While recent efforts have begun integrating large language models (LLMs) into English education, they often rely on traditional approaches to learning tasks without fully embracing educational methodologies, thus lacking adaptability to language learning. To address this gap, we argue that LLMs have the potential to serve as effective tutors in English Education. Specifically, LLMs can play three critical roles: (1) as data enhancers, improving the creation of learning materials or serving as student simulations; (2) as task predictors, serving as learner assessment or optimizing learning pathway; and (3) as agents, enabling personalized and inclusive education. We encourage interdisciplinary research to explore these roles, fostering innovation while addressing challenges and risks, ultimately advancing English Education through the thoughtful integration of LLMs.
@article{arxiv.2502.05467,
title = {Position: LLMs Can be Good Tutors in English Education},
author = {Jingheng Ye and Shen Wang and Deqing Zou and Yibo Yan and Kun Wang and Hai-Tao Zheng and Ruitong Liu and Zenglin Xu and Irwin King and Philip S. Yu and Qingsong Wen},
journal= {arXiv preprint arXiv:2502.05467},
year = {2025}
}