Unlocking emotional resilience: Exploring the impact of AI-enhanced support systems on EFL teachers' burnout and EFL students' well-being in modern classrooms.

This study investigates the relationship between AI-enhanced emotional support systems, teacher burnout, and student well-being in contemporary classrooms. A total of 377 undergraduate students from English-related programs across universities in Guangdong Province, China, participated in the study. Data were analyzed using SPSS (version 27) and AMOS (version 24), employing descriptive statistics, reliability analyses, factor analyses, correlation analysis, multiple regression, and Structural Equation Modeling (SEM). Results indicate that AI-enhanced emotional support systems significantly reduce teacher burnout, particularly emotional exhaustion, while enhancing students' emotional well-being, engagement, and resilience. Regression and SEM analyses reveal that AI tools predict meaningful improvements in students' emotional regulation, classroom participation, and satisfaction, and concurrently support teachers by providing timely feedback and reducing psychological strain. These findings underscore the potential of AI-driven interventions to create emotionally sustainable and supportive learning environments. By integrating AI technologies into classroom practices, educators can foster both student development and teacher well-being, highlighting the transformative role of AI in modern education. This study contributes to the growing body of research on AI in education and provides empirical evidence of its impact on emotional dynamics in classroom settings, offering practical insights for policymakers, administrators, and educators seeking to enhance educational outcomes through technology-mediated emotional support.