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Cohesion / Knowledge Interactions in Post-tutoring Reflective Text

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Artificial Intelligence in Education (AIED 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6738))

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Abstract

In a previous paper we showed that providing a reflective/abstractive text can significantly improve how much middle motivation students learn from qualitative physics tutoring. In this paper we further find that the effect can be substantially improved by adjusting the cohesiveness of that text according to these students’ level of prior knowledge. However, in contrast to previous work in the field, we find that our high knowledge students learned significantly more from high rather than low, cohesion text.

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References

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Author information

Authors and Affiliations

  1. Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, 15232, USA

    Arthur Ward

  2. University of Pittsburgh, USA

    Diane Litman

Authors
  1. Arthur Ward
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  2. Diane Litman
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Editor information

Editors and Affiliations

  1. EECS Department/ISIS, Vanderbilt University, TN 37235, Nashville, USA

    Gautam Biswas

  2. Electronic, Electrical and Computer Engineering, University of Birmingham, U.K.

    Susan Bull

  3. School of Information Technologies, University of Sydney, 1 Cleveland Street, 2006, Sydney, Australia

    Judy Kay

  4. College of Engineering, Department of Computer Science and Software Engineering, University of Canterbury, Private Bag 4800, 8140, Christchurch, New Zealand

    Antonija Mitrovic

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© 2011 Springer-Verlag Berlin Heidelberg

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Ward, A., Litman, D. (2011). Cohesion / Knowledge Interactions in Post-tutoring Reflective Text. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds) Artificial Intelligence in Education. AIED 2011. Lecture Notes in Computer Science(), vol 6738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21869-9_107

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  • DOI: https://doi.org/10.1007/978-3-642-21869-9_107

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21868-2

  • Online ISBN: 978-3-642-21869-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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