A Study on a New Way of Thinking Based on Linear Programming to Analyze Civic Education in Colleges and Universities

Author:

Tang Qi1,Yang Yue1

Affiliation:

1. Wuxi Institute of Technology , Wuxi , Jiangsu , , China .

Abstract

Abstract This paper intends to construct a new multi-dimensional preference analysis model for learners by using the improved linear programming method of multi-dimensional preference analysis (LINMAP) to get the weight vector of attributes under the situation that the weights of attributes are completely unknown and for the uncertain multi-attribute decision-making problem that the elements of decision-making matrix are triangular fuzzy numbers, and the preference information is ordered pairs. The data of subjective or objective Civics education learning preferences are aggregated, and the statistical analysis of the data is carried out using SPSS.21 to generate the Civics education learning preference input degree weighting system. The results show that the offline behavioral input weight in the college Civics course is 0.5769, which is greater compared to the online input. And the attribute weights of course Civics preference are calculated to get Z max = 2.29, Z min = 0.73. Multiple feasible solutions can be obtained by taking any value between [0,1]. Based on the development law of the times, this paper makes a new thinking on ideological and political education and actively explores a new road suitable for the development of ideological and political education in colleges and universities.

Publisher

Walter de Gruyter GmbH

Reference18 articles.

1. Tian, Y. (2022). Teaching effect evaluation system of ideological and political teaching based on supervised learning. Journal of Interconnection Networks.

2. Wang, Z. C. G. (2015). Investigation of the effective combined method of ideological, political education and psychological health education. International Journal of Technology, Management.

3. Xia, T., & Ahmad, M. T. (2022). Method of ideological and political teaching resources in universities based on school-enterprise cooperation mode. Mathematical Problems in Engineering, 2022.

4. Gao, B. (2022). Application of convolutional neural network in emotion recognition of ideological and political teachers in colleges and universities. Scientific Programming.

5. Zhang, A., & Liu, F. (2017). Research on the computer-based multi-dimensional ideological and political education of college students. Revista de la Facultad de Ingenieria, 32(8), 303-310.

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