Theory of physical education ecosystem based on SFIC model

Abstract

Through comparison and logical analysis, the author expounds the basic concepts and components of the physical education ecosystem are expounded, the SFIC physical education ecosystem model is established, and a student sports performance warning method based on machine learning is proposed. In view of the heterogeneous student behavior data, data preprocessing technology is adopted to preprocess sample data, and data characteristics are extracted based on knowledge points and item types. A sports achievement warning model (K-DNN) based on knowledge points and item types is established, and the students' sports achievement warning model is designed and implemented. The experimental results show that, compared with DNN algorithm, Adaboost and ridgeregregression, K-DNN algorithm has the highest accuracy in predicting Ac and the lowest mean square error in predicting MS, indicating that K-DNN model has higher accuracy and better motion prediction effect.