The role of metacognitive skills in learning to solve problems

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96 is a variable that influences the dependent variable(s), for which the analysis should be controlled. Concerning declarative knowledge, an interaction effect is found with time-on-task (F = 7.68, p < 0.01). Furthermore, the test result shows a main effect of learning (F = 5.73, p < 0.05), which indicates that students acquired declarative knowledge from pre- to post-test. This result is similar to the results of the t-test. Concerning procedural knowledge, an interaction exists between the acquisition of procedural knowledge and time-on-task (F = 7.16, p < 0.05). Also a main effect exists for the acquisition of procedural knowledge (F = 5.88, p < 0.05). These results indicate that the overall time one spends playing KM Quest significantly influences the acquisition of both declarative and procedural knowledge from pre- to post-test. Students who spend more time on task, learn significantly more than students who spend less time. This implies that for future empirical studies, time-on-task should be taken into account. As for relations between game results and learning results, corrected for time on task, no significant correlations exist. 5.3.3 Metacognition The internal consistency of the scale metacognition of the MSLQ was calculated by means of Cronbach’s alpha. Alpha is 0.62. This indicates a moderate reliability. Students self-report to slightly agree using metacognitive skills in general (Mean = 3.92, SD = 0.48, N = 29, measured on a six-point scale) A partial correlation analysis was carried out in order to investigate the relation between learning and the self-reported use of metacognitive skills, corrected for pre-test scores. None of the relations between posttest measures of learning and self-reported use of metacognitive skills is significant. 5.3.4 Process measures An overview of the average time that a team spends on various elements of KM Quest is presented in figure 5.3. On page 90 the grouping of the elements is given. Figure 5.2 shows that 1 extreme case and two outliers exist. These cases are excluded from the data set. Two of these cases are member of team 82 (that only consisted of two members). Therefore this team is discarded from the analysis. The difference between this figure and table 5.3 is that the table gives an indication of average time per individual whereas the figure gives an indication of average time per team. Figure 5.3 shows that the teams vary quite a lot in the average amount of hours they spend playing KM
Study II: learning revisited 97 Figure 5.3. per team. Average time (hours) spent on using the various elements of KM Quest Quest. Resources are not used extensively. These include the handbooks incorporated in KM Quest. Quite some time is spent on the features of KM Quest. These include amongst others using the chat facility to communicate, the visualizations, the history books and the feedback on events. All teams spend a lot of time in the KM model. This takes up at least half of their playing time. This suggests that the KM model is at least partly responsible for the learning that takes place. An exploratory partial correlation analysis is performed in order to find out if a relation exists between post-test scores of learning (controlled for pre-test scores) and the time spend in the KM model. Posttest scores for both types of knowledge do not correlate significantly with time spend using the KM model. This exploratory analysis does not show any relation between the amount of time spent in the KM model versus knowledge acquisition. This hypothesis could however be investigated more thoroughly by contrasting a no-model environment with a model environment. This is also suggested by the theoretical model on page 32. In the next chapter this is taken into account in the design of the final experiment.
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The role of metacognitive skills in
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The role of metacognitive skills in
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Contents 1. INTRODUCTION 1 2. THEOR
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Contents ix 6. STUDY III: ADDED VAL
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xii Rienke Schutte, zonder de medew
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2 in realistic settings and everyda
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4 use a trade-off between efforts i
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6 of this thesis are described. In
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8 First an overview of relevant lit
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10 In research concerning reading a
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12 problem has actually been found
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14 or whether domain specific metac
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16 learners should be able to artic
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18 piece of origami paper. Both mat
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20 tion given to the problem solver
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22 is rather directive. It does not
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24 The problem solver has declarati
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26 problem and the fact that studen
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28 learn from them. In terms of Jan
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30 This model is called DORMOBILE (
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32 Second, the meta-level in proble
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34 Figure 2.8. Theoretical model of
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36 task-level. In order to keep the
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Chapter 3 KM QUEST The goal of this
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KM Quest 41 Figure 3.1. The Knowled
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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
Page 59 and 60: KM Quest 49 cesses in Coltec. For e
Page 61 and 62: KM Quest 51 Figure 3.5. The Knowled
Page 63 and 64: KM Quest 53 3.3.1.3 The IMPLEMENT p
Page 65 and 66: KM Quest 55 process in an electroni
Page 67 and 68: Chapter 4 STUDY I: PILOT This chapt
Page 69 and 70: Study I: Pilot 59 the spontaneous o
Page 71 and 72: Study I: Pilot 61 Also, the questio
Page 73 and 74: Study I: Pilot 63 however, to what
Page 75 and 76: Study I: Pilot 65 ceived 12 questio
Page 77 and 78: Study I: Pilot 67 objective, a seco
Page 79 and 80: Study I: Pilot 69 other. It also ex
Page 81 and 82: Study I: Pilot 71 In conclusion, th
Page 83 and 84: Study I: Pilot 73 Finally, the othe
Page 85 and 86: Study I: Pilot 75 Figure 4.2. Scree
Page 93: Study I: Pilot 83 alizations of the
Page 96 and 97: 86 of meaningful learning which can
Page 98 and 99: 88 opportunity events (instead of t
Page 100 and 101: 90 different occasions or settings.
Page 102 and 103: 92 conceptual correctness (54) the
Page 104 and 105: 94 The score on KMQUESTions indicat
Page 108 and 109: 98 5.4 Discussion The hypothesis fo
Page 110 and 111: 100 mal company results. In the fol
Page 112 and 113: 102 more inclined to regulate domai
Page 114 and 115: 104 these skills in order to solve
Page 116 and 117: 106 Hypothesis 1: students acquire
Page 118 and 119: 108 KMQUESTions of study II was per
Page 120 and 121: 110 The second measurement of game
Page 122 and 123: 112 T-PROS because they did not occ
Page 124 and 125: 114 Category Rule Example Task Indi
Page 126 and 127: 116 vised by one experimenter in or
Page 128 and 129: 118 6.3 Results 6.3.1 Game results
Page 130 and 131: 120 to Coltec. Only threats have a
Page 132 and 133: 122 6.3.2.1 Effects of learning and
Page 134 and 135: 124 Prospective Pre-test Post-test
Page 136 and 137: 126 Distribution Frequency 1 high 2
Page 138 and 139: 128 No − model Model Retrospectiv
Page 140 and 141: 130 model condition. Perhaps, perfo
Page 142 and 143: 132 Cog Tas Meta Total No-model con
Page 144 and 145: 134 Condition * Metacognition G MET
Page 146 and 147: 136 Figure 6.5. Relations between m
Page 148 and 149: 138 in the model condition: Visuali
Page 150 and 151: 140 Figure 6.7. Overview of relatio
Page 152 and 153: 142 ‘monitoring’. Prospective s
Page 154 and 155: 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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Prototyping of CMS Storage Manageme
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Human-Computer Interaction and Pres
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