A Study on AI-Based English Writing Pedagogy: A Case Study of Application-Oriented Higher Education Institutions
- DOI
- 10.2991/978-2-38476-479-2_24How to use a DOI?
- Keywords
- Artificial Intelligence; College English Writing; iWrite Platform; Instructional Optimization
- Abstract
With the rapid advancement of artificial intelligence technologies, their application in the field of education has been continuously deepening, demonstrating significant potential particularly in language instruction. However, local applied undergraduate institutions still face numerous challenges in the teaching of English writing. Against this backdrop, the iWrite platform—by virtue of its intelligent assessment and feedback mechanisms—offers substantial advantages in efficiency and provides a novel solution for enhancing students’ writing proficiency and learning motivation. This study focuses on the current application and optimization strategies of AI technologies in college English writing instruction at local applied universities, using the iWrite platform as a case study. It further proposes targeted pedagogical strategies to improve teaching effectiveness in this context.
- 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 - Yilin Shen AU - Xiao Shao AU - Jingyu Tan AU - Xuxiao Chen AU - Huizhi Chen AU - Simin Pu AU - Xiyan Cao AU - Tianhui Chen AU - Lirong Zhu PY - 2025 DA - 2025/11/19 TI - A Study on AI-Based English Writing Pedagogy: A Case Study of Application-Oriented Higher Education Institutions BT - Proceedings of the 2025 International Conference on Education Research and Training Technologies (ERTT 2025) PB - Atlantis Press SP - 205 EP - 211 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-479-2_24 DO - 10.2991/978-2-38476-479-2_24 ID - Shen2025 ER -