Redefining Language Education: How Integrating <scp>EFL</scp> Teacher‐Student Relationships With <scp>AI</scp> ‐Powered Classrooms Impacts Emotional Health and <scp>EFL</scp> Learners' Depression

ABSTRACT The present study investigates the interplay between EFL teacher–student interactions, AI‐powered classroom integration, learners' emotional health, and depression in Chinese English majors. A total of 529 students participated voluntarily, completing four validated instruments: the AI‐Enhanced Learning Environment Assessments Questionnaire, the Emotion Measurement Scale, the Questionnaire on Teacher Interaction (QTI), and Beck's Depression Inventory (BDI). Using SPSS 27 and AMOS 24, analyses included descriptive statistics, reliability assessments, correlation analyses, confirmatory factor analysis, structural equation modeling, and multiple regression analyses. Results indicated that both teacher–student interactions and AI‐enhanced classroom environments were positively associated with emotional health and negatively associated with depressive symptoms. Predictive analyses further demonstrated that teacher–student interactions and AI integration significantly predicted learners' emotional well‐being and depression, with relational interactions showing slightly stronger effects. These findings highlight the complementary roles of human relational support and adaptive technology in promoting positive emotional outcomes and mitigating depressive symptoms in language learning contexts. Implications for theory, pedagogy, and AI‐supported educational design are discussed, alongside recommendations for future research.