Analysis of the Innovation Path of Marxism Popularization Based on Big Data Analysis

Abstract

Marxist theory points out that practice is the method of understanding the world, and it is also the essential characteristic of human beings. Based on the above theoretical basis and guidance, this paper, from the perspective of ideological and political education evaluation, conducts research on student behavior in Marxist popular classrooms, grasps the characteristics of student behavior in Marxist popular classrooms in the new era, and explores behavioral research. Approaches and methods for ideological and political education evaluation and student evaluation were introduced. This paper analyzes the combination method of AHP and BP neural network in the previous research and points out its limitations. On this basis, it innovatively proposes an inherited combination method of AHP and BP neural network and conducts model training and exact match experiment based on AHP and BP neural network. Finally, by comparing and analyzing the above four sets of experimental results, it is found that the inheritance-type combination method of AHP-BP neural network not only avoids the problem of small AHP capacity but also scientifically integrates hierarchical weights with theoretical basis into the calculation of BP neural network. In addition, the inheritance-type combination of AHP-BP neural network in this study can replace the normalization of data and effectively improve the training speed and matching accuracy of the precise matching model for political classrooms in colleges and universities under the new situation.