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Scaffolding Self-directed Learning with Personalized Learning Goal Recommendations

  • Conference paper
User Modeling, Adaptation, and Personalization (UMAP 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6075))

Abstract

Adaptive scaffolding has been proposed as an efficient means for supporting self-directed learning both in educational as well as in adaptive learning systems research. However, the effects of adaptation on self-directed learning and the differential contributions of different adaptation models have not been systematically examined. In this paper, we examine whether personalized scaffolding in the learning process improves learning. We conducted a controlled lab study in which 29 students had to solve several tasks and learn with the help of an adaptive learning system in a within-subjects control condition design. In the learning process, participants obtained recommendations for learning goals from the system in three conditions: fixed scaffolding where learning goals were generated from the domain model, personalized scaffolding where these recommendations were ranked according to the user model, and random suggestions of learning goals (control condition). Students in the two experimental conditions clearly outperformed students in the control condition and felt better supported by the system. Additionally, students who received personalized scaffolding selected fewer learning goals than participants from the other groups.

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Author information

Authors and Affiliations

  1. Know-Center, Inffeldgasse 21a, 8010, Graz, Austria

    Tobias Ley

  2. Cognitive Science Section, University of Graz, Universitätsplatz 2, 8010, Graz, Austria

    Tobias Ley & Cornelia Gerdenitsch

  3. Knowledge Management Institute, Graz University of Technology, Inffeldgasse 21a, 8010, Graz, Austria

    Barbara Kump

Authors
  1. Tobias Ley
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  2. Barbara Kump
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  3. Cornelia Gerdenitsch
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Editor information

Editors and Affiliations

  1. Computer Science Department, Eindhoven University of Technology, 5600, Eindhoven, MB, The Netherlands

    Paul De Bra

  2. School of Information and Computer Sciences, University of California, 92697-3440, Irvine, CA, USA

    Alfred Kobsa

  3. Department of Information and Computer Sciences, University of Hawaii, 96822, Honolulu, HI, USA

    David Chin

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Ley, T., Kump, B., Gerdenitsch, C. (2010). Scaffolding Self-directed Learning with Personalized Learning Goal Recommendations. In: De Bra, P., Kobsa, A., Chin, D. (eds) User Modeling, Adaptation, and Personalization. UMAP 2010. Lecture Notes in Computer Science, vol 6075. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13470-8_9

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  • DOI: https://doi.org/10.1007/978-3-642-13470-8_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13469-2

  • Online ISBN: 978-3-642-13470-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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