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Getting the Wiggles Out: Movement Between Tasks Predicts Future Mind Wandering During Learning Activities

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Artificial Intelligence in Education (AIED 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13916))

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Abstract

Mind wandering (“zoning out”) is a frequent occurrence and is negatively related to learning outcomes, which suggests it would be beneficial to measure and mitigate it. To this end, we investigated whether movement from a wrist-worn accelerometer between tasks could predict mind wandering as 125 learners read long, connected, informative texts. We examined random forest models using both basic statistical and more novel nonlinear dynamics movement features, finding that the former were more predictive of future (i.e., about 5 min later) reports of mind wandering. Models generalized across students with AUROCS up to 0.62. Importantly, vertical movement as measured by the Z-axis accelerometer channel, e.g. flexion or extension of the elbow in stretching, was the most predictive signal, whereas horizontal arm movements (measured by X- and Y-axis channels) and rotational movement were not predictive. We discuss implications for theories of mind wandering and applications for intelligent learning interfaces that can prospectively detect mind wandering.

R. Southwell and C.E. Peacock—These authors contributed equally

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Authors and Affiliations

  1. University of Colorado Boulder, Boulder, CO, 80301, USA

    Rosy Southwell, Candace E. Peacock & Sidney K. D’Mello

Authors
  1. Rosy Southwell
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  2. Candace E. Peacock
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  3. Sidney K. D’Mello
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Corresponding author

Correspondence to Rosy Southwell .

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Editors and Affiliations

  1. University of Southern California, Los Angeles, CA, USA

    Ning Wang

  2. University of British Columbia, Vancouver, BC, Canada

    Genaro Rebolledo-Mendez

  3. North Carolina State University, Raleigh, NC, USA

    Noboru Matsuda

  4. Despacho 3.01, UNED-Grupo de Investigación aDeNu, Madrid, Spain

    Olga C. Santos

  5. University of Leeds, Leeds, UK

    Vania Dimitrova

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Southwell, R., Peacock, C.E., D’Mello, S.K. (2023). Getting the Wiggles Out: Movement Between Tasks Predicts Future Mind Wandering During Learning Activities. In: Wang, N., Rebolledo-Mendez, G., Matsuda, N., Santos, O.C., Dimitrova, V. (eds) Artificial Intelligence in Education. AIED 2023. Lecture Notes in Computer Science(), vol 13916. Springer, Cham. https://doi.org/10.1007/978-3-031-36272-9_40

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  • DOI: https://doi.org/10.1007/978-3-031-36272-9_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36271-2

  • Online ISBN: 978-3-031-36272-9

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