Experienced teachers pay close attention to their students, adjusting their teaching when students seem lost. This dynamic interaction is missing in online education. We hypothesized that attentive students follow videos similarly with their eyes. Thus, attention to instructional videos could be assessed remotely by tracking eye movements. Here we show that intersubject correlation of eye movements during video presentation is substantially higher for attentive students and that synchronized eye movements are predictive of individual test scores on the material presented in the video. These findings replicate for videos in a variety of production styles, for incidental and intentional learning and for recall and comprehension questions alike. We reproduce the result using standard web cameras to capture eye movements in a classroom setting and with over 1,000 participants at home without the need to transmit user data. Our results suggest that online education could be made adaptive to a student’s level of attention in real time.
Experienced teachers pay close attention to their students, adjusting their teaching when students seem lost. This dynamic interaction is missing in online education. We propose to measure attention to online videos remotely by tracking eye movements, as we hypothesize that attentive students follow videos similarly with their eyes. Here we show that inter-subject correlation of eye movements during instructional video presentation is substantially higher for attentive students, and that eye movements are predictive of individual test scores on the material presented in the video. These findings replicate for videos in a variety of production styles, for intentional and incidental learning and for recall and comprehension questions alike. We reproduce the result using standard web cameras in a classroom setting, and with over 1,000 participants at-home without the need to transmit user data. Our results suggest that online education could be made adaptive to a student's level of attention in real-time.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.