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    Learning task-related strategies from user data through clustering

    Cocea, Mihaela and Magoulas, George D. (2012) Learning task-related strategies from user data through clustering. In: UNSPECIFIED (ed.) International Conference on Advanced Learning Technologies. New York, USA: Institute of Electrical and Electronics Engineers, pp. 400-404. ISBN 9781467316422.

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    Abstract

    In exploratory learning environments, learners can use different strategies to solve the same problem. Not all these strategies, however, are known to the teacher and, even if they were, they need considerable time and effort to introduce them in the knowledge base. In this paper we propose a learning mechanism that extracts strategies from user data and presents them to the teacher for further authoring. To this end, a clustering approach is used in which the strategies of learners are grouped into clusters and the teacher is presented with a representative strategy for each cluster. The teacher can then decide whether to store the proposed strategies or to author them further. This approach allows populating the knowledge base using user data, thus saving authoring time for the teacher.

    Metadata

    Item Type: Book Section
    Keyword(s) / Subject(s): vectors, tiles, resource management, image color analysis, knowledge based systems, clustering algorithms, educational institutions, exploratory learning environments, clustering, learning from user data
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centre: Birkbeck Knowledge Lab
    Depositing User: Sarah Hall
    Date Deposited: 18 Jul 2013 11:05
    Last Modified: 02 Dec 2016 13:23
    URI: http://eprints.bbk.ac.uk/id/eprint/7717

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