| Issue |
SHS Web Conf.
Volume 222, 2025
2025 3rd International Conference on Education, Psychology and Cultural Communication (ICEPCC 2025)
|
|
|---|---|---|
| Article Number | 01001 | |
| Number of page(s) | 11 | |
| Section | Artificial Intelligence and Digital Transformation in Education | |
| DOI | https://doi.org/10.1051/shsconf/202522201001 | |
| Published online | 17 September 2025 | |
Research on Generative Artificial Intelligence in Senior High Schools’ English Reading Teaching
College of Foreign Languages, Shanghai Ocean University, 201306 No.999, Huchenghuan Rd, Nanhui New City, Shanghai, P.R., China
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
The advent of generative artificial intelligence (GAI) and the prominence of core literacy in senior high school have jointly promoted innovative transformations in teaching. This paper employs literature review methodology to first examine current problems in senior high school English reading class, subsequently proposing GAI’ s integrative advantages. Then further identifies implementation challenges and corresponding countermeasures. It is found that traditional English reading class has problems of single reading resources, lacking thinking training and one- sided reading evaluation system, while GAI can enrich reading materials, promote critical thinking, and achieve diversified evaluation. However, there are problems of lacking emotional interaction, teachers’ technical dependence and difficulties in changing teaching concepts. Therefore, this paper proposes a teacher-led, GAI-assisted emotional interaction mechanism, teacher-student-AI triadic collaboration, and progressive conceptual iteration strategies. The paper shows that the deep integration of GAI and English reading teaching needs to balance technological empowerment and traditional educational values.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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