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Autor/inn/enWong, Lung-Hsiang; Looi, Chee-Kit
TitelAdaptable Learning Pathway Generation with Ant Colony Optimization
QuelleIn: Educational Technology & Society, 12 (2009) 3, S.309-326 (18 Seiten)Infoseite zur Zeitschrift
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1436-4522
SchlagwörterTechnology Uses in Education; Web Based Instruction; Internet; Artificial Intelligence; Cognitive Style; Intelligent Tutoring Systems; Adjustment (to Environment); Logical Thinking
AbstractOne of the new major directions in research on web-based educational systems is the notion of adaptability: the educational system adapts itself to the learning profile, preferences and ability of the student. In this paper, we look into the issues of providing adaptability with respect to learning pathways. We explore the state of the art with respective to deriving the most apt learning pathway to recommend to the learner. Our proposal suggests a novel way of modeling learning pathways that combines rule-based prescriptive planning, which could be found in many of the classic Intelligent Tutoring Systems, and Ant Colony Optimization-based inductive planning, for recommending learning paths by stochastically computing past learners' traveled paths and their performances. A web-based prototype has been developed using C# and .NET technologies. (Contains 4 figures and 4 tables.) (As Provided).
AnmerkungenInternational Forum of Educational Technology & Society. Athabasca University, School of Computing & Information Systems, 1 University Drive, Athabasca, AB T9S 3A3, Canada. Tel: 780-675-6812; Fax: 780-675-6973; Web site: http://www.ifets.info
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2017/4/10
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