Skip to Main content Skip to Navigation
Conference papers

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

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
Complete list of metadata

Cited literature [13 references]  Display  Hide  Download
Contributor : Jerome Zeiliger Connect in order to contact the contributor
Submitted on : Friday, November 23, 2007 - 8:46:37 AM
Last modification on : Tuesday, September 17, 2019 - 10:38:09 AM
Long-term archiving on: : Monday, April 12, 2010 - 4:09:54 AM


Files produced by the author(s)


  • HAL Id : hal-00190438, version 1



Peter Gerjets, Katharina Scheiter, Werner H. Tack. Resource-adaptive Selection of Strategies in Learning from Worked-Out Examples. Twenty Second Annual Meeting of the Cognitive Science Society (CogSci2000), 2000, Philadelphia, United States. pp.161-171. ⟨hal-00190438⟩



Record views


Files downloads