In recent years, machine translation (MT) has been gaining popularity, both in academic settings and in everyday life among foreign language students. However, insufficient research has been conducted in this field. Moreover, the findings of extant literature are often contradictory, and there are few empirical studies based on students’ actual outcomes. Therefore, the present study investigates the effectiveness of using MT in English-as-a-Foreign-Language (EFL) writing classes. It particularly examines whether students’ L2 writing proficiency levels influence their revisions when using MT. According to the results, using MT helped all levels of students improve their revisions, but to a different extent depending on their L2 writing proficiency levels. Compared to the higher-level students, the lower-level students made fewer changes per error, resulting in less improvement in the revised versions. Furthermore, this study found that the lowest- level students benefited the least from MT, mainly due to their limited L2 knowledge. Conversely, the higher-level students benefited more from MT by critically selecting better options between their own translations and those produced by MT. Overall, this study includes several pedagogical implications for using MT in L2 writing classrooms.
endingpage:
21
format:
Article
format.extent:
21
identifier.citation:
Lee, S.-M. (2022). Different effects of machine translation on L2 revisions across students’ L2 writing proficiency levels. Language Learning & Technology, 26(1), 1–21. https://hdl.handle.net/10125/73490
identifier.issn:
1094-3501
identifier.uri:
https://hdl.handle.net/10125/73490
language:
eng
number:
1
publicationname:
Language Learning & Technology
publisher:
University of Hawaii National Foreign Language Resource Center Center for Language & Technology (co-sponsored by Center for Open Educational Resources and Language Learning, University of Texas at Austin)
rights.license:
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License