Reform and innovation of physical education teaching methods in universities based on fuzzy decision support systems

Innovative Physical Education (PE) teaching methods rely on technologies and innovative environments to improve the fitness and efficiency of students. Such teaching/ training methods need periodic assessments to improve quality and cope with modern trends. This article introduces an Active Teaching Assessment Method (ATAM) using fuzzy decision support systems (FDSS). By analyzing performance data and physiological features, a Fuzzy Decision Support System may provide individualized training programs for athletes. FDSS considers factors like fitness level, recovery rate, and injury history to provide personalized suggestions. The fuzzy generates a series of membership functions based on the different performance levels of the students. Such performance levels provide optimal efficacy-adhered teaching methods randomly. The random outputs are combined based on student feasibility factors; the feasibility factors include PE time and academic performance. The active assessments are classified based on suitable outputs to persuade new PE sessions. The assessment is provided using fuzzy decision recommendation through feasible derivative improvements. In this process, the fuzzy derivatives only consider the best-fit (maximum efficient) teaching method. Therefore, the recommendations from the best fit are provided with a much better assessment from the previous sessions. With 12 categories, it can handle various classroom situations and student requirements. Compared to other methodologies, ATAM's evaluation time of 75 s is the shortest, indicating excellent efficiency. Lastly, an output combination percentage of 85% best integrates performance and recommendation indicators.