Given the complex nature of teachers' professional development (PD) processes, it is crucial to examine how various factors surrounding teachers are associated with the evaluation of their PD experience. By applying a machine-learning technique, least absolute shrinkage and selection operator (LASSO), we were able to include numerous factors in an…

Teacher shortages and attrition are problems of international concern. One of the most frequent reasons for teachers leaving the profession is a lack of job satisfaction. Accordingly, in this study we have adopted a causal inference machine learning approach to identify practical interventions for improving overall levels of job satisfaction. We…

In the ongoing endeavour to increase student learning, restructuring schools into professional learning communities (PLCs) remains a popular strategy globally. Multiple studies have investigated positive outcomes associated with PLCs for students and teachers, but limited knowledge exists about factors associated with well-functioning PLCs, such…

Effective teaching practices are essential for enhancing classroom instruction and student learning. However, a comprehensive understanding of the factors influencing teachers' instructional practices remains elusive. This study employs machine learning (ML) to identify the most significant predictors influencing the instructional practices of…