Nowadays, physical education teachers are constantly accepting and absorbing the concepts and ideas of the new curriculum standards, but there are still problems in understanding the new curriculum standards, the selection of teaching content is single, and the content is outdated. In addition, the teaching content and teaching methods of physical education also take the students’ test scores as the ultimate goal and have not really implemented the guiding ideology of “health first,” so the reform of physical education is imperative. This paper starts with the investigation of college students’ online courses and traditional classroom learning and analyzes what requirements these students who have received online courses have on university classrooms. Secondly, through in-depth observation of university classrooms, we can understand the current situation and existing problems of university classroom teaching. Based on the innovative characteristics and advantages of artificial intelligence big data AI technology, this paper designs a smart service platform for smart sports classrooms in colleges. The platform can timely find out the problems existing in the process of students’ physical education so as to solve them in time. Through the comparison between the experimental class and the control class, it is verified that the platform improves the reliability of PE classroom teaching. Judging from the practice density of the 25PE classes observed, the highest practice density reached 57.5%, and the average density was 41.6%. During the interview, we learned that the practice density of most physical education teachers in each class is controlled at about 45%, which is close to the average practice density obtained by the survey. This paper provides a practical basis for the reform of physical education teaching.

The education system begins a significant dimension characterized by continuous improvement and impacted by technology, society, and cultural developments. This pattern shows the need to enhance physical and athletic scientific training methods. To make the teacher’s role more successful is the usage of computer systems and other computing infrastructure. This article aims to show the use of Information and Communication Technology (ICT) in the national association for physical education. The digitalization consequences in the profession can be synthesized into the following elements: an operating system for learning, application essential to finish actions, findings recording, movement monitoring, video processing, efficiency correlation and synchronization, object tracking and duration measurement systems, and exercise assessment. While physical activity and athletics are realistic activities, current instructional technology is not sufficient. An intelligent physical education tracking system (IPETS) is proposed in this research. This study analyses and investigates the methodology for the formative assessment of athletic knowledge in computer evaluation. During the first segment, the evaluation technique for the athletic education program was presented. The second step of the paper is to understand the contents of the mathematical formula of particular activity based on the complete approaches proposed for the theory of assessment. A different phase of modernizing teaching activities using the computerized quality education for Artificial Intelligence (AI) technology is established in this article. The experimental findings are high in identifying university students’ regular exercise.

A nanoscaffold is a porous scaffold. It injects antibiotics, cells, and polymer particles into damaged cavities in the form of injectables and forms hydrogels after the molecules self-assemble at the injection site. Sports rehabilitation is a new frontier field integrating sports, health, and medicine, also known as physical therapy. It is the use of various sports methods for the injured or disabled, so that they can fully recover their physical functions and spirits, and can make them reintegrate into society. It mainly studies the relationship between sports and health. Among the tissue engineering scaffolds used as seed cell carriers, nanomaterials are playing an increasingly important role in the study of joint injury and repair due to their unique effects such as cell adhesion and proliferation. The purpose of this paper is to study a reliable nanoscaffold material for the treatment of patients with hip injuries in athletes and to observe its actual effect in combination with sports rehabilitation therapy. In this paper, an electrospinning method was proposed to prepare nanoscaffold materials, and the nanoscaffold materials were applied to the exercise rehabilitation process of two groups of hip patients, and the data of the patients’ rehabilitation were calculated. The results showed that the OD value of the cells in the exercise rehabilitation therapy using nanofiber scaffolds increased significantly, and the average daily growth rate of the OD value was 0.112. And the rehabilitation after 5 months was 19.8 points higher in hip range of motion score, 11.3 points higher in overall function score, and 6.2% lower in complication rate compared with ordinary exercise rehabilitation therapy. Therefore, it can be concluded that the therapy of the nanofiber scaffold material combined with exercise rehabilitation can more efficiently help patients with hip joint injury to recover, and the probability of complications is lower compared with the traditional exercise rehabilitation therapy.

Introduction: In today's rapid development of science and technology, digital network data mining technology is developing as fast as the expansion of the frontiers of science and technology allows, with a very broad application level, covering most of the civilized environment. However, there is still much to explore in the application of sports training. Objective: Analyze the feasibility of data mining based on the digital network of sports training, maximizing athletes’ training. Methods: This paper uses the experimental analysis of human FFT, combined with BP artificial intelligence network and deep data mining technology, to design a new sports training environment. The controlled test of this model was designed to compare advanced athletic training modalities with traditional modalities, comparing the athletes’ explosive power, endurance, and fitness. Results: After 30 days of physical training, the athletic strength of athletes with advanced fitness increased by 15.33%, endurance increased by 15.85%, and fitness increased by 14.23%. Conclusion: The algorithm designed in this paper positively impacts maximizing athletes’ training. It may have a favorable impact on training outcomes, as well as increase the athlete's interest in the sport. Level of evidence II; Therapeutic studies - investigating treatment outcomes.

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