Teaching Content Optimization for College Sports Courses Based on Analytic Hierarchy Process

As modern education pays more and more attention to students' physical and mental health and comprehensive quality development, how to optimize college physical education courses and improve teaching quality has become an important topic. At present, there are still some outstanding problems in physical education courses, such as single teaching content, unclear course objectives, and low student participation. These problems have affected students' learning effects to a certain extent and weakened their interest in sports. To address these problems, we proposed a course optimization method that integrates analytic hierarchy process (AHP), fuzzy AHP and genetic algorithm. Specifically, we first use traditional AHP to prioritize the importance of different physical education teaching contents; then, we introduce fuzzy AHP to deal with the uncertainty in the evaluation process, thereby improving the accuracy of the evaluation results; finally, combined with genetic algorithm, the weight of AHP judgment matrix is ​​optimized to achieve scientific configuration of physical education course content. The experimental results show that the optimized course content is more in line with the actual needs of students, and significantly improves their learning effects and participation enthusiasm. Compared with the traditional AHP method, our improved algorithm has obvious improvements in optimization accuracy and computational efficiency.