2021/04/22 by Sangmin-Michelle Lee, Sangmin‐Michelle Lee · 1 citation
Computer Science · Medicine · Psychology · #Artificial intelligence #Computer science #Foreign language #Machine translation #Mathematics education #Medicine #Meta-analysis #Natural Language Processing Techniques #Online Learning and Analytics #Psychology #Quality (philosophy) #Skepticism #Text Readability and Simplification
paper · doi:10.1080/09588221.2021.1901745
openalex publication_date 2021/04/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/02
With a significant number of students using machine translation (MT) for academic purposes in recent years, language teachers can no longer ignore it in their classrooms. Although an increasing number of studies have reported its pedagogical benefits, studies have also revealed that language teachers are still sceptical about using MT for various reasons. Most of all, they have limited trust in MT quality and the effectiveness of using MT in foreign language (FL) learning. Hence, the current study examined these issues to provide an overview and a guide to language teachers regarding the use of MT in FL education. The study examined 87 MT studies related to FL education published between 2000 and 2019. It employed both systematic review (primary) and meta-analysis (secondary) as research methods for a robust data analysis. The results showed that the number of publications in this area has increased in recent years and that MT quality has been significantly enhanced. Most studies also reported the positive impacts of using MT in FL learning, particularly for writing. However, this study also found that students had mixed emotions about MT and that there are disparities in perceptions between instructors and students. Based on the results, the present study presents several pedagogical implications and suggestions for future research on MT.