Analysis of the Influence Path of Confucianism in the Civic Education of Contemporary College Students in the Context of Big Data

Abstract

Abstract Under the background of big data, college students’ Civic Education has realized the adjustment of teaching technology and educational paradigm, and the value of big data technology for college students’ Civic Education has become increasingly intuitive. In this paper, firstly, the data points designated for clustering are selected in the dataset as the initial clustering centroids. In response to the Euclidean distance treating variables equally, the coefficient of variation method is proposed for subjective weighting. The support vector machine for solving the two-class classification problem is obtained as a real-valued function to test the parallel efficiency of different clustering mining algorithms in the same experimental setting. Finally, for the training sample input data, it is concluded that the algorithm has a better clustering effect and improves the speed and accuracy of clustering. The feasibility of the proposed influence path is demonstrated by comparing it with the data application of the subjective empirical weighting method. The results show that 8% of students before the experiment thought that integrating Confucianism into Civic Education was valuable and meaningful, and after the experiment, the number of students who thought it was valuable and meaningful increased from 8% to 58%. It indicates that the integration of excellent traditional Confucianism into the ideological and political education of college students is very important to strengthen the ideological and political education of college students.