Research on the Application of Data Mining Technology in the Construction of Collaborative Educational Mechanism of Party Building and Civic Education in Colleges and Universities

Abstract

In the data related to the parenting activities of party building and ideological education in colleges and universities, there are association laws that cannot be judged intuitively. In order to promote the development of this nurturing activity, this paper constructs a data mining model to mine the comprehensive features of student activity data based on three dimensions: logistic regression, random forest and support vector machine. Then, using the dynamic association rule mining algorithm, we analyze the association rules between activities and students' comprehensive characteristics from the dimensions of party building activities and ideological activities to optimize the collaborative parenting mechanism. After the optimized parenting mechanism in practice, the average score of comprehensive literacy of students in the experimental group increased from 5.70-6.00 to 9.59-9.82, and there was a significant difference at the 0.001 level. Optimizing the mechanism of collaborative education through data mining has a promoting effect on students' party building and civic and political quality.