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Using Multiple Intelligence Informed Resources in an Adaptive System

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Intelligent Tutoring Systems (ITS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 4053))

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Abstract

Adaptive educational systems capture and represent, for each student, various characteristics such as knowledge and traits in an individual learner model. However, there are some unresolved issues in building adaptive educational systems that adapt to individual traits. For example it is not obvious what is the appropriate educational theory with which to develop instructional resources and model individual traits. This paper describes an experiment using the Multiple Intelligence (MI) based adaptive intelligent educational system, EDUCE, that explores how different categories of resources are used when the learner has complete control and when adaptive presentation strategies are employed. In particular it explores how Musical/Rhythmic traits and resources impact on performance. Results suggest that students prefer using Musical/ Rhythmic resources to other types of resources, however it is not clear how this preference can be best employed to enhance learning performance.

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Author information

Authors and Affiliations

  1. National College of Ireland, Dublin, Ireland

    Declan Kelly

  2. Trinity College, University of Dublin, Ireland

    Brendan Tangney

Authors
  1. Declan Kelly
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  2. Brendan Tangney
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Editor information

Editors and Affiliations

  1. JAIST, 1-1, Asahi-dai, Nomi, 923-1292, Ishikawa, Japan

    Mitsuru Ikeda

  2. Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA

    Kevin D. Ashley

  3. Graduate Institute of Network Learning Technology, National Central University, 300, Jhongda Rd., 32001, Jhongli City,Taoyuan County, Taiwan

    Tak-Wai Chan

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© 2006 Springer-Verlag Berlin Heidelberg

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Kelly, D., Tangney, B. (2006). Using Multiple Intelligence Informed Resources in an Adaptive System. In: Ikeda, M., Ashley, K.D., Chan, TW. (eds) Intelligent Tutoring Systems. ITS 2006. Lecture Notes in Computer Science, vol 4053. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11774303_41

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  • DOI: https://doi.org/10.1007/11774303_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35159-7

  • Online ISBN: 978-3-540-35160-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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