Teacher job satisfaction in post-conflict developing countries: The case of Bosnia and Herzegovina

BackgroundTeacher job satisfaction is an important component of educational quality and professional well-being. In post-conflict and post-socialist developing countries such as Bosnia and Herzegovina, socio-economic challenges and limited resources may shape teachers' professional experiences, while empirical evidence from such contexts remains limited.ObjectivesThis study aimed to develop a predictive model of teacher job satisfaction using artificial neural networks (ANN) and to identify variables with the greatest predictive relevance for reported job satisfaction among teachers in Bosnia and Herzegovina.MethodA cross-sectional study was conducted with 1024 primary and secondary school teachers in the Republic of Srpska. Data were collected using questionnaires assessing job satisfaction, sociodemographic characteristics, burnout, professional stress, working conditions, self-efficacy, and life satisfaction. The ANN model was applied to examine nonlinear patterns and predict reported job satisfaction.ResultsThe ANN model achieved 86.7% accuracy. Life satisfaction demonstrated the highest predictive importance, followed by salary satisfaction, decision-making autonomy, and overall workplace burnout. Satisfaction with student progress and work-related stress also showed relevant predictive contributions, whereas sociodemographic variables demonstrated comparatively lower predictive importance.ConclusionThis study demonstrates the potential of ANN and explainable predictive modelling for examining patterns associated with teacher job satisfaction in a post-conflict and post-socialist educational context. The findings suggest that reported job satisfaction is associated with interconnected psychosocial and organizational factors rather than a single workplace characteristic. The study contributes to a more inclusive understanding of teacher occupational well-being and provides context-sensitive evidence that may inform future research and policy discussions in similar settings.