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Explaining Engagement: Learner Behaviors in a Virtual Coding Camp

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Artificial Intelligence in Education (AIED 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12749))

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Abstract

Engagement is critical to learning, yet current research rarely explores its underlying contextual influences, such as differences across modalities and tasks. Accordingly we examine how patterns of behavioral engagement manifest in a diverse group of ten middle school girls participating in a synchronous virtual computer science camp. We form multimodal measures of behavioral engagement from learner chats and speech. We found that the function of modalities varies, and chats are useful for short responses, whereas speech is better for elaboration. We discuss implications of our work for the design of intelligent systems that support online educational experiences.

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Author information

Authors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    Angela E. B. Stewart, Jaemarie Solyst & Amy Ogan

  2. University of Pittsburgh, Pittsburgh, PA, 15213, USA

    Amanda Buddemeyer & Erin Walker

  3. Uplift Inc., Washington D.C., 20013, USA

    Leshell Hatley

  4. Arizona State University, Tempe, AZ, 85281, USA

    Sharon Henderson-Singer & Kimberly Scott

Authors
  1. Angela E. B. Stewart
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  2. Jaemarie Solyst
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  3. Amanda Buddemeyer
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  4. Leshell Hatley
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  5. Sharon Henderson-Singer
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  6. Kimberly Scott
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  7. Erin Walker
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  8. Amy Ogan
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Corresponding author

Correspondence to Angela E. B. Stewart .

Editor information

Editors and Affiliations

  1. Technion – Israel Institute of Technology, Haifa, Israel

    Ido Roll

  2. Arizona State University, Tempe, AZ, USA

    Danielle McNamara

  3. Utrecht University, Utrecht, The Netherlands

    Sergey Sosnovsky

  4. London Knowledge Lab, London, UK

    Rose Luckin

  5. University of Leeds, Leeds, UK

    Vania Dimitrova

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Stewart, A.E.B. et al. (2021). Explaining Engagement: Learner Behaviors in a Virtual Coding Camp. In: Roll, I., McNamara, D., Sosnovsky, S., Luckin, R., Dimitrova, V. (eds) Artificial Intelligence in Education. AIED 2021. Lecture Notes in Computer Science(), vol 12749. Springer, Cham. https://doi.org/10.1007/978-3-030-78270-2_60

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  • DOI: https://doi.org/10.1007/978-3-030-78270-2_60

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78269-6

  • Online ISBN: 978-3-030-78270-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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