Unveiling the potential of structural equation modelling in educational research: a comparative analysis of Ukrainian teachers' self-efficacy

Abstract

This article delves into the application of structural equation modelling (SEM) methodology within the realm of educational research, enabling researchers to construct comprehensive multidimensional models that elucidate the intricacies of studied phenomena and processes. Based on well-established statistical techniques such as correlation, regression, factor analysis, variance analysis, and covariance analysis, SEM methodology utilizes deductive logic to preliminarily construct a structural model of variable relationships, subsequently tested for consistency with empirical data. This study presents a comprehensive overview of diverse SEM software employed in doctoral training programs across leading global universities, while showcasing a practical example of employing SEM methodology in educational research for training PhD students. An essential aspect of SEM training for specialists involves the careful selection or acquisition of representative and valid datasets. Furthermore, this research examines the Ukrainian teacher's self-efficacy model using SEM methodology and compares the obtained results with data from the internationally renowned Teaching and Learning International Survey (TALIS). The findings underscore the lower self-efficacy levels among Ukrainian teachers, particularly within the student engagement domain, thereby shedding light on crucial aspects of teacher effectiveness and potential areas for improvement.