The current literature on test equating generally defines it as the process necessary to obtain score comparability between different test forms. The definition is in contrast with Lord's foundational paper which viewed equating as the process required to obtain comparability of measurement scale between forms. The distinction between the notions…

Measurement invariance (MI) is a psychometric property of an instrument indicating the degree to which scores from an instrument are comparable across groups. In recent years, there has been a marked uptick in publications using MI in intellectual and developmental disability (IDD) samples. Our goal here is to provide an overview of why MI is…

This article is based on my 2023 NCME Presidential Address, where I talked a bit about my journey into the profession, and more substantively about comparable scores. Specifically, I discussed some of the different ways 'comparable scores' are defined, highlighted some areas I think we as a profession need to pay more attention to when considering…

Structural equation modeling (SEM) is a widely used technique for studies involving latent constructs. While covariance-based SEM (CB-SEM) permits estimating the regression relationship among latent constructs, the parameters governing this relationship do not apply to that among the scored values of the constructs, which are needed for…

Propensity score matching and weighting methods are applied to balance covariates and reduce selection bias in the analysis of observational study data, and ultimately estimate a treatment effect. We wish to evaluate the impact of a Supplemental Instruction (SI) program on student success in an Introductory Statistics course. In such student…

Artificial-intelligence-based automated scoring is often an afterthought and is considered after assessments have been developed, resulting in nonoptimal possibility of implementing automated scoring solutions. In this article, we provide a review of Artificial intelligence (AI)-based methodologies for scoring in educational assessments. We then…

Technical difficulties and other unforeseen events occasionally lead to incomplete data on educational tests, which necessitates the reporting of imputed scores to some examinees. While there exist several approaches for reporting imputed scores, there is a lack of any guidance on the reporting of the uncertainty of imputed scores. In this paper,…

The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…

The purpose of this study is to introduce a method for converting scored 4-option multiple-choice (MC) items into scored 3-option MC items without re-pretesting the 3-option MC items. This study describes a six-step process for achieving this goal. Data from a professional credentialing exam was used in this study and the method was applied to 24…

In October 2023, the California Department of Education released test scores for all students in Grades 3-8 and 11 for the 2022-23 school year. These results represent an opportunity to analyze whether and to what extent student learning has rebounded after the dramatic declines in scores resulting from the COVID-19 pandemic and related school…

The use of brief dyslexia rating scales is increasing given current dyslexia legislation efforts across the United States. The purpose of this article is to provide an overview of the historical context of the use of brief dyslexia rating scales, strengths, and limitations of using these measures, criteria for selecting these measures, and a…

In a 1984 essay, Benjamin Bloom, an educational psychologist at the University of Chicago, asserted that tutoring offered "the best learning conditions we can devise" and that tutors could raise student achievement by two full standard deviations--or, in statistical parlance, two "sigmas." The influence of Bloom's two-sigma…

This paper introduces a simple, quotient effect size, termed (for 'quotient'), suitable for reporting on the effectiveness of educational interventions. The quotient effect size for a pre-test-post-test design is defined as the gain score (i.e. post-test minus pre-test) for the intervention group, divided by the gain score for the control group.…

Longitudinal studies can produce biased estimates of learning if children miss tests. In an application to summer learning, we illustrate how missing test scores can create an illusion of large summer learning gaps when true gaps are close to zero. We demonstrate two methods that reduce bias by exploiting the correlations between missing and…

Oral reading fluency (ORF) assessments are commonly used to screen at-risk readers and to evaluate the effectiveness of interventions as curriculum-based measurements. As with other assessments, equating ORF scores becomes necessary when we want to compare ORF scores from different test forms. Recently, Kara et al. (2023) proposed a model-based…