Adaptation to AI-integrated Translation Education: A Case Study
DOI:
https://doi.org/10.62819/bej.2026.3194Keywords:
Translation teaching and learning (TTL), English as a foreign language (EFL), Vietnamese higher education, artificial intelligence (AI) translation tools, novice lecturersAbstract
Translation teaching and learning (TTL) in Vietnamese higher education, particularly within English as a Foreign Language (EFL) programmes, is increasingly reshaped by the integration of artificial intelligence (AI) in translation education through AI translation tools. This development has prompted lecturers, especially novices, to reconsider their teaching practices. This qualitative single-case study explores how a novice lecturer at a university in central Vietnam perceives the benefits and challenges of these tools in TTL and how she adapts her instructions in response. Collected through a semi-structured interview and video-based classroom observations of four online class sessions conducted in January 2026, the data were analyzed using an inductive thematic approach, with themes developed through iterative coding and triangulation across interview and observational sources. The findings indicate that AI translation tools are seen as an inevitable feature of contemporary TTL. While acknowledging their affordances in supporting drafting, comparison, reflective learning, and pedagogical innovation, the lecturer also raise concerns about student overreliance, assessment validity, and institutional constraints. In response, she adopts a three-step approach-independent translation, consultation of AI translation tools, and critical justification-which appears to enhance students’ performance, confidence, and decision-making. The study highlights the importance of pedagogically guided AI integration in TLL and its implications for EFL and English Language Teaching.
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