Unleashing pre-service language teachers’ productivity with generative AI: Emotions, appraisal and coping strategies

Abstract

The potential of Generative Artificial Intelligence (AI) in language education has been widely recognized. However, there has been limited attention given to the emotional experiences of language teachers using AI and its relationship with AI-enabled productivity. By investigating 1,683 pre-service language teachers’ experiences of using generative AI in their teaching practicum or learning, this study explored how teachers’ emotional responses to AI use in teaching and learning are related to their AI-enabled productivity through the mediation of appraisal and coping. We uncovered several key findings: (1) achievement, challenge, and loss emotions were directly and/or indirectly related to AI-enabled productivity, while deterrence emotions were not; (2) achievement and challenge emotions were positively correlated with challenge appraisal and negatively correlated with hindrance appraisal, whereas loss and deterrence emotions showed the opposite pattern of correlation; (3) challenge emotions were positively related to approach-oriented coping, while loss and deterrence emotions were positively associated with avoidance-oriented coping; (4) among the coping strategies, only positive reinterpretation was positively associated with AI-enabled productivity; and (5) challenge appraisal and positive reinterpretation were significant mediators in the relationships between emotions and AI-enabled productivity, either separately or sequentially. These findings provide valuable insights for future research and practice, aiming to support the application of generative AI in the context of language education.