IDEAS home Printed from https://ideas.repec.org/a/igg/jkm000/v21y2025i1p1-20.html

AI-Driven Transformation of Vocational Education: Opportunities, Challenges, and Future Paths

Author

Listed:
  • Yingchao Zhang

    (Zhengzhou Railway Vocational and Technical College, China)

Abstract

AI's rapid development offers new opportunities for China's vocational education. This study (experiments + interviews) across five colleges (eastern, central, western) highlights key breakthroughs: AI learning analysis improved skill pass rates by 22.7% (36.3% for underperforming students), virtual simulation cut costs by 89.6%, and AI platforms enabled cross-regional resource flow, allowing western colleges to surpass eastern ones in VR training hours. Challenges include high AI customization costs (over 1 million yuan), limited teacher AI training (15% trained), data security risks, and industry gaps. The paper proposes a “technology adaptation-talent support-mechanism guarantee” ecosystem: lightweight technologies, regional equipment sharing, teacher training, enhanced data security, and policy-backed collaboration (subsidies + real-time data links) to shift vocational education from “standardized” to “precision” training.

Suggested Citation

  • Yingchao Zhang, 2025. "AI-Driven Transformation of Vocational Education: Opportunities, Challenges, and Future Paths," International Journal of Knowledge Management (IJKM), IGI Global Scientific Publishing, vol. 21(1), pages 1-20, January.
    • Handle: RePEc:igg:jkm000:v:21:y:2025:i:1:p:1-20
    as

    Download full text from publisher

    File URL: https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJKM.394819
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jkm000:v:21:y:2025:i:1:p:1-20. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.