Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

October 17, 2023


Pages


DOI

Article

An Innovative Discussion on Ideological and Political Education for College Students Based on Digital Mining

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Authors

Dan Hu Affiliation:
School of Computer Science, Southwest Petroleum University, Nanchong, Sichuan, 637001, China.
, Jing Xue Affiliation:
School of Science, Southwest Petroleum University, Nanchong, Sichuan, 637001, China.
and Guoyong Shi Affiliation:
School of Computer Science, Southwest Petroleum University, Nanchong, Sichuan, 637001, China.


Abstract

In this paper, a self-organized data mining model for college students’ ideological and political education is constructed. Firstly, a suitable input-output association set is specified to build the model, and then one or more are selected as the outer criterion to filter the model. The models of each layer are evaluated by the outer criterion, and the optimal complexity model is established by finding the model structure and the law of system operation through the selection of different models. Then unknown correlations between factors of ideological and political education were mined from the data samples, and the system variables were predicted and analyzed. Finally, the model is applied to analyze the effect of ideological education and the influencing factors of College A. The p-value of the degree of matching between education level and professional level is 0.456, and the education level will have a significant influence on ideological and political education. The research in this paper is important for the development of ideology and politics in colleges and universities.


Keywords

Optimal complexity, Data mining, Least squares, Ideology and politics, 97Q70


Citation

Hu, D., Xue, J., & Shi, G. (2023). An innovative discussion on ideological and political education for college students based on digital mining. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.00677

Published by: Engineering Journals

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