Research on Regional Vocational Education Resource Platform Based on Artificial Intelligence

Authors

  • Xiaoxue Yang Wuhan Vocational College of Software and Engineering, Wuhan, Hubei, China Author

DOI:

https://doi.org/10.64229/x9qe9257

Keywords:

Artificial Intelligence, Vocational Education, Resource Platform, Industry-Education Integration, Regional Sharing

Abstract

With the continuous advancement of artificial intelligence, the digital transformation of education has entered a new stage. Vocational education, as a key force supporting regional economic development and industrial upgrading, has long faced problems such as scattered resources, insufficient school-enterprise cooperation, and limited sharing of high-quality courses and training resources. Building a regional vocational education resource platform empowered by AI can help integrate resources across schools, promote industry-education integration, and enhance the relevance and adaptability of talent training. Based on a review of domestic and international research, this paper analyzes the current needs of vocational education in platform construction, proposes AI-enabled functions such as resource integration, intelligent recommendation, and industry-education collaboration, and discusses its potential value for improving education quality and supporting regional development. The study shows that the platform will not only enhance the informatization level of vocational education but also contribute to educational equity and talent strategies for regional industrial upgrading.

References

[1]Yan, J., & Li, Q. (2023). "Digital badge + AI" platform for promoting process evaluation: Technical framework and implementation path. Modern Educational Technology, 33(8), 107-116. https://doi.org/10.3969/j.issn.1009-8097.2023.08.012.

[2]Li, R., Su, Z., Zhang, M., et al. (2025). Construction of an AI neuroimaging education platform for medical students and pre-service residents during the clinical practice stage. Chinese Journal of Medical Education Research, 24(2), 150-154. https://doi.org/10.3760/cma.j.cn116021-20230927-01964.

[3]Li, X., Gu, Y., & Yao, C. (2024). Design and implementation of an online programming experiment platform integrated with AI large language models. Experimental Technology and Management, 41(8), 215-221. https://doi.org/10.16791/j.cnki.sjg.2024.08.030.

[4]Zhai, S., Chen, H., & Wang, Z. (2022). Research on the influencing mechanism of users' willingness to continuously use AI learning platforms based on SES differences. Information Science, 40(2), 28-35. https://doi.org/10.13833/j.issn.1007-7634.2022.02.004.

[5]Wang, S., & Guo, X. (2023). Online teaching of "Python Programming" course based on Baidu AI Studio platform + Tencent Classroom. Journal of Jiangsu Normal University (Natural Science Edition), 41(1), 73-75. https://doi.org/10.3969/j.issn.2095-4298.2023.01.014.

[6]Lu, W. (2019). The connotation, function, and implementation path of the AI+5G adaptive learning platform: Based on the construction of an intelligent seamless learning environment concept. Distance Education Journal, 37(3), 38-46.

[7]Wang, X. (2022). Construction and application of an AI teaching platform for primary and secondary schools based on Scratch3. Journal of Nanjing Xiaozhuang University, 38(6), 105-112. https://doi.org/10.3969/j.issn.1009-7902.2022.06.018.

[8]Zhang, C., Chu, D., Zhang, Q., et al. (2024). Metaverse teaching: A higher-level form of digital teaching transformation in higher education. Computer Science, 51(10), 1-9. https://doi.org/10.11896/jsjkx.240400083.

[9]Tian, Y. (2020). Research on the AI virtual English education training system for the SELL corpus. Microcomputer Applications, 36(12), 42-44. https://doi.org/10.3969/j.issn.1007-757X.2020.12.012.

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Published

2025-09-25

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Articles