Artificial Intelligence And Emotional Intelligence In Second Language Pedagogy

Abstract

This study investigates how learning anxiety, classroom setting, emotional intelligence (EI), foreign language learning pleasure (FLE), and artificial intelligence (AI)-assisted intervention interact to influence undergraduate students' English learning outcomes. The data from three survey rounds involving 426 undergraduates who did not major in English were analyzed using a mixed-methods methodology and longitudinal structural equation modeling (SEM). The findings show that while anxiety has a major detrimental impact, FLE is the most important positive predictor of academic achievement and learner engagement, followed by EI. This process is mediated and moderated by the classroom environment, which improves FLE and somewhat mitigates the detrimental effects of anxiety First-generation college students gain more from cooperative learning despite having lower EI and higher anxiety, according to group study. Additionally, by offering tailored emotional control techniques and adaptive feedback, the AI-assisted platform greatly enhances students' academic achievement and emotional resilience. The study suggests that language learning should be viewed as an affective-cognitive complex system rather than a solely cognitive process, highlighting the theoretical significance of combining positive psychology with the second language motivating self-system. Practically speaking, the study highlights the importance of emotion-responsive instruction, focused assistance for first-generation college students, and the need for a blended learning approach that blends humanistic care with AI flexibility. The study provides novel perspectives on teacher intervention, emotional dynamics, and the long-term growth of language learning in higher education.