Research on Effective Methods to Enhance the Quality of Ideological and Political Education in Colleges and Universities under the Perspective of Internet Plus

Abstract

More current research focuses mainly on the construction and innovation of the mechanism of Civic and Political education, and there are few studies related to improving the quality of Civic and Political education from the perspective of student behavioral data. In this paper, we use the data mining structure to deeply mine the students’ civic and political behavior, give the improved K-means and plain Bayesian algorithms based on principal component analysis, and design a data warehouse by applying the campus card data for college students. The data on students’ ideological and political behaviors were mined from three aspects of consumption, study, and life. A perception model of students’ mental health status was established by combining the data of students’ ideological and political behaviors in the campus one-card system with the plain Bayesian algorithm to analyze the students’ mental health status in depth. The results show that the peak monthly consumption of students in the second category of student consumption behavior reaches 893.4 yuan, and the proportion of students in the second category of life behavior reaches 62.13%. In the results of mental health state perception, 32.67% of students have the potential risk of suicide, and more than 50% of students have different degrees of depression. Ideological and political education in colleges and universities need to focus on developing students’ mental health and carry out diversified educational activities to improve the quality of ideological and political education in colleges and universities.

Keywords

• k-means algorithm
• plain bayes
• data mining
• state perception model
• student behavior
• 93c62