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Identifying user strategies in exploratory learning with evolving task modelling

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    Abstract

    In this paper we present work on adaptive identification of learners’ strategies, gradually developing a higher level of adaptation based on evolving models of mathematical generalisation tasks in an Exploratory Learning Environment. A similarity-based classification approach is defined for the identification of strategies, using an initially small number of classes (i.e. strategies). A strategy is composed of several patterns with relations between them. An evolution monitor component observes changes in the environment and triggers a mechanism that builds-up the task model. The task model evolves when new relevant information becomes available by adding a new strategy (class) or a new inefficient pattern, i.e. patterns that make it difficult for the learner to generalise.
    Original languageEnglish
    Title of host publication2010 5th IEEE International Conference on Intelligent Systems (IS 2010): Proceedings of a meeting held 7-9 July 2010, London, United Kingdom
    Place of PublicationPiscataway
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages13 -18
    Number of pages6
    ISBN (Print)9781424451630
    DOIs
    Publication statusPublished - Jul 2010
    EventIntelligent Systems (IS), 2010 5th IEEE International Conference - London
    Duration: 7 Jul 20109 Jul 2010

    Conference

    ConferenceIntelligent Systems (IS), 2010 5th IEEE International Conference
    Period7/07/109/07/10

    Keywords

    • evolution monitor component
    • evolving task modelling
    • exploratory learning environment
    • similarity-based classification approach
    • user strategy identification
    • computer aided instruction
    • pattern classification
    • user interfaces

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