Exploring Collaborative Parenting Strategies for Civics and Student Management in Colleges and Universities Using Multiple Data Chain Networks

In this paper, the multivariate data chain network is used to obtain the lexical sequence of Civics and Political Education, which needs to be labeled considering the convenience of research and analysis. According to the C-RTT algorithm can reduce the number of synchronization time slots required for fine synchronization of Civic and Political Network Teaching, use the Transformer encoder to assign and define the model parameters, and then construct the automatic scoring model with the theme of Civic and Political Work and Student Management. Starting from the content of the research and evaluation of the Civics and Political Science Program, the research variables and measurements are determined, and the research on the evaluation of the Civics and Political Science Program in colleges and universities is designed. Initial data for research and analysis are obtained by distributing questionnaires, and simulation analysis and statistical analysis are used to empirically analyze the Civics education combined with a multivariate data chain network. The results show that on the model analysis, the P value of the model in this paper can be up to 80.6, the R value can be up to 85.7%, the F1 value can be up to 83.2%, and the accuracy rate can be up to 82.4%, and the automatic scoring model with the theme of Civic and Political Work and Student Management has achieved good results. On the analysis of the Civics course, the mean values of the seven topics of student management are in the range of 3.78-4.18, and the standard deviations are all greater than 0.84. This study skillfully applies the theory of Civics to student management and ultimately helps the students to establish the correct three views. © 2023 Zengqiang Kong, Lingling Chen and Qiaoran Jia, published by Sciendo.