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TRANSLATION STRATEGIES IN EFL/ESL AND MTGEN/AI POST-EDITING Lusi, Lusinda Juliani; Zubaidah, Nailah; Isabel, Cyntya; Andriani, Refika
ELTR Journal Vol. 10 No. 1 (2026)
Publisher : English Language Education Study Program Association (ELESPA) or Asosiasi Program Studi Pendidikan Bahasa Inggris (APSPBI), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37147/eltr.v10i1.294

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.
Human and Machine Collaboration in Translation: A Systematic Review of Emerging Practices Andani, Alda Dea; Sinaga, Jesika Bungaria; Putri, Silvia Ramanda; Andriani, Refika
Journal of English Language and Education Vol 11, No 1 (2026)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jele.v11i1.2093

Abstract

The rapid advancement of Artificial Intelligence (AI) has transformed translation from something primarily done by humans to something done by humans and computers working together to create meaning. This study aims to deeply analyze research on AI-Assisted Translation (AIAT) published from 2020 to 2025 to understand the linguistic, collaborative, and ethical dynamics influencing this profession. Using the PRISMA framework and the CASP checklist, twenty empirical studies were analyzed from the Crossref, Scopus, and Google Scholar databases. The findings revealed three dominant themes: improved linguistic performance thru neural systems and large language models; the emergence of human-AI collaboration reshaping translators' cognitive and professional roles; and ethical concerns regarding bias, transparency, and cultural accountability. These findings indicate that AIAT should not only be understood as a technological innovation, but also as a sociolinguistic phenomenon that requires critical human involvement. This study concludes that effective translation in the digital age relies on the synergy between technological accuracy and human interpretive intelligence
English Subtitle Viewing Tasks: Enhancing EFL University Students' Listening Comprehension and Learning Perceptions Destina, Destina; Andriani, Refika; Herdi, Herdi; Simbolon, Wulandari
J-SHMIC : Journal of English for Academic Vol. 13 No. 2 (2026): J-SHMIC: Journal of English for Academic
Publisher : UIR Press

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Listening comprehension remains one of the most challenging skills for English as a Foreign Language (EFL) learners, particularly in higher education where students are expected to comprehend authentic spoken English. Although previous studies have demonstrated the benefits of subtitles for language learning, limited research has examined English subtitle viewing tasks as structured classroom activities while simultaneously investigating students' listening achievement and learning perceptions. This study therefore aimed to examine the effect of English subtitle viewing tasks on students' listening comprehension and to explore their perceptions of the instructional approach. A quantitative pre-experimental study employing a one-group pretest-posttest design was conducted with 24 third-semester undergraduate students in an English Education program at a private university in Indonesia. Data were collected using a listening comprehension test and a four-point Likert-scale questionnaire and analyzed through descriptive statistics, a paired-samples t-test, and normalized gain (N-Gain) analysis. The findings revealed a statistically significant improvement in students' listening comprehension, with the mean score increasing from 77.54 to 84.29 (t = 12.597, p < .001), while the mean N-Gain score (0.308) indicated a moderate level of learning improvement. Students also reported highly positive perceptions of the instructional approach, with an overall mean score of 3.82 across five measured dimensions. These findings suggest that English subtitle viewing tasks provide meaningful support for listening comprehension while fostering positive learning experiences. The study offers empirical evidence for the effective integration of subtitle-assisted learning into university EFL listening instruction.