Evaluation of Physical Education Teaching Quality Based on Optimized Apriori Algorithm

The evaluation of physical education means to improve students’ literacy and teaching level. This study is based on the optimized Apriori algorithm and aims to propose an efficient and accurate method. Firstly, we collected a large amount of physical education teaching data, including students’ physical fitness test scores, classroom performance, and teachers’ teaching evaluations. Then, use the Apriori algorithm to mine association rules in the data and identify features related to the quality of physical education teaching. Next, we improved the accuracy and efficiency of the evaluation model by optimizing the Apriori algorithm. In the evaluation process, we considered multiple factors, such as student participation, teacher guidance level, and utilization of teaching resources. By analyzing the relationship between these factors, we can comprehensively education teaching and propose corresponding improvement measures. The indicate that the optimized Apriori has high accuracy and feasibility. It teachers their teaching effectiveness, but also provides scientific basis for schools education teaching. In summary, the optimized Apriori algorithm has the potential the accuracy and efficiency of the evaluation. Future research can further explore how to use other algorithms and technologies to improve the methods and results education teaching.