Research on the interaction between university physical culture education and college students’ physical exercise in the context of big data

Abstract

The background of big data has developed deeply, the application of the field has been broadened, and the value of data has been vigorously manifested. In order to study the interaction between physical culture education and exercise in universities in this era, this paper uses Clementine 12.0 data mining software to build a data mining model of association rules of university physical culture education courses and mine the course feature vectors. Based on the mining results, we designed the second classroom physical culture education courses with different physical culture characteristics. Constructing a scoring method and rating scale for the effectiveness of physical exercise among college students, and the physical exercise index scores are obtained through fuzzy operations. Finally, the interaction between physical culture education and exercise in universities in this context is analyzed according to the relationship between physical culture education courses and physical exercise performance. After the physical culture education course began, the physical exercise intensity score of the experimental group of first-year college girls increased by 8%, the physical exercise time score increased by 10%, the physical exercise frequency score increased by 15.2%, and the total physical exercise score increased by 7% after the physical culture education course. This shows that university physical culture education is positively correlated with college students’ physical activity, and campus physical culture has a significant predictive effect on students’ subjective performance of physical activity behavior. Optimizing university physical culture education not only improves students’ physical quality and promotes the development of their physical and mental health but also provides a reference for strengthening students’ physical education.