraph to another one becomes a part of the structure of other concept, and is none other than implementation of intrasubject connection through this concept. As an example, we consider a formation of the structure of magnetic field concept, studying at the 8th grade. We shall list all the physics concepts used in a material of this paragraph. We shall classify these concepts by levels of aggregation (see fig. 1). At the lower level of aggregation there are concepts: northern magnetic pole, southern magnetic pole, current


371

source, electric current which are included in the structure of concepts of the next level of aggregation: current-carrying conductor and magnetic needle. These concepts are necessary for carrying out of Oersted experiment which corresponds to the third level of aggregation, and conclusion of the experiment is located at subsequent higher level. The concept of a magnetic field considered in the paragraph is in the top column and completes the formation of semantic structure of the same paragraph. Representation of content in the form of semantic structures has a lot of advantages over traditional text representation. The first and most important advantage is that the structural image is easily read and acquired. Besides the text describing the content of magnetic field concept is presented on two pages. The semantic structure of this concept takes one third of page and it is easily read from a mobile device display. The structures are easy-transmitted and stored in mobile devices. They are disposable. By all means, a preliminary studying of content by its structure together with a teacher is required. The semantic structure is a vision of content which should remain in memory and when required may be restored after saving it as a picture in a mobile device.

Figure 1. Semantic structure of magnetic field concept

The textbook made in the form of semantic structures is convenient when using any mobile devices. The structures in such textbooks represent the interconnected academic tasks. For example, as the above presented semantic structure of magnetic field concept shows, the concept of electric current also has its own semantic structure. It is included in the problem of magnetic field concept formation as a part of its solving. The textbook posted on a site becomes available using any mobile wireless device enabled with WiFi. The semantic structures may be used for independent solving of physics tasks using any mobile devices. Thus, using the approach offered by us, a psychological principle of mobile learning efficiency is implemented.

3. RESULTS OF USE

This approach of structuring of any content within the scope of mobile learning have being applied at physics lessons for 7-9 form pupils at College of the Far Eastern Federal University, Vladivostok, Russian Federation. A public opinion poll using questionnaires which purpose was to reveal any complications arising in the offered way of mobile physics learning has been taken. 95% of respondents have noted that mobile learning generates the interest as it allows to study everywhere and at any convenient time, 100% have noted the efficiency of such studying as it is a great self-directed learning, and only 1% of respondents would like to study without use of mobile wireless technologies. Inventors have developed the methods of mobile physics learning at lectures when executing any laboratory researches and completing any tasks which will be published in other articles.

REFERENCES

1. Gnitetskaya T.N. Modern Educational Technologies: Vladivostok, FENU press, 2004. - 256 p. 2. Zinchenko P.I. Involuntary memorizing and activities, Direct-Media-Press 2010. - 717 p. 3. Kozlowski S.A. Short-term memory and visual evoked potential. Journal of higher nervous activity. 2000, T 50, №4,

pp.638-646./ 4. Perishkin A.V. 8th Form Physics. Textbook for general education institutions. The 5th public/ pattern. - M.: Drofa,

2003.-192 p.

Magnetic field

Oersted experiment

Magnetic needle Current-carrying conductor

North Pole South Pole Current source Electric current

Magnetic action

ISBN: 978-972-8939-66-3 © 2012 IADIS

372

A STUDY ON THE DEVELOPMENT OF LEARNING CONTENTS AND PLATFORM FOR ENVIRONMENTAL

EDUCATION

Uk Kim, Jaemoon Choi and Jiwon Yun Dept. of Architecture, Hong ik university

72-1 Sangsu-dong, Mapo-gu, Seoul, Korea

ABSTRACT

Global urbanization brought up economic prosperity and cultural diversity to a society, but people became insensible to social order and law-abiding. This study aims at developing a method for civil education to restore civil sense to improve urban environment. Learning processes and educational materials are modeled and written into digital contents. The success of this research will reduce social cost to reform the urban condition, and cultivate the competiveness of the city.

KEYWORDS

Environmental education, urban space monitoring, digital contents, mobile learning platform, ICT

1. INTRODUCTION

1.1 The Background and Objective of the Research

As cities become a complex place, unpredictability of urban life increase. Through the new millennium urbanization brings economic prosperity and cultural diversity to a society, but it also causes increasing insensibility to social order and law-abiding. In other words, the community has collapsed and a moral sense is lost.

In most global cities in this situation are being suffered from littering, illegal parking, etc. Solving these problems in a conventional way costs enormous amount of man-power. Thus, this study aims at developing a method for civil education using mobile devices and contents for restoring civil sense in order to improve current urban conditions.

1.2 Research Goals

Three research goals are set in this study. First, mobile learning processes are suggested to monitor and report problematic situations, while citizens

are taking a stroll, riding a bike, and playing in park. Second, a number of scenarios are scripted to cover mobile learning processes in various situations. Third, a mobile learning platform is implemented to communicate with a host server and other citizens by

various digital tools.


373

2. MAIN DISCOURSE

2.1 Mobile Education Process related to the Real Life in an Urban Environment

The mobile educational process is based on education that is processed in a learner’s daily life. It will be implemented to improve awareness through observing studies and data while the field trip studies and experimental studies are composed to lend an educational process that opens up social campaigns.

2.1.1 Program Selection and Individual Validation

Selecting a program will require validation of a participating individual before proceeding. (RFID is installed in the map and educational courses utilize smart devices).

2.1.2 Mission Disposition

Selecting one from diary of images in the local town, cleaning a town, Be a civic reporter- Preventing illegal occupation of the streets and trash refuse, Saving a town in emergency, Reporting and sharing of the AR ecology education provides duty to individual experience study.

2.1.3 Initiating the Mission

Using smart devices, one performs the work-study program in the urban streets or squares. The contents of the act include reports of town environment’s recordings (text, image, audio, and video) through smart devices, studies and reports on illegal occupation or illegal parking, and studies of ecological databases on AR.

2.1.4 Completing the Mission

The learner sends the final result of the learning program and ends the urban environmental education course.

2.1.5 Review and Discussion

Based on the final results collected through daily life, opinions are applied to regional streets for progress.

2.2 Mobile Educational Contents & Scenarios to improve Urban Environment

The content scenarios of the study are aiming to improve urban situation (littering, natural disaster, and ecological system).

The content scenarios are developed by process mentioned in 2-1, 1) program selection and individual validation, 2) mission disposition, 3) mission initiation, 4) mission completion, and 5) review and discussion

The results will be posted on the community board, and reported to municipal offices.

ISBN: 978-972-8939-66-3 © 2012 IADIS

374

2.2.1 Case 1: Reporting Illegal Occupations of Urban Street and Littering

Table 1. Reporting Illegal occupations and littering (Uk Kim, ubiquitous amenities lab, Hongik University)

1) Contents Violation of laws on urban environment : Illegal parking , Illegal occupation, Littering, Smoking in public area

2) Scenario Name Lee, MinSun Sex Female Age 12 Grade 5 Mobile technologies GPS, LBS, Camera, WiFi, 3G ①①①① Program selection and individual validation Register a individual validation to the environmental education platform using smart phone at home. ②②②② Mission disposition When the registration is done, the environmental education platform sends the following mission to Minsun through smart phone. ③③③③ Mission initiation She films the scene using Smart Phone. ④④④④ Mission completion She sends the images to the environmental education platform. ⑤⑤⑤⑤ Review Mobile discussion is held based on the dumped rubbish images Minsun has uploaded. ⑥⑥⑥⑥ Report Reported images and the GPS is reported to the neighborhood & district office. ⑦⑦⑦⑦ Affirmation The sent illegal-scene images are reported to the neighborhood & district office.

The results will be posted on the community board, and will be reported to municipal offices. ①②①②①②①② ③③③③ ④④④④ ⑤⑤⑤⑤ ⑥⑥⑥⑥ ⑦⑦⑦⑦

2.2.2 Case 2: Reporting of Natural Disaster

Table 2. Reporting of natural disaster (Uk Kim, ubiquitous amenities lab, Hongik University)t

1) Contents Preparation for emergency situations : Reporting emergency situations, Connecting to campaigns

2) Scenario Name Ji Hoon, Jung Sex Male Age 17 Grade 10 Mobile technologies GPS, LBS, Camera, CCTV, WiFi, ①①①① Program selection and individual validation Register a individual validation evacuational education platform

using smart phone ②②②② Mission disposition When he wakes up in the morning, the streets are filled with snow and traffic jam is serious.

He logs in to the community board using smart phone to alert the situation to other learners and residents. ③③③③ Mission initiation Straight away, the learners and the residents who received the text message gathers in the street

with files of snow. ④④④④ Mission completion They work together to clean up the snow. ⑤⑤⑤⑤ Review A mobile discussion is held on this urgent situation. Messages of support and cooperation are sent to the

community review. ⑥⑥⑥⑥ Report Pictures and the GPS taken in the place of possible collapse from snow can be reported to the neighborhood

& district office. ⑦⑦⑦⑦ Affirmation Place with concern for collapse is reported and handled, or the process is uploaded in the evacuational

education platform. ①②①②①②①② ③③③③ ④④④④ ⑤⑤⑤⑤ ⑥⑥⑥⑥ ⑦⑦⑦⑦

2.3 Mobile Learning Platform

The functions of mobile learning platform are to transmit educational contents to citizens, for citizens to select and carry out a mission for participating learning about urban environment and to share the collected information with the other citizens.

Mobile learning platform is connected to the simulator called Service Rule Engine which integrates various smart devices, and Event Management Rules are developed. The series of Events of a mission that


375

provokes Action of digital devices are modeled so that the interactions of learning and normalized.

Figure 1. Composition of mobile learning

3. CONCLUSIONS

The purpose of this study is to develop educational contents which allows citizens to participate in a mission where they monitor and report urban environments. The learning platform for civil education,

First, urban environment can be monitored in real time, and environmental conditions be improved significantly.

Second, civil education evokes the attention of civil rights and stimulates moral sense in urban environment.

Third, the community will be restored with the participation of citizens and ease the tension on urban life.

Forth, the collected data can be utilized for services.

ACKNOWLEDGEMENT

This study is supported by research grant (11CHUDthe Ministry of land, Transport and Maritime Affairs(MLTM).

REFERENCES

Book Edward L. Glaeser, 2011. Triumph of the City, How Our grea

and happier, The Penguin Press HC, USAUK. Kim, Hee-Ryoung. Park, Ji-Hyun. Lee, 2008. Body Metaphor : Ubiquitous technology and environment,

Korea Journal Hwang, G.-J., Tsai, C.-C., & Yang, S. J. H. 2008

Learning. Educational Technology & Society

Uk. Kim, Ji-Young. Jang, Seung Sik. Yoon, 2010. The innovative urban artifacts on streets and parks using ubitechnology, IADIS international e

Uk. Kim, Kyu-Man. Song, Ji-Young. Jang, 2008. A Study on user interface design for the public information service of Ubiquitous Street Light - based on the Itaewon Tourist Special District,

ction of digital devices are modeled so that the interactions of learning and

mobile learning platform (Uk Kim, ubiquitous amenities lab, Hongik University)

The purpose of this study is to develop educational contents which allows citizens to participate in a mission where they monitor and report urban environments. The following outcomes are expected using the mobile

atform for civil education, First, urban environment can be monitored in real time, and environmental conditions be improved

Second, civil education evokes the attention of civil rights and stimulates moral sense in urban

rd, the community will be restored with the participation of citizens and the neighborhood will help to

Forth, the collected data can be utilized for various purposes in modeling urban stimulates and civil

LEDGEMENT

by research grant (11CHUD-B054382-05) of advanced urban development project, the Ministry of land, Transport and Maritime Affairs(MLTM).

Triumph of the City, How Our greatest invention makes us richer smarter greener healthier , The Penguin Press HC, USA

Hyun. Lee, 2008. Body Metaphor : Ubiquitous technology and environment,

ang, S. J. H. 2008. Criteria, Strategies and Research Issues of ContextEducational Technology & Society, 11 (2), 81-91

Young. Jang, Seung Sik. Yoon, 2010. The innovative urban artifacts on streets and parks using ubiIADIS international e- society, pp 115-119.

Young. Jang, 2008. A Study on user interface design for the public information service of based on the Itaewon Tourist Special District, Society of Design Convergence

ction of digital devices are modeled so that the interactions of learning and participation are

Hongik University)

The purpose of this study is to develop educational contents which allows citizens to participate in a mission outcomes are expected using the mobile

First, urban environment can be monitored in real time, and environmental conditions be improved

Second, civil education evokes the attention of civil rights and stimulates moral sense in urban

the neighborhood will help to

purposes in modeling urban stimulates and civil

05) of advanced urban development project,

smarter greener healthier

Hyun. Lee, 2008. Body Metaphor : Ubiquitous technology and environment, Spacetime,

. Criteria, Strategies and Research Issues of Context-Aware Ubiquitous

Young. Jang, Seung Sik. Yoon, 2010. The innovative urban artifacts on streets and parks using ubiquitous

Young. Jang, 2008. A Study on user interface design for the public information service of Society of Design Convergence, pp 57-68.

ISBN: 978-972-8939-66-3 © 2012 IADIS

376

IACADEMY – AN INNOVATIVE MLEARNING APPROACH FOR LIFELONG LEARNING

Astrid Jancke1, Dr. Roman Götter1, Dr. Sebastian Vogt2 and Prof. Olaf Zawacki-Richter3 1Fraunhofer Academy, Munich, Germany

2FernUniversität in Hagen, Educational Technology, Hagen, Germany 3Center for Lifelong Learning (C3L) at Oldenburg University, Oldenburg, Germany

ABSTRACT

Based on iAcademy, we show in our demonstration a native App for the Apple iPad and how the Fraunhofer Academy in Munich (Germany), the FernUniversität in Hagen (Germany) and the Center for Lifelong Learning (C3L) at Oldenburg University (Germany), are implementing a mobile learning strategy for lifelong learning. Opportunities, potentials and implications of mobile learning for the near future are discussed in the paper.

KEYWORDS

Mobile learning, lifelong learning, definition of padcast, learning app, app content editor

1. INTRODUCTION

Already in 1910, the futurist Jehan von der Straaten [1] predicted that in the then still distant future of the year 2010, learning and teaching will be shaped by discussions taking place via waves across the "ether" as an exchange of ideas. He added that a question frequently arising will be who is actually teaching – the teacher or the student. School walls will fall, and fortresses of the spirit will be replaced by open flowery meadows. Van der Straaten‘s visionary prognoses are reflected today in the mobile learning approach that is integrated in lifelong learning processes. The technical innovation of web- and platform-based apps on mobile devices plays a key role here (see figure 1), influencing the mobile learning strategy for lifelong learning developed by education providers.

Figure 1. Tablet computers (e.g. Apple iPad) with native apps and browsers are very well suited for mobile learning

In 2010 the Fraunhofer Academy has started to create a prototype learning app for the Apple iPad and a dedicated editor to create highly interactive learning units. Together with our academic partners from Oldenburg University and FernUniversität in Hagen (Germany's Open University) we have set up pilot projects to create several mobile learning units of 1-3 hours length to examine the technical possibilities, the acceptance and learning patterns for different target groups.

We would like to suggest the new terms "padcast" and "padcasting" that describe the result and the process of creating and distributing dedicated learning units for a tablet computer. For this paper we would define the term padcast as follows: A padcast is a hypermedia file that can be distributed to and used on a


377

tablet mobile computer for (lifelong) learning purposes. A padcast contains all necessary assets (discrete-time and continuous-time media contents incl. rights management) to efficiently support the process of self-regulated learning independent from time and space on a mobile tablet computer. Padcasts are capsuled in native or web-based apps for different mobile tablet computer platforms.

2. PEDAGOGICAL CONCEPT

In our various trainings and study courses we successfully build on a blended learning concept. Our experience in several learning projects demonstrates that eLearning and mLearning cannot and should not replace traditional class room based trainings but rather provide additional means to enhance their effectiveness. Especially in the area of technical or scientific education for professional experts in parallel to their job, blended learning has proven to be the most effective learning setup. For example our Master online Building Physics (http://www.mob.uni-stuttgart.de/) has a mix of 20% face-to-face and 80% online training over a period of 2 years.

In several workshops and user interviews we have identified numerous possibilities for the effective use of mobile learning before, during and after classroom trainings. For example, before a class room training the students can get an introduction to the topic. One can do a preliminary test of prior knowledge to get an understanding of knowledge levels. It is also possible to form different learning groups based on those results. Furthermore, short polls or tests can be provided during the training. Additionally one can provide supplemental material after the course.

3. MOBILE LEARNING SCENARIO

But what are the opportunities that mobile learning affords? Our non-traditional learning groups have to fulfill various tasks every day. They work in typical (at least) 9am-to-5pm jobs, they commute from work to home (often more than one hour) and they try to have a family life. They find it very hard to do normal eLearning at the home PC or company PC. Our interviews have indicated that modern mobile devices like smart phones and tablet PC ease this situation a lot. They are instant on, you almost always have them with you and you can use them almost everywhere. In our field test we want to provide iPads to people who commute to work or travel a lot. Our application should support micro learning with intervals of 5-15 minutes with no (constant) connectivity to the internet. The learner should be able to use the app in the underground, on a long distant train or in a plane. As learning is a social exercise, interaction between learners and teachers is very important [2, 3]. We plan to extend the functionality beyond the current email possibilities.

4. TECHNICAL IMPLEMENTATION

The basic idea to use consumer electronic devices (phones, iPods) learning is not new [4]. But current devices like smart phones and tablet PCs provide larger screens and much improved usability. Together with our implementation partner Ziemann IT (Munich) we decided to implement a native app on iOS5 for iPad 1or 2. The app supports the handling of several learning units. The user can access the different padcasts in a bookshelf-like user interface. The main user interface is a so-called learning map (see figure 2). It provides a flexible non-linear access to the interactive lessons, the illustrated glossary, a PDF document library, questionnaires and interactive mini-games. Small indicators (�,�) show the learning progress in the different learning units.

ISBN: 978-972-8939-66-3 © 2012 IADIS

378

Figure 2. Flexible Learning Map provides access to all elements

We have totally separated the specific learning content from the app functionality and created a dedicated editor for Mac and PC (see figure 3) that can create a padcast without programming skills. With this editor an author can padcast a learning map and all content of the application easily.

Figure 1. Intuitive editor allows creation of interactive learning units without programming

5. CONCLUSION

We believe that mobile learning will play a very important role in future learning scenarios. With the learning app iAcademy and its editor we have created a first tool set to padcast interactive learning units for various user groups and topics efficiently. We plan to use it in existing programs and plan to expand its functionality in the coming months.

REFERENCES

[1] Straaten, J. van der (2010). Unterricht und Erziehung in 100 Jahren. In Brehmer, A. (ed.) Die Welt in 100 Jahren (pp. 161-170). Hildesheim : Georg Olms Verlag.

[2] Garrison, D. R., Anderson, T., and Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. American Journal of Distance Education, vol. 15, no. 1, pp. 7-23.

[3] Naidu, S. (2003). Designing instruction for e-learning environments. In Moore, M. G. and Anderson, W. G. (ed.), Handbook of distance education (p. 349-365). Mahwah, NJ: Lawrence Erlbaum Associates.

[4] Kukulska-Hulme, A., and Traxler, J. (2005). Mobile learning - a handbook for educators and trainers. London: Routledge


379

AN INVESTIGATION INTO UNIVERSITY STUDENTS’ EXPERIENCES AND PERCEPTIONS OF USING MOBILE

PHONES

Yukiko Maruyama Tokai University

Hiratsuka, Kanagawa, Japan

ABSTRACT

In order to introduce mobile devices smoothly into the classroom, it is crucial to reveal in detail the nature of users’ experiences and perceptions of using mobile phones. This poster shows the results of a preliminary investigation to gain insight into university students’ experiences and perceptions of their use of mobile phones.

KEYWORDS

Mobile phone, university, students’ experiences and perceptions, education

1. INTRODUCTION

The mobile phone is an essential tool for communication in our daily lives, and changes and advancements in mobile technologies and the Internet have brought many changes in the ways we use our mobile phones. As much research on m-learning (Yengin et al. 2011, Wang and Hirose 2011) has shown, mobile devices are promising tools in education.

In order to introduce mobile devices smoothly into the classroom, it is crucial to reveal in detail the nature of users’ experiences and perceptions of using mobile phones. Yilmaz and Akpinar (2011) investigated the mobile technologies and activities used by prospective teachers. Grund (2011) reported the results of a pilot study on the beliefs, attitudes and experiences of secondary teachers regarding the practices and opportunities that the use of mobile phones as an educational tool can provide on the educational stage. Thus, some studies have been conducted on users who teach with mobile phones. However, only a few studies have investigated the detailed nature of students’ experiences and perceptions of using mobile phones.

The aim of this study is to reveal in detail the nature of university students’ experiences and perceptions of using mobile phones. This poster shows the results of a preliminary investigation to gain insight into university students’ experiences and perceptions of their use of mobile phones.

2. BACKGROUND

Grund (2011) conducted a questionnaire survey on the beliefs, attitudes, and experiences of secondary teachers about practices and opportunities surrounding the use of mobile phones as an educational tool. The following conclusions were drawn (Grund 2011, pg305). 1) The attitudes of teachers are generally pro–integration of mobile phones as an educational resource. However, there are uncertainties or ignorance regarding its application or how to achieve it. 2) In relation to teacher receptivity to mobile telephony as an educational resource, segmentation into three groups were identified: “receptive or highly receptive” group, a “while waiting” group, and a “skeptical” group. 3) There is a lack of applications or experiences of mobile telephony as an educational resource. 4) Teachers do not have a rigid position with regard to the prohibition or restriction of mobile phones in the classroom to the degree expected. 5) Of the teachers surveyed, 40.9% do not fear spreading images in different communication channels without their permission or awareness.

ISBN: 978-972-8939-66-3 © 2012 IADIS

380

Yilmaz and Akpinar(2011) surveyed prospective teachers’ mobile device usage and mobile activities as well as what type of Internet connection they use. The results showed that prospective teachers mainly use mobile phones, flash drives, and notebook computers. However, some new technologies, such as smartphones, PDAs, and so on are not so frequent among them. More than half of participants did not engage in mobile activities such as downloading and reading e-books, playing interactive games via the Internet or on handheld game consoles, or downloading and listening to podcasts or audio book. Concerning the types of Internet connection used, wi-fi access is the most commonly used technology among participants. In contrast, 3G, EDGE, GRPS, and mobile modems are not so popular among them.

Thus, some studies have been conducted on users who teach with mobile phones. However, only a few studies have investigated in detail the nature of students’ experiences and perceptions using mobile phones. The next sections present the methodology and results of a preliminary investigation to gain insight into university students’ experiences and perceptions of their use of mobile phones.

3. INVESTIGATION

A group of 205 university students answered the questionnaire handed out for the present study; all of them were enrolled in a computer classes for beginners.

Data was collected at the beginning of the school semester, in September of 2011. During the first lesson of each class, the students were invited to participate in the study. Students were provided with information about the aim of the study and were informed that their participation was voluntary and confidential. They were then given the questionnaire.

The questionnaire was composed of seven questions: 1) purposes for using the computer; 2) positive experiences and perceptions of using the computer, 3) negative experiences and perceptions of using the computer, 4) purposes for using the mobile phone; 5) positive experiences and perceptions of using the mobile phone, 6) negative experiences and perceptions of using the mobile phone, 7) whether they use a conventional mobile phone or a smartphone. Students were asked to answer questions freestyle. This paper analyzes the answers concerned with mobile phones.

4. FINDINGS

107 students answered that they use conventional mobile phones (henceforth “mobile phones”), 95 that they use smartphones, and 3 that they do not use either.

From the answers, it was confirmed that students use their mobile phones and smartphones as tools for 1) communication (text, e-mail, and phone calls), 2) connecting to the Internet (searching for information, entertainment, shopping, and so on), 3) audio and video (watching TV and listening to music), and 4) other uses (games, taking notes, and so on). About one-fifth of the smartphone users answered that they use application software on their smartphone. Moreover, three smartphone users mentioned that they use smartphone as a supplement to their computer. About one-fifth of the mobile phone users answered that they use the mobile phone only for making calls and sending e-mails.

Regarding positive experiences, more than half of the mobile phone users answered that it is convenient to be able to communicate with friends and family anytime and anywhere by making calls and sending texts and e-mails. About one fifth of the mobile phone users mentioned using their mobile phones as a convenient tool for information. Further, some of them pointed out the usefulness of mobile phones in emergency situations. In comparison, about 30% of the smartphone users mentioned the convenience of the smartphone as a tool for communication, and about 27% mentioned its convenience as a tool for getting information online.

Regarding negative experiences, both groups mentioned the bad manners of other users. They said that they felt bad when they read rude posts on social networking sites. Some smartphone users mentioned awkward interfaces for character input, insufficient performance, and similar issues.


381

5. CONCLUSIONS

From the investigation, we suggest that the following issues exist in introducing mobile devices into classrooms.

The smartphone is a promising tool for education because of the availability of various application software for it. Since the smartphone was introduced into the Japanese market in 2004, the number of users who have changed from mobile phones to smartphones has increased rapidly, especially in the past few years. As our results showed, nearly half of participants use the smart phone. The trend of smartphone instead of mobile phone use continues to grow. However, this study has revealed that only one-fifth of the students who use smartphone also use application software on their smartphone. To smoothly introduce smartphone application software into classrooms, teachers have to show students the range of uses their smartphones have and support the expansion of their use.

Moreover, about one-fifth of the mobile phone users answered that they use their mobile phone only for making calls and sending e-mails. And while more than half of the mobile phone users mentioned using their mobile phones as a convenient tool for communication, only about one fifth of the mobile phone users mentioned using their mobile phones as a convenient tool for information. Teachers have to show students the usefulness of the mobile devices as tool for information retrieval.

Further, a few students still don’t have either device. It seems to be difficult for those students to accept the usefulness of the mobile phone and the smart phone, and it is likely that they will see it as a large challenge to use both devices as an education tool. Therefore, consideration of these students is needed if mobile tools are to be introduced into classrooms as education tools.

REFERENCES

Grand, F. B., 2011, High school teachers face the challenge of integrating the mobile phone in the class room, Proceedings of IADIS International Conference Mobile Learning 2011, Avila, Spain, pp. 304-306.

Wang, S. and Hirose, K., 2011, Developing English reading comprehension ability via mobile phones, Proceedings of IADIS International Conference Mobile Learning 2011, Avila, Spain, pp. 212-216.

Yengin, I., Karahoca, A., Karahoca, D. and Uzunboylu, H., 2011, Is SMS still alive for education? Analysis of educational potentials of SMS technology, Procedia Computer Science, Vol. 3, pp. 1439-1445.

Yilmaz, Y. and Akpinar, E., 2011, Mobile technologies and mobile activities used by prospective teachers, Proceedings of IADIS International Conference Mobile Learning 2011, Avila, Spain, pp. 144-150.

ISBN: 978-972-8939-66-3 © 2012 IADIS

382

LINGOBEE: A MOBILE APP FOR IN-SITU LANGUAGE LEARNING

Lyn Pemberton and Marcus Winter University of Brighton

Lewes Rd, Brighton, East Sussex, BN2 4GJ, UK

ABSTRACT

LingoBee is a mobile-phone app aimed at advanced language learners, developed as part of a nine partner EU Lifelong Learning Project. The demonstration and poster will show delegates how learners use the app to collect, annotate and share language- and culture-related items from the target language culture.

KEYWORDS

Informal learning, language, multimedia, social network

1. INTRODUCTION

Language learning has long been recognized as an area well suited to support from mobile devices, particularly informal learners [Kukulska-Hume, 2009; Kukulska-Hume & Shield, 2008]. Once immigrants and international students have gone through the formal language learning opportunities available to them, they often find that support for further learning is non-existent, and the community of practice formed by their fellow class members breaks up. Mobile learning networks offer an alternative to more traditional communities of learners [Traxler, 2010]. The SIMOLA EU Lifelong Learning project has developed a mobile Android app that encourages the continuation of active language learning by providing a simple but powerful tool for collecting and annotating items of linguistic and cultural interest in their target culture. These items are then shared with a new virtual community of interested fellow language e-learners via a common database, integrated with a range of social networking apps [Pemberton, Winter & Fallahkhair, 2009].

2. DESIGN AND FUNCTIONALITY

The app was developed following a learner-centred methodology, using participatory design workshops and rapid prototypes. An English-interface version was piloted with international students in the UK and design modifications made. The major issues at the pilot evaluation stage regarded the concerns of the (mainly far-Eastern) students about the value and reliability of user-generated content rather than the app’s functionality or usability. A further refined version was then developed with eight different interface language versions (English, Dutch, Hungarian, Italian, Japanese, Lithuanian and Norwegian).

Figure 1 illustrates the main functionality of the system (in a Norwegian example). After the welcome screen, with its synchronisation message, the user clicks on the vocabulary book icon to bring up a list of items created by herself and other users. She can look at her favourites (her own contributions plus those she has “favourited”) in alphabetical or chronological order. Alternatively she can view all the entries via the “heads” icon. One of the entries, the blueberry, has been illustrated with a photo by its contributor, while the rest are combinations of text, audio and web links.

Clicking on an item, in this case the top entry, brings up a full screen version, showing an automated text to speech function. The user can decide to enter a new version of the word, perhaps capturing a native pronunciation or clicking on the WWW icon to link to a Google search result for the word. This will then be


383

available to all members of her user group, who can flag it to the administrator in case of an offensive or incorrect post, or rate it on a scale of 1-4, with the best liked items rising to the top of the list for that word.

Table 1. Screenshot for Norwegian language items

New user groups can be set up via a web site, and a user may skip between as many public groups as they like. Private groups can also be formed, e.g. for a specific school tri or other closed interest group.

3. FURTHER DEVELOPMENT

LingoBee is currently being evaluated in six EU countries with a range of language learners including Erasmus students, immigrants and vocational students. We are working with partners to integrate the app into the practices of language schools and independent learners alike. On the one hand, this involves using the app in the context of formal language classes, such as those held by universities for Erasmus students, further education settings for vocational workers and also classes in international schools. Here we are most interested in the role of the app as a potential bridging device between the classroom and the lived experience of the learner in the foreign language setting. On the other, we are recruiting independent learners, e.g. immigrants, to use the app outside a formal learning setting: here the focus will be the development of communities of learners.

Further technological development will involve extending the range of interface languages but more importantly, developing iPhone and possibly Blackberry versions of the app.

ACKNOWLEDGEMENTS

The SIMOLA project was funded by the EU as part of its Lifelong Learning Programme in ICT LLP 511776-LLP-1-2010-1-UK-KA3-KA3MP. We gratefully acknowledge this support and the work of our project partners.

REFERENCES

Kukulska-Hulme, A. (2009) Will mobile learning change language learning?, ReCALL 21 (2): 157-165. Kukulska-Hulme, A. and Shield, L. (2008) ‘An overview of mobile assisted language learning: From content delivery to

supported collaboration and interaction’, ReCALL 20 (3): 271- 289. Pemberton, L., Winter, M, & Fallahkhair, S. (2009) ‘A User Created Content Approach to Mobile Knowledge Sharing

for Advanced Language Learners’, Proceedings of mLearn 2009. Traxler, J. (2010) ‘Students and mobile devices’, ALT-J, 18: 2, 149-160.

ISBN: 978-972-8939-66-3 © 2012 IADIS

384

AUTHOR INDEX Aguilar, G. ..........................................................51 Albrecht, U. .................................................... 247 Andergassen, M. ............................................ 189 Ando, Y. ......................................................... 307 Arslan, P. ........................................................ 222 Asada, T. ......................................................... 307 Attard, J. ............................................................43 Bagula, A. ...................................................... 331 Bayyurt, Y. ...................................................... 242 Benedek, A. ..................................................... 351 Bengtsson, M. ................................................. 359 Bergström, P. ................................................. 147 Bollaert, H. ...................................................... 335 Boyinbode, O. ................................................ 331 Braun, S. .......................................................... 123 Braz, L. ............................................................ 253 Breuer, H. ..........................................................75 Brienne, C. .........................................................83 Brügge, B. ....................................................... 197 Brunnberg,, L. ................................................. 222 Bryfczynski, S. ..................................................... 3 Buchem, I. ...................................................... 311 Burton, P. ..........................................................99 Camacho, M. ................................................... 311 Capus, L. ......................................................... 315 Casalegno, F. ................................................... 222 Choi, J. ........................................................... 373 Chotel, L. ...........................................................83 Churchill, D. .................................................... 320 Clunie, G. ........................................................ 253 Cochrane, T. .................................................... 165 Cochrane, T. .................................................... 311 Connolly, T. .................................................... 107 Cooper, M. ........................................................... 3 Cruz, C. ........................................................... 291 Dang, C. .............................................................83 Davidsson, M. ................................................. 263 Debattista, J. .......................................................43 Delgado, F. ...................................................... 139 Dierichs, T. ........................................................75 Dikk, D. ........................................................... 115 Dingli, A. ......................................................... 271 Divitini, M. ...................................................... 213 Dubovaya, L. ................................................... 370 Eliasson, J ...........................................................67

Elsholz, S. .......................................................... 75 Fukushige, Y. ................................................. 307 Gair, G. ............................................................ 347 Glaroudis, D. .................................................... 26 Gnitetskaya, T. ................................................ 370 Gordon, A. ....................................................... 311 Götter, R. ........................................................ 377 Guerra, V. ....................................................... 189 Guhr, D. .......................................................... 347 Hainey, T. ....................................................... 107 Haladjian, J. .................................................... 197 Häussermann, B. ............................................. 247 Hou, B. ............................................................... 19 Hsu, H. ............................................................. 237 Isabwe, G. ....................................................... 296 Ishikaw, M. ........................................................ 59 Ismailović, D. .................................................. 197 Ivanova, E. ....................................................... 370 Iwak, K. ............................................................. 11 Iwaka, K. ......................................................... 205 Jahnke, I. ......................................................... 147 Jan, U. .............................................................. 247 Jancke, A. ....................................................... 377 Jia, G. ............................................................... 320 Kaneko, K. ......................................................... 59 Kankaanranta, M. ............................................. 91 Karataş, N. ....................................................... 242 Karnauhova, E. ................................................ 370 Keegan, H. ...................................................... 311 Kenny, R. .......................................................... 99 Ketterl, M. ...................................................... 181 Kim, U. ........................................................... 373 King, M............................................................ 320 Kitazawa, T. ................................................... 275 Knutsson, O. ...................................................... 67 Köhler, B. ....................................................... 197 Konnestad, M. ................................................. 296 Kotini, I. ............................................................. 26 Kozuki, Y. ......................................................... 11 Kozuki, Y. ....................................................... 205 Kristiansen, A. ................................................. 213 Krogstie, B. ..................................................... 213 Kylmkowsky, M. ................................................. 3 Ledermüller, K. .............................................. 189 Lindsay, S. ....................................................... 132

Lindwall, K. ................................................... 147 Lund, M. .......................................................... 355 Macphail, A. ................................................... 107 Maeda, T. ........................................................ 307 Maillet, K. ..........................................................83 Manitsaris, A. .....................................................26 Mårell-Olsson, E. ........................................... 147 Marinagi, C. .................................................... 325 Marsden, G. ..................................................... 285 Maruyama, Y. ................................................. 380 Matthies, H. .................................................... 247 McGreal, R. .................................................... 157 Mendes, F. ...................................................... 291 MengMeng, L. ...................................................19 Menkhoff, T. .................................................. 359 Miki, K. .................................................... 11, 205 Ming, G. ......................................................... 359 Mitschian, H. ................................................... 233 Mitsuhara, H. ............................................ 11, 205 Miyakoda, H. .....................................................59 Mohanna, M. .................................................. 315 Molnár, G. ....................................................... 351 Montebello, M. ..................................................43 Mora, S. .......................................................... 213 Mugwanya, R. ................................................ 285 Müller, L. ........................................................ 123 Müller, N. ....................................................... 115 Mulrennan, D. ................................................. 165 Naga, M. .......................................................... 275 Neittaanmäki, P. .................................................91 Neumann, G. ................................................... 189 Ng’ambi, D. .................................................... 331 Nicolle, C. ....................................................... 291 Noda, Y. .................................................... 11, 205 Noguez, J. ..........................................................51 Noma, H. ........................................................ 173 Nouri, J. ..............................................................35 Nousiainen, T. ...................................................91 Ogata, H. ...........................................................19 Okada, M. ........................................................ 173 Oldenburger, L. .............................................. 181 Oliveira, C. ...................................................... 367 Olmedo, J. .........................................................51 Olsson, A. ........................................................ 147 Ortega, E. ...........................................................51 Pargas, R. ............................................................. 3 Park, C. ...............................................................99 Paulsson, F. .................................................... 147

Pemberton, L. ................................................. 383 Pérez-Novelo, R. ............................................... 51 Pinto, S. .......................................................... 253 Possemiers, P. .................................................. 335 Reader, K. ....................................................... 132 Reichert, F. ...................................................... 296 Renge, K. ......................................................... 173 Rivera-Pelayo, V. ............................................ 123 Robledo-Rella, V. .............................................. 51 Rubner, G. ....................................................... 302 Runco, L. ......................................................... 237 Sapargaliyev, D. .............................................. 279 Serrão, L. ......................................................... 253 Seychell, D. ..................................................... 271 Shea, S. ............................................................. 51 Sissons, H. ....................................................... 165 Skourlas, C. ..................................................... 325 Soualah-Alila, F. ............................................. 291 Storlien, A. ..................................................... 213 Storz, C. ............................................................ 83 Sultany, A. ....................................................... 132 Tada, M. .......................................................... 173 Takemura, A. ................................................... 258 Tamés, E. .......................................................... 51 Tannert, B. ....................................................... 355 Toiminen, P. ...................................................... 51 Traxler, J. ......................................................... 285 Uosaki, N. .......................................................... 19 Utsumi, A. ...................................................... 173 Van Neste-Kenny, J. ........................................ 99 Vinnervik, P. .................................................... 147 Vogt, S. ........................................................... 377 Vornberger, O. ................................................. 181 Wang, J. ........................................................... 343 Wang, S. .......................................................... 237 Wasti, R. .......................................................... 157 Winter, M. ....................................................... 383 Yamamoto, M. ................................................ 307 Yano, Y. ..................................................... 11, 205 Yıldız, S. .......................................................... 267 Yun, J. .............................................................. 373 Zacharias, V. ................................................... 123 Zare, S. ............................................................. 355 Zawacki-Richter, O. ........................................ 377 Zhang, L. ......................................................... 343