A BP Neural Network Model for Evaluating the Literature and Art Career of College Students’ Political and Ideological Education

Abstract

The evaluation of the literary and artistic carrier of the political as well as the ideological education of college students is an important research topic in contemporary college education concepts. Since it consists of multiple variables, there are still many difficulties in evaluating the ideological productivity of college students. The same statement is true for political education as well. This paper builds a model for the literary and artistic carrier of the political as well as the ideological education of college students based on the backpropagation neural network (BPNN) structure. Furthermore, we study the current status of the literary and artistic carrier of the political along with the ideological education of college students. This paper implements the BP neural network to model the literary and artistic carrier of college level graduate students’ political and ideological education in order to analyze the dynamics of contemporary college students’ ideological differences. Finally, we provide an adequate theoretical basis for inquiry, from qualitative description to quantitative analysis. The suggested approach may successfully avoid the old model’s instability and sluggish convergence issues as well as significantly increase the correctness of the evaluation findings for literary and artistic carrier of the political as well as the ideological education of college students.