A0265
Title: Mentorship and teacher job satisfaction: An econometric meta-analysis using TALIS 2018 data
Authors: Mike Smet - KU Leuven (Belgium) [presenting]
Abstract: The purpose is to fill a gap by concurrently assessing the effects of receiving and providing mentorship on teacher job satisfaction using a large-scale TALIS 2018 dataset comprising 123,299 teachers nested in 8,848 schools across 54 regions. While previous research has primarily focused on the benefits of having a mentor, the dual role of being a mentor has received little attention. Robust regression models are employed with school fixed effects and control for teacher demographics, professional development, and other relevant factors. To account for regional heterogeneity, a meta-analytic framework is further implemented, estimating effect sizes separately by region and aggregating them using both random and fixed effects methods. Results indicate that having a mentor is associated with a positive and statistically significant effect on job satisfaction (overall coefficient = 0.14, I = 0\%), suggesting a robust, uniform benefit across regions. Conversely, providing mentorship yields a similarly positive association (overall coefficient = 0.15) but with moderate heterogeneity (I = 33.6\%), highlighting context-specific variations. Robustness checks and heterogeneity tests (Cochran's Q, tau-squared, and H-squared) support these findings. Novel econometric evidence is provided that both dimensions of mentorship can enhance teacher well-being and retention, offering valuable insights for policy design and future research on educational workforce dynamics.
