There is a need for valid and reliable instruments to assess learning outcomes in education for sustainable development (ESD). Measurement invariance (MI) needs to be established before results of these instruments can be validly compared between groups. Despite its importance, establishing MI is an often overlooked validation step. To provide an…

Confirmatory factor analyses (CFA) are often used in psychological research when developing measurement models for psychological constructs. Evaluating CFA model fit can be quite challenging, as tests for exact model fit may focus on negligible deviances, while fit indices cannot be interpreted absolutely without specifying thresholds or cutoffs.…

Scale errors are intriguing phenomena in which a child tries to perform an object-specific action on a tiny object. Several viewpoints explaining the developmental mechanisms underlying scale errors exist; however, there is no unified account of how different factors interact and affect scale errors, and the statistical approaches used in the…

Educational large-scale assessment (LSA) studies like the program for international student assessment (PISA) provide important information about trends in the performance of educational indicators in cognitive domains. The change in the country means in a cognitive domain like reading between two successive assessments is an example of a trend…

This study examined the false positive (FP) rates and sensitivity of Bayesian fit indices to structural misspecification in Bayesian structural equation modeling. The impact of measurement quality, sample size, model size, the magnitude of misspecified path effect, and the choice or prior on the performance of the fit indices was also…

Previous research on student thinking about experimental measurement and uncertainty has primarily focused on students' procedural reasoning: Given some data, what should students calculate or do next? This approach, however, cannot tell us what beliefs or conceptual understanding leads to students' procedural decisions. To explore this…

Data harmonization is an emerging approach to strategically combining data from multiple independent studies, enabling addressing new research questions that are not answerable by a single contributing study. A fundamental psychometric challenge for data harmonization is to create commensurate measures for the constructs of interest across…

Scientific research is vital for student's education, fostering critical thinking, problem-solving skills, and deepening subject knowledge. To assess students' attitudes towards research, the attitude towards research scale was developed (EACIN). This study addresses three gaps regarding this instrument: inconsistent latent structure, lack of…

Autism screening questionnaires are sometimes used as a measure of "autism-associated traits" in samples drawn from the general population, even though such tools are primarily developed and designed for use in samples of children diagnosed with or being assessed for autism. Here, we explore the psychometric properties of the Social…

Previous research has been limited regarding the measurement of computational thinking, particularly as a learning progression in K-12. This study proposes to apply a multidimensional item response theory (IRT) model to a newly developed measure of computational thinking utilizing both selected response and open-ended polytomous items to establish…