Artificial Intelligence in Women’s Physical Education: A Systematic Review of Student Engagement, Pedagogical Optimization, and Educational Equity

Abstract

Against the backdrop of accelerating digital transformation in education, this study critically examines the integration of Artificial Intelligence (AI) within women’s physical education (PE) settings, with the overarching objectives of enhancing student engagement, refining pedagogical content, and advancing educational equity across gender lines. Employing a comprehensive and systematic literature review methodology, the study maps the current landscape of AIdriven educational innovations, investigating how personalized training systems, realtime motion recognition feedback, and sophisticated data analytics can be leveraged to address genderspecific learning needs, improve female students’ PE experiences, and foster holistic physical and affective development. The synthesized evidence indicates that AI technologies significantly enhance teaching interactivity and learner autonomy, thereby boosting intrinsic motivation and cultivating sustainable physical literacy among female participants. Concurrently, however, the analysis unveils critical implementation challenges, including unequal access to technical infrastructure, heightened concerns over data privacy and security, and the latent risk of algorithmic bias that may inadvertently perpetuate rather than mitigate existing gender disparities. By systematically delineating both the transformative potential and the inherent limitations of AI applications in this domain, this study contributes a robust theoretical foundation and offers actionable practical guidance for policymakers, curriculum developers, and PE practitioners seeking to navigate the intelligent transformation of women’s physical education in a globally connected and digitally mediated era.