Optimization of physical education classes using artificial intelligence for students of SMG

Abstract

Objective of the study was to exploration of the potential for employing artificial intelligence to tailor physical education lessons for students in a specialized medical group, and the evaluation of the impact of this approach on the educational experience within the university.

Methods and structure of the study. The research work was conducted in two distinct phases. In the initial phase, which commenced in early 2023, an AI-based model was created. This model was employed to evaluate physical abilities and create personalized physical education plans for students in a special medical group at the Tomsk State University. The model is based on a multimodal neural network, specifically Generative Pretrained Transformer 4o.

Results and conclusions. The potential of AI in tailoring physical education lessons for students with specific medical conditions has been explored, and the success of its implementation in the university's curriculum has been evaluated. The use of AI has been shown to be highly effective in personalizing lessons for students with special medical needs. By considering the unique characteristics of each student's illness and physical abilities, AI has helped to enhance physical performance, reduce the frequency of disease flare-ups, and increase student satisfaction with their lessons.