| Asia Pacific Journal of Language, Culture, and Education Vol. 1, No. 1, pp. 13-17 |
| Abbreviation: APJLCE |
| ISSN: 3092-362X |
| Publication date: 30 June 2026 |
| Received: 24 March 2026 / Received in Revised Form: 10 June 2026 / Accepted: 19 June 2026 |
| DOI: https://doi.org/10.23403/apjlce.2026.1.1.13
|
AI-based Translation and the Future Directions of English Education |
| Chang-Yong Sim (Gyeongin National University of Education), SOUTH KOREA |
| Copyright 2026 APJLCE This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted, distribution, and reproduction in any medium, provided the original work is properly cited. |
Abstract |
| Recent advances in generative artificial intelligence (AI), particularly Large Language Models (LLMs), have fundamentally transformed translation technologies and language-use environments. Unlike traditional machine translation systems, LLM-based translation systems increasingly reconstruct meaning at the contextual and discourse levels. Although generative AI can produce highly natural and fluent translations, it still faces challenges in accurately preserving nuances of meaning, discourse functions, and cultural implications. In specialized domains such as academia, law, medicine, and diplomacy, even subtle shifts in meaning may result in significant professional and social consequences. Consequently, human judgment remains essential for evaluating, revising, and validating AI-generated translations. As a result, the role of human translators/language users is being redefined from language producers to meaning supervisors who critically assess and assume responsibility for the appropriateness of translated content. These developments also highlight the need to redefine the goals of English education. Rather than focusing solely on linguistic production, future English education should emphasize the ability to critically evaluate AI-generated outputs, interpret contextual and discourse-level meanings, understand cultural implications, and make informed linguistic choices among alternative expressions. Ultimately, English education in the AI era should move beyond the teaching of language itself and foster advanced language literacy that enables learners to understand, evaluate, and responsibly utilize AI-generated content. |
Keywords |
| Generative Artificial Intelligence, Large Language Models, Machine Translation, English Language Education, Critical Language Literacy, Meaning Evaluation |
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The Author |
| Chang-Yong Sim is a Professor in the Department of English Education at Gyeongin National University of Education, South Korea. His research focuses on linguistics, second language acquisition, teacher education, and the integration of artificial intelligence into language education. He has published extensively in the areas of linguistics, AI-assisted language learning, English language education, and educational technology. |
The Author’s Address |
| First and Corresponding Author Chang-Yong Sim Professor Department of English Education Gyeongin National University of Education 155 Sammak-ro, Manan-gu, Anyang, Gyeonggi-do, South Korea E-mail: simyong@ginue.ac.kr |
