The Practical Effects of College Ideological and Political Education Course Based on Artificial Neural Network Model
Xiaojuan Chen
Journal of E-Technology, Vol. 15, No. 1, 2024.
DOI: https://doi.org/10.6025/jet/2024/15/1/14-19
Link: https://www.dline.info/jet/fulltext/v15n1/jetv15n1_3.pdf
Abstract:
Constructing an evaluation system for the practical effects of college Marxist ideological and political education courses is beneficial for assessing existing ideological and political education work and also serves as a â€œcompassâ€ for improving corresponding work. Therefore, this study explores the practical effects of college Marxist ideological and political education courses based on a computer artificial neural network model. The article first establishes a â€œthree-dimensional index systemâ€ for evaluating ideological and political education in colleges based on the characteristics of artificial neural networks. Then, it introduces the computer artificial backpropagation (BP) neural network evaluation method and obtains strong empirical support through simulation experiments. Finally, a feasible â€œcollege artificial neural network ideological and political education evaluation modelâ€ is constructed. The simulation experiments show that the modelâ€™s actual output is very close to the expected results, and satisfactory results are achieved when testing the model with sample data. Using the BP neural network model effectively eliminates traditional evaluation methods, significantly increasing the implementation efficiency of the evaluation. The improvement of the BP neural network enhances its flexibility and performs excellently in training. The modelâ€™s expected performance in simulation experiments is highly consistent with actual performance, and it also achieves satisfactory results when measuring its performance using test data. In the field of college Marxist ideological and political education, it is a widely used evaluation method.