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The role of metacognitive skills in learning to solve problems

The role of metacognitive skills in learning to solve problems

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Summary 165<br />

be an improvement.<br />

In chapter 3 a learn<strong>in</strong>g environment for the doma<strong>in</strong> <strong>of</strong> Knowledge Management<br />

(KM) is described that permits empirical <strong>in</strong>vestigation <strong>of</strong> the<br />

theoretical model. An explora<strong>to</strong>ry feasibility study on a paper version <strong>of</strong><br />

the environment showed that a gam<strong>in</strong>g approach could elicit appropriate<br />

behaviour for learn<strong>in</strong>g <strong>to</strong> <strong>solve</strong> KM <strong>problems</strong>.<br />

<strong>The</strong> f<strong>in</strong>al learn<strong>in</strong>g environment is called KM Quest. In KM Quest,<br />

players are asked <strong>to</strong> manage the knowledge household <strong>of</strong> a fictitious<br />

company called Coltec. This company produces adhesives and coat<strong>in</strong>gs.<br />

Dur<strong>in</strong>g a number <strong>of</strong> quarters <strong>in</strong> the life <strong>of</strong> Coltec various events take<br />

place. Events are <strong>in</strong>cidents that represent a threat or an opportunity<br />

<strong>to</strong> Coltec. It is up <strong>to</strong> the players, who are organised <strong>in</strong> teams <strong>of</strong> three<br />

members, <strong>to</strong> react <strong>to</strong> these events, given their objectives concern<strong>in</strong>g the<br />

status <strong>of</strong> the knowledge household <strong>of</strong> the company.<br />

<strong>The</strong> behaviour <strong>of</strong> Coltec is simulated by a Bus<strong>in</strong>ess Model (BM). This<br />

bus<strong>in</strong>ess model consists <strong>of</strong> both knowledge and bus<strong>in</strong>ess <strong>in</strong>dica<strong>to</strong>rs such<br />

as the speed <strong>of</strong> knowledge ga<strong>in</strong><strong>in</strong>g <strong>in</strong> the Market<strong>in</strong>g department or the<br />

number <strong>of</strong> patents pend<strong>in</strong>g. Teams can react <strong>to</strong> events by choos<strong>in</strong>g<br />

<strong>in</strong>terventions. Interventions represent solutions for the KM <strong>problems</strong><br />

described <strong>in</strong> the events. Interventions positively affect the status <strong>of</strong><br />

the <strong>in</strong>dica<strong>to</strong>rs <strong>of</strong> the BM. It is up <strong>to</strong> the players <strong>to</strong> decide on a set <strong>of</strong><br />

<strong>in</strong>terventions that counteracts the effects <strong>of</strong> the events <strong>in</strong> order <strong>to</strong> achieve<br />

their objectives.<br />

<strong>The</strong> KM model is part <strong>of</strong> the game <strong>in</strong> order <strong>to</strong> support a systematic approach<br />

<strong>to</strong> problem solv<strong>in</strong>g. This model gives a cyclic, normative view on<br />

how KM <strong>problems</strong> can be <strong>solve</strong>d. This model comes close <strong>to</strong> the notion<br />

<strong>of</strong> the task model as discussed <strong>in</strong> the theoretical model <strong>in</strong> chapter 2. <strong>The</strong><br />

KM model consists <strong>of</strong> four phases: FOCUS, ORGANISE, IMPLEMENT<br />

and MONITOR. Each phase is decomposed <strong>in</strong><strong>to</strong> subtasks and activities<br />

relevant for that particular phase. In the FOCUS phase an analysis <strong>of</strong><br />

the knowledge household is made and bus<strong>in</strong>ess and knowledge objectives<br />

are stated. In the ORGANISE phase hypotheses are formulated concern<strong>in</strong>g<br />

the effects <strong>of</strong> types <strong>of</strong> <strong>in</strong>terventions on the knowledge household <strong>of</strong><br />

Coltec and <strong>in</strong>terventions are shortlisted. In the IMPLEMENT phase the<br />

<strong>in</strong>terventions are implemented and <strong>in</strong> the MONITOR phase the effects <strong>of</strong><br />

the <strong>in</strong>terventions are evaluated.<br />

In chapter 4 the results <strong>of</strong> the pilot study on KM Quest are described.<br />

This is an explora<strong>to</strong>ry study s<strong>in</strong>ce the <strong>in</strong>tended functionality <strong>of</strong> the<br />

simulation-game was not yet fully implemented. <strong>The</strong> two research goals<br />

that guide this study are: (1) <strong>to</strong> explore mean<strong>in</strong>gful learn<strong>in</strong>g and meta-

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