| Issue |
ITM Web Conf.
Volume 88, 2026
The 2026 International Conference on Artificial Intelligence, Big Data and Computer Science (AIBDCS 2026)
|
|
|---|---|---|
| Article Number | 01001 | |
| Number of page(s) | 5 | |
| Section | Artificial Intelligence, Big Data and Computer Science | |
| DOI | https://doi.org/10.1051/itmconf/20268801001 | |
| Published online | 27 July 2026 | |
Application of Natural Language Processing Technology in Foreign Language Teaching
School of European Languages and Culture, Beijing Foreign Studies University, Beijing, 100089, China
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
This paper will summarize the development and current situation of the application of natural language processing technology in foreign language teaching. According to the comprehensive literature, the application of NLP in foreign language teaching has gradually upgraded from the initial application in writing assessment and grammar error correction to the key technology supporting personalized learning and resource generation. It is estimated that it will develop in the direction of human-machine collaboration in the future. This paper will first clarify the use of NLP in foreign language teaching scenarios such as automatic marking and personalized learning, and then analyze the problems that affect the actual effect of technology, such as feedback engagement and learner differences. Finally, it will discuss the technical challenges, ethical considerations and future directions in the context of the large language model, so as to provide reference for the realization of more efficient and responsible technologies in the future, and provide literature support for the development of foreign language teaching in the future.
© The Authors, published by EDP Sciences, 2026
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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