Analysis of the Correlation Between Student Listening Behavior and Academic Performance

With the popularization and application of artificial intelligence technology, classroom behavior research has once again become a research hotspot in the field of educational information technology. Many researchers have attempted to use computer vision technology to recognize the behavior of teachers and students in the classroom, among which the head posture classification method with object detection as the core has received more attention. It has been effectively used to calculate classroom head up rate and characterize the overall attention level of the classroom. However, unlike previous studies, this article focuses for the first time on the calculation of individual student head up rate and head posture switching, and analyzes the correlation between these listening behavior data and academic performance. The results showed that student seating and head posture switching were significantly correlated with academic performance, while individual head up rates were not significantly correlated with academic performance.