The role of metacognitive skills in learning to solve problems

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62 prior to task performance with one alteration, namely that questions can be made specifically applicable to the learning activity that has just been completed. Prospective and retrospective methods are usually less valid in determining metacognitive behaviour than concurrent ones (Veenman, 2001, Pintrich, Wolters & Baxter, 2000). One common pitfall is the phenomenon that students report that they use certain strategies but when compared to actual behaviour, the reported strategies do not always occur. Thus it is better to use concurrent methods. This is more so because results indicate that concurrent methods of measuring metacognitive behaviour such as the use of think-aloud protocols correlate more strongly with learning outcomes than other measures (Veenman, in press). The think-aloud method assumes that a participant verbalizes all thoughts that occur during the problem solving process. All the information that is active in the working memory of the participant is put into words (Van Someren, Barnard & Sandberg, 1994). The task of thinking-aloud usually does not interfere with task performance provided that participants are instructed merely to verbalise their thoughts, not to reflect on their thinking (Ericsson & Simon, 1990). Think-aloud protocols appear to be ideal in studying metacognition from an individual viewpoint but are they appropriate when learning is collaborative in nature? Collaborative learning requires students to externalize their thoughts and to monitor whether their ideas come across well. Since in collaborative learning communication is part of the task, it may very well interfere with using the think-aloud method in order to capture thought processes. Instead, the communication protocols that capture the ongoing discussions between learners and not the individual thought processes, could be used to tap (meta-)cognitive processes. According to Ericsson and Simon, the process of deliberately externalising thoughts to other learners does not necessarily reflect spontaneous thinking with complete accuracy. Both types of protocols might very well differ. However, collaborative learning could require learners to work in a more orderly way and to use more rigorous strategies to monitor the learning process. In fact, the authors argue that the necessity to verbalise thoughts in a coherent manner would require a more active approach to learning. In conclusion, to measure the use of metacognitive skills the preference is to use protocol analysis as a direct behavioural measure. It is plausible that students need their metacognitive skills in order to effectively communicate their ideas in a collaborative learning setting. The question is,
Study I: Pilot 63 however, to what extent the use of metacognitive skills is demonstrable in the communication protocols. The second hypothesis in this study is that metacognitive activities as delineated in the coding scheme can be identified in communication protocols originating from a collaborative learning setting. 4.2 Method 4.2.1 Participants Forty-one students from the Polytechnic Hogeschool Zuyd in Maastricht participated in the pilot study in Autumn 2002. The average age of these 41 students was 22.83 years (SD = 1.72). Twenty-four students were male, the remaining 17 female. Students were enrolled in the study of Information Management and Services. They were in the fourth year of their study. The pilot study took place during the course ‘Knowledge management’ that ran from September to October 2002. 4.2.2 KM Quest A detailed description of KM quest is presented in chapter 3 which covers the main functionalities of the game. However, the pilot study was conducted with prototype II of the learning environment. This prototype lacked certain functionalities with respect to the final version that is described in chapter 3. The functionalities that were not implemented in prototype II are: Group call, Visualizations, Advisor, History, the e- mail notification system that informs students overnight about changes in their environment and the information in the How to and What to work sheets. Additionally, several bugs existed in this prototype. They included the fact that the chat did not automatically refresh, players had to open and close chat windows in order to see the latest messages. Also voting for interventions was not protected. So, participants could vote under each other’s name. 4.2.3 Instruments 4.2.3.1 Learning results Several product measures for learning results were included in the study. Three sets of data were used. First, the status results of the three Organisational Effectiveness Indicators (OEI) in the 7th quarter in the game were used (see chapter 3). Game scores for the nine teams were created by transforming the results on the business indicators Customer Satisfaction Index (CSI), Market Share (MS) and Profit (P) to a 10-point scale and subsequently calculating the average of these three indicators per team. Second, institutional KM course grades served as an indication
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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
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
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: Study I: Pilot 61 Also, the questio
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 106 and 107: 96 is a variable that influences th
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
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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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Prototyping of CMS Storage Manageme
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Human-Computer Interaction and Pres
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A Model-driven Approach for Buildin
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