Modeling Student Management and Civic Education Strategies from an Interdisciplinary Perspective

Abstract

Abstract This paper issues from an interdisciplinary perspective, combining computer technology, principles of management and other multi-disciplinary knowledge to build a model of student management and civic education strategy. Two modules are part of the student management model: student behavior analysis and prediction. In student behavior analysis, the fuzzy C-means clustering algorithm is improved, and the Gaussian density function is used to determine the initial clustering center. In student behavior prediction, the convolutional network is used to input raw data, and the extracted features are inputted into the CABLSTM model for training and prediction of student behavior. The Civic Education Strategy Model is built on the principle of feedback control and is constructed at the school, family, and individual levels. In the analysis of student management and Civic and Political Education practice, teaching practice was conducted at University C in Lanzhou City, Gansu Province, China. After the practice, the number of students who are very satisfied and satisfied with the overall student management is 2, 356, accounting for 65.81%, and the comprehensive quality of students is in the middle to high range. The students’ life values, family and national sentiment, and thought level dimensions in Civic and political literacy have significant differences (P<0.05), and the level of mastery of Civic and political knowledge is good.