A Strategic Study on the Enhancement of the Effect of Data Analysis Technology on Student Management and Civic and Political Education in Colleges and Universities from an Interdisciplinary Perspective

Abstract

 Data analysis technology brings new historical opportunities for the innovative development of student management work in colleges and universities in the new era. This paper relies on the K-prototypes clustering algorithm to construct a student portrait method that serves the precise work of ideological and political work, proposes the index system and modeling method of student portrait, and carries out the clustering division of students in a university. Based on the results of student portrait, we discuss the optimization strategy of Civic Education, construct the Civic Education Effect Evaluation Model, and evaluate the effect of Civic Education before and after the experiment. The study divided the sample students into six categories: "weak awareness", "leading progress", "exemplary leader", "silent effort", "innovative practice" and "poor discipline", among which "guiding progress" and "silent effort" had the largest number of students, accounting for 36.7% and 23.3% respectively. After the implementation of the optimization strategy of the ideological education, the effect of the ideological education was improved from the average level to the better level, and the overall score was improved by 10.39%, which confirms the improvement effect of the student portrait and optimization strategy based on cluster analysis on the ideological education. Data analysis technology can help the development of ideological education in colleges and universities and improve the quality and efficiency of student management through the collection, organization and analysis of student-related data.