Quality Evaluation of College Physical Training considering Apriori Algorithm

Abstract

With the continuous progress of society and economy, more and more attention has been paid to the physical quality of students. As an essential support carrier, physical education (PE) class is responsible for the exercise and improvement of the physical quality and fitness of students. In this paper, with physical training as a breakthrough point, the data on training quality are evaluated based on the Apriori algorithm and the factor mining is carried out accordingly. Through the Apriori algorithm, an in-depth analysis is carried out in this paper on the practical teaching status of physical training programs at colleges and universities in the country. From various perspectives such as the development of the existing physical training programs and their functional features, the advantages of physical training programs in teaching at colleges and universities are analyzed. At the same time, suggestions are given with regard to the current teaching model and status quo at colleges and universities to achieve the goal of driving the development of physical training in the country. Finally, the results of the practical case analysis indicate that physical training programs are feasible in the education curriculum at colleges and universities. To some extent, the spirit of physical training programs is similar to the concept of physical education at colleges and universities. There are many types of physical training programs, which can be used as rich resources for physical education at colleges and universities. From the results of the research, it can be seen that the Apriori algorithm can be used to evaluate the training quality of physical education effectively; the mastery levels of physical education skills among male students are generally higher than those among female students, and the difference is relatively significant; the algorithm proposed in this paper can be used to evaluate the data effectively, which is of great significance for supporting the decisions on improving the quality of training.