Abstract

This paper investigates the use of machine translation tools (MTT) for reflective language learning. Drawing on Bowker’s (2020) concept of machine translation literacy, it suggests that machine translation tools can support learners in their language development if used critically. It argues that language learners should be supported to seek out affordances of MMT to develop machine translation literacies for specific language skills (reading, writing, listening and speaking) and vocabulary building. This paper presents the preliminary findings of a small-scale study involving ten advanced German language students who explored the features of MTT to meet their individual learning goals for reading. The process of affordance development was analyzed through the lens of Affordance-Actualization Theory.

Suggested citation

Alm, A. (2022). Actualizing the affordances of Machine Translation Tools for language learning. In J. Colpaert, Y. Wang, & G. Stockwell (Eds.), Proceedings of the XXIst International CALL Research Conference (pp. 1–6). London: Castledown Publishers. https://doi.org/10.29140/9781914291050-1