Exploring the Differential Impacts of MT and GenAI on Multidimensional L2 Writing Anxiety

ABSTRACT This study investigated how machine translation (MT) and generative AI (GenAI) differentially influence multiple dimensions of L2 writing anxiety among 146 young Japanese EFL learners. Using pre–post data from the second language writing anxiety inventory (SLWAIr), the analyses showed that both MT and GenAI reduced somatic anxiety and avoidance behavior, but neither tool produced group‐level differences. GenAI, however, was accompanied by a non‐significant increase in appraisal concerns and a significant increase in communication apprehension, whereas MT did not. These contrasting within‐group patterns indicate that AI tools do not uniformly alleviate writing anxiety but instead redistribute its internal structure across subcomponents. Regression analyses further revealed that post‐test anxiety was most strongly predicted by avoidance behavior and communication apprehension, underscoring the need to examine multidimensional profiles rather than relying on global scores. The findings contribute to a more nuanced understanding of the affective mechanisms underlying AI‐assisted writing and highlight the importance of selective, guided integration of AI tools in classroom contexts. Limitations related to the lack of usage data and the short‐term design are noted, along with directions for future research.