Learner cognition and behavioral engagement in GenAI-mediated professional language education: a critical integrative review

Generative Artificial Intelligence (GenAI) is transforming professional language education, particularly in high-cognitive-load fields like translation and interpreting. A critical integrative review of 21 core studies reveals a significant gap in understanding the cognitive and behavioral mechanisms of learner engagement with GenAI-mediated tasks. Students in these domains must navigate evaluating AI outputs, regulating feedback, and maintaining accountability for meaning, highlighting the complex interaction between human learning and advanced AI tools.

Why it matters

The integration of GenAI into professional language education necessitates a deeper understanding of how learners cognitively and behaviorally interact with these tools. This is crucial for developing effective pedagogical strategies, optimizing training programs, and ensuring the continued development of human expertise alongside evolving technological capabilities in critical communication fields.

Key insights

• GenAI is rapidly changing professional language education.
• There is an insufficient synthesis of behavioral and cognitive mechanisms through which learners engage with GenAI-mediated language tasks.
• Translation and interpreting education are identified as high-cognitive-load cases of professional language learning.
• Learners in these contexts must evaluate AI output, regulate feedback usage, and remain accountable for meaning across languages.
• A review of 21 core studies (selected from 690 potentially relevant records) forms the basis of this analysis, directly addressing GenAI in this domain.

Source

Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1909485