Research on the Interdisciplinary “AI+X” Innovation and Entrepreneurship Education Paradigm at Local Application-Oriented Universities Driven by AI for Science (AI4S)
DOI:
https://doi.org/10.54097/7pezv452Keywords:
AI for Science, AI+X, Local Application-oriented Universities, Interdisciplinary, Innovation and Entrepreneurship Education ParadigmAbstract
The new era of AI for Science (AI4S) promises changing the paradigms of science and industry research, offering local application-focused universities a new chance to address long-term challenges in the field of innovation and entrepreneurship education. To address widespread issues such as strict disciplinary boundaries, the disconnect between education in innovation and entrepreneurship and professional education, and shallow AI integration, this paper presents an interdisciplinary "AI+X" paradigm of innovation and entrepreneurship education that is based on AI4S. This paradigm uses real research and industrial problems as its basis and data-driven approaches and interdisciplinary integration as the main mechanisms. The course cluster-project workshop-platform ecosystem-evaluation incentive four-dimensional synergy leads students through basic AI literacy to domain specific innovative application, finally reaching a progressive improvement of innovation and entrepreneurial abilities. The paper explains the theoretical rationale and structural framework of the paradigm and suggests implementation strategies that include reconstructing curricula, hybrid virtual-physical practice platforms, mentor teams of industry-education, and cascades of progressive incubation. It also discusses the initial experience of an "Intelligent Seed Industry" AI4S project in an application-oriented university. It can be concluded that local application-oriented universities ought to actively integrate into the AI4S ecosystem and convert regional industrial features into the resources of interdisciplinary innovation and entrepreneurship education, thus producing high quality applied personnel who are endowed with AI thinking, interdisciplinary competence and entrepreneurial spirit.
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[1] Wang, S., Zhang, X., Wu, C., Yan, Y., & Li, Z. (2025). AI for science: Cognitive collaboration, whole-process effects and action fields. Journal of Xi'an Jiaotong University (Social Sciences), 45(3), 117–128. (In Chinese)
[2] Jia, X. (2017). Double logic and related problems of “the fourth paradigm” against the background of big data. Journal of Jiangsu Administration Institute, (6), 14–20. (In Chinese)
[3] Wu, Y. (2018). New engineering: The future of higher engineering education — strategic thinking on the future of higher education. Research in Higher Education of Engineering, (6), 1–3. (In Chinese)
[4] Hu, X., Sun, S., Yang, W., & Ding, G. (2022). Artificial intelligence empowering high-quality development of education: Demands, visions and pathways. Modern Educational Technology, 32(1), 5–15. (In Chinese)
[5] Hu, Q., Zhang, Y., & Wu, W. (2026). Deep integration of artificial intelligence and education: Logic, dilemma and path. China Educational Technology, (6), 1–6+23. (In Chinese)
[6] Yang, Y., Huang, Y., & Liu, S. (2019). Research on talent training mode of data science and big data technology major in local colleges and universities. Modernization of Education, 6(4), 19–21. (In Chinese)
[7] Lin, Y. (2021). Practical study on the integration of artificial intelligence virtual reality technology in education information 2.0. Wireless Internet Technology, 18(14), 118–120. (In Chinese)
[8] Ministry of Education of the People's Republic of China. (2020). Opinions on deepening the reform of undergraduate education and teaching to comprehensively improve the quality of talent cultivation. Gazette of the State Council of the People's Republic of China, (2), 91–95. (In Chinese)
[9] Wu, Y., Ni, J., & Shen, J. (2024). Construction and practice path of innovation and entrepreneurship education ecosystem in application-oriented undergraduate universities. Education and Vocation, (2), 105–112. (In Chinese)
[10] Wang, F., & Miao, Q. (2023). A new paradigm of scientific research driven by artificial intelligence: From AI4S to intelligent science. Bulletin of Chinese Academy of Sciences, 38(4), 536–. (In Chinese)
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