Schools conduct comprehensive psychoeducational evaluations to identify students with specific learning disabilities (SLDs) and determine whether they qualify for special education services. This decision-making process is complex and research has documented many factors influencing SLD identification decisions. One such factor may be…

Purpose: The purpose of this study is to propose and explore a conceptualization of decisional capital that is suitable for early career teachers. Design/methodology/approach: This study uses exploratory factor analysis on a sample of early career teachers to examine a literature-derived conceptualization of decisional capital. Findings: The…

In this study, the factorial invariance of the ASIS (Anadolu-Sak Intelligence Scale) was examined across time. Data were obtained from there groups of first-grade students who were administered the ASIS in 2020, 2021, and 2022. The analyses were conducted using multisample confirmatory factor analyses. Factorial invariance was tested with six…

In this study, the extent to wording effects impact structure and factor loadings, internal consistency and measurement invariance was outlined. The modified form, which includes items that semantically reversed, explains %21.5 more variance than the original form. Also, reversed items' factor loadings are higher. As a result of CFA, indexes…

Based on previous research, it can be assumed that teachers' self-efficacy (TSE) varies across situations, domains and individual students' behaviors confronting teachers with particularly challenging tasks. The construct of student-specific TSE is considered informative theoretical basis for understanding the relationship between…

Bayesian methods to infer model dimensionality in factor analysis generally assume a lower triangular structure for the factor loadings matrix. Consequently, the ordering of the outcomes influences the results. Therefore, we propose a method to infer model dimensionality without imposing any prior restriction on the loadings matrix. Our approach…

Compared to traditional confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM) has been shown to result in less structural parameter bias when cross-loadings (CLs) are present. However, when model fit is reasonable for CFA (over ESEM), CFA should be preferred on the basis of parsimony. Using simulations, the current…

Matrix decomposition structural equation modeling (MDSEM) is introduced as a novel approach in structural equation modeling, contrasting with traditional structural equation modeling (SEM). MDSEM approximates the data matrix using a model generated by the hypothetical model and addresses limitations faced by conventional SEM procedures by…

Context is considered to greatly impact student engagement. However, little is known about the association between students' situational engagement in a particular lesson and their overall engagement with school and learning over time. The current study aims to validate the InSitu measure of situational engagement in a Norwegian context and to…

In this exploratory study, we adapted items from a previously developed measure of job satisfaction, the Measure of Job Satisfaction (MJS), an instrument first developed for use with community nurses in the UK, to create a brief, 15-item instrument (Job Satisfaction--Brief) applicable to practitioners of school psychology from Pennsylvania (N =…

In confirmatory factor analysis (CFA), model parameters are usually estimated by iteratively minimizing the Maximum Likelihood (ML) fit function. In optimal circumstances, the ML estimator yields the desirable statistical properties of asymptotic unbiasedness, efficiency, normality, and consistency. In practice, however, real-life data tend to be…

Academic engagement plays a crucial role in students' learning and performance. One of the most popular measures for assessing this construct is the Utrecht Work Engagement Scale for Students (UWES-S), which is based on a tridimensional conceptualization consisting of dedication, vigor, and absorption. However, prior research on its factor…

The KeyMath-3 Diagnostic Assessment (KM-3) is an individually-administered math assessment used in educational placement and diagnostic decisions. It includes 10 subtests making up Basic Concepts, Operations, and Applications indexes and a "Total Test" composite that measures overall math ability. Here, covariances among subtests from…

Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…

Executive function (EF) is frequently an area of vulnerability in conditions associated with intellectual disability, like Down syndrome (DS). However, current EF evaluation approaches are not designed for children with underlying neurodevelopmental conditions and may not demonstrate construct validity due to interpretational confounds. The…