Meta-Synthesis of Qualitative Research on Artificial Intelligence in Physical Education: Performance, Ethics, and Global Trends

Background: This study explores the transformative potential of Artificial Intelligence (AI) in Physical Education (PE), examining its capacity to enhance instructional quality and student engagement. It also critically addresses ethical concerns and implementation challenges across culturally diverse and resource-variable contexts.Methods: This qualitative study employed the Sample, Phenomenon of Interest, Design, Evaluation, and Research type (SPIDER) framework to systematically retrieve and synthesize 41 peer-reviewed articles from academic databases including ScienceDirect, Elsevier, ProQuest, ERIC, Taylor & Francis, and UNESCO. The studies were preliminarily screened and then appraised for quality utilizing the Mixed Methods Appraisal Tool (MMAT). Lastly, thematic synthesis was done in a bid to discern significant patterns and results regarding the research point of emphasis.Results: Thematic synthesis identified six key themes in the integration of AI in PE: performance optimization, individualized learning, data-informed assessment, engagement and motivation, improvement in the educational process, and ethical challenges in implementation. Whereas AI shows considerable promise in remodeling PE practices, implementation remains differential across locations. Inhibitors like restricted access to equipment and technology, ethical concerns, and differences in institutional emphasis persist in dictating the course of AI implementation. Comparative analysis across locations also served to emphasize differences in approach and areas of emphasis in AI-infused pedagogy.Conclusion: Effective AI integration in PE is contingent upon context-aware design, improved instructor readiness, and effective ethical leadership. Inclusive professional development and culturally informed frameworks ought to initiate balanced and resilient use.