Construction of Innovative Training and Evaluation Model for Generative AI Industrial Application in Engineering General Education
- DOI
- 10.2991/978-94-6239-691-3_62How to use a DOI?
- Keywords
- Generative AI; engineering education; virtual-real integrated training; multi-dimensional ability evaluation; OBE-CDIO; process evaluation
- Abstract
With the in-depth development of Industry 4.0, Generative AI has become a key technology driving the transformation towards smart manufacturing. However, current general AI education in engineering generally faces pain points such as “technology suspension, disconnection between production and education,” and a single evaluation dimension. This paper proposes an innovative teaching paradigm for the course “Generative AI Industrial Application Training.” This paradigm constructs a progressive training module design logic, from virtual simulation to physical production line joint debugging, and then to full-scenario coverage, to solve the engineering deployment challenges in complex industrial scenarios. Furthermore, this paper innovatively proposes a multi-dimensional capability evaluation framework based on the OBE-CDIO concept, deeply integrating process evaluation with student capability matrix portraits. This model demonstrates high replicability through the decomposition of lightweight application scenarios and collaborative sharing of open-source resources, providing a highly promotable new educational paradigm for engineering and technical talent cultivation in the context of new engineering.
- Copyright
- © 2026 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 - Xiangyu Li AU - Congying Qi AU - Xueqi Yang AU - Yannan Yu AU - Peng Yang PY - 2026 DA - 2026/05/31 TI - Construction of Innovative Training and Evaluation Model for Generative AI Industrial Application in Engineering General Education BT - Proceedings of the 2026 5th International Conference on Educational Innovation and Multimedia Technology (EIMT 2026) PB - Atlantis Press SP - 619 EP - 625 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6239-691-3_62 DO - 10.2991/978-94-6239-691-3_62 ID - Li2026 ER -