Turning examples into cases: Acquiring knowledge structures for analogical problem solving

Autor:	Thomas J. Schult, Peter Reimann
Rok vydání:	1996
Předmět:	Computational model Experimental psychology business.industry Developmental and Educational Psychology Contrast (statistics) Artificial intelligence Psychology business Transfer problem
Zdroj:	Educational Psychologist. 31:123-132
ISSN:	1532-6985 0046-1520
DOI:	10.1207/s15326985ep3102_4
Popis:	It has often been observed that students learn from and use examples in a suboptimal fashion, leading to transfer problems. We address this important transfer problem by first identifying features of effective approaches to analogical problem solving, based on insights from experimental psychology and computational models. We then contrast the effective approach with the manner that the average student goes about learning from and using examples. This comparison allows us to identify certain problems with analogical problem solving that instructional measures should address. We describe the principle components of computer-based learning environments that should help students overcome such problems, and we provide an illustration with an implemented system that employs a dynamic case-based reasoning approach for tutoring about chess end games.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::882cbba4d0fdd05c0793a97a7b58a1bc https://doi.org/10.1207/s15326985ep3102_4 Zobrazit plný text záznamu