Teaching Quality Evaluation Method of Higher Education based on Particle Swarm Optimization Neural Network

DOI

10.2991/978-94-6463-264-4_73How to use a DOI?

Keywords

Institutions of higher learning; Teaching quality evaluation; PSO neural network

Abstract

In order to address the shortcomings of traditional teaching quality evaluation systems, researchers have implemented PSO neural network technology to develop a teaching quality evaluation system for colleges and universities. This system utilizes PSO neural network technology, with teaching evaluation standards as inputs and teaching evaluation results as outputs. By using Anhui University of Science and Technology as a case study, empirical research demonstrates that this approach not only mitigates the direct impact of human factors on evaluation outcomes, but also provides a basis for establishing a comprehensive and rational evaluation index system.

Copyright

© 2024 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  - Bin Tang
AU  - Haibing Cai
AU  - Changbo Wang
AU  - Xiaohu Liu
AU  - Fenglin Zhang
PY  - 2023
DA  - 2023/09/28
TI  - Teaching Quality Evaluation Method of Higher Education based on Particle Swarm Optimization Neural Network
BT  - Proceedings of the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023)
PB  - Atlantis Press
SP  - 633
EP  - 639
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-264-4_73
DO  - 10.2991/978-94-6463-264-4_73
ID  - Tang2023
ER  -