Communications in Humanities Research ISSN: 2753-7072
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Research Article

GenAI in Written Translation Education: A Systematic Review of Challenges and Pedagogical Pathways

Ying WuBeijing Foreign Studies University；Wenhua College*

* Corresponding author: [email protected]

Abstract

Since late 2022, generative artificial intelligence has steadily found its way into written translation classrooms, setting off a wave of discussion about what these tools mean for how translation is taught. This paper surveys the recent literature—spanning both English and Chinese academic journals over roughly four years—to map out the specific challenges GenAI has created for written translation education and the teaching strategies scholars have proposed in response. The review finds that two concerns dominate the conversation. One is the breakdown of feedback loops: AI-generated feedback tends to stay at the surface of language and misses the deeper, context-sensitive judgment that written translation instruction depends on. The other is the erosion of foundational skills—students leaning too heavily on large language models before doing their own analytical work. Beyond these, several additional themes run through the literature: the difficulty novice translators face in catching subtle errors embedded in fluent-looking AI drafts, the anxiety that pervasive AI use generates around professional identity and ethical boundaries, the tendency of existing AI scoring tools to favor safe, formulaic output while penalizing creative or stylistically distinctive translation, and the well-documented but under-researched problem of cultural transfer failures in LLM-generated texts. On the response side, curriculum and pedagogical redesign is the most widely endorsed direction, with growing interest in building translation-specific AI literacy and in designing structured human-AI collaborative workflows. The review also finds that scholars writing in Chinese and in English emphasize different priorities—particularly around whether translator role reshaping should be institution-led or learner-driven—and that the teaching of cultural transfer competence in an AI-mediated environment remains at an early stage in both research communities.

Keywords: GenAI; written translation education; systematic review; pedagogical pathways; human-AI collaboration
Published: June 29, 2026
DOI: 10.54254/2753-7064/2026.34990
Volume: CHR Vol.111
pp. 249-260
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