DEVELOPING LINGUISTIC AND CULTURAL AWARENESS THROUGH MACHINE TRANSLATION POST-EDITING IN JAPANESE–INDONESIAN TRANSLATION LEARNING

Authors

  • Dewi Universitas Negeri Jakarta
  • Dewanti Universitas Negeri Jakarta

DOI:

https://doi.org/10.21009/ishel.v2i1.69894

Keywords:

machine translation post-editing, translation pedagogy, linguistic awareness, cultural awareness, translation learning

Abstract

The rapid development of Neural Machine Translation (NMT) has changed the way translation is taught and learned. Although machine translation systems are now widely used in translation classrooms, many students still tend to accept machine-generated translations without carefully examining their linguistic and cultural appropriateness. This study investigates how Machine Translation Post-Editing (MTPE) helps develop students' linguistic and cultural awareness in Japanese–Indonesian translation learning. A convergent mixed-methods design was employed involving undergraduate students who participated in ten instructional meetings using three Japanese folktales as translation materials. Data were collected from students' MTPE products, reflection sheets, and perception questionnaires. The findings show that students went beyond correcting errors in machine-generated translations by actively evaluating and revising linguistic and cultural meanings. During the post-editing process, they reconsidered word choices, revised semantic and pragmatic meanings, and adjusted culturally embedded expressions. Many students were also able to explain the reasons behind their revisions and reflect on the linguistic and cultural issues they encountered, although some revisions still resulted in overly free interpretations that altered the original meaning. These preliminary findings indicate that MTPE provides students with opportunities to examine machine-generated translations more critically while gradually developing greater awareness of linguistic and cultural aspects of translation. This study offers preliminary insights into how MTPE can support the development of linguistic and cultural awareness in Japanese–Indonesian translation learning.

References

Aboelnagah, H. (2025). An investigative study into the role extralinguistic information plays in producing accurate meaning in the post-MT-editing of Arabic texts with culturally embedded terms. Arabic Journal for Translation Studies, 4(13), 77–98. https://doi.org/10.63939/ajts.qrdxnt19

Bowker, L., & Buitrago Ciro, J. (2019). Machine translation and global research: Towards improved machine translation literacy in the scholarly community. Emerald Publishing. https://doi.org/10.1108/9781787567214

Castilho, S., Moorkens, J., Gaspari, F., Calixto, I., Tinsley, J., & Way, A. (2017). Is neural machine translation the new state of the art? The Prague Bulletin of Mathematical Linguistics, 108.

Cholewska, D. (2021). Machine translation post-editing (MTPE) from the perspective of translation trainees: Implications for translation pedagogy. In J. Campbell, B. Huyck, S. Larocca, J. Marciano, K. Savenkov, & A. Yanishevsky (Eds.),. Proceedings of Machine Translation Summit XVIII: Users and Providers Track, 200–210.

Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). Sage.

Doherty, S. (2016). The impact of translation technologies on the process and product of translation. International Journal of Communication, 10, 947–969.

Gu, Q., Wang, S., Ren, X., & Ji, X. (2025). Post-editing of AI-assisted translation in translator education: A genre-based classroom study. Journal of Historical, Cultural and Social Sciences, 1(2), 10–22. https://doi.org/10.71204/7mdsqs66

Harto, S. e. al. (2022). No TitleExploring undergraduate students’ experiences in dealing with post-editing of machine translation. Indonesian Journal of Applied Linguistics, 11(3), 696–707. https://doi.org/10.17509/ijal.v11i3.42825

House, J. (2015). Translation quality assessment: Past and present. Routledge.

Koponen, M., Mossop, B., Robert, I. S., & Scocchera, G. (Eds. ). (2021). Translation revision and post-editing. Routledge.

Läubli, S., Sennrich, R., & Volk, M. (2018). Has machine translation achieved human parity? a case for document-level evaluation. ArXiv Preprint ArXiv:1808.07048.

Molina, L., & Albir, A. H. (2002). Translation techniques revisited: A dynamic and functionalist approach. Meta. Meta, 47(4), 498–512.

Nitzke, J., & Hansen-Schirra, S. (2021). A short guide to post-editing. Language Science Press.

O’Brien, S. (2022). Machine translation and post-editing, Routledge encyclopedia of translation studies (M. Baker & G. Saldanha (ed.); 3rd ed.). Routledge.

Pym, A. (2013). Translation skill-sets in a machine-translation age. Meta, 58(3), 487–503.

Roza, V., Melani, M., & Zulfahmi, M. R. Y. (2024). Cross-cultural echoes: Exploring cultural nuance through student translation practices. Elsya: Journal of English Language Studies, 6(3), 265–277. https://doi.org/10.31849/elsya.v6i3.22410

Downloads

Published

2026-10-15

How to Cite

Dewi, & Dewanti. (2026). DEVELOPING LINGUISTIC AND CULTURAL AWARENESS THROUGH MACHINE TRANSLATION POST-EDITING IN JAPANESE–INDONESIAN TRANSLATION LEARNING. Proceeding of International Seminar on Humanity, Education, and Language, 2(1), 1094–1111. https://doi.org/10.21009/ishel.v2i1.69894

Similar Articles

<< < 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 > >> 

You may also start an advanced similarity search for this article.