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Interdisciplinary Practice of the "Four-in-One" Teaching Reform for "AI + Courses"

Author(s)

Chao Liu, Hongyuan Wen, Lei Yang*

Affiliation(s)

Taizhou Institute of Science and Technology, Nanjing University of Science and Technology, Taizhou, Jiangsu, China *Corresponding Author

Abstract

Addressing the common challenges in the Artificial Intelligence (AI) course within the Electrical Engineering and Automation major—such as weak foundational knowledge, disconnection from application, and misaligned evaluation—this study proposes a comprehensive "Four-in-One" teaching reform scheme. The curriculum framework adopts a "three-layer progression, specialty-general integration" structure: the general foundation layer eliminates technological intimidation, the professional core layer focuses on power scenarios, and the advanced practical layer connects with complex engineering problems. The teaching model employs "virtual-real integration and dual-teacher collaboration", using virtual simulation to lower practical barriers and involving AI teachers, professional faculty, and industry engineers to bridge the gap between technological knowledge and industry needs. The practical system implements "micro-project chains and competition-course integration", deconstructing large projects into progressive micro-tasks and aligning them with industry competitions. The evaluation mechanism introduces "multi-dimensional scoring and competency alignment", replacing single written exams with comprehensive process evaluation, with indicators mapped to engineering education certification competencies. This scheme effectively enhances students’ AI literacy and engineering practical abilities, providing a replicable and scalable paradigm for interdisciplinary teaching reform in the context of "AI+".

Keywords

Electrical Engineering and Automation; Artificial Intelligence+Course; Teaching Reform

References

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