accessible user profile modeling for academic services based on moocs
TRANSCRIPT
Modelado de perfiles de usuario accesibles para servicios académicos basados en MOOC
Accessible user profile modeling for academic services based on MOOCs
Interacción 2015
XVI International Conference on HCI
7-9 September
Vilanova i La Geltrú
Francisco Iniesto y Covadonga Rodrigo
Universidad Nacional de Educación a Distancia (UNED)
INDEX
1. Study context
2. Objectives
3. Accessibility issues in MOOCs
4. Analysis of accessible metadata for user profile
definition
5. Conclusions
Integrates education, work and personal life in a continuous process. People with special needs choose distance education universities (eLearning)
for their studies. 7.500 enrolled students at UNED represents 50% of total Spanish university
students with a disability
STUDY CONTEXT: LLL FOR PEOPLE WITH SPECIAL NEEDS
Evolution of enrolment of disabled students over period 2003 – 2015 at UNED (UNIDIS)
25542966
34623830
4283 4224
4808
6294 6104
74697670
7847
7469
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
STUDY CONTEXT
Context: ICT + Disabilities:
• The possibilities that ICT offer people with disabilities to improve their wellbeing and the possibility of their insertion into the work market.
• The fact to make digital people with special needs increases the work rate in this collective.
• 100% consider that the incorporation of ICT into the workplace has increased their work possibilities.
Context: Accessible MOOC Learning:
Benefits such as:
• Openness
• Low cost
• Ubiquity (Time, space and rhythm)
• Acquiring knowledge
• Social learning: Connectivism
• Achieving new competences
• Develop professionally
OBJECTIVES
• The system will help to find MOOCs that best suit their professional needs and that are more accessible regarding his\her disability.
• Accessibility Analysis of both of eLearning platforms and educational resources.
• Personalization: adaptation to each assistive technology.
• Rated list of recommended MOOCs to best fit accessibility requirements and learning preferences.
DESIGN a personalized app for recommending MOOCs adapted to user needs: achieve new professional competences + learner’s preferences.
OBJECTIVES
Competence-based recommendation app for people with functional diversity.
1. Enriched user profile.
• User’s device personalization: preferences / needed assistive technologies -> technical needs regarding user’s functional diversity.
2. Accessible MOOCs.
• Accessibility evaluation on MOOC platforms and their educational resources-> automated recommendation list adapted to user’s functional diversity (user’s profile).
ACCESSIBILITY ISSUES IN MOOCs
MOOC platforms:
• Web based eLearning engines • Scheduling academic curriculum • Synchronous and asynchronous
communication
Interface elements:
• Logging in, logging out • Navigating in courses and content• Multi layered structures
eLearning materials:
• Specific technology.
Barriers :
• The interface elements• The manner in which users interact with
these objects • Components which do not always share
a consistency of interface logic:
• Posting in a forum • Making up elements in tests
or timed quizzes• Embedded videos • Variety of document formats
ACCESSIBILITY ISSUES IN MOOCS
Effective eLearning environment :
• Learner’s abilities• Learning goals• Where learning takes place • Which specific devices the learner uses
Learner’s preferences : PROFILE
• Learners can specify which kind of adapted and\or alternative resource they prefer or need.
(text may be preferred over visual resources or audio might be preferred over text or images)
ACCESSIBILITY ISSUES IN MOOCs
"Emprendimiento y Desarrollo de Aplicaciones de Realidad Aumentada" (COLMENIA: Weprendo + UnX).
"España+Francia+Cerca I" (UNED COMA).
"Estrategias de Marketing Online. Community Manager" (Miriada X).
“As alterações climáticas - or contexto das experiências de vida” (UAb iMOOC).
Accessibility evaluation of MOOC platforms and courses to achieve a map of accessible MOOCs versus functional diversities.
Iniesto, F., Rodrigo, C., Moreira Teixeira, A. Accessibility analysis in MOOC platforms. A case study: UNED COMA and UAb iMOOC. CAFVIR, 2014Iniesto, F.; Rodrigo, C., "Accessibility assessment of MOOC platforms in Spanish: UNED COMA, COLMENIA and Miriada X," Computers in Education (SIIE), 2014
ANALYSIS OF ACCESSIBLE METADATA FOR USER PROFILE DEFINITION
Learning Profiling:
•Display information: the user preferences to have information presented, text (fonts and colors), video (resolution), mouse (pointer, motion)
•Control information: user preferences to control the device keyboard (virtual), zoom preferences, voice recognition)
•Content information: user preferences for visualizing learning content.
•Privacy and data protection information.
•Technological: the technology to develop and edit the resources. (authoring tools to facilitate the production of accessible materials)
•Adapted Devices: when a user accesses a resource available on the Internet, it can be accessed directly or a device would have to be used specifically (screen reader, specialized mouse, virtual keyboard, magnifying glass).
•Existing Inclusive Methodologies and Educational Standards: XML markup languages.
ANALYSIS OF ACCESSIBLE METADATA FOR USER PROFILE DEFINITION
Learning Resources
ANALYSIS OF ACCESSIBLE METADATA FOR USER PROFILE DEFINITION
IMS Access for All (AfA) : Personal Needs and Preferences (PNP) and Digital
Resource Description (DRD) -> Multiplicity (Collections)
• Define the access mode requested by the user.
• The type of accommodation needed.• Information about the educational
resource.• Language.
Adapting the resources
depending on user’s
limitation
CONCLUSIONS
It is necessary to describe learner’s preferences and needs by means of a specific user profile and how this profile interacts with the eLearning platform interface.
The use of the most adapted LR will affect positively the learning experience of users with different capabilities.
Access for All (AfA) in its PNP and DRD standards offer the possibility to learners so they can specify which kind of adapted and\or alternative resource they prefer or need.
Future work: refine the user profile modeling.
Francisco Iniesto, Covadonga Rodrigo
Department of Computer Systems and Languages
Research Chair “Technology and Accessibility”
School of Computer Science
UNED – Fundación Vodafone España
E-mail: [email protected], [email protected]