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The Application of Optimal Topic Sequence in Adaptive e-Learning Systems

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Book cover Databases and Information Systems (DB&IS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 615))

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Abstract

In an adaptive e-learning system an opportunity to choose a course topic sequence is given to ensure personalization. The topic sequence can be obtained from three sources: teacher-offered topic sequence that is based on teacher’s pedagogical experience; learner’s free choice that is based on indicated links between topics, and, finally, the optimal topic sequence acquisition method described in this article. The optimal topic sequence is based on previous learners’ experience. With the help of the optimal topic sequence method, data about previous learners’ course topic sequence and course results are obtained. After the data analysis the optimal topic sequence for the specific course is obtained based on the links between course topics. In this article the experimental test of this method is described.

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Authors and Affiliations

  1. University of Latvia, Raina boulv.19, Riga, Latvia

    Vija Vagale & Laila Niedrite

Authors
  1. Vija Vagale
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  2. Laila Niedrite
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Corresponding author

Correspondence to Vija Vagale .

Editor information

Editors and Affiliations

  1. University of Latvia, Riga, Latvia

    Guntis Arnicans

  2. University of Latvia, Riga, Latvia

    Vineta Arnicane

  3. University of Latvia, Riga, Latvia

    Juris Borzovs

  4. University of Latvia, Riga, Latvia

    Laila Niedrite

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© 2016 Springer International Publishing Switzerland

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Vagale, V., Niedrite, L. (2016). The Application of Optimal Topic Sequence in Adaptive e-Learning Systems. In: Arnicans, G., Arnicane, V., Borzovs, J., Niedrite, L. (eds) Databases and Information Systems. DB&IS 2016. Communications in Computer and Information Science, vol 615. Springer, Cham. https://doi.org/10.1007/978-3-319-40180-5_24

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  • DOI: https://doi.org/10.1007/978-3-319-40180-5_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40179-9

  • Online ISBN: 978-3-319-40180-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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