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Evaluating the Effectiveness of an AI-Assisted Personalized Learning Pathway in Mobile-Supported Online Physical Education

Oct 2026 · International Journal of Mobile and Blended Learning · 24 references
Educational Technology and Pedagogy

Abstract

This study evaluates the effectiveness of an AI-assisted personalized learning pathway in mobile-supported online physical education. To overcome issues of homogeneous content and delayed feedback, a system integrating cognitive knowledge, physical fitness, and motor skills was developed. Reinforcement learning dynamically adapted learning pathways, while edge-based computer vision enabled real-time feedback on low-end mobile devices. A randomized controlled trial with 120 students over eight weeks compared the proposed system to conventional video-based instruction. Results showed low inference latency (34.8 ms) and a 61.2% reduction in movement variability. NASA-TLX scores revealed lower mental demand and frustration, with high learner engagement. The findings highlight the effectiveness of AI-assisted personalization and mobile feedback in improving learning outcomes and experiences in online physical education.

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