Although generalizability theory (GT) designs typically are analyzed using analysis of variance (ANOVA) procedures, they also can be integrated into structural equation models (SEMs). In this tutorial, we review basic concepts for conducting univariate and multivariate GT analyses and demonstrate advantages of doing such analyses within SEM…

Traditional statistical model evaluation typically relies on goodness-of-fit testing and quantifying model complexity by counting parameters. Both of these practices may result in overfitting and have thereby contributed to the generalizability crisis. The information-theoretic principle of minimum description length addresses both of these…

Educational reform priorities such as emphasis on quantitative modelling (QM) have positioned undergraduate biology instructors as designers of QM experiences to engage students in authentic science practices that support the development of data-driven and evidence-based reasoning. Yet, little is known about how biology instructors adapt to the…

This paper aims to unsettle assumptions of generalizability and representativeness in quantitative research using queer framings and positionalities. We argue that generalizability and representativeness are tools of supremacist dominance that reinforce harmful and essentialist categories of identities for the false purpose of statistical…

Likert-type item is the most popular response format for collecting data in social, educational, and psychological studies through scales or questionnaires. However, there is no consensus on whether parametric or non-parametric tests should be preferred when analyzing Likert-type data. This study examined the statistical power of parametric and…

Students often believe that statistical significance is the only determinant of whether a quantitative result is "important." In this paper, I review traditional null hypothesis statistical testing to identify what questions inferential statistics can and cannot answer, including statistical significance, effect size and direction,…

Both school and district administrators use the results of standardized, large-scale tests to inform decisions about the need for, or success of, educational programs and interventions. However, test results at the school level are subject to random fluctuations due to changes in cohort, test items, and other factors outside of the school's…

Under the generalizability-theory (G-theory) framework, the estimation precision of variance components (VCs) is of significant importance in that they serve as the foundation of estimating reliability. Zhang and Lin advanced the discussion of nonadditivity in data from a theoretical perspective and showed the adverse effects of nonadditivity on…

Generalizability theory is a modern, powerful, and broad framework used to assess the reliability, or dependability, of measurements. While there exist classic works that explain the basic concepts and mathematical foundations of the method, there is currently a lack of resources addressing computational resources for those researchers wishing to…

The 0.70 and 0.80 reliability standards, proposed by Jum Nunnally, are widely employed across a spectrum of research domains. Nonetheless, due to their arbitrary nature, both standards fail to satisfy the needs of researchers. This paper presents a set of formulas that can be used to compute minimum reliability standards as a function of a…

Research Findings: We evaluated the score stability of the Mathematical Quality of Instruction (MQI), an observational measure of mathematics instruction. Three raters each scored, independently, 100 video-recorded lessons taught by 20 kindergarten teachers in the spring. Using generalizability theory analyses, we decomposed the MQI's score…

Purpose of the Study: Missing data are a common problem encountered while implementing measurement instruments. Yet the extent to which reliability, validity, average discrimination and difficulty of the test results are affected by the missing data has not been studied much. Since it is inevitable that missing data have an impact on the…

To meet recent accountability mandates, school districts are implementing assessment frameworks to document teachers' effectiveness. Observational assessments play a key role in this process, albeit without compelling evidence of their psychometric rigor. Using a sample of kindergarten teachers, we employed Generalizability theory to investigate…

Rubrics are widely used in higher education to assess performance in project-based learning environments. To date, the sources of error that may affect their reliability have not been studied in depth. Using generalisability theory as its starting-point, this article analyses the influence of the assessors and the criteria of the rubrics on the…

The aim of this study is to develop a scoring rubric to assess primary school students' problem posing skills. The rubric including five dimensions namely solvability, reasonability, mathematical structure, context and language was used. The raters scored the students' problem posing skills both with and without the scoring rubric to test the…