Platform Construction of “Double Line” Intelligent Physical Education Teaching Mode in Universities

In the stage of realizing “Double Line” intelligent physical education (PE) instructional mode, one of the key links is to recommend individualized instructional resources for students. In order to realize the innovation and optimization of “Double Line” intelligent PE instructional platform, this article puts forward a individualized recommendation model of PE instructional resources based on knowledge map (KG) and collaborative filtering (CF) algorithm. This model uses KG technology to carry out semantic analysis and association rules mining on sports knowledge, so as to find similar interests and needs among students. Moreover, CF algorithm is used to screen and sort a large number of PE instructional resources in order to recommend high-quality resources that meet the individual needs of students. The results show that the individualized recommendation model of PE instructional resources based on KG and CF algorithms proposed in this article is superior to the traditional recommendation methods in terms of recommendation accuracy and recall. Applying this model to the platform construction of “Double Line” intelligent PE instructional mode can provide students with more accurate and individualized recommendation of instructional resources and improve instructional effect and learning experience.