This study aims to explore and optimize the "teaching, practicing, and competing" sports teaching model by integrating artificial intelligence (AI) technology. It focuses on building a new intelligent ecosystem for sports education, emphasizing the connection between "teaching," the bridging role of "practicing," and the efficiency of "regular competition" to enhance students' sports skills and literacy. Through AI, the study enables personalized teaching content, intelligent practice feedback, and automated competition management. This approach provides innovative ideas and theoretical support for school physical education, promotes the deep integration of "learning, practicing, and competing," and strengthens school sports education in the new era. This paper explores the new path of AI-enabled extracurricular physical activity practice from the perspective of "teaching, practicing, and competing" by means of literature and logical analysis to lay a theoretical foundation for promoting the development of school physical education. Currently, there is a formalism erosion in extracurricular activities in schools, single and boring organizations, and a lack of activity resources, which seriously impede the integrated development of "learning, training, and competing" and affect students' interest and the effect of physical exercise. The AI intelligent sports program in this study integrates artificial intelligence and competitive elements, which can greatly enhance students' motivation to learn and practice. At the same time, the system can realize the daily exercise and competition, flexibly arrange the study and practice plan, combine online and offline, enrich the after-school life, and cultivate sports habits. Secondly, the AI system provides comprehensive data support to ensure fair and accurate teaching evaluation. Finally, AI Smart Sports also saves teaching resources, reduces teachers' burden, and improves teaching efficiency and quality through intelligent teaching assistance. Since the AI intelligent sports system is in the initial development stage, there are still deficiencies, so in order to better solve the dilemma of the problem put forward the following suggestions: (I) Innovate the content of AI learning and practicing, the core of the AI intelligent sports system lies in the diversified learning and practicing content, and the need to continue to update sports knowledge. (II) Build an information-sharing platform to promote cross-school communication, integrate teaching resources, and stimulate dynamic updating potential. (III) Implement stratified optimization management, staggered use of resources, and intelligent scheduling to improve efficiency. (IV) Establish a quality assessment system, collect user feedback, regularly evaluate system effectiveness, and continuously optimize content to ensure user experience.
Ye Wu (Thu,) studied this question.