<scp>GenAI</scp> ‐assisted interpreting learning: A survey of Chinese postgraduates' experience, evaluation and expectations

Abstract

Abstract As generative artificial intelligence (GenAI) transforms language educational practices, understanding its pedagogical role in specialised domains like interpreter training has become increasingly important. Still, little is known about how translation and interpreting students, also advanced second‐language learners, perceive and engage with this emerging technology. This study explores how Master of Translation and Interpreting (MTI) students in China experience and evaluate this technology in interpreting learning, as well as their expectations for its integration into training programmes. An exploratory mixed‐methods approach was adopted, drawing on both qualitative and quantitative data from a survey of 244 MTI students with diverse demographics, training backgrounds and usage experience. Quantitative data were analysed using descriptive statistics and inferential analysis, while qualitative data underwent thematic analysis. Findings revealed relatively low levels of GenAI usage in interpreting tasks. However, students with more intensive GenAI use in daily life reported higher usage frequency in interpreting contexts. Technology instruction and moderate self‐learning time could lower barriers to GenAI adoption, making it easier for students to begin using these tools. Overall, students held favourable views of GenAI, particularly for preparation activities such as terminology extraction, information prediction and the real‐world interpreting scenario simulation. Nonetheless, students raised concerns regarding GenAI's limitations in processing cultural and contextual nuances, algorithmic bias and GenAI translationese. Concerning integration into interpreter education, students expressed a strong desire for more systematic and practice‐oriented training, especially in prompt engineering and enhanced feedback functions tailored to interpreting performance. These findings may inform the pedagogical design and technological integration of GenAI in interpreter education.

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