Artificial Intelligence-Driven Pedagogical Transformation in Physical Education: A Systematic Literature Review of Trends, Applications, and Implementation Challenges

Abstract

The rapid development of Artificial Intelligence (AI) is reshaping pedagogical practice in Physical Education (PE), yet evidence on how AI functions pedagogically and what impedes its implementation remains fragmented. This study conducted a Systematic Literature Review (SLR) following the PRISMA 2020 guidelines using the Scopus database. Of 2,096 records initially identified, 400 were screened and 27 peer-reviewed studies published between 2020 and 2025 met the eligibility criteria and were synthesized thematically. AI applications in PE clustered into four categories: activity monitoring through wearable and IoT sensors, motor skill assessment using computer vision and machine learning, personalized learning through adaptive systems, and AI-enhanced gamification. These applications were associated with higher student motivation, more objective assessment, and more responsive instruction. However, the review identified four specific and interrelated implementation challenges: (1) limited teacher readiness, reflecting gaps in data literacy and in the pedagogical competence needed to interpret algorithmic feedback; (2) infrastructural and cost barriers, including dependence on connectivity, sensors, and technical maintenance, which disadvantage resource-constrained schools; (3) ethical and data-governance risks related to the collection of physiological and behavioral data, consent, and algorithmic bias; and (4) an evidence gap, as most studies were short-term, conducted in higher education, concentrated in a few national contexts, and rarely examined long-term learning outcomes. The review offers an integrative account of AI-driven pedagogical transformation in PE and argues that its effectiveness depends on the alignment of technological capability, teacher competence, and institutional support. Practical implications include content-specific teacher professional development, equitable infrastructure provision, and explicit data-governance policies.