Opportunities, Challenges and Paths of AI Large Language Models to Promote the Digital Transformation of Higher Vocational Education

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  • Wuxi City College of Vocational Technology

Online published: 2025-06-27

Abstract

The application of various AI products or technologies in the field of education will drive a more profound digital transfor‐ mation and innovation in education, which is an inevitable requirement for advancing high-quality education development in the era of Artificial Intelligence. The intervention of AI large language model technology in higher vocational education has overturned the traditional paradigms and methods of educational technology intervention in this field from multiple dimensions such as precise modeling, intelligent interaction, emotional identification, and has facilitated the transformation and sublimation of the educational model in higher vocational education. However, the inherent weaknesses of AI large language models also pose potential risks and challenges to higher vocational education and teaching in areas such as ideology, values, scientific ethics, and more. Therefore, while integrating AI large language model technology and seizing the opportunity for high-quality development in higher vocational educa‐ tion, it is also crucial to establish design norms for technology application. This study puts forward the construction method of inte‐ grating AI technology into the curriculum system of higher vocational education from three dimensions: curriculum content, learning mode and curriculum environment. On the basis of analyzing the potential risks, this paper implements the path of promoting the digital transformation of higher vocational education through top-level design, content construction, audit algorithm and strengthen‐ ing supervision by implementing AI large language model.

Cite this article

CHANG Da-quan . Opportunities, Challenges and Paths of AI Large Language Models to Promote the Digital Transformation of Higher Vocational Education[J]. Computer & Telecommunication, 2025 , 1(1-2) : 5 . DOI: 10.15966/j.cnki.dnydx.2025.01.006

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