CURRENT USE OF AI TRANSLATION AND INTERPRETING TOOLS AMONG VIETNAMESE STUDENTS - A PRELIMINARY SURVEY OF THEIR IMPACT ON MOTIVATION TO LEARN JAPANESE
Main Article Content
Abstract
In recent years, artificial intelligence (AI) has made remarkable advances, particularly in the field of language translation and interpreting. Numerous studies have indicated that once AI surpasses a certain threshold of capability, its performance can improve in a non-linear manner, resulting in profound impacts across various practical application domains. Specifically, machine translation applications on computers and smartphones now enable users to access high-quality translations within a few seconds. Automatic interpreting devices and software have also been widely adopted. Moreover, some applications integrate optical character recognition (OCR) through smartphone cameras, allowing instant translation of text in images without the need for manual input. In this context, an important question arises as to whether the widespread use of AI-based translation tools influences learners’ motivation to study foreign languages. At the same time, it is necessary to consider how the role of teachers and approaches to foreign language instruction should adapt to these technological changes. To address these issues, the present study investigates the current state of AI-based translation and interpreting tool usage among third- and fourth-year Japanese language majors. On this basis, the study conducts a preliminary analysis of the impact of these tools on learners’ motivation to study Japanese. Furthermore, the paper offers insights and proposals regarding future directions for Japanese language education in the contemporary AI- era.
Keywords
Artificial Intelligence (AI), interpreting, translation, Japanese language learners, learning motivation
Article Details
References
Dörnyei, Z. (2001). Motivational strategies in the language classroom. Cambridge University Press. https://doi.org/10.1017/CBO9780511667343
Enomoto, A. (2024). Perceptions and use of AI and online translation software in an EFL classroom at a Japanese university. In Proceedings of the International Academic Conference (Paper No. 14616407). International Institute of Social and Economic Sciences. https://doi.org/10.20472/IAC.2024.064.005
Gardner, R. C. (1985). Social psychology and second language learning: The role of attitudes and motivation. Edward Arnold. https://doi.org/10.1017/S0272263100007634
Huang, J., & Mizumoto, A. (2024). Examining the effect of generative AI on students’ motivation and writing self-efficacy. Digital Applied Linguistics, 1, Article 102324. https://doi.org/10.29140/dal.v1.102324
Kimura, S. (2023). Examining the impact of AI translation on foreign language education: A case from the “Text Studies (Arts & Culture)” course in the German Department. Dokkyo University German Studies, 81, 1–22. https://dokkyo.repo.nii.ac.jp/?action=repository_action_common_download&item_id=6745&item_no=1&attribute_id=18&file_no=1
Kuraya, N. (2019). The Potential Use of Machine Translation Services as a Learning Tool in English Writing - As a Theoretical Preparation. The Journal of Japanese Society for Global Social and Cultural Studies, 16(1), 24–35. https://www.jstage.jst.go.jp/article/gscs/16/1/16_24/_article/-char/ja/
Noguchi, H. (2023). Teaching writing using technology. Journal of Liberal Arts, Tokyo Medical and Dental University, 53, 91–94. https://www.jstage.jst.go.jp/article/kyoyobukiyo/2023/53/2023_9/_pdf?utm_source
Oda, T. (2021). The influence of machine translation on general education English in Japan. The Journal of Humanities and Natural Sciences, 149, 3–27. https://repository.tku.ac.jp/dspace/handle/11150/11672
Oda, T. (2022). A search for meaningful general education English in the era of machine translation. The Journal of Humanities and Natural Sciences, 151, 17–49. https://repository.tku.ac.jp/dspace/handle/11150/11817
Oda, T. (Ed.). (2023). English education and machine translation: Thinking and practice in a new era (M. Yamada, Superv. Ed.). Kinseido. https://researchmap.jp/yamada_trans/books_etc/43110291
Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67. https://doi.org/10.1006/ceps.1999.1020
Sasaki, M., Mizumoto, A., & Matsuda, P. K. (2024). Machine translation as a form of feedback on L2 writing. International Review of Applied Linguistics in Language Teaching, 63(4), 2301–2326. https://doi.org/10.1515/iral-2023-0223
Schunk, D. H., Pintrich, P. R., & Meece, J. L. (2008). Motivation in education: Theory, research, and applications (3rd ed.). Pearson.
Sumida, E. (2022). The AI translation revolution. Asahi Shimbun Publishing. https://publications.asahi.com/product/23728.html
Wu, Y., Schuster, M., Chen, Z., Le, Q. V., Norouzi, M., Macherey, W., Krikun, M., Cao, Y., Gao, Q., Macherey, K., Klingner, J., Shah, A., Johnson, M., Liu, X., Łukasz Kaiser, Gouws, S., Kato, Y., Kudo, T., Kazawa, H., . . . Dean, J. (2016). Google’s neural machine translation system: Bridging the gap between human and machine translation (arXiv:1609.08144). https://arxiv.org/pdf/1609.08144
Yamada, M., Langlitz, H., Oda, T., Morita, T., Tamura, H., Hiraoka, Y., & Irie, T. (2021). A preliminary survey on the use of machine translation in English education at Japanese universities. Invitation to Interpreting and Translation Studies, 23, 139–155. https://www.jstage.jst.go.jp/article/iits/23/0/23_2307/_article/-char/ja/
Yanase, Y. (2023, October 13). English Language Teaching with ChatGPT in College: An English Instructor's Recognition of the Large Language Model AI's Potential and Limitations. Online Symposium, National Institute of Informatics, Japan. https://www.nii.ac.jp/event/upload/20231013-05_Yanase.pdf