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Has machine translation killed conversation? With James Lamont and Jiaoyue Chen
Language students using machine translation has certainly raised lots of questions for those of us teaching English for Academic Purposes over the past few years. But most of the conversation has been around its impact on written compositions. A new study by Lamont and Cirocki looks at how and why it's changing the way international students interact verbally with each other and their teachers.
We're joined today by James Lamont, the lead author of the study, to dig into the data and talk about the implications for the language classroom. What steps do teachers need to take to enable learning to actually take place?
Speaker bios
Jiaoyue Chen is an Academic Practice Adviser at the University of York, where she supports colleagues’ professional journey through the PGCAP programme, York Professional and Academic Development scheme recognition, and the York SoTL network. With a background in Applied Linguistics, she worked as a Lecturer in English Language and Education at Huazhong University of Science and Technology in China. She still returns to this area of research with great interest, but also seeks to disentangle the nuanced relationship between SoTL and formal pedagogical research to better support student learning.
James Lamont is an Associate Lecturer at the University of York in the Department of Education and the School of Business and Society, where he supports student skills development. His research interests are student use of technology and developing working relationships across student cohorts.
Further reading
Lamont, J., & Cirocki, A. (2025). Talking to algorithms, not students: Students’ and lecturers’ perceptions of machine translation in academic discussion. The JALT CALL Journal, 21(3), 103256. https://doi.org/10.29140/jaltcall.v21n3.103256
Timecodes
00:00 Intro to MT in the classroom
01:19 James Lamont and Jiaoyue Chen
03:08 Talking to algorithms
04:58 Groves and Mund’s previous work on MT
04:58 Real time translation in class
07:36 Language acquisition concerns
12:19 Tasks versus learning goals
16:15 The impact of MT on non-language learning
20:42 Overreliance and false confidence
26:00 Accuracy culture and dependency
29:48 Policy gaps and overreliance
31:04 Setting classroom expectations
32:57 Phone boundaries and culture
34:15 Structured tech use phases
35:23 Proficiency gaps and support
38:06 Accents, idioms and listening load
43:24 Anxiety comfort and safe seminars
48:50 Privacy, recording and shame
51:48 Student buy-in and agency
54:56 Ideal classroom and future research
58:03 Final Takeaways And Paper Credit
View all episodes
By Phil MartinLanguage students using machine translation has certainly raised lots of questions for those of us teaching English for Academic Purposes over the past few years. But most of the conversation has been around its impact on written compositions. A new study by Lamont and Cirocki looks at how and why it's changing the way international students interact verbally with each other and their teachers.
We're joined today by James Lamont, the lead author of the study, to dig into the data and talk about the implications for the language classroom. What steps do teachers need to take to enable learning to actually take place?
Speaker bios
Jiaoyue Chen is an Academic Practice Adviser at the University of York, where she supports colleagues’ professional journey through the PGCAP programme, York Professional and Academic Development scheme recognition, and the York SoTL network. With a background in Applied Linguistics, she worked as a Lecturer in English Language and Education at Huazhong University of Science and Technology in China. She still returns to this area of research with great interest, but also seeks to disentangle the nuanced relationship between SoTL and formal pedagogical research to better support student learning.
James Lamont is an Associate Lecturer at the University of York in the Department of Education and the School of Business and Society, where he supports student skills development. His research interests are student use of technology and developing working relationships across student cohorts.
Further reading
Lamont, J., & Cirocki, A. (2025). Talking to algorithms, not students: Students’ and lecturers’ perceptions of machine translation in academic discussion. The JALT CALL Journal, 21(3), 103256. https://doi.org/10.29140/jaltcall.v21n3.103256
Timecodes
00:00 Intro to MT in the classroom
01:19 James Lamont and Jiaoyue Chen
03:08 Talking to algorithms
04:58 Groves and Mund’s previous work on MT
04:58 Real time translation in class
07:36 Language acquisition concerns
12:19 Tasks versus learning goals
16:15 The impact of MT on non-language learning
20:42 Overreliance and false confidence
26:00 Accuracy culture and dependency
29:48 Policy gaps and overreliance
31:04 Setting classroom expectations
32:57 Phone boundaries and culture
34:15 Structured tech use phases
35:23 Proficiency gaps and support
38:06 Accents, idioms and listening load
43:24 Anxiety comfort and safe seminars
48:50 Privacy, recording and shame
51:48 Student buy-in and agency
54:56 Ideal classroom and future research
58:03 Final Takeaways And Paper Credit