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Curriculum Reconstruction and Teaching Methodology Reform for "Modern Power Electronics Technology" with AI Integration

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DOI: 10.23977/aetp.2026.100314 | Downloads: 0 | Views: 30

Author(s)

Qingqing Yuan 1, Kun Xia 1, Jingxia Wang 1, Han Li 1

Affiliation(s)

1 Department of Electrical Engineering, University of Shanghai for Science and Technology, Shanghai, China

Corresponding Author

Qingqing Yuan

ABSTRACT

Against the backdrop of the "Carbon Neutrality" goal and the digital transformation of the energy sector, modern power electronics technology is rapidly evolving toward higher switching frequencies, greater integration, and enhanced intelligence. Addressing persistent challenges in traditional curricula — such as outdated knowledge structures, insufficient interdisciplinary integration, and inadequate cultivation of innovative capabilities, this study proposes a reconstruction scheme for an "AI+" modern power electronics curriculum system. Utilizing a "vertically tiered and horizontally integrated" curricular framework, artificial intelligence methodologies are systematically embedded into teaching modules encompassing device characterization, topology optimization, control strategy design, and engineering case studies. Furthermore, by leveraging project-based learning (PBL), virtual-real fused experimentation, and innovation-driven practical activities, a progressive competency development pathway is established, bridging "foundational theory, comprehensive application, and innovative practice". Teaching practice demonstrates that this pedagogical model significantly enhances students' ability to solve complex engineering problems and fosters interdisciplinary innovative thinking.

KEYWORDS

Artificial Intelligence; Modern Power Electronics Technology; Curriculum Reconstruction; Innovative Capability

CITE THIS PAPER

Qingqing Yuan, Kun Xia, Jingxia Wang, Han Li. Curriculum Reconstruction and Teaching Methodology Reform for "Modern Power Electronics Technology" with AI Integration. Advances in Educational Technology and Psychology (2026). Vol. 10, No. 3, 110-115. DOI: http://dx.doi.org/10.23977/aetp.2026.100314.

REFERENCES

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[2] Jiazhi L., Jin M., Yue W. Exploration of teaching and practical reform paths for power electronics technology courses empowered by artificial intelligence technology [J]. Education Insights, 2025.2(11), 349-355. 
[3] Xiaohong S., Xiaofei X., Tiantian W. Innovation of teaching and learning scenes and models empowered by artificial intelligence: practice and experience of AI-powered programming courses [J].Frontiers of Digital Education, 2026, 3(1): 4. 

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