Perceptions of an AI-based Translator and its Application by Pre-Service EFL Teachers

Purpose: This present study was to investigate how pre-service English as a foreign language (EFL)teachers perceive AI-based machine translation systems (KEMSs) as a learning/teaching tool. Methods: The 54 EFL learners taking English syntax courses in the department of English Educationparticipated in an online survey which included 20 items quantitatively measured on a Likert scaleand four open questions. The research questions addressed three areas: (1) students’experiences withmachine translation (MT); (2) teachers’perceptions of using MT to teach English; and (3) their plansfor using MT as future English teachers. Results: The main findings are as follows: First, the students in this study actively utilized the MTs,especially in English writing and reading comprehension classes. The study also related that the useof MTs helped them to improve their English language skills. Second, the students mostly consideredthe results of the MTs as reliable, but the teachers revealed that the use of MTs would have a negativeimpact on future students' English learning. Finally, the teacher-participants had plans to actively useMTs in their future classes and were aware of the advantages and disadvantages of using MTs inclassroom settings. Conclusion: This study showed that future English teachers have positive perceptions of using machinetranslations to improve English writing and reading skills in foreign language learning; however, theyalso think their future students will lose the chance to use the language for successful learning. Considering these findings, the present work examined pedagogical implications for pre-service teachersand suggests how to apply information and communication technology (ICT)-based teaching aids inEnglish education.