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Building Group Recommendations in E-Learning Systems

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Book cover Agent and Multi-Agent Systems: Technologies and Applications (KES-AMSTA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6070))

Abstract

Building groups of students of similar features enables to suggest teaching materials according to their member needs. In the paper, it is proposed the agent-based recommender system, which, for each new learner, suggests the student group of similar profiles and consequently indicates suitable learning resources. It is assumed that learners may be characterized by cognitive styles, usability preferences or historical behavior, represented by nominal values. It is considered to build recommendations by using Naïve Bayes algorithm. The performance of the technique is validated on the basis of data of learners described by cognitive traits such as dominant learning style dimensions. Tests are done for real data of different groups of similar students as well as of individual learners.

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Author information

Authors and Affiliations

  1. Institute of Information Technology, Technical University of Lodz, Wolczanska 215, 90-924, Lodz, Poland

    Danuta Zakrzewska

Authors
  1. Danuta Zakrzewska
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Editor information

Editors and Affiliations

  1. Gdynia Maritime University, 81-221, Gdynia, Poland

    Piotr Jędrzejowicz

  2. Institute of Informatics, Wroclaw University of Technology, Str. Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

  3. University of Brighton, BN2 4GJ, Brighton, United Kingdom

    Robert J. Howlet

  4. University of South Australia, Mawson Lakes, 5095, SA, Australia

    Lakhmi C. Jain

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Zakrzewska, D. (2010). Building Group Recommendations in E-Learning Systems. In: Jędrzejowicz, P., Nguyen, N.T., Howlet, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2010. Lecture Notes in Computer Science(), vol 6070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13480-7_41

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  • DOI: https://doi.org/10.1007/978-3-642-13480-7_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13479-1

  • Online ISBN: 978-3-642-13480-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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