Design of AIGC Content Generation Framework for Gymnastics Teaching Based on Diffusion Model - Creation and Practical Application of Personalized Learning Resources

For the strategy of building a sports power, gymnastics teaching is confronted with the core contradiction between the high-precision requirements of movements and the insufficient supply of personalized resources. Generative artificial intelligence (AIGC) provides a technical path for innovation in this field. This study constructs an AIGC content generation framework for gymnastics teaching based on the diffusion model. Experimental verification shows that this framework significantly outperforms the baseline model in terms of generation quality, action coherence and personalized adaptability, enriching the application research of AIGC in the vertical teaching field.