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dc.contributor.authorGoldstein, Ira P.en_US
dc.date.accessioned2004-10-01T20:33:27Z
dc.date.available2004-10-01T20:33:27Z
dc.date.issued1978-01-01en_US
dc.identifier.otherAIM-449en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/5740
dc.description.abstractI 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.en_US
dc.format.extent45 p.en_US
dc.format.extent14897916 bytes
dc.format.extent10533434 bytes
dc.format.mimetypeapplication/postscript
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.relation.ispartofseriesAIM-449en_US
dc.titleThe Genetic Epistemology of Rule Systemsen_US


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