Research on the application of intelligent tutoring system based on deep learning in physical education

Based on the deep learning model, this paper studies the application of intelligent tutoring system in physical education and evaluates its effect through empirical analysis. The system uses a deep learning model that combines convolutional neural network (CNN) and long short-term memory network (LSTM) to automatically diagnose technical errors in students’ sports and provide personalized feedback. In order to verify the effectiveness of the model, this article designed a set of experiments involving 300 students, and used the pre-test/post-test method to compare the differences in students’ physical performance between using the intelligent tutoring system and traditional teaching methods. Through multiple regression analysis, the results show that the intelligent tutoring system can significantly improve students’ physical performance, and has a more obvious improvement effect on students with weak physical fitness. The research of this article provides theoretical support for the application of intelligent tutoring systems and provides practical basis for personalized teaching in physical education.