Research on University Mathematics Curriculum Reform Empowered by GAI under the STEM Education Philosophy
- DOI
- 10.2991/978-94-6463-988-9_21How to use a DOI?
- Keywords
- STEM Education; Generative Artificial Intelligence (GAI); University Mathematics; Interdisciplinary Integration
- Abstract
With the successive release of China’s Education Modernization 2035 and STEM Education 2035 Action Plan, and driven by the policy of digital transformation in education, the integration of STEM education and Generative Artificial Intelligence (GAI) has emerged as a pivotal direction for higher education reform. This study focuses on university mathematics courses, based on the core essence of STEM education: “interdisciplinary integration and innovative practice”, and systematically explores pathways for empowering curriculum reform through GAI technology. It puts forward specific reform strategies from three dimensions: optimizing teaching practices, strengthening technological support, and constructing evaluation systems, providing a theoretical framework and practical paradigm for the interdisciplinary integration and digital-intelligent transformation of university mathematics curricula in the era of artificial intelligence.
- 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 - Ajie Zhang AU - Xinshe Qi PY - 2026 DA - 2026/02/15 TI - Research on University Mathematics Curriculum Reform Empowered by GAI under the STEM Education Philosophy BT - Proceedings of the 2025 5th International Conference on Education, Language and Art (ICELA 2025) PB - Atlantis Press SP - 173 EP - 182 SN - 2352-5398 UR - https://doi.org/10.2991/978-94-6463-988-9_21 DO - 10.2991/978-94-6463-988-9_21 ID - Zhang2026 ER -