the effects of deductive and inductive based...

THE EFFECTS OF DEDUCTIVE AND INDUCTIVE

BASED COURSEWARE ON LEARNING

PERFORMANCE AND ENGAGEMENT AMONG

STUDENTS WITH DIFFERENT LEVELS OF

SELF-REGULATED LEARNING

SUBASHINI A/P LETCHUMANAN

UNIVERSITI SAINS MALAYSIA

2015

THE EFFECTS OF DEDUCTIVE AND

INDUCTIVE BASED COURSEWARE ON

LEARNING PERFORMANCE AND

ENGAGEMENT AMONG STUDENTS WITH

DIFFERENT LEVELS OF

SELF-REGULATED LEARNING

by

SUBASHINI A/P LETCHUMANAN

Thesis submitted in fulfillment of the requirement

for the degree of

Doctor of Philosophy

July 2015

ii

ACKNOWLEDGEMENTS

I would not have been able to finish my thesis without the unfailing love of

god, guidance of my lecturers and support from my husband and daughter. First and

foremost I offer my sincerest gratitude to my supervisor, Associate Professor Dr

Irfan Naufal Umar, who has supported me throughout my thesis with his patience,

knowledge and guidance to pursue high standards in research. Without his

encouragement and effort, this thesis would not have been completed or written. I

sincerely express my thanks to my co-supervisor Associate Professor Dr Mona

Masood who gave me timely suggestions to improve my thesis. I also extend my

sincere thanks to the Director of Centre for Instructional Technology and Multimedia

(CITM) at Universiti Sains Malaysia, Professor Dr Merza Abbas, retired Professor

Toh Seong Chong and all lecturers at CITM for their comments and advice.

My gratitude goes to the lecturers at School of Education, Universiti Sains

Malaysia for their assistance. I would like to thank the faculty and administrative

staff of CITM at Universiti Sains Malaysia who have provided facilities, technical

support and assistance. I would also like to thank the principals, teachers and

students of the secondary schools which served as the research sites. Thank you to

my mother, family and friends for the continuous support.

A very special thank you to my husband, Arivanandhan Venugopal and

daughter, Varshah Arivanandhan for their sacrifice, understanding, moral support

and encouragement throughout my pursuit for academic improvement. I wish to

dedicate this research to my late father Letchumanan Kaliperma, my husband and

daughter whom I love with all my heart.

iii

TABLE OF CONTENTS PAGE

Acknowledgements ………………………………………………………….. ii

Table of Contents ……………………………………………………………. iii

List of Tables ……………………………………………………………… xi

List of Figures ……………………………………………………………….. xiii

List of Abbreviations ……………………………………………………… xvi

List of Appendices …………………………………………………………... xvii

List of Publications ………………………………………………………….. xviii

Abstrak ……………………………………………………………………… xix

Abstract ……………………………………………………………………… xxi

1.1 Introduction …………………………………………………………. 1

1.2 Research Background ……………………………………………….. 4

1.3 Problem Statement ………………………………………………….. 14

1.4 Research Objectives ………………………………………………… 16

1.5 Research Questions …………………………………………………. 17

1.6 Research Hypotheses ……………………………………………….. 18

1.7 Theoretical Framework ……………………………………………... 20

1.8 Research Framework ………………………………………………... 24

1.9 Research Significance ………………………………………………. 25

1.10 Research Limitations ………………………………………………... 28

1.11 Operational Definitions ……………………………………………... 29

1.12 Summary ……………………………………………………………. 32

CHAPTER 1 – INTRODUCTION

iv

2.1 Overview …………………………………………………………… 34

2.2 Mathematics Education in Malaysia………………………………… 34

2.3 Mathematics and Multimedia ………………………………………. 36

2.4 Problems in Teaching and Learning Mathematics …………………. 39

2.5 Learning Difficulties in the Topic of Straight Line ………………... 41

2.6 Instructional Strategies …………………………………………….. 43

2.6.1 Deductive Method …………………………………………… 43

2.6.1.1 Ausubel’s Deductive Model ………………………... 45

2.6.1.2 Model for the Deductive Method of Teaching ……… 46

2.6.1.3 Deductive Method in a Multimedia Environment …... 48

2.6.2 Inductive Method …………………………………………….. 49

2.6.2.1 Bruner’s Inductive Model …………………………... 51

2.6.2.2 Model for the Inductive Method of Teaching ………. 53

2.6.2.3 Inductive Method in a Multimedia Environment …… 54

2.6.3 A Comparison of Deductive Method and Inductive Method… 55

2.7 Student Centered Learning …………………………………………. 56

2.8 Cognitive Theory of Multimedia Learning ………………………… 58

2.8.1 Assumptions of Theory ……………………………………… 59

2.8.2 Design Principles based on Cognitive Theory of Multimedia

Learning ……………………………………………………... 60

2.9 Cognitive Load Theory ……………………………………………... 65

2.10 Transfer of Learning ………………………………………………... 70

2.10.1 Near Transfer ……………………………………………….. 72

CHAPTER 2 - LITERATURE REVIEW

v

2.10.2 Far Transfer ………………………………………………… 72

2.10.3 Problems in Transfer of Learning …………………………... 73

2.11 Learning Engagement ………………………………………………. 74

2.11.1 Types of Learning Engagement …………………………….. 75

2.11.2 Learning Engagement in Mathematics ……………………... 76

2.11.3 Learning Engagement in a Multimedia Environment ………. 78

2.12 Self-Regulated Learning ……………………………………………. 79

2.12.1 Phases of Self-Regulated Learning …………………………. 80

2.12.2 Self-Regulated Learning in a Multimedia Environment …... 83

2.12.3 Self-Regulated Learning in Mathematics …………………... 84

2.13 Summary ……………………………………………………………. 85

3.1 Introduction …………………………………………………………. 86

3.2 Population and Sampling …………………………………………… 87

3.3 Research Design …………………………………………………….. 88

3.4 Experimental Conditions ……………………………………………. 90

3.5 Variables ……………………………………………………………. 91

3.6 Instructional Materials ……………………………………………… 93

3.7 Research Instruments ……………………………………………….. 93

3.7.1 Pretest-Posttest ……………………………………………….. 94

3.7.2 Learning Engagement Scale (LES) …………………………... 96

3.7.3 Motivated Strategies for Learning Questionnaire (MSLQ) …. 98

3.8 Research Procedures ………………………………………………... 101

CHAPTER 3 - METHODOLOGY

vi

3.8.1 Procedure of the Design and Development of the IMCSL …..... 101

3.9 Pilot Study …………………………………………………………... 101

3.10 Validity and Reliability of Research Instruments …………………... 104

3.10.1 Validity and Reliability of Pretest and Posttest ……………... 105

3.10.2 Validity and Reliability of the Learning Engagement Scale

(LES) ………………………………………………………... 108

3.10.3 Validity and Reliability of Motivated Strategies for Learning

Questionnaire (MSLQ) ……………………………………... 109

3.10.4 Validation of the Content in the Interactive Multimedia

Courseware(IMCSL)..………………………………………... 109

3.11 Procedure of Data Collection ……………………………………….. 110

3.12 Internal and External Validation of This Study …………………….. 113

3.13 Data Analysis ……………………………………………………….. 115

3.13.1 Descriptive Statistics ………………………………………... 115

3.13.2 Inferential Statistics …………………………………………. 115

3.13 Summary ……………………………………………………………. 117

4.1 Introduction …………………………………………………………. 118

4.2 Allesi & Trollip Instructional Design and Development (ATID)

Model ……………………………………………………………….. 119

4.2.1 The Planning Phase …………………………………………... 123

4.2.1.1 Define the Scope …………………………………….. 124

4.2.1.2 Identify Learner Characteristics …………………….. 125

4.2.1.3 Identify and Collect Resources ……………………… 126

4.2.1.4 Brainstorming and Define Look and Feel of Product .. 127

4.2.2 The Design Phase …………………………………………….. 127

CHAPTER 4 - DESIGN AND DEVELOPMENT

vii

4.2.2.1 Develop Initial Content Ideas ……………………….. 128

4.2.2.2 Conduct Task and Concept Analyses ………………... 128

4.2.2.3 Do a Preliminary Program Description ……………… 130

4.2.2.4 Prepare Prototype ……………………………………. 133

4.2.2.5 Create Flowchart and Storyboards …………………... 135

4.2.2.6 Prepare Scripts ………………………………………. 136

4.2.3 The Development Phase ……………………………………… 136

4.2.3.1 Prepare Text and Create Graphics …………………… 137

4.2.3.2 Produce Audio and Video …………………………… 137

4.2.3.3. Assemble the Pieces ………………………………… 138

4.2.3.4 Prepare Support Materials …………………………… 138

4.2.3.5 Evaluate and Revise …………………………………. 138

4.3 Application of Theories ……………………………………………... 139

4.3.1 Mayer’s Cognitive Theory of Multimedia Learning …………. 139

4.3.2 Cognitive Load Theory ………………………………………. 142

4.4 Features of Multimedia Learning Environment …………………….. 145

4.4.1 Interface Design ……………………………………………… 145

4.4.2 Consistency …………………………………………………... 146

4.4.3 Simplicity …………………………………………………….. 147

4.4.4 Aesthetics …………………………………………………….. 148

4.4.5 Positioning of Controls ………………………………………. 150

4.4.6 Navigation ……………………………………………………. 151

4.4.7 System Requirements ………………………………………… 152

4.4.8 Formative Evaluation ………………………………………… 152

4.5 Summary ……………………………………………………………. 158

viii

5.1 Introduction …………………………………………………………. 159

5.2 Distribution of Sample …………………………………………….... 160

5.3 Appropriateness of Covariate ……………………………………….. 160

5.3.1 Analysis of Pretest Score …………………………………….. 161

5.4 Classifications of Students as LSRL and HSRL ……………………. 165

5.5 Testing Assumptions for ANCOVA ………………………………... 166

5.6 Testing Assumptions for ANOVA ………………………………….. 173

5.7 Testing of H01, H02 and H03 ………………………………………... 177

5.7.1 ANCOVA (Hypotheses H01, H02 and H03) …………………. 178

5.8 Testing of H04, H05 and H06 ………………....................................... 181

5.8.1 ANCOVA (Hypotheses H04, H05 and H06) ………………….. 182

5.9 Testing of H07, H08 and H09 ………………………………………... 186

5.9.1 ANOVA (Hypotheses H07, H08 and H09 ) ………………… 187

5.10 Summary of Findings ……………………………………………….. 190

5.11 Summary ……………………………………………………………. 193

CHAPTER 5 - DATA ANALYSIS AND FINDINGS

CHAPTER 6 - DISCUSSION, IMPLICATIONS AND

RECOMMENDATIONS

6.1 Introduction …………………………………………………………. 194

6.2 The Effect of Instructional Method on Near Transfer Performance

score, Far Transfer Performance Score and Learning Engagement

Score among LSRL and HSRL Students …………………………… 195

6.3 Research Question 1: Effect of the Treatment Conditions on

Students’ Near Transfer Performance score.………………………...

196

ix

6.4 Research Question 2: The Effect of the Self- Regulated Learning

(SRL) Levels on Students’ Near Transfer Performance Score……… 198

6.5 Research Question 3: The Interaction Effect between Treatment

Conditions and Students’ SRL Levels on Near Transfer …………… 200

6.5.1 The Interaction Effect between the Treatment Conditions and

LSRL students on the near transfer performance of the study.. 201

6.5.2 The interaction effect between the treatment conditions and

HSRL students on the near transfer performance of the study... 203

6.5.3 The Interaction Effect between the DM and SRL Levels on

the Near Transfer Performance of the Study ………………… 204

6.5.4 The Interaction Effect between the IM and SRL Levels on the

Near Transfer Performance of the Study …………………….. 206


Students’ Far Transfer Performance Score …………………………. 207

6.7 Research Question 5: The Effect of the SRL Levels on Students’

Far Transfer Performance Score ……………………………………. 209


Conditions and Students’ SRL Levels on Far Transfer …………….. 211


LSRL on the Far Transfer Performance of the Study ……….. 212


HSRL on the Far Transfer Performance of the Study ……….. 215


the Far Transfer Performance of the Study ………………….. 216

6.8.4 The Interaction Effect between the IM and SRL Levels on the

Far Transfer Performance of the Study ……………………… 218


Students’ Learning Engagement Score ……………………………... 220

6.10 Research Question 8: Effect of the Self- Regulated Learning (SRL)

Levels on Students’ Learning Engagement Score ………………….. 221


Conditions and Students’ SRL Levels on Learning Engagement …...

223

x

6.11.1 The Interaction Effect between the Treatment Conditions

and LSRL Students on the Learning Engagement ………….. 224

6.11.2 The Interaction Effect between the Treatment Conditions

and HSRL Students on the Learning Engagement …………. 225


the Learning Engagement …………………………………... 227

6.11.4 The Interaction Effect between the IM and SRL Levels on

the Learning Engagement …………………………………... 228

6.12 Conclusion ………………………………………………………...... 230

6.13 Implications of the Study …………………………………………… 231

6.14 Recommendations for Future Research …………………………….. 233

6.15 Summary ………………………………………………………......... 235

REFERENCES ………………………………………………….. 237

xi

LIST OF TABLES

PAGE

Table 1.1 Malaysian Eighth-Graders (Secondary Two)

Mathematics and Science Achievement of TIMSS in

1999, 2003, 2007 and 2011

8

Table 1.2 Eighth-Graders (Secondary Two) Mathematics

Achievement of TIMSS in 1999, 2003, 2007 and 2011

8

Table 1.3 Analysis of Mathematics Performance in the SPM Exam

2008 – 2012.

11

Table 2.1 Comparison of Deductive Method and Inductive Method

56

Table 2.2 The Characteristics of Student-Centered Learning

57

Table 2.3 Cognitive Theory of Multimedia Learning

65

Table 2.4 Different Types of Transfer and Their Characteristics

71

Table 2.5 Variables of Self- Regulated Learning Among

Individuals

82

Table 3.1 Characteristics of the Instructional Method of

Experiment Conditions

91

Table 3.2 Subtopics and Test Items (Posttest)

95

Table 3.3 Subtopics and Breakdown of Near Term Transfer and Far

Term Transfer (Posttest).

95

Table 3.4 The MSLQ Self-Regulated-Learning Scales and Items

99

Table 3.5 Descriptive Statistics for Pretest, Posttest Scores and LES

from the Pilot Study

104

Table 3.6 Time Table Detailing the Administration and Duration of

Tests, Questionnaires and Treatments

113

Table 3.7 Data Analysis

116

Table 4.1 Chart of Learner Characteristics

126

Table 5.1 Number of Sample according to the Schools

160

Table 5.2 Descriptive Statistics of Pretest Score of DM and IM

Groups

161

xii

Table 5.3 Skewness and Kurtosis Statistics of Pretest Score of DM

and IM Groups

162

Table 5.4 Test of Homogeneity of Variances for Pretest Scores

between Groups

164

Table 5.5 ANOVA Result for the Pretest Scores between the

Treatment Groups

164

Table 5.6 Descriptive Statistics of SRL Score of DM and IM

Groups

165

Table 5.7 Tests of Normality for Overall Posttest Scores and

Posttest Scores of DM and IM Groups

167

Table 5.8 Test of Homogeneity of Variances for Posttest Scores

between Groups

170

Table 5.9 Homogeneity of Regression Slopes Test

173

Table 5.10 Test of Homogeneity of Variances for Learning

Engagement Scores between Groups

177

Table 5.11 Descriptive Statistics for Near Transfer Performance

Score

178

Table 5.12 Test of Between-Subject Effects (Near Transfer)

179

Table 5.13 Pairwise Comparisons for Near Transfer Performance

180

Table 5.14 Descriptive Statistics for Far Transfer Performance Score

183

Table 5.15 Test of Between-Subject Effects (Far Transfer)

183

Table 5.16 Pairwise Comparisons for Far Transfer Performance

184

Table 5.17 Descriptive Statistics for Learning Engagement Score.

187

Table 5.18 Test of Between-Subject Effects (Learning Engagement)

188

Table 5.19 Pairwise Comparisons for Learning Engagement Score

189

Table 5.20 Summary of Findings

190

xiii

LIST OF FIGURES

PAGE

Figure 1.1 Mathematics Achievements in TIMSS 1999 – 2011

8

Figure 1.2 Cognitive and Content Domains of Mathematics in

TIMSS 2011

12

Figure 1.3 Theoretical Framework

23

Figure 1.4 Research Framework

24

Figure 2.1 Deductive Model

46

Figure 2.2 Deductive Teaching Model

47

Figure 2.3 Inductive Model

52

Figure 2.4 Model of Inductive Method of Teaching

53

Figure 2.5 Mayer’s Cognitive Theory of Multimedia Learning

59

Figure 2.6 Phases of Self-Regulated Learning

81

Figure 3.1 Quasi Experimental Pretest and Posttest

89

Figure 3.2 The 2 X 2 Quasi Experimental Design Using the

Instructional Method and the Self-Regulated Learning

Level

90

Figure 3.3 The Relationship Between the Variables

93

Figure 3.4 Constructs of Learning Engagement Scale (LES)

97

Figure 3.5 The MSLQ Dimensions

100

Figure 3.6 Pilot Study in Progress

104

Figure 3.7 Graphical Representation of the Research Procedure

111

Figure 4.1 Applications of Models and Theory in IMCSL Design

119

Figure 4.2 Alessi & Trollip Model for Design and Development of

IMCSL

122

Figure 4.3 Task Analysis of Straight Line Topic

129

Figure 4.4 Tutorial Model of IMCSL Using Deductive Method 131

xiv

Figure 4.5 Tutorial Model of IMCSL Using Inductive Method

132

Figure 4.6 Prototypes for the Title Page and Submenus

134

Figure 4.7 Flowchart of IMCSL

135

Figure 4.8 An Example of a Screen Demonstrating the Multimedia

and Contiguity Principles

140

Figure 4.9 An Example Demonstrating the Modality Principle

142

Figure 4.10 Transition from Fully Complete Example and Partially

Complete Example to Problem Solving

144

Figure 4.11 Screen Layout Design of Both the Deductive Method and

the Inductive Method of IMCSL

147

Figure 4.12 An Example of a Screen with Sub Topic Items

148

Figure 4.13 An Example of the Use of Colour to

Differentiate Portions of a Visual

149

Figure 4.14 An Example of a Screen with Video Visuals

150

Figure 4.15 An Example of Screen Caption Showing the

“Check Answer” Button

151

Figure 4.16 Flow of the Content Using Deductive Method in IMCSL

154

Figure 4.17 Flow of the Content Using Inductive Method in IMCSL

156

Figure 5.1 Normal Probability Plot of Pretest scores for the DM

group

163

Figure 5.2 Normal Probability Plot of Pretest scores for the IM

group

163

Figure 5.3 Normal Probability Plot of the Overall Posttest Scores

168

Figure 5.4 Normal Probability Plot of Posttest Scores for the DM

Group

169

Figure 5.5 Normal Probability Plot of Posttest scores for the IM

group

169

Figure 5.6 A Scatterplot Showing Relationship between Pretest and

Posttest for DM Group

170

xv


Posttest for IM Group

171


Posttest for Both Groups

172

Figure 5.9 Normal Probability Plot of the Overall Learning

Engagement Scores

175

Figure 5.10 Normal Probability Plot of Learning Engagement

Scores for the DM Group

175

Figure 5.11 Normal Probability Plot of Learning Engagement

Scores for the IM Group

176

xvi

LIST OF ABBREVIATION

ATID Allesi & Trollip Instructional Design and Development

DM Deductive Method

HOTS Higher Order Thinking Skills

HSRL High Self-Regulated Learning

IM Inductive Method

IMCSL Interactive Multimedia Courseware on Straight Line

LES Learning Engagement Scale

LSRL Low Self-Regulated Learning

MSLQ Motivated Strategies Learning Questionnaire

PISA Programme for International Student Assessment

SRL Self-Regulated Learning

TIMSS Trends in International Mathematics and Science Study

xvii

LIST OF APPENDICES

Appendix A Lesson Protocol for Teacher

Appendix B Posttest

Appendix C Learning Engagement Scale (LES)

Appendix D Subscales of Motivated Strategies for Learning

Questionnaire (MSLQ)

Appendix E Motivated Strategies for Learning Questionnaire (MSLQ)

Appendix F Reliability of Pretest and Posttest

Appendix G Index Difficulty and Discrimination Index of Posttest

Appendix H Courseware Evaluation Form

Appendix I Permission Application emails and Letters

Appendix J Guide for Student

Appendix K Teacher and Student Manual

Appendix L Survey of Students and Teachers

Appendix M Objective of the Straight Line Lesson

Appendix N Storyboard

Appendix O Sample of Scripts for Interactive Multimedia Courseware

(IMCSL)

Appendix P Data for Analysis with SPSS (version 20.0 for Windows)

xviii

LIST OF PUBLICATIONS

Conference Proceeding

Subashini, L., & Fatimah, S. (2011). Comparison between cooperative computer-

assisted instruction and individual computer-assisted instruction on students’

performance with different cognitive styles. Paper presented at the

International Technology, Education and Development Conference, 7-9 March

2011 at Valencia, Spain.

Subashini, L., & Irfan, N.U. (2013). A proposed study on the effectiveness of

deductive and inductive methods in learning mathematics using multimedia

courseware. Paper presented at the International Conference and Computing,

Mathematics and Statistics, 28-29 August 2013 at Bayview Beach Resort

Penang, Malaysia.

xix

KESAN KOSWER BERASASKAN DEDUKTIF DAN INDUKTIF

TERHADAP PRESTASI DAN PENGLIBATAN PELAJAR YANG BERBEZA

TAHAP PEMBELAJARAN PENGATURAN KENDIRI

ABSTRAK

Pelajar perlu memiliki kebolehan untuk memindahkan pengetahuan matematik yang

dipelajari kepada domain atau masalah lain. Kemahiran ini akan memudahkan

mereka mengendalikan masalah kehidupan sebenarnya pada masa hadapan.

Berdasarkan sorotan literatur, kebolehan pelajar untuk membuat suatu kesimpulan

mengenai konsep matematik yang dipelajari dapat melahirkan individu yang

berupaya berfikir dan inovatif, dan seterusnya membolehkan pemindahan

pembelajaran berlaku. Oleh yang demikian, satu perubahan pedagogi perlu ada di

mana peralihan dari penyampaian isi kandungan matematik secara menyeluruh yang

dihafal oleh pelajar kepada pembelajaran yang merangsang pemikiran mereka.

Kajian ini mencadangkan satu pendekatan yang menggunakan kaedah pengajaran

yang kreatif bersama multimedia interaktif untuk menggalakkan pelajar membina

pengetahuan matematik. Penyelidikan ini dijalankan bagi mengkaji kesan koswer

multimedia interaktif dengan dua kaedah pengajaran yang berbeza terhadap prestasi

dan penglibatan pembelajaran dalam kalangan pelajar Tingkatan Empat dalam topik

matematik ‘Persamaan Garis Lurus’. Koswer berasaskan kaedah deduktif dan koswer

berasaskan kaedah induktif telah dibangunkan. Seramai 97 pelajar menerima

kaedah deduktif manakala 94 pelajar menerima kaedah induktif. Kajian eksperimen

kuasi ini menggunakan reka bentuk faktorial 2 x 2. Pembolehubah bebas melibatkan

kaedah pengajaran, iaitu sama ada kaedah deduktif atau kaedah induktif, manakala

pembolehubah bersandar melibatkan prestasi pelajar dalam pembelajaran

pemindahan dekat, pembelajaran pemindahan jauh serta penglibatan pembelajaran

xx

mereka. Pembolehubah moderator ialah tahap pembelajaran pengaturan kendiri

pelajar iaitu tahap rendah dan tahap tinggi. Hasil kajian terhadap kesan utama

kaedah pengajaran menunjukkan bahawa kumpulan rawatan induktif memperolehi

skor yang lebih tinggi secara signifikan berbanding kumpulan rawatan deduktif dari

aspek pemindahan dekat dan pemindahan jauh serta penglibatan pembelajaran. Bagi

kesan utama tahap pembelajaran pengaturan kendiri, pelajar tahap tinggi

memperolehi skor prestasi pembelajaran pemindahan jauh dan penglibatan

pembelajaran yang lebih tinggi berbanding skor pelajar tahap rendah. Hasil kajian

juga menggariskan kesan interaksi yang signifikan antara kaedah pengajaran dan

tahap pengaturan kendiri bagi kesemua pemboleh ubah bersandar. Satu dapatan

nyata daripada kajian ini ialah, pelajar tahap rendah dan tahap tinggi telah

memperolehi manfaat yang setara dalam prestasi pembelajaran pemindahan dekat.

Selain itu, dalam kumpulan kaedah deduktif, pelajar tahap rendah dan tinggi juga

memperolehi skor yang sama bagi prestasi pembelajaran pemindahan dekat dan

penglibatan pembelajaran. Secara umumnya, dapatan-dapatan ini menunjukkan

kesan positif, khususnya yang dibawa oleh mod induktif terhadap prestasi dan

penglibatan pelajar bagi pembelajaran topik ‘Persamaan Garis Lurus’. Lantaran itu,

perekabentuk koswer, penulis buku, pegawai pendidikan dan guru harus

mempertimbangkan penggunaan kaedah induktif agar pemindahan pembelajaran

dalam matematik dapat dilaksanakan dengan jayanya. Selain itu koswer multimedia

interaktif berdasarkan kaedah induktif boleh digunakan sebagai media yang

berpotensi untuk membantu pelajar yang memiliki tahap pembelajaran pengaturan

kendiri yang berlainan.

xxi

THE EFFECTS OF DEDUCTIVE AND INDUCTIVE BASED

COURSEWARE ON LEARNING PERFORMANCE AND ENGAGEMENT

AMONG STUDENTS WITH DIFFERENT LEVELS OF

SELF- REGULATED LEARNING

ABSTRACT

Mathematical knowledge gained by the students must be successfully transferred to

another domain or problem which will enable them to handle real life problems.

Literature supports that designing and making one’s own conclusion of the learnt

concepts can produce students who are thinkers and innovators which will lead to a

better transfer of learning. Therefore, pedagogical shift from delivering a whole mass

of knowledge that is mostly memorized to one that enhances students’ thinking skills

is necessary. In this study, a combination of creative instructional method and

interactive multimedia that allows students to construct their own knowledge in

mathematics concepts is proposed. This study is conducted to examine the effects of

interactive multimedia courseware (IMCSL) with different instructional methods on

Form Four students’ learning performance and engagement in the mathematics topic

of ‘Straight Line’. Two modes of IMCSL were developed, with one using the

deductive method (DM) and the other using inductive method (IM) in presenting the

mathematics contents. The DM was assigned to 97 students whereas the IM was

assigned to 94 students. This quasi-experimental study employed a 2 x 2 factorial

design. The independent variable was the instructional method namely; DM and IM

incorporated in an IMCSL. The dependent variables were the students’ performance

scores in near transfer of learning, far transfer of learning and also their learning

engagement score. The students’ self-regulated learning (SRL) level – either low

self-regulated learning (LSRL) or high self-regulated learning (HSRL) was identified

xxii

as the moderator variable. Findings on the main effect of the treatment conditions

indicated that the IM group scored significantly higher than the DM group in terms

of near transfer, far transfer and learning engagement. As for the main effects of

their SRL levels, the HSRL students performed significantly better than the LSRL

students in far transfer performance and learning engagement. The findings also

outlined significant interaction effect between treatment conditions and the students’

SRL levels on near transfer, far transfer and learning engagement. One key finding

that was discovered in this study was that the LSRL and HSRL students profited

equally in the measures of near transfer performance. These two categories of

students in the DM group also scored equally in near transfer and learning

engagement. Overall, these findings support the positive effects of IMCSL using IM

on the learning of ‘Straight Line’. Based on these positive impacts of inductive-based

courseware on LSRL and HSRL students, courseware designers, book writers,

education officers and teachers should consider applying the inductive examples as a

transition towards transfer of learning in mathematics and also as a promising

medium to accommodate the different SRL levels in students.

1

CHAPTER 1

INTRODUCTION

1.1 Introduction

Malaysia’s long term vision 2020 calls for establishing a scientific and

progressive society that is innovative and forward-looking. The vision intends to

produce a society which is not only a consumer of technology but also a contributor

to the scientific and technological civilization of the future. Vision 2020 can only be

achieved by producing a critical-thinking workforce which is technology-literate and

is prepared to participate fully in the global economy of the 21st century (Mahathir,

1991). A reformation in the educational system was seen as an important means to

realize this vision.

The Ministry of Education Malaysia has since initiated the transformation of

the nation’s educational system whereby multimedia learning using information

communication technology (ICT) has been the central concept. The usage of

multimedia courseware in the education system obviously benefits teachers and

students in the teaching and learning process (Harun & Tasir, 2003). Cognizant to

this vision, the ministry has launched the Smart School project in 1997. Malaysian

government began to equip schools with ICT equipment and digital learning objects

such as CD-ROMS, laptops, LCD projectors and learning packages to teachers. The

government is channeling a huge sum of expenditure to upgrade and improve the

education system in Malaysia. However whether there has been a fair return of

investment towards this end is still questionable.

2

Besides this, an educational reformation in mathematics and science was also

seen as an important move in realizing the vision 2020. The mathematics curriculum

only became standardized and official after the year of 1956 when the Razak Report

suggested that there should be a formal curriculum for all government schools (Heng

& Tan, 2006). The Malaysian Education Ministry has revised the mathematics

syllabus several times to improve its curriculum and has introduced various

movements to enhance the usage of ICT in the subject to fulfil the needs of the

students in today’s technology world. Technology is an essential tool for learning

mathematics in the 21st century (Dede, 2000).

The recent Trends in International Mathematics and Science Study (TIMSS)

shows that Malaysia’s ranking in Mathematics fell from 20th in 2007 to 26th in 2011

while its ranking in Science fell by an ever greater margin, from 21st in 2007 to 32nd

in 2011 (Mullis et al., 2012). The average Mathematics score fell from 474 in 2007

to 440 and the average Science score fell by an even greater degree from 471 in 2007

to 426 in 2011 (Daniel, 2013). Thus, the launch of the Preliminary Malaysia

Education Blueprint 2013-2025 (Pelan Induk Pembangunan Pendidikan) on Sept 11,

2012 acknowledges weaknesses in the education system and seeks to produce

students who will be thinkers and innovators, prepared for jobs that are yet to exist.

The main aim of the blueprint is to move the Malaysian students from the bottom

one-third category to the top one-third in the world.

With this, the students’ interest in science and mathematics should be enhanced

as these are the fundamental subjects in the usage of advanced technology. Effective

teachers maximize the potential of technology to develop students’ understanding,

stimulate their interest, and increase their competency in mathematics. However,

3

many Malaysian teachers are still skeptical and lack creativity in the use of

technology in teaching mathematics (Lau & Sim, 2008). Since Malaysia is

committed to develop and provide world class educational system, an effective

instructional medium is needed in order to transfer the knowledge learnt by the

students within and to other domains. This will produce students who are able to

transfer learning from one setting to another which is essential as the knowledge and

job skills needed to be productive are also changing with the rapid changes in

technology.

Teachers need to understand their students’ potential problems and learning

difficulties in order to implement effective instructional method to produce

meaningful learning among students (Meese, 2001). Malaysian education system

must also be in line to meet the needs of new economy which is the thrust of

knowledge, innovation and technology (Najib, 2012). The Ministry of Education

reiterated in its Preliminary Malaysia Education Blueprint 2013 - 2025 that it will

leverage on all existing ICT initiatives such as expanding the 1 BestariNet (Wifi) for

all schools by 2013 in order to scale up quality learning across Malaysia (Educational

Planning and Research Division, 2012). This must be incorporated with the effective

and creative instructional methods to enhance the students’ learning.

It has been reported that mathematics is a subject that is difficult to understand

by many students and they exhibited weakness in mastering the mathematics skills

(Berch & Mazocco, 2007; Pegg, Graham, & Bellert, 2005; Seo & Bryant, 2009;

Tambychik & Meerah, 2010; Tambychik et al., 2010). Hence, a pedagogical shift

from delivering a whole mass of knowledge that is mostly memorized to one that is

problem solving oriented is necessary. Knowledge should be delivered to enhance

4

students’ thinking skills. Thus, this study intended to investigate the effectiveness of

two different instructional methods on students’ performance in the transfer of

knowledge and learning engagement in learning mathematics by using an interactive

multimedia courseware. The main aim of this study was to find a suitable

technology-based instructional method which will enable students to transfer

learning from one setting to another, thus, producing critical thinking students who

will help to fulfill the main aim of the Preliminary Malaysia Education Blueprint

2013-2025.

1.2 Research Background

Technology innovations have brought tremendous changes in the Malaysian

education system. In the aim to produce a technological literate society, the

traditional chalk-and-talk method of teaching which has been used for decades in the

Malaysian educational system has been modified and enhanced by the technological

advances. The introduction of ETeMS (English for Teaching Mathematics and

Science) initiative in 2003 and Smart Schools’ policy in 1999 have enhanced the

instructional technology environment in schools. In line with the ETeMS policy,

many educational digital materials were designed and developed to aid teachers.

This move was also to incorporate ICT into the teaching and learning of

mathematics. It was also to take science and mathematics to international standards.

New technological teaching methods were introduced and used by the teachers to

improve the students’ mathematical understanding. However, it was uncertain how

many teachers were using the digital materials provided by the Ministry of

Education.

5

Mathematics is a compulsory subject in all primary and secondary schools in

Malaysia. It is the foundation for many fields of study such as engineering, science,

medicine, business, economics and many other subjects. There have been many

issues pertaining to the competency of mathematics among teachers and students.

With this, the Malaysian government took many steps to raise the teachers’

knowledge on pedagogy, content and technology and also the students’ conceptual

understanding, knowledge and skills in mathematics through the instructional

technology environment.

The use of technology in conjunction with effective instructional method is

emphasized in most of the delivery methods of knowledge to enhance better

mathematical understanding among students. The various innovations in the

Malaysian education system show a gradual paradigm shift from objectivism to

constructivism learning environment. However, the educational approach is very

much into teacher centered. Teachers have been encouraged to deliver an instruction

mode which is more student centered where students can construct their own

knowledge critically. Despite teachers attending many courses and teaching

programs, there is still a lot of room for improvement in conducting a constructivist

learning environment which focuses heavily on students’ involvement. Students’

learning is dependent on the quality of instruction that teachers provide in the

classroom (Zakaria & Iksan, 2006).

With the use of computer technology and appropriate pedagogical and content

knowledge, learning should not only be about mastering the information. It is more

of designing and making one’s own conclusion of concepts learnt that can produce

students who are thinkers and innovators. As such, teachers are encouraged to use the

6

appropriate multimedia materials, learning method and instructional strategy to help

the students experience and construct abstract ideas (Ministry of Education, 2006).

Furthermore, the establishment of Smart Schools across Malaysia has activated a

demand for more locally produced educational multimedia courseware. Most of the

foreign educational multimedia courseware is not quite appropriate for the Malaysian

educational environment and learning needs (Boon Shiong et al., 2008). Most of the

courseware provided by the Malaysian Ministry of Education, Curriculum

Development Centre and the commercialized CD-ROMs are based on the behaviorist

and objectivist model that encourage rote learning (Vikneasvari, 2007). This is

similar to teacher-centered teaching where the computer is used to replace the

teachers in transferring the knowledge to the students.

The constructivist approach with the use of different instructional methods in

an interactive multimedia courseware should be explicitly implemented to ensure

students construct their own mathematical concepts and knowledge. This is to ensure

that the mathematical knowledge gained is successfully transferred to another

domain or problem which will enable them to handle real life problems. This is in

par with the Preliminary Malaysia Education Blueprint (2013-2025) which focuses

on key changes to bring about more effective teaching and learning in the classroom

to match global standards.

Education is a main concern in Malaysia and every year, the government

allocates a big percentage of the federal budget for the development expenditure in

education. Many education policies have been developed and implemented to

upgrade and improve the education system in Malaysia. Taking cognizance to this

importance, Malaysia has allocated 21.7% of the total budget for the operational and

development expenditure in year 2009 for education (SSY Partners Chartered

7

Accountants, 2010). This amount of allocation is huge by any standards, even for

developed countries like Korea and Singapore. With the government spending such

a huge sum of money in its continuous effort to upgrade and improve the education

system in Malaysia, has there been a fair return of investment towards this end? To

measure if there has been a fair return on this investment, an analysis on students’

performance in Mathematics and Science would be a good yardstick.

Malaysia has been participating in the Trends in International Mathematics and

Science Study (TIMSS) since 1999. The population of the international assessment

study are students from the fourth and eighth grades. TIMSS are divided into content

and cognitive domain scores with the International Benchmark of 500 points average

scale score. The score is to measure and analyze the performance of each country

based on their respective curriculum. Malaysian eighth graders (Secondary Form

Two students) had participated in TIMSS 1999, 2003, 2007 and 2011. Therefore a

comparison of mathematics achievement among these years can be made.

In the 2011 TIMSS, about 20% of Malaysian students failed to meet minimum

benchmarks for both mathematics and science. Malaysia was ranked 26th in

mathematics in this TIMSS 2011 assessment. (Malaysia was 20th in TIMSS 2007,

10th in TIMSS 2003 and 16th in TIMSS 1999). Based on the average scale score in

both Mathematics and Science (Table 1.1), there has been a great decline in both

subjects in 2011. The data obtained does not imply that the education policies and

the government’s effort are inefficient. There are many other factors that may have

influenced the scores such as inability of students in understanding the concept, lack

of critical thinking, lack of diversity in instructional strategy and learning method,

poor unrealistic examples in a topic and the limited use of ICT by teachers due to

time constrain.

8

Table 1.1 Malaysian Eighth-Graders (Secondary Two) Mathematics and Science

Achievement of TIMSS in 1999, 2003, 2007 and 2011 [National Center for

Education Statistics, Trends in International Mathematics and Science Study].

Average Scale Score

Subject 1999 2003 2007 2011

Mathematics 519 508 474 440

Science 492 510 417 426

(Source: http://nces.ed.gov/timss/)

The data in Table 1.2 shows that Malaysian students were outperformed in

mathematics by Singapore, Republic of Korea, Hong Kong, Chinese-Taipei and

Japan.

Table 1.2 Eighth-Graders (Secondary Two) Mathematics Achievement of TIMSS

in 1999, 2003, 2007 and 2011 [Trends in International Mathematics and Science

Study (TIMSS) 2011]

Average Scale Score

Countries 1995 1999 2003 2007 2011

Singapore 609 604 605 593 611

China Taipei - 585 585 598 609

Korea 581 587 589 597 613

Hong Kong 569 582 586 572 586

Japan 581 579 570 570 570

Malaysia - 519 508 474 440

(Source: http://timss.bc.edu/timss2011)

Figure 1.1. Mathematics Achievements in TIMSS 1999 - 2011

http://nces.ed.gov/timss/

http://timss.bc.edu/timss2011

9

Figure 1.1 shows the trends in mathematics achievement of form two students

in Malaysia in their participation in TIMSS 1999 – 2011. There is a great decline in

the performance of mathematics in the TIMSS assessment.

Malaysia has also been participating in the Programme for International

Student Assessment (PISA) arose from the Organisation for Economic Co-operation

and Development (OECD) policy initiatives in the second half of the 1980s. PISA is

an international study which began in the year 2000. It aims to evaluate education

systems worldwide by testing the skills and knowledge of 15-year-old students in

participating countries. Since the year 2000, over 70 countries and economies have

participated in the PISA assessment. An additional 10 economies were added in 2010

under PISA 2009+ in which Malaysia is one of them. The PISA sample is drawn

from the population of students aged between 15 years and 16 years (equivalent

to Grade 9 or above) who attend educational institutions. PISA assesses outcomes

primarily in the areas of reading literacy, mathematical literacy and scientific

literacy.

Mathematical literacy assessed in PISA is an individual’s capacity to identify

and understand the role that mathematics plays in the world. Besides this, the

assessment also sees the individuals’ capacity to make well-founded judgements and

to use and engage mathematics in ways that meet the needs of that individual’s life as

a constructive, concerned and reflective citizen. Students in Malaysia attained a mean

score of 421 on the mathematical literacy scale (PISA, 2012). This mean score is

below the average mean score of 500 in the PISA assessment. Malaysia’s mean

score is also lower than all the means attained in all OECD countries. In Malaysia,

only 41% of students are proficient in mathematics at least to the baseline level at

10

which they begin to demonstrate the kind of skills that enable them to use

mathematics in ways considered fundamental for their future development.

Based on the data on TIMSS and PISA assessment, it is unfair to say that the

education policy has failed to improve the performance of students. A more detailed

emphasis should be given to the reformation of education system to enhance

students’ performance in mathematics. There is also a general perception among

students in Malaysia that mathematics is a difficult, abstract and a boring subject

(Azizi, Jamaluddin & Yusof, 2007). Students are not interested in following

mathematics lessons and they lack learning engagement in this subject. They are shy

to voice out their opinion since most of them are used to the supervised instruction

and learn through the traditional approach. This is contrary to the essence of

mathematics education where students have to gather information, think, analyze,

engage in learning and apply knowledge or concepts in solving real life problems.

Malaysian mathematics teachers carry a difficult task in producing students

with a world class mathematical competency. Despite numerous curricular programs

organized by the Ministry of Education (MOE), students’ performance in

mathematics has not shown significant improvement (Sharifah, 2003). Table 1.3

shows the analysis of students’ mathematical performance for the Sijil Pelajaran

Malaysia (SPM) for the year 2008 - 2012.

11

Table 1.3 Analysis of Mathematics Performance in the SPM Exam

2008 – 2012.

(Source: Malaysian Examination Board, 2008 – 2012)

The data shows that students’ performance in mathematics are equally

scattered from Distinction (A+, A and A-), Credit (B+, B, C+ and C), Pass (D and E)

and Fail (G). Majority of them obtained either pass or fail in 2008 (51.5% as

compared to 48.5% who scored Distinction and Credit). However, there are some

small changes from 2009-2012. Though it is a very minimum improvement, students

are incapable to keep up with the international scene in the TIMSS and PISA exams

as both assessments, require them to use the higher order thinking skills.

Algebra is one topic that is commonly viewed as a difficult topic by many

students in the Malaysian secondary school. The study of algebra is essential because

it has important applications to topics in basic mathematics and other subjects

(Downing, 2009). The low ranking in TIMSS 2011 reflects that the eighth graders’

level of algebra thinking is still far from satisfactory. Based on the 2011

mathematics TIMSS content analysis (Zabani, 2012), Malaysian eighth graders

performed satisfactorily well only in the number and geometry domain. The

students’ performance was poor in algebra, data handling and probability questions.

As for the cognitive domain, students performed well in the knowing and applying

level but were weak in the reasoning level. Figure 1.2 shows part of the mathematics

results of TIMSS 2011 for eighth-grade Malaysian students on content and cognitive

Year Distinction Credit Pass A+ E Fail Number of

students

GPMP

2008 26.6 22.0 29.0 77.5 22.5 381,567 5.54

2009 28.8 21.9 27.2 77.9 22.1 399,085 5.29

2010 31.1 23.6 25.9 80.6 19.4 401,558 5.05

2011 28.7 23.9 28.0 80.6 19.4 402,747 5.21

2012 32.7 23.2 25.1 81.0 19.0 406,134 4.91

Percentage of student (%)

12

domains (Zabani, 2012). It is important to provide students with a strong foundation

of algebra because algebra is a foundation study in fields such as science,

engineering, architecture, geology and astronomy (Arcavi, 2003).

Figure 1.2 Cognitive and Content Domains of Mathematics in TIMSS 2011

(Zabani, 2012)

TIMSS questions basically test the thinking skills of students in the usage of

mathematical concepts in real life situations. The poor performance of TIMSS (1995

– 2011) shows that Malaysian students are unable to transfer their mathematical

knowledge into an unfamiliar situation or other subject domains. According to Zainal

(1998), Malaysian students in schools might know how to count but they are unable

to apply mathematics concept in questions that involved real life situations. Thus,

transfer of learning and problem solving skills should be emphasized among students

Cognitive Domains

60

30

0

-30

-60

Kn

ow

ing

Ap

ply

ing

Rea

son

ing

Content Domains

60

30

0

-30

-60

Nu

mb

er

Alg

ebra

Geo

met

ry

Dat

a &

Ch

ance

13

in Malaysia. According to Posamentier and Krulik (1998), solving mathematical

problems is a skill that will be carried over to everyday problem and serve a person

well throughout life.

Many studies have been carried out to investigate the effectiveness of learning

mathematics using various teaching strategies, learning methods and digital materials

available. However, very few studies have been carried out to measure the

effectiveness of using digital materials developed with different instructional

methods which emphasize on higher order thinking skills (HOTS) to enhance

students’ performance in mathematics. Studies on the effects of other alternative

instructional strategies in the teaching and learning of mathematics such as

constructivism, e-learning and cooperative learning have been established in

Malaysian secondary schools. However, the effects of interactive multimedia

materials with deductive and inductive teaching methods on different level of self-

regulated learning students’ mathematical performance and learning engagement are

yet to be discovered although studies on the effects of deductive and inductive

approaches in the teaching of science and mathematics subjects have been reported

in Malaysia. No further empirical studies has being undertaken on the present digital

natives in this aspect.

The main reason that hinders the performance of Malaysian students in the two

international assessment is the inability to think critically to solve HOTS questions.

Thus, a suitable instructional method is important to enable students master the

concept being taught. In this study, an interactive multimedia courseware which was

designed and developed based on deductive method and inductive method for the

Malaysian educational environment was used to see which method would help

14

students enhance their higher order thinking skills thus enabling the transfer of

learning.

1.3 Problem Statement

Mathematics is essential to the development of science and technology. Thus,

the acquisition of mathematical knowledge is important for Malaysia to achieve its

vision of becoming a developed nation by year 2020. The analysis TIMMS report of

mathematics ranking of Malaysia has left much to be desired. Obviously, Malaysian

students’ performance in mathematics needs to be improved to keep up with the

international scene. As the questions in TIMSS and PISA are related to HOTS, the

poor performance of Malaysian students in these international assessment can be said

due to their lack of higher order thinking skills. Student are also unable to transfer

the knowledge learnt to another situation. This clearly shows the lack of systematic,

logical and creative thinking among the students in solving the mathematics

questions.

The discovery of ideas, theorems, methods of reasoning, and problem solving

by the students themselves should be the central objective of mathematics education

at every grade level. The treatments given to students regarding concept learning

should emphasize the "process-product" approach rather than merely providing

ready-made definitions and mechanical procedures that is devoid of meaning.

However, the process aspect of mathematics is neglected in most of the teaching.

Students tend to memorize rather than understand the mathematical concepts that

underlie due to the over emphasis on assessments and exams (Mohd, 2009).

15

Algebra has important application to real-life problems and is an instrumental

topic in producing critical thinkers. However, the performance of Malaysian

students in algebra was still unsatisfactory as shown in the recent TIMSS 2011

Report. Students will not learn algebra if they are memorizing rules for moving

symbols around on paper. Moreover, the use of symbols without an understanding

cannot develop students’ relational understanding of algebra (Foster, 2007). The

Straight Line topic is one important component of algebra which is used widely in

higher education and the working world. Learning, understanding and reasoning out

the Straight Line topic is not only important in understanding mathematics concept

but also essential in application to real life problems.

Lecture-based instruction and teacher-centered instruction are two pedagogical

limitations identified as the major shortcomings in traditional secondary mathematics

education in Malaysia (Zakaria & Iksan, 2006). The main aim of teaching should not

only be about transferring the mathematical knowledge but to allow students to

identify and construct the mathematical concept on their own. A pedagogical

innovation should take place in Malaysia where constructivist approach and student-

centered learning should be the priority in order to foster meaningful learning

amongst the students. Malaysian teachers must also carefully and smartly incorporate

ICT in their teaching and learning process as it can enhance the students

understanding and interest in the subject.

Therefore, this study was undertaken with the hope to find an appropriate

instructional method that can help students successfully transfer the knowledge

gained to another domain or problem which will enable them to solve real life

problems. The straight line topic from the algebra component was chosen as it is the

16

basis for the mastery of other subjects such as Additional Mathematics, Chemistry

and Physics. Two instructional methods; deductive and inductive methods were

chosen to see the effects on students’ performance in transfer of learning and

learning engagement. Technology was incorporated in the two methods to further

enhance students’ understanding of the concept taught. This study intended to find

the most appropriate instructional method to be used as a platform that will allow

students to perform higher order thinking skills and also to move the Malaysian

students in the international assessment from the bottom one-third category to the top

one-third in the world thus achieving the main aim of Preliminary Malaysia

Education Blueprint 2013-2025. Finally, this study hopes to add new knowledge to

the limited literature of deductive and inductive study using technology in Malaysian

secondary schools specifically on mathematics performance and learning

engagement among high and low self-regulated learning students.

1.4 Research Objectives

This study developed and used two interactive multimedia courseware on

straight line (IMCSL) with different instructional methods to enhance students’

transfer of learning performance. One of the IMCSL used the deductive method (DM)

and the other used the inductive method (IM) in presenting the mathematics contents.

Both the IMCSL were used in a constructivist environment which was student

centered. The IMCSL was used to identify the effectiveness of the two instructional

methods on the students’ transfer of learning performance. Two components of

transfer of learning; near transfer and far transfer were used to evaluate the students’

performance on conceptual understanding. Furthermore, this study investigated the

students’ learning engagement towards the two IMCSL that applied two instructional

17

methods. At the same time, this study also investigated whether the students’

different self-regulated learning level had an effect on the transfer of learning and

learning engagement. Therefore, this study was based on the following objectives:-

a) to design and develop an interactive multimedia courseware with two

treatment conditions; DM and IM

b) to investigate the effects of the DM compared to the IM in the learning of

Straight Line on the students’ near transfer and far transfer performance score

as well as learning engagement using an IMCSL.

c) to investigate the effects of DM compared to the IM in the learning of

Straight Line on the students’ near transfer and far transfer performance

score as well as learning engagement among low self-regulated learning

(LSRL) students and high self-regulated learning (HSRL) students using an

IMCSL.

d) to investigate the interaction effect of the treatment conditions and students’

self-regulated learning levels on students’ near transfer and far transfer

performance score as well as learning engagement.

1.5 Research Questions

Based on the proposed objectives, several research questions were derived:

1. Is there any significant difference in the near transfer performance score

between students following two instructional methods (DM and IM) using an

IMCSL?

2. Is there any significant difference in the near transfer performance score

between LSRL students and HSRL students in both treatment conditions?

18

3. Is there any significant interaction effect between treatment conditions and

students’ self-regulated learning levels on near transfer performance score?

4. Is there any significant difference in the far transfer performance score

between students following two instructional methods (DM and IM) using an

IMCSL?

5. Is there any significant difference in the far transfer performance score

between LSRL students and HSRL students in both treatment conditions?


students’ self-regulated learning levels on far transfer performance score?

7. Is there any significant difference in the learning engagement between

students following two instructional methods (DM and IM) using an IMCSL?

8. Is there any significant difference in the learning engagement between LSRL

and HSRL in both treatment conditions?


students’ self-regulated learning levels on learning engagement?

1.6 Research Hypotheses

The aim of this study was to investigate which mode of instructional method

(DM or IM) enhanced the performance of near transfer and far transfer and also the

learning engagement in learning the Straight Line using the IMCSL. Most of the past

studies looked into the ability of students to transfer their learning within the near

and far transfer of learning using multimedia in other subjects. Intention to use the

19

interactive multimedia courseware in mathematics with two different instructional

methods such as the deductive method and the inductive method to test the

performance of transfer of learning among different level of self-regulated learners

had not been emphasized. The following null hypotheses were formulated from the

research questions. The probability level of 0.05 was used to test the statistical

significance.

H01: There is no significant difference in terms of students’ near transfer

performance between students who received DM and IM using an IMCSL.

H02: There is no significant difference in terms of students’ near transfer

performance between LSRL and HSRL students in both treatment conditions.

H03: There is no significant interaction effect between treatment conditions

and students’ self-regulated learning levels on near transfer performance score.

H04: There is no significant difference in terms of students’ far transfer

performance between students who received DM and IM using an IMCSL.

H05: There is no significant difference in terms of students’ far transfer

performance between LSRL and HSRL students in both treatment conditions.


and students’ self-regulated learning levels on far transfer performance score.

H07: There is no significant difference in terms of students’ learning

engagement between students who received DM and IM using an IMCSL.

20

H08: There is no significant difference in terms of students’ learning

engagement between LSRL and HSRL students in both treatment conditions.


and students’ self-regulated learning levels on learning engagement score.

1.7 Theoretical Framework

The theoretical framework of this study was based on Ausubel’s Deductive

Model, Bruner’s Inductive Model, Mayer’s Cognitive Theory of Multimedia

Learning, Sweller’s Cognitive Load Theory and Bandura’s Social Learning Theory.

Mayer (2003) introduced e-learning where instruction is delivered on a

computer using a CD ROM and internet. The content of e-learning is based on the

learning objectives. The objective of e-learning material is to help students meet

their objective and to help students build knowledge to achieve their personal goals.

Mayer (2001) emphasizes a student-centered approach rather than the technology-

centered approach. The importance of learning is based upon the ability to grasp the

content and also to integrate the new information with prior knowledge to show a

successful transfer of knowledge. Mayer’s (2001) model on Cognitive Theory of

Multimedia Learning is based on the Information Processing Model (shown in

section 2.8). This theory was appropriate in supporting this study as the various

principles used in developing the IMCSL made the courseware a powerful medium in

enhancing learning.

The Cognitive Load Theory (Sweller, 1999) emphasizes on the limitation of

working memory capacity as an important factor in instructional design. Students

should be given a structured information to avoid unnecessary overload on working

21

memory. The theory is based on the assumption that a person has a limited

processing capacity and proper allocation of cognitive resources is important to

learning. Cognitive resources for learning decrease when more resources are needed

for processes which is not directly linked to learning. Learning engagement among

students is also effected by overload on working memory. Thus, this theory was used

carefully in designing the courseware to avoid unnecessary cognitive overload

among students when they were using the IMCSL to construct the knowledge and also

to enhance their learning engagement.

Ausubel’s deductive model (1968) shows students form and organize

knowledge themselves from a structured framework. The teachers’ duty is to

integrate the teaching material into a meaningful schema. The teacher is responsible

to expose the learning material meaningfully through the computer so that students

may follow and understand the concepts taught. In this study, the deductive method

was based upon this expository model.

Bruner’s inductive model (1971) is used in problem solving situations where

the student discovers facts and new truths based on his or her own past experience

and existing knowledge. Students are likely to remember concepts and knowledge

discovered on their own and this is a contrast to the traditional method. In this study,

the inductive method was based upon this discovery learning model. From the

presentation point of view in this study, the IMCSL was presented in a constructive

environment (student centered) where students solved the given problems by

constructing their own concepts and knowledge.

Pintrich & Zusho (2002) and Zimmerman (2000) stresses that self-regulation

operates through a set of psychological sub functions. These include self-monitoring

22

of one’s activities, applying personal standards for judging and directing one’s

performances, enlisting self-reactive influences to guide and motivate one’s effort

and applying appropriate strategies to achieve success. Self-regulating students

actively participate in learning from the metacognitive, motivational and behavioral

point of view. Characteristics attributed to self-regulating persons coincide with

those attributed to high-performance, high-capacity students as opposed to those with

low performance. Performance of students is influenced by self-regulated learning

levels especially in a student centered environment. Thus, in this study, the low and

high self-regulated learning levels were used to see the effect on the performance of

students. Mayer (2001) stresses multimedia learning engages active processes such

as paying attention to relevant information. The above mentioned theories and

models formed the theoretical framework of this study. The framework is depicted in

Figure 1.3.

23

Figure 1.3 Theoretical Framework

Ausubel’s Deductive Model (1968)

Advance organizer

Content Differentiation

Integration

Cognitive Theory of Multimedia

Learning (Mayer, 2001)

Multimedia principle

Contiguity principle

Modality principle

Redundancy principle

Coherence principle

Personalization principle

Alessi and Trollip

Instructional Design and

Development Model (2001)

Pintrich & Zusho, 2002

Zimmerman, 2000

Self- regulated

learning

Cognitive Load Theory

(Sweller, 1999)

Intrinsic load

Extraneous load

Germane load

Tutorial Model: Alessi

and Trollip (2001)

Bruner’s Inductive Model (1971)

Concept formation

Interpretation of data

Application of principles

Tutorial Model:

Sajap and Irfan (2004)

Alessi and Trollip (2001)

Mayer (2001)

Learning Engagement

24

1.8 Research Framework

24

Figure 1.4 Research Framework

Dep

end

ent

Vari

ab

les

Mo

der

ato

r V

ari

ab

le

Deductive

Method

Ind

epen

den

t V

ari

ab

le

Self-Regulated

Learning

Level

Straight Line Interactive

Multimedia Courseware

Performance

score on near

transfer

Inductive

Method

Performance

score on far

transfer

Learning

engagement

score

Sa

mp

le Form Four students from four secondary schools in Penang

(pretest given before the treatment)

posttest

the effects of deductive and inductive based...

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