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Article In:
Approaches to Machine Translation
Edited by Mahdieh Fakhar, Monica Vilhelm and Paz Díez-Arcón
[Translation and Translanguaging in Multilingual Contexts 11:1] 2025
► pp. 88–110

Applying neural machine translation and ChatGPT in the teaching of business English writing

 | China University of Political Science and Law
 | China University of Political Science and Law
As language teaching becomes more complex and diverse, there has been a rapid increase in the demand for advanced technology, driving the widespread adoption of neural machine translation (NMT) and ChatGPT in the field. This study contributes to the literature on the use of technology in language teaching by evaluating the application of NMT technology and ChatGPT in teaching English as a foreign language (EFL) writing in three business fields: finance, economics, and business administration. By building six comparable corpora consisting of students’ direct-writing and post-edited writing based on machine-translated texts, we examined whether NMT can help improve students’ performance in business English writing classes, and whether ChatGPT can complement NMT. Our statistical analyses show that in general, NMT can enhance the proficiency of students’ academic writing, but its improvement effect works on different dimensions for those students studying in different majors. Specifically, for finance students, NMT can improve their academic writing at the word and syntax levels and mechanics, while it harms the organizational dimension. For students in economics, the improvement effect of NMT mainly focuses on enhancing the dimensions of syntax, cohesion, and mechanics, whereas for students in business administration, NMT works primarily on the dimensions of content, cohesion, and mechanics. As for the dimensions where NMT performs poorly, our analysis of students’ essay writing shows that ChatGPT can complement NMT by making improvements and providing feedback to students. Our paper adds value to existing research on the use of technology in language teaching by investigating the application of NMT and ChatGPT in teaching EFL writing, and by proposing potential directions for their use in the teaching of writing business English.
Keywords: neural machine translation, ChatGPT, EFL teaching, academic writing, business English
Article outline
  • 1.Introduction
  • 2.Literature review
    • 2.1The application of technology in the teaching of EFL and ESL writing
    • 2.2The application of NMT and ChatGPT in foreign language teaching
    • 2.3The application of direct-, translated-, and post-edited writing in the teaching of EFL writing
  • 3.Data and methodology
    • 3.1Participants
    • 3.2The selection of the NMT system
    • 3.3Corpus construction and evaluation methods
  • 4.Results and discussion
    • 4.1Evaluating essays by finance students in the DW and PW modes
    • 4.2Evaluating essays by economics students in the DW and PW modes
    • 4.3Evaluating essays by business administration students in the DW and PW modes
  • 5.Conclusions and future research
  • Acknowledgement
  • Notes
  • References
This content is being prepared for publication; it may be subject to changes.
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