Automated gaze-based mind wandering detection during computerized learning in classrooms

Stephen Hutt, Kristina Krasich, Caitlin Mills, Nigel Bosch, Shelby White, James R. Brockmole, Sidney K. D’Mello

Research output: Contribution to journalArticle

Abstract

We investigate the use of commercial off-the-shelf (COTS) eye-trackers to automatically detect mind wandering—a phenomenon involving a shift in attention from task-related to task-unrelated thoughts—during computerized learning. Study 1 (N = 135 high-school students) tested the feasibility of COTS eye tracking while students learn biology with an intelligent tutoring system called GuruTutor in their classroom. We could successfully track eye gaze in 75% (both eyes tracked) and 95% (one eye tracked) of the cases for 85% of the sessions where gaze was successfully recorded. In Study 2, we used this data to build automated student-independent detectors of mind wandering, obtaining accuracies (mind wandering F1 = 0.59) substantially better than chance (F1 = 0.24). Study 3 investigated context-generalizability of mind wandering detectors, finding that models trained on data collected in a controlled laboratory more successfully generalized to the classroom than the reverse. Study 4 investigated gaze- and video- based mind wandering detection, finding that gaze-based detection was superior and multimodal detection yielded an improvement in limited circumstances. We tested live mind wandering detection on a new sample of 39 students in Study 5 and found that detection accuracy (mind wandering F1 = 0.40) was considerably above chance (F1 = 0.24), albeit lower than offline detection accuracy from Study 1 (F1 = 0.59), a finding attributable to handling of missing data. We discuss our next steps towards developing gaze-based attention-aware learning technologies to increase engagement and learning by combating mind wandering in classroom contexts.

Original languageEnglish (US)
Pages (from-to)821-867
Number of pages47
JournalUser Modeling and User-Adapted Interaction
Volume29
Issue number4
DOIs
StatePublished - Sep 1 2019

Keywords

  • Attention-aware learning
  • Cyberlearning
  • Eye-gaze
  • Intelligent tutoring systems
  • Mind wandering

ASJC Scopus subject areas

  • Education
  • Human-Computer Interaction
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Automated gaze-based mind wandering detection during computerized learning in classrooms'. Together they form a unique fingerprint.

  • Cite this