FL Instructor Beliefs About Machine Translation: Ecological Insights to Guide Research and Practice

Emily Hellmich and Kimberly Vinall
Additional contact information
Emily Hellmich: University of Arizona, USA
Kimberly Vinall: UC Berkeley Language Center, USA

International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT), 2021, vol. 11, issue 4, 1-18

Abstract: Machine translation (MT) platforms have gained increasing attention in the educational linguistics community. The current article extends past research on instructor beliefs about MT by way of an ecological theoretical framework. The study reports on a large-scale survey (n=165) of FL university-level instructors in the U.S. Findings indicate strong lines being drawn around acceptable MT use (e.g., in relation to text length and skill, policies), an acknowledgement of widespread student use driven by diverse motivations, and the Janus-faced nature of MT's potential threat to the profession. These findings reveal several salient tensions in how MT mediates relationships in language education (e.g., constructions of students, the nature of language and language learning, goals of the profession) that shed new light on the impact of MT technologies on the field. Implications for future research and the development of pedagogical practices anchored in digital literacies conclude the piece.

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 8/IJCALLT.2021100101 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jcallt:v:11:y:2021:i:4:p:1-18

Access Statistics for this article

International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT) is currently edited by Bin Zou

More articles in International Journal of Computer-Assisted Language Learning and Teaching (IJCALLT) from IGI Global
Bibliographic data for series maintained by Journal Editor ().