The Application and Reform of Artificial Intelligence in the Computer Application Technology Major: Exploring the Path of Innovation for Vocational Colleges
- DOI
- 10.2991/978-94-6463-803-5_5How to use a DOI?
- Keywords
- Artificial Intelligence; Computer Application Technology; Vocational Education; Curriculum Reform; Integration of Industry and Education
- Abstract
The rapid advancement of Artificial Intelligence (AI) technology is reshaping the educational ecosystem of the Computer Application Technology major. This paper, focusing on vocational colleges, systematically analyzes the impact of AI technology on the curriculum system, teaching models, practical skills training, and employment directions within the Computer Application Technology major. It proposes future-oriented educational reform pathways. By integrating industry demands, technological trends, and educational resources, this paper aims to provide theoretical support and practical references for vocational colleges to construct a comprehensive talent training system adapted to the AI era. Additionally, it explores strategies to address potential challenges such as technological ethics and data security.
- 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 - Qiuyue Chen PY - 2025 DA - 2025/07/31 TI - The Application and Reform of Artificial Intelligence in the Computer Application Technology Major: Exploring the Path of Innovation for Vocational Colleges BT - Proceedings of the 5th International Conference on Internet, Education and Information Technology (IEIT 2025) PB - Atlantis Press SP - 34 EP - 42 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-803-5_5 DO - 10.2991/978-94-6463-803-5_5 ID - Chen2025 ER -