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Exploring the Reform Path of Artificial Intelligence General Education Courses for Non-Computer Science Majors

Author(s)

Guoyuan Lin1*, Congxin Wu2, Liang Wang2, Lai Zhou3

Affiliation(s)

1School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu, China 2Sun Yueqi Honors College, China University of Mining and Technology, Xuzhou, Jiangsu, China 3School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, Jiangsu, China *Corresponding Author

Abstract

Against the backdrop of a new round of technological revolution and industrial transformation, artificial intelligence technology has become a core competency for modern citizens and a key ability for non-computer science students to enhance employability and adapt to industrial upgrading demands. Current AI general education courses for non-computer majors suffer from issues such as rigid knowledge systems, monotonous teaching methods, lack of practical components, and insufficient interdisciplinary integration, making it difficult to meet the needs of talent cultivation and societal development. This paper proposes reform pathways from four aspects—curriculum system reconstruction, teaching model innovation, faculty development, and practical platform construction—to establish an AI general education system tailored for non-computer majors, aiming to cultivate cross-disciplinary talents with AI collaborative capabilities.

Keywords

Non-Computer Science Major; Artificial Intelligence General Education Courses; Curriculum Reform; Talent Cultivation

References

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