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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
6.6 Research Question 4: Effect of the Treatment Conditions on
Students’ Far Transfer Performance Score …………………………. 207
6.7 Research Question 5: The Effect of the SRL Levels on Students’
Far Transfer Performance Score ……………………………………. 209
6.8 Research Question 6: The Interaction Effect between Treatment
Conditions and Students’ SRL Levels on Far Transfer …………….. 211
6.8.1 The Interaction Effect between the Treatment Conditions and
LSRL on the Far Transfer Performance of the Study ……….. 212
6.8.2 The Interaction Effect between the Treatment Conditions and
HSRL on the Far Transfer Performance of the Study ……….. 215
6.8.3 The Interaction Effect between the DM and SRL Levels on
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
6.9 Research Question 7: Effect of the Treatment Conditions on
Students’ Learning Engagement Score ……………………………... 220
6.10 Research Question 8: Effect of the Self- Regulated Learning (SRL)
Levels on Students’ Learning Engagement Score ………………….. 221
6.11 Research Question 9: The Interaction Effect between Treatment
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
6.11.3 The Interaction Effect between the DM and SRL Levels on
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
Figure 5.7 A Scatterplot Showing Relationship between Pretest and
Posttest for IM Group
171
Figure 5.8 A Scatterplot Showing Relationship between Pretest and
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
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?
6. Is there any significant interaction effect between treatment conditions and
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?
9. Is there any significant interaction effect between treatment conditions and
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.
H06: There is no significant interaction effect between 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.
H09: There is no significant interaction effect between 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