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Emotional, Epistemic, and Neutral Feedback in AutoTutor Trialogues to Improve Reading Comprehension

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Artificial Intelligence in Education (AIED 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9112))

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Abstract

We manipulated three types of short feedback (emotional, epistemic, and neutral) in an intelligent tutoring system designed to help struggling adult readers improve reading comprehension strategies. Although participants self-reported a preference for emotional feedback, there were no differences in individual motivation or usefulness ratings between emotional and epistemic feedback. Analysis from coded facial emotions indicated that participants tended to be more sensitive to epistemic feedback than emotional feedback.

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References

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Author information

Authors and Affiliations

  1. Institute for Intelligent Systems, University of Memphis, Memphis, TN, USA

    Shi Feng, Janay Stewart, Danielle Clewley & Arthur C. Graesser

Authors
  1. Shi Feng
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  2. Janay Stewart
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  3. Danielle Clewley
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  4. Arthur C. Graesser
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Corresponding author

Correspondence to Shi Feng .

Editor information

Editors and Affiliations

  1. University of British Columbia, Vancouver, British Columbia, Canada

    Cristina Conati

  2. Computer Science Department, Worcester Polytechnic Institute, Worcester, Massachusetts, USA

    Neil Heffernan

  3. Department of Computer Science and Software Engineering, University of Canterbury, Christchurch, New Zealand

    Antonija Mitrovic

  4. E.T.S.I. Informática, Universidad National de Educacion a Distancia, Madrid, Spain

    M. Felisa Verdejo

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© 2015 Springer International Publishing Switzerland

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Feng, S., Stewart, J., Clewley, D., Graesser, A.C. (2015). Emotional, Epistemic, and Neutral Feedback in AutoTutor Trialogues to Improve Reading Comprehension. In: Conati, C., Heffernan, N., Mitrovic, A., Verdejo, M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science(), vol 9112. Springer, Cham. https://doi.org/10.1007/978-3-319-19773-9_64

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  • DOI: https://doi.org/10.1007/978-3-319-19773-9_64

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19772-2

  • Online ISBN: 978-3-319-19773-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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