Research on AIGC-Enabled Mentorship Project System and Innovative Talent Cultivation in Higher Vocational Colleges

Bin Li; Jiahua Wen; Chijianhui Zhang; Linqi Huang

doi:10.63313/EH.9057

Authors

Bin Li Sichuan Aerospace Vocational College, DeYang City, 618300, China Author
Jiahua Wen Sichuan Aerospace Vocational College, DeYang City, 618300, China Author
Chijianhui Zhang Sichuan Aerospace Vocational College, DeYang City, 618300, China Author
Linqi Huang Sichuan Aerospace Vocational College, DeYang City, 618300, China Author

DOI:

https://doi.org/10.63313/EH.9057

Keywords:

AIGC-Enabled Mentorship, Higher Vocational Colleges, Innovative Talent Cultivation, Project-Based Learning

Abstract

Against the backdrop of rapid development of artificial intelligence, generative artificial intelligence has become an important force driving change in the field of education. This study explores the application and effectiveness of AIGC-empowered mentorship project system in the cultivation of innovative talents in vocational colleges. Through empirical research and case analysis, it has been found that the mentorship project system empowered by AIGC can significantly enhance students' innovation and problem-solving abilities, optimize project output and achievement transformation, enhance learning engagement and team collaboration. The study also constructed a "six-in-one" innovation path model, providing a systematic framework for the deep integration of AIGC and mentorship project system. However, research also suggests that the long-term effects, ethical standards, and institutional safeguards of AIGC in education still need further exploration. This study provides theoretical support and practical reference for vocational colleges to achieve high-quality development in the context of digital transformation.

References

[1] China National Academy of Educational Sciences. (2025) China Vocational Education Quality Annual Report (2023) [R]. Beijing: Higher Education Press. (in Chinese)

[2] Xue, L. (2021) Optimization Analysis of Learning Motivation Incentive Methods in Higher Vocational Colleges [J]. Journal of Jiamusi Vocational Institute, 37(3): 114-115. (in Chinese)

[3] Department of Teacher Affairs, Ministry of Education of the People's Republic of China. (2022) Basic Standards for "Double-Qualified" Teachers in Vocational Education (Trial) [EB/OL]. Beijing: Ministry of Education. (in Chinese)

[4] Zhang, Z.F. (2023) Research on Innovative Paths of Higher Vocational Education from the Perspective of Industry-Education Integration [J]. Research in Higher Education of Engineering, 2023(7): 43-51. (in Chinese)

[5] Che, Y.N., Shao, B. and Lei, X.Y. (2023) Realistic Dilemmas and Future Shifts of Higher Vocational Colleges from the Perspective of High-Quality Development [J]. Vocational and Technical Education, 2023(36): 43-49. (in Chinese)

[6] Song, Y.L. and Luo, J.H. (2024) Vision, Challenges and Paths of AIGC Empowering Digital Resource Services in Vocational Education [J]. China Vocational and Technical Education, 2024(17): 27-33. (in Chinese)

[7] The State Council of the People's Republic of China. (2019) National Vocational Education Reform Implementation Plan [EB/OL]. Beijing: China Government Network. (in Chinese)

[8] Vygotsky, L. (1978) Mind in Society: The Development of Higher Psychological Processes [M]. Cambridge, MA: Harvard University Press.

[9] Wen, Q.F. (2014) The "Output-Driven, Input-Enabled Hypothesis": An Attempt to Construct a Theory for College Foreign Language Classroom Teaching [J]. Foreign Language Education in China, 7(2): 3-12. (in Chinese)

[10] Rychen, D.S. and Salganik, L.H. (Eds.) (2003) Key Competencies for a Successful Life and a Well-Functioning Society [M]. Cambridge, MA: Hogrefe & Huber.

[11] Huang, R.H., Li, M. and Liu, J.H. (2021) An Analysis of the Value of Artificial Intelligence in Educational Modernization [J]. Journal of National Academy of Education Administration, 2021(9): 8-15+66. (in Chinese)

[12] Gartner. (2023) Emerging Technologies and Trends Impact Radar: Artificial Intelligence.

[13] MIT. (2022-2023) Undergraduate Research Opportunities Program (UROP) [EB/OL]. Cambridge, MA: MIT Course Catalog.

[14] Niemi, H. and Liu, J. (2021) AI in Learning: Intelligent Digital Tools and Environments for Education [J]. Journal of Pacific Rim Psychology, 15: 1-9.

[15] Wang, Y. (2022) Discussion on the Tutorial System Model in Higher Vocational Colleges Based on Students' Personalized Development [J]. China Multimedia and Network Teaching Journal (Mid-Month), 2022(02): 142-145. (in Chinese)

[16] Wang, W.L. (2024) Practical Exploration and Reflection on AIGC Empowering Higher Vocational Teaching [J]. China Vocational and Technical Education, 2024(4): 77-85. (in Chinese)

[17] Ministry of Education of the People's Republic of China. (2023) Implementation Plan for the Digitalization Strategy of Vocational Education [EB/OL]. Beijing: Ministry of Education. (in Chinese)

[18] Stanford University. (2023) AI Summit 2023: ChatGPT and the Future of Teaching and Learning [EB/OL]. Stanford, CA: Stanford HAI.

[19] Stufflebeam, D.L. (2003) The CIPP Model for Evaluation [C] // Kellaghan, T., Stufflebeam, D.L. and Wingate, L.A. (Eds.). International Handbook of Educational Evaluation. Dordrecht: Springer, 31-62.

[20] Bandura, A. (1977) Self-Efficacy: Toward a Unifying Theory of Behavioral Change [J]. Psychological Review, 84(2): 191-215.

[21] Zheng, Q.S. (2021) From a Spark to a Prairie Fire: Exploring the Paradigm of Cultivating Top-Notch Innovative Talents [J]. Bulletin of Chinese Academy of Sciences, 36(5): 580-588. (in Chinese)

[22] Hochschule München. (2022) KI in der Produktion: Kooperationsprojekt mit BMW [EB/OL]. München: HM.

[23] Toyota Research Institute. (2023) Generative AI for Automotive Design [EB/OL]. Toyota City: Toyota.

[24] Liu, Y. (2024) RETRACTED ARTICLE: Examining the Impact of Assistive Technology on the Talent Development Path in AI-Driven Vocational Education [J]. Journal of Autism and Developmental Disorders, 54(4): 1621.