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With the advent of the era of big data, the wide application of information technology has promoted the development of the modernization of physical education in colleges and universities. However, at present, there are still many problems in physical education in most colleges and universities, such as the lack of professional application and management personnel, and the imperfect application system of big data. This paper starts from the specific application of big data in college physical education practice, and provides the practical exploration of big data in college physical education [1].

Under the current educational environment of constant reform, the PE (hereinafter referred to as PE) teaching mode (hereinafter referred to as TM) of colleges is also facing the need of reform. The rapid development of IT and computer technology provides a more powerful guarantee for the TM of PE. However, there are still many deficiencies in the current sports information-based TM in colleges. Therefore, relevant managers should take some actions to strengthen the PE teachers’ awareness of using IT to carry out sports teaching, which can better promote the innovation of sports teaching as well as the transformation and upgrading of sports TMl in colleges. Based on the current situation of information application, this paper discusses the path of innovation in order to provide innovative ideas for the following PE.

With the advent of the era of big data, the wide application of information technology has promoted the development of the modernization of physical education in colleges and universities. However, at present, there are still many problems in physical education in most colleges and universities, such as the lack of professional application and management personnel, and the imperfect application system of big data. This paper starts from the specific application of big data in college physical education practice, and provides the practical exploration of big data in college physical education [1].

With the continuous maturity and iteration of multimedia tech, computer multimedia tech has been widely used in college physical education. However, there are still many problems and deficiencies in the current utilization mode, such as teachers’ information literacy demand to be improved, resulting in their lack of multimedia utilization ability and utilization thinking. Based on this, this paper first analyzes the current situation of the expansion of college physical education teaching mode, then studies the advantages of computer multimedia tech in college physical education teaching, and finally gives the innovative design of computer multimedia university physical education teaching mode.

With the reform of education system, China has changed from the traditional concept of achievement education to the direction of comprehensive quality education. At present, according to the big data, quality education has become the mainstream theory of education. At present, college students in China have many objections to physical education. With the general decline of College Students’ physical quality, the reform of college education and teaching has become an urgent problem. This paper first analyzes the important role of quality education in college physical education. Then, this paper puts forward some practical problems of physical education reform. Finally, some suggestions are put forward [1].

Blockchain technology, with its decentralization, traceability, and immutability, offers promising solutions across various sectors, including education. This study explores the application of blockchain in enhancing the security and personalization of educational resource sharing within university physical education (PE). We ensure secure resource sharing by developing a blockchain-based model for PE resource distribution and refining the consensus algorithm. Our research involved a 10-week experiment with 80 university students, measuring changes in psychological factors (e.g., anxiety, depression) and physiological parameters (e.g., lung capacity). Results indicated a notable improvement in students’ psychological well-being, with anxiety and depression levels dropping by an average of 15%, and a significant enhancement in physiological health, evidenced by an average increase in lung capacity of 2.11±1.00 ml/kg. These findings underscore the potential of blockchain technology to elevate university PE teaching practices and positively impact student health, highlighting its significant applicability and future potential in educational contexts.

In recent years, with the deepening reform of domestic education, the education mode of education mode is changing. The physical education teaching system based on artificial intelligence technology can not only improve the work efficiency of the management department, but also promote the construction of digital, information and intelligent School Park. In this paper, college physical education curriculum as the center, artificial intelligence technology as the research direction, put forward the introduction of artificial intelligence into physical education, through the construction of agent layer and data service layer to achieve personalized teaching. By comparing the results of the control group and the experimental group after the experiment, and through the investigation of the experimental group students, the system improved the students’ sports performance to a certain extent, the experimental group compared with the control group, the average score increased by 3%, improved the students’ interest in sports.

With the development of educational informationization in Colleges and universities, cloud computing technology has become the main means of educational informationization in Colleges and universities. The application of educational information technology in college physical education promotes the integration with physical education. It realizes the transformation of physical education teaching mode and physical learning mode in Colleges and universities, gives full play to the greatest advantage of information technology, and provides students with a good education environment and a scientific and effective learning tool. This paper studies the application of physical education in the cloud computing environment. This paper investigates the current situation of College Physical Education in the cloud computing environment, analyzes and summarizes the problems in the process of college physical education teaching, and gives the corresponding countermeasures and suggestions. It can provide theoretical basis and reference for the future application of cloud computing in college physical education. From the point of view of physical education, this paper studies the relationship between education informatization and physical education, explores new physical education teaching mode, improves the use of school physical education informatization, creates a good teaching atmosphere, and promotes the improvement of teaching quality.

The improvement of the quality of college physical education teaching has been widely concerned by all walks of life, and information technology is being applied to all aspects of college physical education teaching in various forms. This paper adopts K-means clustering analysis algorithm, combined with the sports prescription knowledge set summarized from physical education teaching, to study and design a collaborative filtering recommendation method for sports prescription based on K-means clustering. The experimental results show that the recommendation method designed using this paper has better overall effect and stability in sports prescription recommendation compared with the traditional recommendation method. The usability and effectiveness of the K-means clustering based sports prescription recommendation method is verified. After using the method proposed in this paper for physical education teaching, the mean value of the total performance of the students in the experimental group after the experiment was 91.78±3.14, and the mean value of the total performance of the students in the control group was 85.76±3.64, and the mean value of the experimental group was significantly higher than that of the control group, which can be obtained from the fact that the use of the method proposed in this paper for teaching has a good role in improving the quality of physical education teaching in colleges and universities.