Machine translation (MT) has become a threat to professional translators and foreign language teachers with its dramatically improved translation performance. The significance of learning English as part of Japanese compulsory education has been questioned by many teachers who believe that the English proficiency of MTs has surpassed that of college English learners (Yamada et al., 2021). Many attempts have been made by teachers and researchers to actively integrate MT into the foreign language teaching classroom. Klimova et al. (2022) provide a systematic review of literature on language teaching using MT on a global level. They found that while using MT, students with lower English proficiency developed their vocabulary and enhanced their writing skills. MT allows learners to acquire vocabulary and expressions that they would not normally find on their own. Ideally, experienced teachers should provide a certain level of support and for students to peer review each other’s work. Students with higher proficiency can improve their metalinguistic awareness of the language differences between L1 and L2 (Klimova et al, 2022). In this presentation, I will introduce an approach called machine translation in language teaching (MTILT), which evolved from translation in language teaching (TILT) (Cook, 2010). The MTILT approach draws on the idea of professional translator training and applies it to foreign language teaching. Particularly, the study proposes the use of MT as a good model to support L2 writing. A preliminary analysis of an experiment conducted with Japanese university English language learners is presented as evidence of the effectiveness of MT-based language learning. [Go to the full record in the library's catalogue]
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