Optimization of Physical Education Model Based on Cluster Analysis in the Context of Big Data

Abstract

In recent years, many foreign advanced teaching concepts have been introduced into China, and teaching reforms have been deepened, increasing the demand for physical education in China. Due to the various influences on the physical education curriculum and changes in the way it operates, curriculum standards provide only theoretical guidance and are often too general and abstract to play a concrete role in physical education. The diversity and inclusiveness of educational goals have led to the emergence of new areas of physical education. The repetitive nature of all physical education content settings is generally high and is detrimental to physical education reform. Based on the method of optimization of physical education models by cluster analysis, this paper proposes to classify and analyze the characteristics of the sample of students. We propose teaching principles and various teaching methods based on education and students’ abilities. The experimental results show that among the 200 data samples, the highest percentage of student performance sample data by grade level was 90–50, indicating that the optimization of the movement model under cluster analysis was more successful. Therefore, the research results of this project provide a theoretical basis for the establishment and research of physical education in Chinese schools and further promote the reform of physical education teaching methods in China.