Driven by the policies of Education Informatization 2.0 and the "14th Five-Year Plan" for Sports Development, artificial intelligence (AI) technology is profoundly reshaping physical education teaching models. This paper aims to explore a new paradigm for scientific exercise among middle school students from the perspective of human-machine collaboration, addressing core issues in traditional physical education such as inefficiency in standardized teaching, high risks of sports injuries, and uneven resource allocation. By leveraging multimodal data collection and intelligent algorithms, a tripartite theoretical framework for physical education is constructed, encompassing "data penetration, scenario creativity, and resource integration." This framework enables innovative scenarios such as sports risk assessment, personalized exercise program generation, and immersive skill training. Practical evidence demonstrates that AI technology significantly enhances teaching precision and educational inclusivity, while also transforming the role of teachers from "skill demonstrators" to "data interpreters" and "lifelong learning facilitators." The study also highlights challenges such as technological dependency, data privacy concerns, and insufficient teacher competencies, proposing solutions such as a "human-machine co-education" decision-making mechanism, optimization of data governance systems, and interdisciplinary teacher training. Future efforts should focus on deepening the integration of AI with curriculum standards and building a "home-school-community" collaborative ecosystem for scientific exercise, providing practical pathways for the Healthy China strategy and the modernization of education.

Zhang Kai. A New Paradigm for Scientific Exercise Among Middle School Students from the Perspective of Human-Computer Collaboration: A Study on Intelligent Transformation and Innovation Pathways in Physical Education Based on DeepSeek. Frontiers in Sport Research(2025), Vol. 7, Issue 2: 13-19. https://doi.org/10.25236/FSR.2025.070203.

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