A model for diagnosing and preventing burnout in inclusive education teachers with elements of artificial intelligence

Perizat Zhaksylykovna Parmankulova

Frontiers in Education, 2026

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DOI 10.3389/feduc.2026.1861982
Data confidence 70 medium
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Abstract

Introduction In the era of the rapid development of artificial intelligence, the problem of teacher burnout is taking on new substantive characteristics. Ignoring teacher burnout will ultimately negatively impact the quality of education. Therefore, the development of effective teacher support measures is crucial for the development of the education system in Kazakhstan. The aim of this study is to develop a structural and substantive model with elements of artificial intelligence for diagnosing and preventing burnout in teachers working in inclusive education settings. Methods This article presents a study and assessment of the level of professional burnout among teachers at higher education institutions, colleges, and general secondary schools in Shymkent. The sample consisted of 200 teachers, of whom 84% were women ( n = 168) and 16% were men ( n = 32), reflecting the gender imbalance characteristic of the teaching profession in Kazakhstan. Results The mean total score M = 28.13 (SD = 9.01), which corresponds to a high level of burnout and exceeds the threshold used for diagnosis. Analysis of the distribution by levels revealed a pronounced asymmetry towards high values: 74.0% of teachers ( n = 148) demonstrated a high level of professional burnout, 24.5% ( n = 49) - moderate, and only 1.5% ( n = 3) - low. Overall, the analysis confirms that the used diagnostic scale has satisfactory characteristics ( α > 0.80) and can be used in further studies of the professional well-being of teachers in inclusive education. Discussion The proposed structural and substantive model is aimed at diagnosing and preventing teacher burnout in inclusive education settings. A SWOT analysis was conducted to assess the internal and external factors involved in implementing the developed model. A comprehensive architecture for an intelligent chatbot was developed, enabling automated screening, forecasting, and personalized recommendation processes. The integration of artificial intelligence tools and digital platforms opens up new possibilities for preventing personalized professional burnout. A specialized training course, “Preventing Teacher Burnout in Inclusive Education”, was developed. The proposed model demonstrated the effectiveness of a comprehensive approach to preventing teacher burnout.