Simulation of English classroom effectiveness based on human-computer interaction and facial identification

Abstract

A variety of factors affect English classroom teaching, which prevents teachers from effectively grasping students’ learning status and learning situation. In particular, classroom management is more difficult during online teaching. In order to improve the effectiveness of English classroom teaching, based on the human-computer interaction algorithm and facial identification algorithm, this paper effectively recognizes the human-computer interaction process and classroom learning status of students in online teaching, and eliminates the image background according to the actual teaching needs. Moreover, by extracting and fusing the time sequence information and spatial information of the motion in the video, a spatiotemporal feature image capable of expressing a dynamic typical feature is obtained. In addition, this paper uses system algorithms to judge the status and feed back the identification results to the teacher’s teaching terminal equipment, which is convenient for timely teaching adjustment. Finally, this paper analyzes the effectiveness of the algorithm through simulation experiments. The research results show that the algorithm constructed in this paper has good performance.