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Web-Based Enhanced Learning Style Index with Integration into an e-Learning System

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Advances in Web-Based Learning – ICWL 2010 (ICWL 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6483))

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Abstract

Learning Style Index is a method to classify the learning preferences for learners. Learning preferences can then help learners to find their better way in the learning process. It also can help teachers to adopt suitable learning materials for efficient learning. This paper is concerned on the study, implementation, and application of a web-based learning style index. We also show a case study on the integration of learning style index into an e-learning system.

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Author information

Authors and Affiliations

  1. Graduate School of Computer Science, The University of Aizu, Aizuwakamatsu, Fukushima, Japan

    Mohamed Hamada & Kosuke Nishikawa

Authors
  1. Mohamed Hamada
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  2. Kosuke Nishikawa
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Editor information

Editors and Affiliations

  1. Shanghai University, Xingjian Building, No. 149 Yanchang Road, 200072, China

    Xiangfeng Luo

  2. Department D5: Databases and Information Systems, MaxPlanck Institute for Informatics, Campus E1 4, 66123, Saarbrücken, Germany

    Marc Spaniol

  3. Pervasive Technology Institute, Indiana University, 2719 East 10th Street, 47408, Bloomington, IN, USA

    Lizhe Wang

  4. Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong SAR

    Qing Li

  5. L3S Research Center, Leibniz University Hannover, Appelstr. 4, 30167, Hannover, Germany

    Wolfgang Nejdl

  6. School of Computer Engineering and Science, Shanghai University, Xingjian Building, No. 149 Yanchang Road, 200072, Shanghai, China

    Wu Zhang

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© 2010 Springer-Verlag Berlin Heidelberg

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Hamada, M., Nishikawa, K. (2010). Web-Based Enhanced Learning Style Index with Integration into an e-Learning System. In: Luo, X., Spaniol, M., Wang, L., Li, Q., Nejdl, W., Zhang, W. (eds) Advances in Web-Based Learning – ICWL 2010. ICWL 2010. Lecture Notes in Computer Science, vol 6483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17407-0_11

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  • DOI: https://doi.org/10.1007/978-3-642-17407-0_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17406-3

  • Online ISBN: 978-3-642-17407-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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