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The role of metacognitive skills in learning to solve problems

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<strong>to</strong> learn<strong>in</strong>g <strong>to</strong> <strong>solve</strong> <strong>problems</strong>. This approach comes close <strong>to</strong> the methods<br />

described at the task-level.<br />

<strong>The</strong> task-level consists <strong>of</strong> task knowledge and methods. Task knowledge<br />

is concerned with knowledge about various classes <strong>of</strong> generic tasks.<br />

For generic tasks different task structures exist that decompose them <strong>in</strong><strong>to</strong><br />

subtasks and activities. <strong>The</strong> activities are executed at the object-level.<br />

This decomposition <strong>of</strong> a task is called the method. <strong>The</strong> method thus<br />

concerns all relevant activities and the control mechanisms <strong>in</strong> order <strong>to</strong><br />

achieve the task goal. <strong>The</strong> method resembles the notion <strong>of</strong> compiled<br />

task models.<br />

<strong>The</strong> highest level <strong>in</strong> the problem solv<strong>in</strong>g process is the meta-level.<br />

This is a generic level that is doma<strong>in</strong>-<strong>in</strong>dependent. It consists <strong>of</strong> <strong>metacognitive</strong><br />

knowledge and <strong>skills</strong>. Metacognitive knowledge <strong>in</strong> this model<br />

<strong>in</strong>volves knowledge that classes <strong>of</strong> tasks exist and that problem solv<strong>in</strong>g<br />

methods exist for those classes. It also conta<strong>in</strong>s knowledge about when<br />

and how <strong>to</strong> use problem solv<strong>in</strong>g strategies. <strong>The</strong> regula<strong>to</strong>ry component<br />

<strong>of</strong> metacognition concerns doma<strong>in</strong>-<strong>in</strong>dependent <strong>metacognitive</strong> <strong>skills</strong> that<br />

deal with moni<strong>to</strong>r<strong>in</strong>g and controll<strong>in</strong>g the problem solv<strong>in</strong>g process <strong>in</strong> a<br />

generic way. Metacognitive <strong>skills</strong> dist<strong>in</strong>guished <strong>in</strong> the theoretical model<br />

are: Reflect<strong>in</strong>g on the nature <strong>of</strong> a problem, Comprehension moni<strong>to</strong>r<strong>in</strong>g,<br />

Predict<strong>in</strong>g consequences <strong>of</strong> activities, Plann<strong>in</strong>g, Moni<strong>to</strong>r<strong>in</strong>g, Check<strong>in</strong>g<br />

plausibility and Evaluat<strong>in</strong>g the problem solv<strong>in</strong>g process.<br />

Two ways <strong>of</strong> learn<strong>in</strong>g are predicted <strong>in</strong> the theoretical model, depend<strong>in</strong>g<br />

on whether a task-level is present. When this level is not present, a<br />

learner applies <strong>metacognitive</strong> knowledge and <strong>skills</strong> directly <strong>to</strong> the objectlevel.<br />

This results <strong>in</strong> the execution <strong>of</strong> cognitive activities relevant for<br />

solv<strong>in</strong>g a specific problem. Through the process <strong>of</strong> generalisation, learners<br />

may develop their own generic task knowledge and methods based<br />

upon the cognitive activities. When no task-level is present, the use <strong>of</strong><br />

<strong>metacognitive</strong> <strong>skills</strong> can have a lot <strong>of</strong> impact on learn<strong>in</strong>g because learners<br />

have no choice but <strong>to</strong> use their <strong>metacognitive</strong> <strong>skills</strong>, if available.<br />

<strong>The</strong> presence <strong>of</strong> a task-level takes over the function <strong>of</strong> the meta-level.<br />

In that case, learners may <strong>in</strong>ternalise task knowledge and methods <strong>to</strong><br />

such an extent that it is used au<strong>to</strong>matically when <strong>problems</strong> from the<br />

same class occur <strong>in</strong> the future. Instead <strong>of</strong> us<strong>in</strong>g any cognitive activity at<br />

any time, learners may then be acqua<strong>in</strong>ted with a compiled task model<br />

specific for the class <strong>of</strong> <strong>problems</strong> that helps them <strong>in</strong> regulat<strong>in</strong>g their<br />

learn<strong>in</strong>g and problem solv<strong>in</strong>g process.<br />

<strong>The</strong> ma<strong>in</strong> corollary <strong>of</strong> the theoretical model is that <strong>in</strong>clud<strong>in</strong>g a task<br />

model <strong>in</strong> a constructivist learn<strong>in</strong>g environment could provide sufficient<br />

support <strong>to</strong> the learner how <strong>to</strong> go about solv<strong>in</strong>g a difficult problem. Given<br />

that learn<strong>in</strong>g effects <strong>of</strong> games and simulations are suboptimal, this might

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