Diagnosing emotional burnout in teachers using the burnout assessment tool (BAT) and ai-powered insights

Abstract

This paper examines the use of the Burnout Assessment Tool (BAT) and Artificial Intelligence (AI) technologies to diagnose teachers' emotional burnout. Due to high professional load, teachers often face emotional burnout manifested in exhaustion, detachment and cognitive impairment. The study involved 200 teachers on the basis of JSC “National Professional Development Center ‘Orleu’, Almaty, distributed by gender and age groups, and applied AI technologies, including diagnostic chatbots that monitor the level of burnout in real time.The results of the study confirm that age significantly affects the level of burnout, especially among men, and that higher levels of exhaustion are observed in older age groups. Differences between age groups were statistically insignificant, a trend towards higher levels of burnout among educators with increasing age was revealed.The application of AI has demonstrated its effectiveness in diagnostics, simplifying data collection and providing instant feedback. Integration of AI-methods allows diagnostics to be conducted more accurately and promptly, facilitating the process of monitoring burnout among teachers.Practical significance of the study lies in the development of recommendations for educational institutions on the implementation of AI-methods for diagnosing emotional burnout. The obtained data can be used to create burnout prevention programs aimed at improving the psycho-emotional state of teachers, increasing their professional stability and the quality of the educational process. Implementation of such programs helps to reduce stress level among teachers and create a more favorable working environment in educational organizations.

Keywords: Emotional burnout, Burnout Assessment Tool (BAT), artificial intelligence, teacher well-being, educational psychology.