Optimization of environmental engineering practical teaching system based on cellular mechanics principles and construction of multi-dimensional evaluation model
Abstract
In the realm of emerging engineering education, the practical teaching of environmental engineering majors cries out for reform and optimization, which can be analogized to the regulatory mechanisms within cellular molecular biomechanics. Cells maintain their functionality and adaptability through a complex network of molecular interactions and signaling pathways. Similarly, an effective practical teaching system must have a well-structured and optimized framework. This study aims to explore the reform of the practical teaching system for environmental engineering majors in the context of emerging engineering education. A multi-dimensional evaluation model was constructed based on the Analytic Hierarchy Process (AHP), and the heuristic algorithm was integrated for weight optimization. The results show that the Improved Genetic Particle Swarm Optimization (IG-PSO) exhibits significant advantages in optimizing the weights of various indicators. After optimization, its Consistency Ratio (CR) decreased to 0.07, representing a 53% and 46% improvement over Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), respectively. Additionally, the fitness value of IG-PSO after 800 iterations reached 0.046, significantly outperforming other comparative algorithms. Furthermore, the assessment of teaching effects in dimensions like experimental performance and innovation ability parallels the overall functionality and responsiveness of a cell. The IG-PSO-optimized evaluation system achieved an excellent score of over 90 in the assessment of actual teaching effectiveness across dimensions such as experimental performance and innovation ability. It shows that the teaching system is a healthy, well-regulated cell that can effectively perform its functions and adapt to different educational needs. Through the analogy with cellular molecular biomechanics, we can gain a deeper understanding of the improvement and optimization of the practical teaching system of environmental engineering, which is crucial for the cultivation of skilled professionals in this field.
References
1. Xie C , Lu H , Shi D .Research on Undergraduate Professional Training Mode of Safety Engineering under Multidisciplinary Crossing.International Journal of Social Science and Education Research, 2020, 2(12):13-18.
2. Semenova N .Project-Based Learning as an Important Element of Training Students Majoring in Environmental Engineering.E3S Web of Conferences, 2021, 244:11051-11057.
3. C Wang, R Zhang, S Zhang, L Wang. Improvement of Cultivation Quality of Future Environmental Protection Talents: from Scientific Literacy Aspects.IOP Conference Series: Earth and Environmental Science, 2021, 676(1):12025-12033.
4. Zhang K, Xie Y, Shi J.Construction of a Decision Model for the Evaluation System of Practical Teaching Quality Based on AHP[J].Springer, Singapore, 2023,9(8):39-48.
5. Guo H .Research on the Construction of the Quality Evaluation Model System for the Teaching Reform of Physical Education Students in Colleges and Universities under the Background of Artificial Intelligence.Scientific programming, 2022, 2022(11):1-9.
6. Huo Y , Feng L .Construction of BMP Education Reform Model Based on Multi-Element Information for Automation Teaching System.Journal of Physics: Conference Series, 2021, 1939(1):12089-12093.
7. Liu M , Chen W, Yang L.Optimization of Experimental Teaching System based on ACSI Model.2022 International Conference on Information System, Computing and Educational Technology (ICISCET), 2022:106-109.
8. Zhang L .Evaluation system of college physical education teaching reform based on wireless sensor network.Journal of computational methods in sciences and engineering, 2022, 2(22): 373-384.
9. Zhang Y, Gao J. Research on Classroom Teaching Quality Evaluation and Feedback System Based on Big Data Analysis .Scientific programming, 2022, 2022, 12:1-13.
10. Zheng Y .Design of a Blockchain-Based e-Portfolio Evaluation System to Assess the Education and Teaching Process.International Journal of Emerging Technologies in Learning (iJET), 2021(5):261-280.
11. Gao B , Jan N .Research and Implementation of Intelligent Evaluation System of Teaching Quality in Universities Based on Artificial Intelligence Neural Network Model.Mathematical Problems in Engineering: Theory, Methods and Applications, 2022, 8(2022):1-10.
12. Streveler, R. A., Brown, S., Herman, G. L., & Montfort, D. (2014). Conceptual Change and Misconceptions in Engineering Education: Curriculum, Measurement, and Theory-Focused Approaches. In A. Johri & B. M. Olds (Eds.), Cambridge Handbook of Engineering Education Research (pp. 83–102). chapter, Cambridge: Cambridge University Press.
13. FU, J., HU, D., & WANG, S. (2023). Empowering the Future of Engineering Education Discipline with Chinese Characteristics: Motivation, Formation, and Promotion. Engineering Education Review, 1(1). https://doi.org/10.54844/eer.2023.0426
14. E. Forcael, G. Garcés and A. D. Lantada, "Convergence of Educational Paradigms into Engineering Education 5.0," 2023 World Engineering Education Forum - Global Engineering Deans Council (WEEF-GEDC), Monterrey, Mexico, 2023, pp. 1-8, doi: 10.1109/WEEF-GEDC59520.2023.10344026.
15. A. Portillo-Blanco et al., "Innovative teaching methods in engineering education: the STEAM-Active project," 2023 32nd Annual Conference of the European Association for Education in Electrical and Information Engineering (EAEEIE), Eindhoven, Netherlands, 2023, pp. 1-5, doi: 10.23919/EAEEIE55804.2023.10181478.
16. Liu, S., Zhang, J., Tao, M., Tang, P., Zhan, C., Guo, J., Li, Y., & Liu, X. (2024). Educational Approaches for Integrating Advanced Environmental Remediation Technologies into Environmental Engineering: The ‘Four Styles’ Model. Processes, 12(8), 1569. https://doi.org/10.3390/pr12081569
17. Hua, I., & Nies, L. (2017, June), Innovations in Environmental Engineering Education Programs Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--28534
Copyright (c) 2025 Na Meng
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright on all articles published in this journal is retained by the author(s), while the author(s) grant the publisher as the original publisher to publish the article.
Articles published in this journal are licensed under a Creative Commons Attribution 4.0 International, which means they can be shared, adapted and distributed provided that the original published version is cited.