Application Research of Emotion Analysis, Eye Tracking, and Head Movement Monitoring Based on Facial Recognition Algorithms in ESL Student Engagement Assessment

This article explores the innovative use of emotion analysis, eye tracking, and head movement tracking with facial recognition to assess ESL students' classroom participation. It overviews the principles and practices of these technologies in education, focusing on facial recognition and emotion analysis to help teachers understand students' emotions in real-time. Experimental data shows how eye tracking evaluates students' attention, while head movement tracking provides intuitive data on student activity. The article discusses challenges and future directions of this multi-technology integration, highlighting its potential to enhance teaching interaction and student engagement. It anticipates the widespread impact of technology-based educational tools in global education.