From field to cloud: Integrating AI-driven coaching in modern sport education

Abstract

The integration of Artificial Intelligence (AI) in sport education has marked a transformative era in how coaching, learning, and performance development are conceptualized. This paper critically examines current research and emerging trends in AI-driven coaching, focusing on its pedagogical potential, technological applications, and challenges within modern sport education. Drawing from peer-reviewed articles published between 2015 and 2025, the analysis synthesizes studies across domains such as biomechanics, learning analytics, machine learning, and educational technology. The findings reveal that AI-based coaching systems—encompassing motion capture analysis, performance prediction algorithms, and virtual training assistants—significantly enhance feedback precision, athlete engagement, and individualized learning experiences. Moreover, AI facilitates adaptive pedagogy, enabling educators to tailor instructional strategies based on learners’ real-time performance data. However, the literature also highlights substantial barriers, including limited educator readiness, ethical concerns about data security, and disparities in access to advanced technologies. Theoretical frameworks such as constructivism and self-determination theory are frequently employed to interpret how AI-mediated environments support active learning, motivation, and self-regulation in sport settings. Despite promising outcomes, gaps remain in empirical validation and in understanding the long-term educational impact of AI integration. This analysis concludes that the shift from traditional field-based coaching to cloud-enabled, AI-driven environments represents a paradigm shift in sport education. By synthesizing the current evidence base, this paper provides a foundation for future research exploring sustainable models for AI adoption in sport education.