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Eliciting Adaptation Knowledge from On-Line Tutors to Increase Motivation

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User Modeling 2007 (UM 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4511))

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Abstract

In the classroom, teachers know how to motivate their students and how to exploit this knowledge to adapt or optimize their instruction when a student shows signs of demotivation. In on-line learning environments it is much more difficult to assess a learner’s motivation and to have adaptive intervention strategies and rules of application to help prevent attrition or drop-out. In this paper, we present results from a survey of on-line tutors on how they motivate their learners. These results will inform the development of an adaptation engine by extracting and validating selection rules for strategies to increase motivation depending on the learner’s self-efficacy, goal orientation, locus of control and perceived task difficulty in adaptive Intelligent Tutoring Systems.

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Authors and Affiliations

  1. National College of Ireland, School of Informatics, Mayor Street 1, Dublin 1, Ireland

    Teresa Hurley & Stephan Weibelzahl

Authors
  1. Teresa Hurley
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  2. Stephan Weibelzahl
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Cristina Conati Kathleen McCoy Georgios Paliouras

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© 2007 Springer-Verlag Berlin Heidelberg

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Hurley, T., Weibelzahl, S. (2007). Eliciting Adaptation Knowledge from On-Line Tutors to Increase Motivation. In: Conati, C., McCoy, K., Paliouras, G. (eds) User Modeling 2007. UM 2007. Lecture Notes in Computer Science(), vol 4511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73078-1_47

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  • DOI: https://doi.org/10.1007/978-3-540-73078-1_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73077-4

  • Online ISBN: 978-3-540-73078-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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