Exploring EFL Learners’ Academic Emotions and Emotion Regulation Strategies in AI-Assisted Collaborative Academic Writing Tasks

Abstract

Incorporating AI tools such as ChatGPT into collaborative academic writing can provide timely, targeted, adaptive, and directly applicable feedback to learning groups. However, few studies have explored the challenges and emotional facet of learners in such learning contexts. The present study took a mixed-methods approach to unveil the academic emotions and their corresponding emotion regulation strategies (ERS) of two groups of college students (n = 8) in a 6-week collaborative academic writing project.. A new scenario-based questionnaire, using the vignette methodology, and a semi-structured interview were conducted to collect the data. The results revealed that EFL learners experienced a wide spectrum of positive and negative emotions in AI-assisted collaborative academic writing. Moreover, it was found that the participants employed different ERS, such as co-regulation, task-related regulation, and cognitive change, to regulate their academic emotions. The choice of ERS seemed to depend on specific situations, the learning context and participant characteristics.