The role of metacognitive skills in learning to solve problems

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viii 3.2.2 The paper-based Coltec material 42 3.2.3 Method 43 3.2.4 Summary of results & conclusions 44 3.3 KM Quest 45 3.3.1 The task model in KM Quest 49 3.3.2 Learning goals 53 3.3.3 KM Quest and the constructivist paradigm 53 4. STUDY I: PILOT 57 4.1 Introduction 58 4.1.1 Types of learning 58 4.1.2 Measuring metacognition 60 4.2 Method 63 4.2.1 Participants 63 4.2.2 KM Quest 63 4.2.3 Instruments 63 4.2.4 Procedure 66 4.3 Results 66 4.3.1 Participants 66 4.3.2 Learning results 66 4.3.3 Metacognition 71 4.3.4 ANALOG 74 4.3.5 Process data analysis 78 4.4 Conclusions 82 5. STUDY II: LEARNING REVISITED 85 5.1 Introduction 85 5.2 Method 86 5.2.1 Participants 86 5.2.2 KM Quest 87 5.2.3 Instruments 87 5.2.4 Procedure 90 5.2.5 Analysis procedures 91 5.3 Results 91 5.3.1 Game results 91 5.3.2 Learning effects 92 5.3.3 Metacognition 96 5.3.4 Process measures 96 5.4 Discussion 98
Contents ix 6. STUDY III: ADDED VALUE OF THE TASK MODEL 101 6.1 Introduction 102 6.1.1 Knowledge acquisition and transfer 102 6.1.2 Task model 103 6.1.3 Measurement of metacognition 104 6.1.4 Hypotheses 105 6.2 Method 106 6.2.1 Participants 106 6.2.2 Game configuration 106 6.2.3 Instruments 107 6.2.4 Procedure 115 6.2.5 Statistics and a-priori comparisons 116 6.3 Results 118 6.3.1 Game results 118 6.3.2 Prospective and retrospective measurements 121 6.3.3 Concurrent measurement 130 6.3.4 Additional measures 135 6.3.5 Overview of results 141 6.4 Discussion and conclusions 144 7. CONCLUSIONS 149 7.1 Introduction 149 7.2 Learning to solve problems 150 7.3 Role of metacognition 152 7.4 The value of a task model 154 Appendices 156 Solving a problem in KM Quest 157 A.1 Introduction 157 A.2 FOCUS phase 157 A.3 ORGANISE phase 159 A.4 IMPLEMENT phase 160 A.5 MONITOR phase 160 8. SUMMARY 163 9. SAMENVATTING 171
Page 1 and 2: The role of metacognitive skills in
Page 3 and 4: The role of metacognitive skills in
Page 5: Contents 1. INTRODUCTION 1 2. THEOR
Page 10 and 11: xii Rienke Schutte, zonder de medew
Page 12 and 13: 2 in realistic settings and everyda
Page 14 and 15: 4 use a trade-off between efforts i
Page 16 and 17: 6 of this thesis are described. In
Page 18 and 19: 8 First an overview of relevant lit
Page 20 and 21: 10 In research concerning reading a
Page 22 and 23: 12 problem has actually been found
Page 24 and 25: 14 or whether domain specific metac
Page 26 and 27: 16 learners should be able to artic
Page 28 and 29: 18 piece of origami paper. Both mat
Page 30 and 31: 20 tion given to the problem solver
Page 32 and 33: 22 is rather directive. It does not
Page 34 and 35: 24 The problem solver has declarati
Page 36 and 37: 26 problem and the fact that studen
Page 38 and 39: 28 learn from them. In terms of Jan
Page 40 and 41: 30 This model is called DORMOBILE (
Page 42 and 43: 32 Second, the meta-level in proble
Page 44 and 45: 34 Figure 2.8. Theoretical model of
Page 46 and 47: 36 task-level. In order to keep the
Page 49 and 50: Chapter 3 KM QUEST The goal of this
Page 51 and 52: KM Quest 41 Figure 3.1. The Knowled
Page 53 and 54: KM Quest 43 the fact that some plan
Page 55 and 56: KM Quest 45 a dynamic simulation-ga
Page 57 and 58:
KM Quest 47 Quest. They are visuali
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KM Quest 49 cesses in Coltec. For e
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KM Quest 51 Figure 3.5. The Knowled
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KM Quest 53 3.3.1.3 The IMPLEMENT p
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KM Quest 55 process in an electroni
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Chapter 4 STUDY I: PILOT This chapt
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Study I: Pilot 59 the spontaneous o
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Study I: Pilot 61 Also, the questio
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Study I: Pilot 63 however, to what
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Study I: Pilot 65 ceived 12 questio
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Study I: Pilot 67 objective, a seco
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Study I: Pilot 69 other. It also ex
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Study I: Pilot 71 In conclusion, th
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Study I: Pilot 73 Finally, the othe
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Study I: Pilot 75 Figure 4.2. Scree
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Study I: Pilot 83 alizations of the
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86 of meaningful learning which can
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88 opportunity events (instead of t
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90 different occasions or settings.
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92 conceptual correctness (54) the
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94 The score on KMQUESTions indicat
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96 is a variable that influences th
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98 5.4 Discussion The hypothesis fo
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100 mal company results. In the fol
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102 more inclined to regulate domai
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104 these skills in order to solve
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106 Hypothesis 1: students acquire
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108 KMQUESTions of study II was per
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110 The second measurement of game
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112 T-PROS because they did not occ
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114 Category Rule Example Task Indi
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116 vised by one experimenter in or
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118 6.3 Results 6.3.1 Game results
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120 to Coltec. Only threats have a
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122 6.3.2.1 Effects of learning and
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124 Prospective Pre-test Post-test
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126 Distribution Frequency 1 high 2
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128 No − model Model Retrospectiv
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130 model condition. Perhaps, perfo
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132 Cog Tas Meta Total No-model con
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134 Condition * Metacognition G MET
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136 Figure 6.5. Relations between m
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138 in the model condition: Visuali
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140 Figure 6.7. Overview of relatio
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142 ‘monitoring’. Prospective s
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144 learning. Finally, in the no-mo
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146 inclusion of a task model speci
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148 interpreting the results on met
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150 When no task model is available
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152 Another perhaps more valid expl
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154 havioural measures prove to be
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Appendix A Solving a problem in KM
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APPENDIX A: Solving a problem in KM
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APPENDIX A: Solving a problem in KM
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164 to learning to solve problems.
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166 cognition in a constructivist l
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168 forward. The most important one
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Chapter 9 SAMENVATTING Het huidige
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Samenvatting 173 De aanwezigheid va
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Samenvatting 175 gebruik van metaco
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Samenvatting 177 nificant leereffec
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References Akhras, F. and Self, J.
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REFERENCES 181 Duffy, T. and Cunnin
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REFERENCES 183 Nelson, T. (1999). C
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REFERENCES 185 van Harmelen, F., Wi
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