The Influence of AI-Powered Personalized Feedback Systems on Motor Skill Development and Self-Efficacy in PE Learning among University Students in Heilojiang, China

Abstract

This study explored the purported benefits of AI-powered personalized feedback systems on university students' motor skill development and self-efficacy within physical education (PE) in Heilongjiang, China. Employing a quantitative, quasi-experimental design, the research sought to compare an AI-feedback group against a control receiving traditional instruction. While the analysis reported robust, statistically significant improvements across all measured motor skill performance indicators and substantial gains in self-efficacy within the AI-feedback group, a critical interpretation is warranted. These preliminary findings, though seemingly positive, originate from a design that, by its quasi-experimental nature, may not fully eliminate confounding variables inherent to educational settings. The reported "very strong" and "significant" improvements in the experimental group, while statistically compelling, lack direct comparative between-group statistical measures in the provided summary, thus preventing a definitive claim about AI's superiority over traditional methods based on this excerpt alone. While the internal gains within the AI group are clear, the extent to which these surpass the improvements of a rigorously controlled traditional group remains to be fully demonstrated. Nonetheless, the observed magnitude of change strongly suggests a notable impact, implying that AI-powered feedback holds considerable potential to address the logistical challenges of individualized instruction in large PE classes, thereby fostering enhanced learning outcomes and bolstering self-efficacy. Future research employing more rigorous comparative analyses with actual data and incorporating qualitative insights is crucial to fully validate and contextualize these promising preliminary results.