BLENDING HUMAN AND AI IN TRANSLATION TEACHING FOR 21ST- CENTURY EFL CLASSROOM

Abstract

The integration of Artificial Intelligence (AI) into language education has transformed translation instruction, offering tools such as Google Translate and ChatGPT to support learners in decoding and producing texts across languages. However, despite their widespread use, these tools are often applied without pedagogical structure, resulting in overreliance, misinterpretation, and limited linguistic development, particularly among university students in non-English dominant contexts. This qualitative case study investigated how sixth-semester students from seven universities in Palembang, Indonesia, utilized AI-based translation tools in academic settings. Fourteen English education majors were selected through random sampling. Data were collected through semi-structured interviews and analysis of students’ translation drafts before and after AI use. Thematic analysis was employed to identify translation behaviours, strategies, and instructional needs. Findings indicated persistent issues, including literal idiom transfer, register mismatches, and limited error detection even after AI assistance. Most participants adopted a tool-first approach with minimal revision. However, structured strategies such as guided post-editing and back-translation enhanced lexical accuracy and metalinguistic awareness. The study proposes a four-phase framework integrating AI meaningfully into translation pedagogy for improved learning outcomes.