Bayesian Hierarchical Model for Measuring Adoption Rates in Ethiopian Secondary School Systems

The adoption rates of new agricultural technologies in Ethiopian secondary schools are a critical area for policy makers and educators. A systematic literature review was conducted using academic databases. The focus was on methodologies that use Bayesian hierarchical models to analyse data from Ethiopian secondary schools. The analysis revealed a significant variation (p < 0.05) in adoption rates across different regions and educational sectors, with some schools adopting technologies at a rate of over 70%. Bayesian hierarchical models provide robust estimates for understanding regional differences in technology adoption. Policy makers should consider the regional variability when implementing agricultural technologies to maximise their impact. Bayesian hierarchical model, secondary school systems, Ethiopian agriculture, adoption rates The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.