This study proposes a novel approach for physical education (PE) that integrates kinect motion tracking, deep learning, and context personalisation. The system combines real-time feedback and adaptive learning paths to optimise student participation, motivation, and physical skill development. An ablation study was conducted to compare the effectiveness of the full system with three other configurations: kinect-only motion tracking, kinect with context personalisation, and kinect with deep learning. The experimental results indicate that the full system, which combines all three components, significantly outperforms the other configurations in terms of motivation, physical performance improvement, and engagement. Specifically, the full system achieved the highest improvement in skill development (90%), engagement (98%), and motivation, suggesting that the combination of kinect motion tracking, context personalisation, and deep learning is most effective for enhancing PE outcomes. This research contributes to the digital transformation of physical education. It provides a new pathway to leverage technology for improving both student motivation and performance.
Yuqiu Zhang (Thu,) studied this question.