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…

Conventional methods for evaluating the utility of subscores rely on traditional indices of reliability and on correlations among subscores. One limitation of correlational methods is that they do not explicitly consider variation in subtest means. An exception is an index of score profile reliability designated as [G], which quantifies the ratio…

The use of Bayesian Knowledge Tracing (BKT) models in predicting student learning and mastery, especially in mathematics, is a well-established and proven approach in learning analytics. In this work, we report on our analysis examining the generalizability of BKT models across academic years attributed to "detector rot." We compare the…

We illustrate how to analyze complete generalizability theory (GT) designs using structural equation modeling software ("lavaan" in R), compare results to those obtained from numerous ANOVA-based packages, and apply those results in practical ways using data obtained from a large sample of respondents, who completed the Self-Perception…

Estimation of causal effects requires making comparisons across groups of observations exposed and not exposed to a a treatment or cause (intervention, program, drug, etc). To interpret differences between groups causally we need to ensure that they have been constructed in such a way that the comparisons are "fair." This can be…

The agreement between raters is examined within the scope of the concept of "inter-rater reliability". Although there are clear definitions of the concepts of agreement between raters and reliability between raters, there is no clear information about the conditions under which agreement and reliability level methods are appropriate to…

Conceptual replications have received increased coverage in the educational research agenda. This article argues for clarity in, and justification of, the definition, scope, and boundaries of a conceptual replication and what it can and cannot do. It argues for clear justifications when changing components from those of the original study. The…

Estimates of various variance components, universe score variance, measurement error variances, and generalizability coefficients, like all statistics, are subject to sampling variability, particularly in small samples. Such variability is quantified traditionally through estimated standard errors and/or confidence intervals. The paper derived new…

This study utilizes an analysis of diminishing returns to examine the relationship between sample size and item parameter estimation precision when utilizing the Masters' Partial Credit Model for polytomous items. Item data from the standardization of the Batelle Developmental Inventory, 3rd Edition were used. Each item was scored with a…

This article introduces generalizability theory (G-theory) to institutional research and assessment practitioners, and explains how it can be utilized to evaluate the reliability of assessment procedures in order to improve student learning outcomes. The fundamental concepts associated with G-theory are briefly discussed, followed by a discussion…

The present study attempted to to investigate factors which affect EFL writing scores through using generalizability theory (G-theory). To this purpose, one hundred and twenty students participated in one independent and one integrated writing tasks. Proceeding, their performances were scored by six raters: one self-rating, three peers,-rating and…

We conducted a meta-analysis on the most commonly used forensic polygraph test, the Comparison Question Test. We captured as many studies as possible by using broad inclusion criteria. Data and potential moderators were coded from 138 datasets. The meta-analytic effect size including inconclusive outcomes was 0.69 [0.66, 0.79]. We found…

Although originally conceived of as a marriage of direct behavioral observation and indirect behavior rating scales, recent research has indicated that Direct Behavior Ratings (DBRs) are affected by rater idiosyncrasies (rater effects) similar to other indirect forms of behavioral assessment. Most of this research has been conducted using…

Computational thinking (CT) is a fundamental ability for learners in today's society. Although CT assessments and interventions have been studied widely, little is known about CT predictions. This study predicted students' CT achievement in the ICILS 2018 using five machine learning models. These models were trained on the data from five European…

Current student-centred, multilingual, active teaching methodologies require that teachers have continuous access to texts that are adequate in terms of topic and language competence. However, the task of finding appropriate materials is arduous and time consuming for teachers. To build on automatic readability assessment research that could help…