A226: The Application and Exploration of an AI Agent in Physical Education Teaching

With the rapid development of artificial intelligence technology, AI-Agent, as a new type of educational technology tool, has gradually attracted widespread attention. As a system based on generative large-scale intelligent models, AI-Agent possesses core capabilities such as environmental perception, autonomous decision-making, and complex task execution. In the field of physical education, this technology holds significant application potential, particularly in personalized teaching, multimodal data processing, and enhancing teaching efficiency. However, current research on the application of AI agents in physical education is relatively scarce. This study explores the application of AI-Agent in physical education, analyzes its advantages, and investigates methods for constructing an AI-Agent system suitable for physical education, aiming to provide theoretical and practical guidance for the digital transformation of physical education. Method: The case study method was adopted, with middle school football-specific teaching as the research object. AI-Agent was applied in teaching practice, and data and feedback information were collected. The research design involved detailed documentation and analysis of the process of building, applying, and optimizing the AI-Agent. Data collection methods included classroom observation, student feedback questionnaires, and teaching effectiveness evaluation. AI-Agent has significant advantages in physical education. It can provide personalized guidance and feedback based on students' situations, enhancing their interest and participation. It supports multiple skill plugins in teaching, such as motion analysis and heart rate monitoring, and processes multimodal data. It can also design complex workflows based on data information and integrate local knowledge bases to generate precise teaching plans. Both students and physical education teachers are generally satisfied with the use of AI-Agent, believing that it can improve teaching efficiency and learning outcomes. AI-Agent can significantly enhance teaching quality and student experience in physical education. Through personalized teaching and multimodal data processing, it improves teaching efficiency and learning outcomes. However, there are still issues such as high technical requirements and limitations in data and network. Future research should focus on optimizing the functions and interactions of AI-Agent, exploring its application effects in different sports and teaching scenarios, and studying how to combine it with traditional teaching methods to improve teaching efficiency. This study provides new teaching tools and methods for physical education teachers, contributing to the digital transformation of physical education, improving teaching quality, and promoting the all-around development of students.