Frontiers in Educational Research, 2025, 8(8); doi: 10.25236/FER.2025.080809.
Qinghong Cao
School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, China
Based on the Outcome-Based Education (OBE) concept, this study constructs a new teaching paradigm of integrating symmetric beauty into engineering electromagnetic field courses with AI empowerment. By analyzing the symmetry nature of electromagnetic theory, a three-level achievement goal of “knowledge - ability – quality” is established. Core knowledge is deeply coupled with symmetry analysis, and a thinking training chain of “symmetry conservation - breaking analysis - reconstruction innovation” is innovatively designed. With the application of AI technology, symmetry cognition diagnosis, virtual simulation, and innovative optimization are realized, which deepens students’ understanding of complex theories and improves compliance rate of symmetry modelling ability for engineering problems. The research provides a teaching reform path of “enlightening truth through beauty and AI empowerment” for engineering education, highlighting the paradigm innovation value of scientific aesthetics.
Symmetrical Aesthetics, Engineering Electromagnetic Field, AI Empowerment, Outcome-Based Education, Teaching Paradigm Reconstruction
Qinghong Cao. An Innovative Study of AI-Empowered and Symmetric Beauty-Driven Teaching of Engineering Electromagnetic Fields Based on OBE. Frontiers in Educational Research (2025), Vol. 8, Issue 8: 48-53. https://doi.org/10.25236/FER.2025.080809.
[1] Li Jinying, Teaching Practice of “Engineering Project Management Theory and Application” Based on OBE Concept [J]. Industrial Engineering and Innovation Management, 2024, 7: 95-99.
[2] Shin Ten, Steven Locke. On the achievement-oriented educational concept [J]. University Education Management, 2016, 10 (05): 47-51.
[3] Goodfellow I, et al. Deep Learning [M]. MIT Press, 2016.
[4] Goodfellow I, Pouget-Abadie J, Mirza M, et al. Generative Adversarial Nets [J]. MIT Press, 2014.
[5] Zhang X, et al. AI-Enabled Intelligent Education [J]. IEEE Transactions on Intelligent Transportation Systems, 2022.