Research on Quality Evaluation and Feedback Mechanism of Engineering Management Education Based on Artificial Intelligence

DOI

10.2991/978-2-38476-452-5_27How to use a DOI?

Keywords

artificial intelligence; engineering management education; dynamic weight adaptive evaluation algorithm; quality assessment; feedback mechanism

Abstract

Aiming at the problem of quality evaluation of engineering management education, this study proposes a dynamic weight adaptive evaluation algorithm (DWAEA) to construct an intelligent evaluation and feedback mechanism. The algorithm is based on the multi-dimensional data characteristics of engineering management education, and uses adaptive weight theory to achieve accurate evaluation through data preprocessing, dynamic weight adjustment and comprehensive evaluation calculation. In the experimental stage, 1,200 student data from 5 colleges and universities were collected to construct a data set. In the Python environment, the simulation was carried out in combination with Scikit-learn and TensorFlow libraries, and the DWAEA algorithm was compared with the traditional weighted average method, BP neural network algorithm, and random forest algorithm. The results show that the accuracy of the DWAEA algorithm is 92.3%, which is 18.7% higher than the traditional method and 12.4% higher than the BP neural network algorithm; the recall rate is 89.6%, which is 15.3% higher than the traditional method and 10.2% higher than the BP neural network algorithm. After the feedback mechanism constructed based on this algorithm was piloted in a certain college, the rate of excellent student grades increased from 18% to 27%, and the course satisfaction increased from 68% to 85%. The study shows that the DWAEA algorithm and feedback mechanism significantly improve the accuracy of education quality assessment and management efficiency, providing a new path for the development of engineering management education.

Copyright

© 2025 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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TY  - CONF
AU  - Luan Kai
AU  - Pan Di
AU  - Zhang Shiyu
PY  - 2025
DA  - 2025/07/31
TI  - Research on Quality Evaluation and Feedback Mechanism of Engineering Management Education Based on Artificial Intelligence
BT  - Proceedings of the 2025 4th International Conference on Science Education and Art Appreciation (SEAA 2025)
PB  - Atlantis Press
SP  - 216
EP  - 222
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-452-5_27
DO  - 10.2991/978-2-38476-452-5_27
ID  - Kai2025
ER  -