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Face Forward: Detecting Mind Wandering from Video During Narrative Film Comprehension

  • Angela StewartEmail author
  • Nigel Bosch
  • Huili Chen
  • Patrick Donnelly
  • Sidney D’MelloEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10331)

Abstract

Attention is key to effective learning, but mind wandering, a phenomenon in which attention shifts from task-related processing to task-unrelated thoughts, is pervasive across learning tasks. Therefore, intelligent learning environments should benefit from mechanisms to detect and respond to attentional lapses, such as mind wandering. As a step in this direction, we report the development and validation of the first student-independent facial feature-based mind wandering detector. We collected training data in a lab study where participants self-reported when they caught themselves mind wandering over the course of completing a 32.5 min narrative film comprehension task. We used computer vision techniques to extract facial features and bodily movements from videos. Using supervised learning methods, we were able to detect a mind wandering with an F1 score of .390, which reflected a 31% improvement over a chance model. We discuss how our mind wandering detector can be used to adapt the learning experience, particularly for online learning contexts.

Keywords

Mind wandering Attention aware interfaces 

Notes

Acknowledgements

This research was supported by the National Science Foundation (NSF) (DRL 1235958 and IIS 1523091). Any opinions, findings and conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the NSF.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.University of Notre DameNotre DameUSA
  2. 2.University of Illinois at Urbana-ChampaignUrbanaUSA
  3. 3.Massachusetts Institute of TechnologyCambridgeUSA

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