Data-driven Modeling of Comprehensive Academic Level and Physical/Moral Education for Students in Control Discipline

Physical education and moral education, as two important components, have a profound impact on the overall development of students. This work deeply studies the relationship between physical/moral education and students’ comprehensive academic level through data-driven modeling. Based on students’ grades in physical/moral-related courses, three machine learning models, logistic regression, support vector machine and random forest, are constructed to realize the high-accuracy classification of the students having different comprehensive academic level. Experimental results show that the constructed data-driven models can achieve significant accuracy and stability in predicting students’ comprehensive academic level. It proves that physical education and moral education have obvious positive correlation with students’ comprehensive academic level, and thus highlights the importance of physical/moral education in students’ all-round development.