July 26, 2021
July 26, 2021
July 19, 2022
Computers in Education
Work in Progress Engage AI: Leveraging video analytics for instructor-class awareness in virtual classroom settings
A difficulty for teachers in COVID-era online teaching settings is assessing engagement and student attention. We developed a system called Engage AI for assessing engagement during live lectures. Engage AI uses video-based machine learning models to detect drowsiness and emotions like happiness and neutrality, and aggregates them in a dashboard that instructors can view as they speak. No video data is transmitted outside of students’ web browsers, and individual students are anonymous to the instructor. Testing in undergraduate engineering lectures resulted in 78.2% of students reporting feeling at least potentially more engaged during the lecture and at least 34.4% reporting feeling more engaged during the lecture. These approaches could be applicable to many forms of remote and in-person education.
Stairs, J., & Mangla, R., & Chaudhery, M., & Chandhok, J. S., & Timorabadi, H. S. (2021, July), Engage AI: Leveraging Video Analytics for Instructor-class Awareness in Virtual Classroom Settings Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://peer.asee.org/37031
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