Research on Teaching Strategies for Electrical Automation Technology Vocational Education Based on Generative Artificial Intelligence

Jun Yu; Xiaopin Xu

doi:10.63313/IJSSEH.9035

Authors

Jun Yu Wenzhou Polytechnic, Wenzhou, Zhejiang, 325035, China Author
Xiaopin Xu Wenzhou Polytechnic, Wenzhou, Zhejiang, 325035, China Author

DOI:

https://doi.org/10.63313/IJSSEH.9035

Keywords:

GAI, Vocational Education, Electrical Automation, Teaching Strategies, Adaptive Learning Framework

Abstract

Generative Artificial Intelligence (GAI), as a machine learning system capable of deeply mining data patterns and automatically generating multimodal content, has become a core disruptive technology in digital transformation, reshaping cognitive paradigms and practical pathways in the field of education. In vocational education for the Electrical Automation Technology major, how to effectively leverage GAI to optimize curriculum structures, enhance teaching quality, and strengthen practical skills remains a critical issue facing the discipline's development. From the perspective of the reconstruction of teaching elements driven by technological and environmental changes, this paper proposes teaching strategies for Electrical Automation Technology vocational education based on GAI. These strategies include constructing a core curriculum system closely aligned with the technical requirements of electrical automation positions, optimizing course design through cognitive augmentation technologies, utilizing digital humans for collaborative practical training, and creating a new teaching ecosystem based on multimodal intelligent interaction. Collectively, these strategies give rise to an adaptive learning framework characterized by "data-driven precision — algorithm-based intelligent adaptation — dynamic continuous evolution," promoting the transformation of professional teaching from traditional knowledge-transfer models to autonomous construction models of cross-domain knowledge networks. This provides theoretical support and practical guidance for improving teaching quality and efficiency, meeting market demands, and cultivating applied skilled talents with innovative spirit and practical capabilities.

References

[1] Wang Y M, Zhang T T, Mao C C. Application scenarios, risk challenges, and countermeasures of generative artificial intelligence in global vocational education [J]. Chinese Vocational and Technical Education, 2025(6): 27-33.

[2] Yin J. The subjectivity issue of generative artificial intelligence [J]. Social Sciences in China, 2024(8).

[3] Zhang Y B, Zheng Y Y, Zhang X Y, et al. Re-understanding the classroom: The empowerment and authorization of generative artificial intelligence [J]. Open Education Research, 2025(4).

[4] Lyu G Z, Shi M. Generative artificial intelligence empowering the digital transformation of higher education: An analysis based on Stanford University [J]. Research in Higher Education of Engineering, 2025(2): 176-181.

[5] Yan X D, Jiang X. Research on the application of generative artificial intelligence in foundational vocational education courses: A case study of information technology courses [J]. Modern Vocational Education, 2025(26): 101-104.

[6] Xiang X. The application and effects of generative artificial intelligence in education [J]. Education and Teaching Methods, 2025(2): 151-156.

[7] Zhou N, Du Y M, Liu F, et al. The application of generative artificial intelligence in the construction of industry-education integration communities for intelligent manufacturing majors in higher vocational education [J]. Papermaking Equipment & Materials, 2025(4).

[8] Wang X M. Generative artificial intelligence driving the paradigm shift of vocational education research: Key dimensions, practical challenges, and coping strategies [J]. Continuing Education Research, 2026(1): 86-93.

[9] Zheng Q S, Wang B. The strategic landscape, practical risks, and prevention strategies of generative artificial intelligence empowering the educational transformation of vocational education [J]. Education and Vocation, 2025(6): 40-47.

[10] Chen Z M, Chen Q. The mechanisms and paths of generative artificial intelligence empowering digital textbook construction in vocational education [J]. 2026.

[11] Yang Z N. Research on the collaborative innovation mechanism of generative artificial intelligence empowering the digital transformation of vocational education [J]. Vocational and Technical Education, 2025, 46(25): 65-71.