Augmentation or substitution: defining role of large language model in physical education

Large language model has seen rapid uptake in education alongside advances in artificial intelligence. Its capabilities in areas such as healthcare planning and question answering suggest strong potential for supporting personalised instruction in physical education. At the same time, studies have raised concerns regarding safety, accuracy, and contextual appropriateness. This study examines the role of large language model in physical education and evaluates its suitability as an assistive tool or possible alternative to human instruction.

This study conducted a questionnaire-based evaluation comparing three generative approaches for producing physical education lesson plans and teacher responses: (1) plans written directly by a large language model, (2) plans produced by a large language model after being provided with domain resources, and (3) plans created collaboratively by physical education teachers together with the large language model. Feasibility, practicality, safety, adaptability, and content quality were assessed across these approaches. Large language model-generated responses in typical physical education scenarios were further evaluated in terms of response accuracy, safety, clarity, adaptability, guidance quality, acceptability to learners, and perceived potential to enhance teacher response efficiency.

Lesson plans produced collaboratively by physical education teachers and the large language model outperformed those produced solely by the large language model-both with and without additional resources-across all evaluated dimensions. In addition, responses generated by the large language model in physical education scenarios were rated highly for clarity, guidance, adaptability, and support for teacher efficiency.

The large language model demonstrates clear value in physical education, particularly as a means to support and augment instructional design and responsiveness. However, it does not yet replace the pedagogical judgment, contextual awareness, and safety oversight of human instructors. Overall, this study concludes that the large language model is best positioned as an assistive tool to optimise teaching practice rather than as a standalone replacement for human teachers.