RESEARCH ON PERSONALIZED PATH RECOMMENDATION OF COLLEGE PHYSICAL EDUCATION ONLINE TEACHING BASED ON IMPROVED PARTICLE SWARM OPTIMIZATION

Abstract

In recent years, colleges and universities have paid great attention to the education of physical health has the characteristics of strong on-site interaction and high requirements for venues and equipment. The construction of online teaching mechanism of college physical education is not only an opportunity but also a challenge for College Physical Education in China. The construction of online physical education teaching mechanism in Colleges and universities not only helps to improve the physical education teaching system in Colleges and universities in China, but also helps to enhance the importance of college teachers and students on physical education network teaching and promote the diversification of college physical education teaching methods. However, in practice, due to the imperfect construction of their own teaching platform, the lack of online teaching ability of physical education teachers, and the lack of online teaching resources, some colleges and universities in China have affected the quality of online physical education teaching to a certain extent. So, this article presents a personalized path recommendation method mabpso based on the improved particle swarm optimization algorithm for college physical education online teaching. First of all, it combs the literature about personalized teaching path recommendation and intelligent optimization algorithm at home and abroad; Secondly, a feature model (Leet) is constructed for educators and teaching resources; Third, it mainly solves the disadvantage of bspo, that is, it is easy to be trapped in the local optimization. The solution is to get rid of this problem by continuously improving the algorithm to get a more accurate algorithm with strong inhibition, so as to maximize the accuracy of teaching path recommendation and have a more accurate probability in the final calculation.