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Context-dependent personalised feedback prioritisation in exploratory learning for mathematical generalisation

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

In this paper we address the problem of prioritising feedback on the basis of multiple heterogeneous pieces of information in exploratory learning. The problem arises when multiple types of feedback are required in order to address different types of conceptual difficulties, accommodate particular learning behaviours identified during exploration, and provide appropriate support depending on the learning mode (e.g. individual or collaborative learning) and/or the stage of the exploratory learning process. We propose an approach that integrates learners’ characteristics and context-related information through a Multicriteria Decision-Making formalism. The outcome is a context-aware mechanism for prioritising personalised feedback that is tested in an ex- ploratory learning environment for mathematical generalisation.
Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization
EditorsG-J. Houben, G. McCalla, F. Pianesi
Place of PublicationBerlin, Heidelberg
PublisherSpringer
Pages271-282
Number of pages12
Edition5535
ISBN (Print)9783642022463
Publication statusPublished - 2009
EventProceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH -
Duration: 1 Jan 2009 → …

Publication series

NameLecture Notes in Computer Science
PublisherSpringer-Verlag
Number5535

Conference

ConferenceProceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Period1/01/09 → …

Documents

  • UMAP09.pdf

    Accepted author manuscript (Post-print), 396 KB, PDF document

Related information

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