This research examines the relationships between first-year college students' attendance at campus-sponsored extracurricular events and grade point average, persistence from fall to spring, and retention to the second year. Students' attendance at various campus life events over the course of an academic year was tracked by scanning students'…

The purpose of the current study was to investigate both studentlevel and school-level factors influencing reading literacy of students in Turkey by using PISA 2018 data. The study focused on reading literacy since the main subject of PISA 2018 was selected as reading literacy. The design of the study is a correlational research examining the…

Among current state-of-art estimation methods for multilevel IRT models, the two-stage divide-and-conquer strategy has practical advantages, such as clearer definition of factors, convenience for secondary data analysis, convenience for model calibration and fit evaluation, and avoidance of improper solutions. However, various studies have shown…

This article presents a latent class model for multilevel data to identify latent subgroups and estimate heterogeneous treatment effects. Unlike sequential approaches that partition data first and then estimate average treatment effects (ATEs) within classes, we employ a Bayesian procedure to jointly estimate mixing probability, selection, and…

Due to the increased use of scientific models and modelling in K-12 education, there is a need to uncover its effects on students over time. Prior research has shown that the use of scientific modelling in K-12 classes is associated with improved conceptual knowledge and problem-solving skills. However, few studies have explicitly tested the…

Multilevel modeling is a statistical approach to analyze hierarchical data, which consist of individual observations nested within clusters. Bayesian methods is a well-known, sometimes better, alternative of Maximum likelihood methods for fitting multilevel models. Lack of user-friendly and computationally efficient software packages or programs…

School effectiveness is a topic of interest addressed by numerous research projects focused on clarifying which variables contribute to the explanation of educational performance. This research aims to find out to what extent social, cultural, and academic variables at the student and school levels, as perceived by families, influence performance,…

In line with assumptions made by the control-value theory of academic emotions, it was hypothesized that the association between the classroom social environment, in terms of students' perceptions of their teachers' interpersonal behaviour, and students' academic emotions was partially mediated by students' achievement goals. The present study…

Many national and international educational data collection programs offer researchers opportunities to investigate contextual effects related to student performance. In those programs, schools are often used in the first-stage sampling process and students are randomly drawn from selected schools. However, the "incidental" dependence of…

Lord's Paradox occurs when a continuous covariate is statistically controlled for and the relationship between a continuous outcome and group status indicator changes in both magnitude and direction. This phenomenon poses a challenge to the notion of evidence-based policy, where data are supposed to be self-evident. We examined 50 effect size…

As the economic landscape changes, a college degree has become increasingly necessary for securing employment in an information-based society. Student engagement is an important factor in predicting and preventing high school dropout, and improving student outcomes. Although the relationship between secondary school engagement and high school…

Most college students work for pay while enrolled, however theoretical and methodological concerns with the extant literature make it nearly impossible to understand how employment affects students. Responding to those shortcomings, I designed a validation study with robust statistical methods to examine relationships between student employment…

The methodology of single-case experimental designs (SCED) has been expanding its efforts toward rigorous design tactics to address a variety of research questions related to intervention effectiveness. Effect size indicators appropriate to quantify the magnitude and the direction of interventions have been recommended and intensively studied for…

Intersectional approaches have become increasingly important for explaining educational inequalities because they help to improve our understanding of how individual experiences are shaped by simultaneous membership in multiple social categories that are associated with interconnected systems of power, privilege, and oppression. For years, there…

This study used a propensity score approach to estimate treatment effects in a multilevel setting. The propensity score approach involves the estimation of propensity scores for covariate balancing and the estimation of treatment effects. This study aimed at understanding how propensity scores estimated through a simple logistic regression compare…