The recent curriculum reform in China puts forward higher requirements for the development of physical education. In order to further improve students’ physical quality and motor skills, the traditional model was improved to address the lack of accuracy in motion recognition and detection of physical condition so as to assist teachers to improve students’ physical quality. First, the physical education teaching activities required by the new curriculum reform were studied with regard to the actual needs of China’s current social, political, and economic development; next, the application of artificial intelligence technology to physical education teaching activities was proposed; and finally, deep learning technology was studied and a human movement recognition model based on a long short-term memory (LSTM) neural network was established to identify the movement state of students in physical education teaching activities. The designed model includes three components: data acquisition, data calculation, and data visualization. The functions of each layer were introduced; then, the intelligent wearable system was adopted to detect the status of students and a feedback system was established to assist teaching; and finally, the dataset was constructed to train and test the designed model. The experimental results demonstrate that the recognition accuracy and loss value of the training model meet the practical requirements; in the algorithm test, the motion recognition accuracy of the designed model for different subjects was greater than 97.5%. Compared with the traditional human motion recognition algorithm, the designed model had a better recognition effect. Hence, the designed model can meet the actual needs of physical education. This exploration provides a new perspective for promoting the intelligent development of physical education.

Aim: This paper aims to enhance the emphasis of college physical education (P.E.) in the psychological education of P.E. students and provide a reference for the innovation of P.E. teaching methods. Methodology and procedures: On the basis of the Internet of Things (IoT) and a deep-learning algorithm, combined with psychological education, the teaching effect and the influence on learning philosophy are comprehensively evaluated through the construction of teaching evaluation index system for college P.E. students. Results: The theoretical courses of P.E. students in colleges and universities lack the integration of psychological-education concepts. It is found that the new teaching mode not only has a significant effect on improvement of training courses, but also promotes learning enthusiasm and theoretical courses. In the aspect of psychological quality evaluation, emotional-control ability significantly improved, the average score increased from below 60 to above 79, and self-challenge ability and adaptability to adversity also effectively improved. In the evaluation of deep-learning ability, students’ critical thinking ability improved most obviously, and their complex problem-solving ability also improved to some extent. Conclusions: Based on the IoT and machine learning, college P.E. teaching mode can effectively improve students’ psychological quality and ability, effectively improve students’ training and theoretical achievements, and significantly improve their academic achievements. It can also improve students’ self-learning ability. Practical applications: This paper reforms the traditional P.E. teaching mode, effectively demonstrates the hypothesis through practical teaching, designs the teaching evaluation index system of college P.E. students, and improves their learning ability and comprehensive achievements.

This study was conducted to explore physical education students’ intrinsic motivation and clarify the influence mechanism of cooperative learning methods on learning intrinsic motivation through meta-analysis. In accordance with the Preferred Reporting Items for Systematic Reviews (PRISMA) criteria, we screened literature from the years 2000–2020. The included literature underwent bias analysis on the basis of the five criteria proposed herein. Data were extracted and summarized from the included literature to analyze the causality before and after cooperative learning intervention. Statistical analysis was conducted to determine principal factors affecting physical education students’ learning intrinsic motivation. Simultaneously, the influencing mechanism of cooperative learning on physical education students’ intrinsic motivation was clarified. Results revealed that intrinsic motivation had a high total effect amount. In the experimental group, only three documents determined the significant influence of cooperative learning on physical education students’ intrinsic motivation. Moreover, the time and age differences needed to be considered thoroughly during the intervention. Therefore, cooperative learning intervention can improve physical education students’ intrinsic motivation significantly, and meta-analysis provided a theoretical foundation for applying cooperative learning to the teaching of physical education majors.

In this study, the impacts of sports gamification on college students’ learning motivation and learning performances were explored by training students majoring in physical education to play tennis. A total of 150 students from a physical education college were selected to participate in this experimental teaching, and they were divided into the experimental group (EG) and the control group (CG). Based on the above purposes, the differences in the teaching methods and teaching objectives of the EG and the CG is that the former uses games as a key method in tennis teaching. All participants were asked to complete questionnaires, with the purpose of evaluating the learning motivation of tennis before and after sports game intervention. Additionally, the differentiated learning motivation and learning performance between EG and CG before and after experimental teaching was tested and evaluated. Results demonstrate that students in the EG have significantly increased their intrinsic motivation and introjected regulation, thereby showing better results than CG in key test items. In addition, the above result reveals the positive role of sports gamification in promoting the learning motivation and performance of college students.

Background: COVID-19 has brought people many negative emotions, such as fear and anxiety about the epidemic. However, when peo-ple in different countries face the COVID-19 epidemic, the impact is also different due to different cultural and sports hab-its. Therefore, this study compares China and Poland’s sports motivations in the face of COVID-19 anxiety to find out the cultural differences behind them.Participants and procedure: In the study were N = 674 participants (female n = 407, male n = 260, other n = 4). Their average age was M = 29.86, SD = 11.03. There were n = 381 participants in the Chinese sample, and n = 293 in Polish. The scales used for the purpose of the study were the Inventory of Physical Activity Objectives (IPAO) and the Coronavirus Anxiety Scale (CAS).Results: The study results showed that the increased level of COVID-19 anxiety changed selected motives for physical activity, and different changes of motives characterized women and men as well as people of different ages. As predicted in the study model, culture was the moderator of the shifts of the selected motives.Conclusions: The understanding of what motivates individuals to participate in sport seems to have significant value, especially for health practitioners and researchers to design appropriate interventions and programs to increase activity.

Background/Objectives: The mechanisms linking eating attitudes to well-being and physical activity objectives have increasingly attracted the attention of researchers in recent years. This research is particularly significant in the context of the COVID-19 pandemic, which has profoundly disrupted eating habits, exercise routines, and psychosocial well-being across the globe. Additionally, these variables are influenced by cultural dimensions, such as individualism in Poland and collectivism in China. These two countries represent distinct approaches to social health and well-being during the pandemic, offering valuable comparative insights into how cultural contexts shape mental and physical health behaviors; Methods: The study included 644 Polish and 690 Chinese participants. It utilized the Psychological Well-Being Scale (PWBS), the Coronavirus Anxiety Scale (CAS), the Eating Attitudes Test (EAT-26), and the Inventory of Physical Activity Objectives (IPAO); Results: The results indicate that both COVID-19 anxiety and eating attitudes fully mediate the relationship between well-being and physical activity objectives. Full mediation implies that the observed relationship between well-being and physical activity objectives operates entirely through the mediators. Notably, the mediating effect of COVID-19 anxiety was observed only in the Chinese sample, highlighting cultural differences in coping mechanisms and societal responses to anxiety. Cultural differences significantly influenced well-being and physical activity objectives, while eating disorders remained unaffected by cultural and social differences. Additionally, a significant positive correlation was found between COVID-19 anxiety, eating attitudes, and health-related physical activity objectives, underscoring the interplay between mental health and physical activity; Conclusions: These findings underscore the importance of addressing anxiety and eating attitudes to enhance well-being and physical activity behaviors. The study provides a strong theoretical basis for targeted interventions tailored to cultural contexts. Potential limitations include the reliance on self-reported data and differences in demographic characteristics between the Polish and Chinese samples, which may affect generalizability.