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A Scalable Solution for Adaptive Problem Sequencing and Its Evaluation

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Adaptive Hypermedia and Adaptive Web-Based Systems (AH 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4018))

Abstract

We propose an associative mechanism for adaptive generation of problems in intelligent tutors. Our evaluations of the tutors that use associative adaptation for problem sequencing show that 1) associative adaptation targets concepts less well understood by students; and 2) associative adaptation helps students learn with fewer practice problems. Apart from being domain-independent, the advantages of associative adaptation compared to other adaptive techniques are that it is easier to build and is scalable.

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Author information

Authors and Affiliations

  1. Ramapo College of New Jersey, Mahwah, NJ, 07430, USA

    Amruth Kumar

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  1. Amruth Kumar
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Editor information

Editors and Affiliations

  1. Knowledge and Data Engineering Group, Trinity College Dublin, Dublin, Ireland

    Vincent P. Wade

  2. School of Computer and Information Science, University of South Australia, Australia

    Helen Ashman

  3. Adaptive Information Cluster, School of Computer Science & Informatics, University College Dublin, Ireland

    Barry Smyth

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© 2006 Springer-Verlag Berlin Heidelberg

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Kumar, A. (2006). A Scalable Solution for Adaptive Problem Sequencing and Its Evaluation. In: Wade, V.P., Ashman, H., Smyth, B. (eds) Adaptive Hypermedia and Adaptive Web-Based Systems. AH 2006. Lecture Notes in Computer Science, vol 4018. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11768012_18

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  • DOI: https://doi.org/10.1007/11768012_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34696-8

  • Online ISBN: 978-3-540-34697-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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