The role of metacognitive skills in learning to solve problems

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46 Learning goals include the acquisition of both declarative knowledge about concepts and relations between them in the domain of knowledge management, and also procedural knowledge about how to solve knowledge management problems. These learning goals are further elaborated on page 53. Figure 3.2. The start page of KM Quest. The effects of interventions on Coltec are simulated by a business model (BM) in KM Quest (De Hoog et al., 2001; De Hoog et al., 2002). Over 500 indicators exist in the BM which are organised in four layers (figure 3.3). The two upper layers of indicators are business-related, the two bottom layers are knowledge-related. The Organisational Effectiveness Indicators (OEI) are situated at the top level of the BM. They represent the relation between the organisation and its environment. This layer consists of three indicators: market share (MS), customer satisfaction index (CSI) and profit (P). The values of these three indicators have a central place in the start page of KM
KM Quest 47 Quest. They are visualized on the white board in the office in KM Quest (figure 3.2). The business process-related variables reflect the way processes run inside the company. Examples of business-related indicators are the number of employees in the marketing department, the number of patents pending, and the product quality index. Knowledge-related indicators represent the relevant knowledge departments in the organisation and their properties. Knowledge departments represent organisational units within Coltec. Three knowledge departments are distinguished: the Marketing, Production and R&D department. Examples of indicators in this layer are the level of competence in each of the departments. Knowledge process-related indicators reflect the properties of knowledge processes in Coltec. Knowledge processes in KM Quest are similar to the classes of knowledge operations distinguished in the KM model by Wiig et al. (1997). Knowledge processes distinguished in KM Quest are: Gaining (bringing new knowledge from outside, into the company), Development (making knowledge in Coltec more relevant for the work performance), Utilisation (implementing work solutions and new ideas), Transfer (making knowledge from one department available to the other departments) and Retention (safeguarding knowledge from loss). Transfer in KM Quest equals ‘Distribution’ in Wiig’s model. Utilisation is a process that is not part of Wiig’s model. For each knowledge process, three properties are distinguished: speed (the speed at which a knowledge process takes place), effectiveness (the degree to which a knowledge process realizes the intended purpose) and efficiency (the time versus resources ratio; e.g. knowledge gaining is efficient if relevant knowledge is received from outside Coltec with a minimum expenditure of energy, time and resources). Figure 3.3 also depicts the relation between the four layers of indicators, and the events and interventions. Events can be either internal or external. An internal event is ,for instance, the fact that a senior manager from the marketing department leaves the company. Internal events influence the properties of knowledge processes in Coltec. When a senior manager leaves the company, essential knowledge is lost, resulting in a decrease of the effectiveness of knowledge retention. A typical external event is the fact that a competitor of Coltec brings a new product on the market. External events influence the main organisational indicators. When a competitor brings a new product on the market, Coltec experiences a threat to its market share. Interventions are the solutions the knowledge manager can propose to improve the knowledge household of Coltec. These interventions influence properties of the knowledge
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The role of metacognitive skills in
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The role of metacognitive skills in
Page 5 and 6: Contents 1. INTRODUCTION 1 2. THEOR
Page 7: Contents ix 6. STUDY III: ADDED VAL
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: KM Quest 45 a dynamic simulation-ga
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
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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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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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The role of metacognitive skills in learning to solve problems

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