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This review aims to synthesize empirical studies on how generative AI influences translation education.

May 15, 2026Journal of Language2 citationsOpen Access

Generative AI and the Transformation of Translation Education: A Systematic Review of Empirical Studies

Key Points

This review aims to synthesize empirical studies on how generative AI influences translation education.
Systematic review of 60 empirical studies from 37 journals or edited volumes.
Utilized the PRISMA framework to analyze included studies.
Addressed three key questions regarding GenAI's definition, outcomes, and pedagogical implications.
GenAI introduced in various pedagogical roles with positive impacts on translation performance and structured feedback.
Mixed findings reported in areas such as learner experience and AI literacy.
GenAI increasingly positioned as a pedagogical actor requiring human oversight, highlighting risks and disparities in its use.

Abstract

This systematic review examines how generative artificial intelligence (GenAI) shapes translation education through a synthesis of 60 empirical studies published across 37 journals or edited volumes in the fields of translation and interpreting training, educational technology, and applied linguistics. Following the PRISMA framework, the review presents the overall profile of the included studies and analyzes them in relation to three questions concerning how GenAI has been defined, introduced, and used in translation education research, what kinds of learning-related outcomes have been reported, and what pedagogical conditions, learner factors, and ethical and technological boundaries appear to shape its role. The findings show that GenAI is already becoming part of translation-related teaching and learning, but not in one uniform or stable way. Across the studies reviewed, GenAI was introduced through multiple pedagogical roles, including translation assistant, feedback provider, revision scaffold, post-editing aid, and interactive learning partner. Reported outcomes were distributed across several domains, with relatively more positive findings in translation performance and in structured feedback or post-editing tasks, and more mixed findings in learner experience, AI literacy, and process-related domains. Compared with the pre-GenAI era, when technologies such as computer-assisted translation tools were more often treated as external resources and aids, translation education in the GenAI era increasingly positions GenAI as a pedagogical actor that participates in drafting, commenting, revising, simulating, and structuring learning activities, while still requiring human-in-the-loop oversight and judgment. At the same time, the review highlights the risk of ChatGPT-centered pedagogy and a gap between academic use and professional workflows. Overall, the review argues that GenAI should be understood not as a simple pedagogical solution, but as part of a broader reorganization of translation education.

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