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The Effect of Interaction Granularity on Learning with a Data Normalization Tutor

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Part of the book series:Lecture Notes in Computer Science ((LNAI,volume 7926))

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Abstract

Intelligent Tutoring Systems (ITSs) have proven their effectiveness in many instructional domains, ranging in the complexity of domain theories and tasks students are to perform. The typical effect sizes achieved by ITSs are around 1SD, which are still low in comparison to the effectiveness of expert human tutors. Recently there have been several analyses done in order to identify the factors that contribute to success of human tutors, and to replicate it in ITSs. VanLehn [6] proposes that the crucial factor is thegranularity of interaction: the lower the level of discussions between the (human or artificial) tutor and the student, the higher the effectiveness. We investigated the effect of interaction granularity in the context of NORMIT, a constraint-based tutor that teaches data normalization. Our study compared the standard version of NORMIT, which provided hints in response to errors, to a version which used adaptive tutorial dialogues instead. The results show that the interaction granularity hypothesis holds in our experimental situation, and that the effect size achieved is consistent with other reported studies of a similar nature.

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Authors and Affiliations

  1. Intelligent Computer Tutoring Group, University of Canterbury, Christchurch, New Zealand

    Amali Weerasinghe, Antonija Mitrovic, Amir Shareghi Najar & Jay Holland

Authors
  1. Amali Weerasinghe

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  2. Antonija Mitrovic

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  3. Amir Shareghi Najar

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  4. Jay Holland

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Editor information

Editors and Affiliations

  1. Institute for Creative Technologies, University of Southern California, 12015 Waterfront Dr., 90094, Playa Vista, CA, USA

    H. Chad Lane

  2. School of Information Technologies, University of Sydney, 2006, Sydney, NSW, Australia

    Kalina Yacef

  3. School of Computer Science, Carnegie Mellon University, 5000 Forbes Avenue, 15213, Pittsburgh, PA, USA

    Jack Mostow

  4. Department of Psychology, University of Memphis, 38152, Memphis, TN, USA

    Philip Pavlik

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© 2013 Springer-Verlag Berlin Heidelberg

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Weerasinghe, A., Mitrovic, A., Shareghi Najar, A., Holland, J. (2013). The Effect of Interaction Granularity on Learning with a Data Normalization Tutor. In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds) Artificial Intelligence in Education. AIED 2013. Lecture Notes in Computer Science(), vol 7926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39112-5_47

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JPY 11439
Price includes VAT (Japan)
  • Available as PDF
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JPY 14299
Price includes VAT (Japan)
  • Compact, lightweight edition
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Purchases are for personal use only


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