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.
This article examines 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 moments when students experienced difficulty disengaging from their own thoughts and to students’ familiarity with the text. The authors discuss implications and possible applications, including webcam-based eye tracking as a viable solution for designing real-time interventions for neurodivergent student populations.
