Meta-Analytic Structural Equation Modeling in Educational Measurement
'Science cannot progress without reliable and accurate measurement of what it is you are trying to study. The key is measurement, simple as that.' —Robert D. Hare (Criminal Psychologist and Developer of the famous ‘Hare Psychopathy Checklist’) Photo: Štefan Štefančík
About the project
Measurement matters. Indeed, the measurement of skills and learning processes is at the heart of educational measurement. This includes gathering evidence for the reliability and validity of measures or, more precisely, the resultant scores. This project takes a meta-analytic perspective on educational measurement, as it describes the measurement of constructs and educational processes based on meta-analytic datasets.
Example: Technology Acceptance Model
One of the projects examines the adequacy and explanatory value of the Technology Acceptance Model (TAM) for teachers’ integration of technology in classrooms. The TAM comprises factors that could determine the behavioral intention and the use of technology for educational purposes. Given the diverse findings on the strengths of associations and the existence of indirect rather than direct effects within the TAM, this meta-analysis is aimed at synthesizing and systematizing the existing body of literature.
The project takes the recently developed correlation- and parameter-based approaches of meta-analytic structural equation modeling (MASEM), and examines the adequacy of theory-implied structural equation models that are designed to gather validity evidence of measures, scores, and models. These approaches synthesize correlation matrices across studies and thus provide more accurate model parameters than approaches using aggregated, single correlations.
Please find more information on the project’s ResearchGate page (external link).