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  1. 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.