Resource-adaptive Selection of Strategies in Learning from Worked-Out Examples

Peter Gerjets; Katharina Scheiter; Werner H. Tack

Resource-adaptive Selection of Strategies in Learning from Worked-Out Examples

Peter Gerjets ¹ Katharina Scheiter ¹ Werner H. Tack ¹

Abstract : Most tasks can be pursued by using different strategies (Logan, 1985; Reder & Schunn, 1998). In this paper we focus on strategies of learning from worked-out examples. Within a resourceoriented framework these different strategies can be classified according to their costs and benefits. These features may determine which strategy will be selected for accomplishing a task in situations with certain resource limitations. We investigate specific hypotheses about strategic adaptations to resource limitations (e.g., time pressure or lack of prior knowledge) within a hypertext-based learning environment. A comparison of the strategy selection of good and poor learners is used to assess the degree of subjects' resource adaptivity. Ideas for modeling resource- adaptive selection of strategies within the ACT-R architecture are discussed.

Document type :

Conference papers

Domain :

Computer Science [cs] / Technology for Human Learning

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https://telearn.archives-ouvertes.fr/hal-00190438
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