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    Adaptive modelling of users’ strategies in exploratory learning using case-based reasoning

    Cocea, Mihaela and Gutierrez-Santos, Sergio and Magoulas, George D. (2010) Adaptive modelling of users’ strategies in exploratory learning using case-based reasoning. In: Rossitza, S. and Ivan, J. (eds.) Knowledge-Based and Intelligent Information and Engineering Systems. Lecture Notes in Computer Science 2 6277. Berlin, Germany: Springer Verlag, pp. 124-134. ISBN 9783642153907.

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    Abstract

    In exploratory learning environments, learners can use different strategies to solve a problem. To the designer or teacher, however, not all these strategies are known in advance and, even if they were, introducing them in the knowledge base would involve considerable time and effort. In previous work, we have proposed a case-based knowledge representation, modelling the learners’ behaviour when constructing/exploring models through simple cases and sequences of cases, called strategies. In this paper, we enhance this approach with adaptive mechanisms for expanding the knowledge base. These mechanisms allow to identify and store inefficient cases, i.e. cases that pose additional difficulty to students in their learning process, and to gradually enrich the knowledge base by detecting and adding new strategies.

    Metadata

    Item Type: Book Section
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centres and Institutes: Birkbeck Knowledge Lab
    Depositing User: Sarah Hall
    Date Deposited: 17 May 2013 11:25
    Last Modified: 02 Dec 2016 13:22
    URI: https://eprints.bbk.ac.uk/id/eprint/6851

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