Intelligent Integration of Civic and Political Elements in Physical Education Teaching and Design of Personalized Learning Paths

Abstract

Based on the application value of Civics and Politics elements in physical education teaching, this paper constructs a personalized management framework that includes learning state feature analysis, learning effectiveness prediction, teaching intervention decision-making and other parts, and utilizes the techniques of reinforcement learning algorithms and Q-functions to study students' behaviors and assist teachers in decision-making. The Civics element is integrated into the personalized management framework of physical education teaching, and the effectiveness of the method in improving students' Civics cognition, physical fitness, and mental health is studied through comparative experiments. In the comparison of the level of civic and political cognition, the P-values of seven indicators such as national self-confidence and three indicators such as the spirit of striving are less than 0.05 after the experiment, which proves that the approach of this paper can significantly improve the level of students' civic and political cognition. In the comparison of physical condition, the P-value of 6 indicators such as 50-meter running after the experiment is less than 0.05, and the physical quality of the students in the experimental class is significantly better than that of the control class, which proves that this paper's approach can effectively improve the physical quality of the students. In the comparison of mental health, the P-value of 5 indicators such as depression factor after the experiment is less than 0.05, and some indicators are less than 0.01, and the mental health of the experimental class is significantly better than that of the control class, and the learning path of this paper also has a certain role in promoting students' mental health.