TRANSLATION STRATEGIES IN EFL/ESL AND MTGEN/AI POST-EDITING


Abstrak terlihat: 8 / PDF terunduh: 0

Authors

  • Lusinda Juliani Lusi Lancang Kuning University
  • Nailah Zubaidah Lancang Kuning University, Indonesia
  • Cyntya Isabel Lancang Kuning University, Indonesia
  • Refika Andriani Lancang Kuning University, Indonesia

DOI:

https://doi.org/10.37147/eltr.v10i1.294

Keywords:

machine translation (MT), post-editing, translation strategies

Abstract

This study investigates the interplay of translation techniques, machine translation (MT), and generative artificial intelligence (GenAI) within English as a Foreign Language (EFL) and English as a Second Language (ESL) settings. Utilizing a Systematic Literature Review (SLR) of 23 peer-reviewed studies from 2021–2025, it delineates prevailing methodologies in literary, business, and cultural texts, investigates determinants affecting strategy selection, and contrasts human translation with MT/GenAI post editing regarding accuracy, fluency, and cultural subtleties. Following PRISMA 2020 criteria, the analysis used descriptive statistics and thematic categorization based on both traditional and postcolonial frameworks. The results show that more and more people want a hybrid approach to translating education and practice, where MT/GenAI makes drafts and human post editing improves the quality of language and culture. The "draft by machine, craft by human" paradigm improves translation skills by connecting tactics like explicitation, compensation, and idiomatic adaptation to better readability and coherence. The study suggests combining MT/GenAI with rubric based post editing to improve translators' tech and strategic skills in modern translation teaching.

Downloads

Download data is not yet available.

References

Abadou, F. (2024). Investigating the role of translation in teaching culture to foreign language learners at institutions of higher education in Algeria. Turkish Academic Research Review, 9(3), 259-276. https://doi.org/10.30622/tarr.1497376

Abdelhalim, S. M., Alsahil, A. A., & Alsuhaibani, Z. A. (2025). Artificial intelligence tools and literary translation: A comparative investigation of ChatGPT and Google Translate from novice and advanced EFL student translators’ perspectives. Cogent Arts & Humanities, 12(1), 2508031. https://doi.org/10.1080/23311983.2025.2508031

Akhan, O., & Uzun, A. (2025). Developing historical thinking skills and creativity of visually impaired middle school students. Frontiers in Psychology, 16. https://doi.org/10.3389/fpsyg.2025.1509297

Alkhbeer, A. T. (2025). A transformer-GAN based approach for evaluating and improving high school students’ English translation skills. Journal of Information Systems Engineering and Management, 10(36), 938–955. https://doi.org/10.52783/jisem.v10i36s.6615

Alwazna, R. (2023). The use of translation theory through reconciling between Englishisation and translanguaging by Arab instructors in EMI higher education classes: Training postgraduate students to be translators …. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.1010704

A.R., R., & Pawar, R. (2020). Exploring the role of artificial intelligence (AI) on student learning. In H.K. Yadav & P.K. Yadav (Eds.), Artificial intelligence and ChatGPT (A transformative approach). https://doi.org/10.25215/9392917538.21

Bilal, D. M. (2021). International students’ acquisition of library research skills: relationship with their English language proficiency. In M. Pastine & B. Katz (Eds.), Integrating Library Use Skills into the General Education Curriculum (pp.129–145). New York: Routledge. https://doi.org/10.4324/9781315859835-15

Bin Dahmash, N. (2020). I can’t live without Google Translate: A close look at the use of Google Translate app by second language learners in Saudi Arabia. Arab World English Journal, 11(3), 226–240. https://doi.org/10.24093/awej/vol11no3.14

Dorst, A. G., Valdez, S., & Bouman, H. (2022). Machine translation in the multilingual classroom: How, when and why do humanities students at a Dutch university use machine translation? Translation and Translanguaging in Multilingual Contexts, 8(1), 49–66. https://doi.org/10.1075/ttmc.00080.dor

Erdogan, S. M., Çetin, H., & Ari, K. (2021). Development of multiple representation translating measurement tool and examination of 9th grade students’ multiple representation translate skills in Algebra. Acta Didactica Napocensia, 14(2), 160-180.

Guo, W. (2023). Analysis of the key points of improving students’ English application ability in English translation teaching. Contemporary Education and Teaching Research, 4(1), 1–4. https://doi.org/10.47852/bonviewcetr2023040101

Junaeny, A., & Nirdayanti, N. (2023). Analysis of students Chinese-Indonesian translation of cultural terms translation. Sinolingua: Journal of Chinese Studies, 1(2), 91–91. https://doi.org/10.20961/sinolingua.v1i2.71964s

Kilaton, L. (2024). Assessing proficiency level of research questionnaire translation skills in higher education students. Psychology and Education: A Multidisciplinary Journal, 20(3), 297-306. https://doi.org/10.2139/ssrn.4845063

Krüger, R. (2021). An online repository of python resources for teaching machine translation to translation students. Current Trends in Translation Teaching and Learning E, 8, 4–30. https://doi.org/10.51287/cttle20212

Liu, K., Kwok, H., Liu, J., & Cheung, A. (2022). Sustainability and influence of machine translation: Perceptions and attitudes of translation instructors and learners in Hong Kong. Sustainability, 14(11), 6399. https://doi.org/10.3390/su14116399

Maid, Y., & Azmi, N. (2025). Bridging the linguistic gap: Translation skills for Moroccan business students in the transition from French to English. European Modern Studies Journal, 9(3), 265–275. https://doi.org/10.59573/emsj.9(3).2025.22

Muñoz-Basols, J. (2023). Potentialities of applied translation for language learning in the era of artificial intelligence. Hispania, 106(2), 171–194. https://doi.org/10.1353/hpn.2023.a899427

Omolu, F. A., & Mappewali, A. (2024). The impact of translation tools towards student translators’ skills. Premise: Journal of English Education, 13(1), 340–340. https://doi.org/10.24127/pj.v13i1.8731

Sinambela, E., Siregar, R., & Pakpahan, C. (2023). Improving students’ ability in using English with a simple translation: A case on elementary school level. Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini, 7(3), 3267–3278. https://doi.org/10.31004/obsesi.v7i3.4647

Varela Salinas, M.-J., & Burbat, R. (2023). Google Translate and DeepL: Breaking taboos in translator training: Observational study and analysis. Ibérica, (45), 243–266. https://doi.org/10.17398/2340-2784.45.243

Wang, A. (2021). A study on the problems and skills of business English translation. Learning & Education, 10(3), 186. https://doi.org/10.18282/l-e.v10i3.2444

Yang, H., Aniceto, N., Allen, C., Bulusu, K. C., & Tsang, S. L. (2022). Predicting anticancer synergistic activity through machine learning and natural language processing. In H. Yang (Ed.), Data science, AI, and machine learning in drug development (pp. 95–120). New York: Chapman and Hall/CRC. https://doi.org/10.1201/9781003150886-5

Yildiz, T. (2023). Measurement of attitude in language learning with AI (MALL:AI). Participatory Educational Research, 10(4), 111–126. https://doi.org/10.17275/per.23.62.10.4

Downloads

Published

2026-01-28

How to Cite

Lusi, L. J., Zubaidah, N. ., Isabel, C. ., & Andriani, R. . (2026). TRANSLATION STRATEGIES IN EFL/ESL AND MTGEN/AI POST-EDITING. ELTR Journal, 10(1), 1-17. https://doi.org/10.37147/eltr.v10i1.294

Issue

Section

Articles