Unleashing Preservice Language Teachers’ Generative AI-Enabled Productivity: A Coping Theory Perspective

• In Event: Generative AI in Teacher Education: Perceptions, Productivity, and Collaborative Insights

Abstract

This research examined 1,683 pre-service language teachers, exploring how their emotional responses to AI use relate to productivity through appraisal and coping mechanisms. The key findings are (1) achievement, challenge, and loss emotions were related to AI-enabled productivity, while deterrence emotions were not; (2) achievement and challenge emotions were positively correlated with challenge appraisal and negatively with hindrance appraisal; (3) challenge emotions were linked to approach-oriented coping, while loss and deterrence emotions were linked to avoidance-oriented coping; (4) only positive reinterpretation among coping strategies was positively associated with AI-enabled productivity; and (5) challenge appraisal and positive reinterpretation significantly mediated the relationship between emotions and AI-enabled productivity. These findings provide insights for supporting the application of generative AI in language education.

Authors

• Hongbiao Yin, The Chinese University of Hong Kong

• Chan Wang, The Chinese University of Hong Kong