Generative AI Reshaping the Future Landscape of Higher Vocational Education
- DOI
- 10.2991/978-2-38476-497-6_5How to use a DOI?
- Keywords
- Higher Vocational Education; Generative AI; Intelligent Vocational Education
- Abstract
With the rapid development of generative AI technology, higher vocational education is undergoing profound transformations. The study aims to investigate how generative AI can enhance teaching quality and personalize learning experiences in vocational colleges. The article delves into the application of generative AI in higher vocational education, encompassing the customization of personalized learning pathways, optimization of curriculum design, innovation in teaching methodologies, and provision of immediate and precise intelligent tutoring and feedback. The research findings reveal that generative AI significantly diversifies educational resources, optimizes curriculum design, and fosters innovative teaching approaches. It demonstrates how AI technology is reshaping personalized learning scenarios and enhancing teaching quality and learning outcomes. Generative AI technology is significantly enhancing higher vocational education, providing robust support for cultivating high-quality skilled talents with innovative and practical abilities.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Shuijian Zhang PY - 2025 DA - 2025/12/15 TI - Generative AI Reshaping the Future Landscape of Higher Vocational Education BT - Proceedings of the 2025 International Conference on Educational Innovation and Information Technology (EIIT 2025) PB - Atlantis Press SP - 38 EP - 44 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-497-6_5 DO - 10.2991/978-2-38476-497-6_5 ID - Zhang2025 ER -