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Facilitating the Comprehension of Online Learning Courses with Adaptivity

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User Modeling 2003 (UM 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2702))

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Abstract

Knowledge acquisition with texts is assumed to be a process of building a mental model of the specific subject. For readers with more prior knowledge, the building of an accurate mental model is easier because they do not have to establish a new structure. Readers with less or no prior knowledge might build an inadequate mental model of a subject. In a hypertext learning environment this could be prevented by several adaptive features that support the user with additional information. We plan to examine the effectiveness and efficiency of such adaptive features within an online course by assessing the user’s acquired domain knowledge, the user’s satisfaction, and achievement of the user’s objectives.

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References

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Author information

Authors and Affiliations

  1. University of Education, Kunzenweg 21, 79117, Freiburg, Germany

    Stefan Lippitsch

Authors
  1. Stefan Lippitsch
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Editor information

Editors and Affiliations

  1. School of Information Sciences, Department of Information Science and Telecommunications, University of Pittsburgh, 135 North Bellefield Avenue, Pittsburgh, PA, 15260, USA

    Peter Brusilovsky

  2. Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Albert Corbett

  3. Intelligent Interfaces, Department of Informatics, University of Bari, Via Orabona 4, 70126, Bari, Italy

    Fiorella de Rosis

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© 2003 Springer-Verlag Berlin Heidelberg

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Lippitsch, S. (2003). Facilitating the Comprehension of Online Learning Courses with Adaptivity. In: Brusilovsky, P., Corbett, A., de Rosis, F. (eds) User Modeling 2003. UM 2003. Lecture Notes in Computer Science(), vol 2702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44963-9_63

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  • DOI: https://doi.org/10.1007/3-540-44963-9_63

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40381-4

  • Online ISBN: 978-3-540-44963-8

  • eBook Packages: Springer Book Archive

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