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From "Formal Interdisciplinary" to "Substantive Integration": Exploring a Training Model for AI Interdisciplinary Master's Programs Driven by Intelligent Production Line Upgrade Projects

Author(s)

Xiang Li, Bin Zhao, Ruohuai Sun

Affiliation(s)

College of Interdisciplinary Science, Liaoning University of Technology, Jinzhou, Liaoning, China

Abstract

With the deep integration of Artificial Intelligence (AI) and traditional disciplines, the construction of "artificial intelligence" interdisciplinary master program has become the focus of a new round of higher education reform. Such master programs generally involve the cross training of "artificial intelligence" and "traditional disciplines", and the tutor team is also mostly formed by the tutors of artificial intelligence and traditional disciplines. However, there are two core difficulties in master programs with such teaching team configuration: first, due to the limitation of knowledge structure, non AI professional tutors lack the mastery of cutting-edge AI technology, which is difficult to support the training standard of master programs; Second, some students who have been admitted to the master's degree program are more expected to engage in the cutting-edge directions related to computer science, such as embodied intelligence and computer vision, because their understanding of artificial intelligence mostly starts from the computer related fields, but in fact they are assigned to the tutor group of disciplines such as machinery and materials, resulting in psychological gap and weakening learning motivation. Based on the theory of interdisciplinary training, this paper systematically analyzes the causes of the above-mentioned double dilemma, nd draws lessons from the reform experience of colleges and universities at home and abroad, puts forward the systematic reform path of interdisciplinary training driven by the intelligent industrialization upgrading project, taking the integration of industry and education as the starting point, and provides theoretical and practical reference for breaking through the "formal intersection" dilemma of interdisciplinary AI master training.

Keywords

AI Interdisciplinary Master's Programs; Artificial Intelligence; Interdisciplinary Training; Intelligent Industrialization Upgrading

References

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