The Genetic Epistemology of Rule Systems

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/5740

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DC Field	Value	Language
dc.creator	Goldstein, Ira P.	-
dc.date	2004-10-01T20:33:27Z	-
dc.date	2004-10-01T20:33:27Z	-
dc.date	1978-01-01	-
dc.date.accessioned	2013-10-09T02:41:02Z	-
dc.date.available	2013-10-09T02:41:02Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-449	-
dc.identifier	http://hdl.handle.net/1721.1/5740	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	I shall describe a model of the evolution of the rule-structured knowledge that serves as a cornerstone of our development of computer-based coaches. The key idea is a graph structure whose nodes represent rules, and whose links represent various evolutionary relationships such as generalization, correction, and refinement. This graph guides both student modelling and tutoring as follows: the coach models the student in terms of nodes in this graph, and selects tutoring strategies for a given rule on the basis of its genetic links. It also suggests a framework for a theory of learning in which the graph serves as a memory structure constructed by the student by means of processes corresponding to the various links. Given this framework, a learning complexity measure can be defined in terms of the topology of the graph.	-
dc.format	45 p.	-
dc.format	14897916 bytes	-
dc.format	10533434 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-449	-
dc.title	The Genetic Epistemology of Rule Systems	-
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