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Microscope or Telescope: Whether to Dissect Epistemic Emotions

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Artificial Intelligence in Education (AIED 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10948))

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Abstract

We empirically investigate two methods for eliciting student emotion within an online instructional environment. Students may not fully express their emotions when asked to report on a single emotion. Furthermore, students’ usage of emotional terms may differ from that of researchers. To address these issues, we tested two alternative emotion self-report mechanisms: the first closed response where students report on a single emotion via Likert scale, the second open response where students describe their emotions via open text.

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Acknowledgement

This research is supported by the National Science Foundation (NSF) # 1324385 IIS/Cyberlearning DIP: Impact of Adaptive Interventions on Student Affect, Performance, and NSF # 1551589 IIS/Cyberlearning INT: Detecting, Predicting and Remediating Student Affect and Grit Using Computer Vision. Any opinions, findings, and conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of NSF.

Author information

Authors and Affiliations

  1. Worcester Polytechnic University, Worcester, MA, USA

    Naomi Wixon & Ivon Arroyo

  2. University of Massachusetts, Amherst, MA, USA

    Beverly Woolf & Danielle Allessio

  3. Carnegie Mellon School of Computer Science, Pittsburgh, USA

    Sarah Schultz

Authors
  1. Naomi Wixon
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  2. Beverly Woolf
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  3. Sarah Schultz
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  4. Danielle Allessio
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  5. Ivon Arroyo
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Corresponding author

Correspondence to Naomi Wixon .

Editor information

Editors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    Carolyn Penstein Rosé

  2. University of Technology, Sydney, NSW, Australia

    Roberto MartĂ­nez-Maldonado

  3. University of Duisburg-Essen , Duisburg, Germany

    H. Ulrich Hoppe

  4. UCL Institute of Education, London, UK

    Rose Luckin

  5. UCL Institute of Education, London, UK

    Manolis Mavrikis

  6. UCL Institute of Education, London, UK

    Kaska Porayska-Pomsta

  7. Carnegie Mellon University, Pittsburgh, PA, USA

    Bruce McLaren

  8. University of Sussex, Brighton, UK

    Benedict du Boulay

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Wixon, N., Woolf, B., Schultz, S., Allessio, D., Arroyo, I. (2018). Microscope or Telescope: Whether to Dissect Epistemic Emotions. In: Penstein Rosé, C., et al. Artificial Intelligence in Education. AIED 2018. Lecture Notes in Computer Science(), vol 10948. Springer, Cham. https://doi.org/10.1007/978-3-319-93846-2_72

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  • DOI: https://doi.org/10.1007/978-3-319-93846-2_72

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93845-5

  • Online ISBN: 978-3-319-93846-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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