How could schools know if students are paying attention in class?

Answer: facial recognition software

by / May 30, 2017

It’s not always easy to pay attention to a lecture, especially in an online class. What if, when you started to drift off, a robot reached through the computer screen and slapped you back to the present? That’s the metaphor used by Nestor, software that tracks when students start to drift off and ultimately improve class time for both students and teachers.

Created by LCA Learning, Nestor uses students’ webcams to analyze eye movements and facial expressions to determine if they are paying attention. It then uses that information to base quiz content on what was covered during those times when students weren’t engaged with the class. Ideally, professors would also be able to use the information to learn when during their lectures students weren’t as attentive, hopefully improving their teaching.

The software is being tested in two online classes at the ESG Management School at the Paris School of Business beginning in September, but its creators are hoping to eventually launch a version that could be used for in-person classes and send real-time notifications to inattentive students.