Abstract
Background: Artificial intelligence (AI) is rapidly transforming physical education and sport science through applications in movement analysis, personalized instruction, performance prediction, injury-risk management, and administrative decision-making. However, its educational and scientific value depends on effective pedagogical integration, reliable data, professional oversight, and equitable access. Objective: This study synthesizes emerging applications of AI in physical education and sport science and develops a human-centered framework for responsible and sustainable adoption. Methods: A structured conceptual review and thematic policy analysis were conducted based on research concerning computer vision, wearable sensing, machine learning, learning analytics, sport performance, and AI ethics. AI applications were systematically examined according to their primary purpose, data sources, users, potential benefits, and associated risks. Results: Five major application domains were identified: intelligent assessment, personalized learning, performance analytics, health and safety support, and program governance. Based on these domains, the study proposes the Human-Centered AI for Physical Education and Sport Science (HAIPESS) framework, structured around five principles: pedagogical purpose, multimodal evidence, professional judgment, learner agency, and accountable governance. Conclusions: AI should function as an augmentative technology rather than a substitute for teachers, coaches, clinicians, and researchers. Responsible adoption requires valid and reliable measurement, robust privacy protection, transparent and explainable systems, inclusive design, AI literacy, and continuous evaluation of educational, performance, and health outcomes. The HAIPESS framework provides a practical foundation for integrating AI into physical education and sport science while maintaining human agency, professional responsibility, and educational quality.
References
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