Emotional Fluctuations in <scp>AI</scp> ‐Enhanced Ecosystems: Exploring <scp>EFL</scp> Learners' Affective States During <scp>AI</scp> Technology Adoption

ABSTRACT Various aspects of artificial intelligence (AI) adoption have been studied in second/foreign language (L2) education over the past decade. However, insufficient attention has been paid to the long‐term affective fluctuations associated with the integration of AI tools in English as a foreign language (EFL) education. It remains unclear how such technologies shape and reshape learners' classroom emotions over time. Drawing on the technology acceptance model (TAM) and control–value theory (CVT) of emotions, this study examined Chinese EFL students' emotional fluctuations during an AI‐mediated course over two semesters. A longitudinal interventional research design was adopted. Questionnaire data were collected from 261 Chinese EFL students at three time points: the beginning, middle and end of an AI‐mediated course. The data were analysed using latent growth curve modelling (LGCM). The results revealed significant changes in both positive and negative emotions induced by AI over time. A negative correlation was also observed between positive and negative emotions, indicating that as learners' positive emotions increased, their negative emotions decreased. This study provides empirical evidence for understanding the dynamic emotional effects of AI integration in EFL education. It also offers pedagogical implications for developing emotion‐oriented AI‐mediated L2 education.