Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023)

Modeling Analysis of Quantitative Evaluation of Ideological and Political System of Engineering Management Course Based on Cluster Analysis Algorithm

Authors
Shu Zong1, *
1Jinqiao College of Kunming University of Technology, Kunming, Yunnan, China
*Corresponding author. Email: 928288652@qq.com
Corresponding Author
Shu Zong
Available Online 30 June 2023.
DOI
10.2991/978-94-6463-172-2_39How to use a DOI?
Keywords
Cluster Analysis; Engineering Management; Ideology and Politics of Engineering Management Courses; Quantitative Evaluation
Abstract

The core connotation of the ideological and political course of engineering management is to widely carry out political identity education centered on supporting the leadership of the Communist Party of China while imparting professional knowledge to students, so as to construct a project for students that is in the same direction as the ideological and political theory course. Manage the course environment. This paper aims study the quantitative evaluation modeling analysis of the ideological and political system of engineering management courses based on the cluster analysis algorithm. Through literature research and empirical investigation, this paper finds that the current ideological and political construction of engineering management courses has the following main problems: At the level of understanding and theoretical research on the ideological and political construction of engineering management courses, it is found that university management, professional teachers, etc. “It is very common to be confused with the “virtue” of establishing morality and cultivating people. In this paper, we write the algorithm program based on the EM algorithm improved by fuzzy theory, and verify the ability to eliminate anomalies and process accurate data and fuzzy data with three examples. The EM algorithm is used to model the comprehensive ideological and political education system in universities. Analyze and put forward the bad data of the department of ideological and political education, build a better and more perfect ideological and political curriculum system, and realize the establishment of the ideological and political curriculum system of engineering management.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
30 June 2023
ISBN
10.2991/978-94-6463-172-2_39
ISSN
2589-4900
DOI
10.2991/978-94-6463-172-2_39How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Shu Zong
PY  - 2023
DA  - 2023/06/30
TI  - Modeling Analysis of Quantitative Evaluation of Ideological and Political System of Engineering Management Course Based on Cluster Analysis Algorithm
BT  - Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023)
PB  - Atlantis Press
SP  - 353
EP  - 361
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-172-2_39
DO  - 10.2991/978-94-6463-172-2_39
ID  - Zong2023
ER  -