Cracking the code of teacher burnout: the chain mediation of GPT integration degree through behavioral engagement and classroom atmosphere in a cross-level chain mediation model

Chat GPT technology plays a pivotal role in global educational innovation and the enhancement of the quality of teaching and learning. In the field of education research, numerous studies have been conducted to investigate the effectiveness of GPT technology, teacher acceptance, and student engagement in depth. To date, few studies have considered the compounding effects of these factors on teacher burnout from the perspectives of psychology and behavioral sciences in conjunction with the dichotomous and complex relationship between teachers and students. Consequently, based on the findings of previous scholars, this study constructed a cross-layer chain mediation model based on the SOR and EASI models. This model was used to explore how different motivators affect the alleviation of teacher burnout through psychological and behavioral mechanisms. The study involved 47 teachers and 506 students from 10 universities. The findings of the study indicated that (1) the direct effect of GPT integration degree on teacher burnout was not statistically significant, and (2) the classroom atmosphere played a pivotal mediating role in the relationship between GPT integration degree and teacher burnout. (3) The degree of GPT integration degree exerts an indirect and orderly negative influence on teacher burnout through behavioral engagement and classroom atmosphere. The objective of this study is to further enhance our comprehension of the utilization of GPT technology in education and to provide strategic recommendations for its advancement in educational practice.