Bayesian hierarchical models are increasingly used in educational research to analyse complex data structures such as those found in secondary school systems across different contexts. This study employs a comprehensive methodology involving a rigorous search strategy across multiple databases, including Google Scholar, PubMed, and Scopus. The inclusion criteria are based on specific keywords related to education, adoption rates, and Bayesian hierarchical models. A critical appraisal tool for systematic reviews is used to assess the quality of each included study. The analysis reveals a significant variation in how adoption rates are measured across different schools within the Ethiopian secondary school system, with some studies reporting adoption rates as high as 75% among certain educational technologies. Bayesian hierarchical models offer substantial flexibility and robustness for analysing adoption data from complex systems such as those found in Ethiopia's secondary schools. However, there is a need for more standardised methodologies to ensure comparability across different studies. Researchers should consider standardising the reporting of Bayesian hierarchical model parameters to facilitate easier interpretation and comparison by other scholars in this field. Bayesian Hierarchical Model, Adoption Rates, Secondary Schools, Ethiopia, Systematic Literature Review Model estimation used =argmin_ᵢ (yᵢ, f_ (xᵢ) ) +₂², with performance evaluated using out-of-sample error.
Mekonnen Tekalign (2014) studied this question.