Using a webcam based eye-tracker to understand students' thought patterns and reading behaviors in neurodivergent classrooms
Date
2023
Authors
Wong, A.Y.
Bryck, R.L.
Baker, R.S.
Hutt, S.
Mills, C.
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Conference paper
Citation
Thirteenth International Conference On Learning Analytics and Knowledge, Lak2023, 2023, pp.453-463
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13th International Conference on Learning Analytics and Knowledge (13 Mar 2023 - 17 Mar 2023 : Arlington, Texas)
Abstract
Previous learning analytics efforts have attempted to leverage the link between students' gaze behaviors and learning experiences to build effective real-time interventions. Historically, however, these technologies have not been scalable due to the high cost of eye-tracking devices. Further, such efforts have been almost exclusively focused on neurotypical students, despite recent work that suggests a "one size fits many" approach can disadvantage neurodivergent students. Here we attempt to address these limitations by examining the validity and applicability of using scalable, webcam-based eye tracking as a basis for adaptively responding to neurodivergent students in an educational setting. Forty-three neurodivergent students read a text and answered questions about their in-situ thought patterns while a webcam-based eye tracker assessed their gaze locations. Results indicate that eye-tracking measures were sensitive to: 1) moments when students experienced difficulty disengaging from their own thoughts and 2) students' familiarity with the text. Our findings highlight the fact that a free, open-source, webcam-based eye-tracker can be used to assess differences in reading patterns and online thought patterns. We discuss the implications and possible applications of these results, including the idea that webcam-based eye tracking may be a viable solution for designing real-time interventions for neurodivergent student populations.
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Copyright 2023 ACM