Student machine translation use in a transnational English-medium instruction university
Abstract Research on machine translation in language courses has proliferated over the last decade, yet few studies have considered use in English medium-instruction programs that aim to simultaneously develop student language ability and knowledge of content. This study therefore investigates student use and beliefs about machine translation at a transnational Chinese university. Interviews with twenty-one undergraduate students and fourteen instructors found that student use of machine translation is widespread, though variable. Students report using machine translation to increase reading comprehension, vocabulary, and speed; translate first language writing to raise target language writing quality and complexity; and decrease the amount of copied (though cited) content. Instructors report student use of simultaneous speech translation in class, mistranslations in student writing indicating a lack of engagement with English language texts, and cross-language plagiarism. Both students and instructors view machine translation as a tool: a potentially beneficial one that, if used uncritically and constantly, can stunt language development. Students are thus faced with a choice between developing their English and the expediency of quickly reading and writing in Chinese, a choice heavily affected by student workload, performance pressures, and, arguably, lack of machine translation literacy.
Authors
- Andrew Mark McIntosh (ORCID: https://orcid.org/0000-0002-0198-4588)
- Michael D. High (ORCID: https://orcid.org/0000-0002-7898-1078)
- Yu Ji (ORCID: https://orcid.org/0009-0007-1249-3366)
- Shuhan Li (ORCID: https://orcid.org/0000-0001-9174-3691)
Institutions
- Pennsylvania State University (US)
- Xi’an Jiaotong-Liverpool University (CN)
Publication Details
- Journal
- Journal of English-Medium Instruction
- Published
- 2024-11-05
- DOI
- https://doi.org/10.1075/jemi.24010.hig
- Primary Topic
- Second Language Learning and Teaching
- Type
- article
- Field-Weighted Citation Impact
- 0.00