Research on Decision Tree-Based Strategic Modeling of Student Management and Civic Education in Colleges and Universities under Interdisciplinary Perspective

In the technical field of data mining domain, decision tree classification method has been widely studied and applied with the advantages of its algorithm theory is clear, easy to be understood and easy to be converted into classification rules. In this paper, we study the interdisciplinary integration of data mining technology with student management and civic education in colleges and universities, and construct a strategy model for student management and civic education in colleges and universities. In the model, based on the decision tree ID3 algorithm, it is proposed to improve the formation of the C4.5 algorithm to form C4.5 decision tree student data mining technology. Learning behavior data from four semesters of University A from 2022 to 2023 are used as samples to analyze the classification results. In the analysis of the decision tree classification results, the student behavior data were counted and the moral education scores were calculated to be greater than 50% in all four semesters for the “normal” classification, with the lowest percentage, less than 10%, in the at-risk period. The five main factors affecting the classification of moral education in the first half of 2022 were “talking and noisy in class”, “absenteeism”, “not tidying up the housekeeping of the dormitory as required”, “using mobile phones during class”, and “disobedience to management”, with corresponding importance of 7.48%, 5.56%, 3.51%, 3.1%, and 2.24%, which can help managers choose the right college student management and ideological and political education decisions.