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van der Linden, Wim J. – Journal of Educational and Behavioral Statistics, 2022
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…
Descriptors: Equated Scores, Test Items, Scores, Probability
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Cristan Farmer; Aaron J. Kaat; Michael C. Edwards; Luc Lecavalier – American Journal on Intellectual and Developmental Disabilities, 2024
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…
Descriptors: Measurement, Psychometrics, Scores, Intellectual Disability
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Deborah J. Harris – Educational Measurement: Issues and Practice, 2024
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…
Descriptors: Scores, Comparative Analysis, Speeches, Career Development
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Ke-Hai Yuan; Zhiyong Zhang – Grantee Submission, 2022
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…
Descriptors: Psychometrics, Structural Equation Models, Scores, Least Squares Statistics
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Shao, Lucy; Levine, Richard A.; Guarcello, Maureen A.; Wilke, Morten C.; Stronach, Jeanne; Frazee, James P.; Fan, Juanjuan – International Journal of Artificial Intelligence in Education, 2023
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…
Descriptors: Statistical Bias, Probability, Scores, Weighted Scores
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Ercikan, Kadriye; McCaffrey, Daniel F. – Journal of Educational Measurement, 2022
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…
Descriptors: Artificial Intelligence, Automation, Scores, Educational Assessment
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Sinharay, Sandip – Journal of Educational Measurement, 2023
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,…
Descriptors: Evaluation Methods, Scores, Standardized Tests, Simulation
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Wolkowitz, Amanda A.; Foley, Brett; Zurn, Jared – Practical Assessment, Research & Evaluation, 2023
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…
Descriptors: Multiple Choice Tests, Test Items, Accuracy, Test Format
Heather J. Hough; Belen Chavez – Policy Analysis for California Education, PACE, 2024
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…
Descriptors: COVID-19, Pandemics, Scores, Grade 3
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Paul T. von Hippel – Education Next, 2024
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…
Descriptors: Tutoring, Academic Achievement, Educational Experiments, Tests
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Foster, Colin – International Journal of Research & Method in Education, 2023
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.…
Descriptors: Effect Size, Intervention, Bias, Randomized Controlled Trials
Paul T. von Hippel – Annenberg Institute for School Reform at Brown University, 2023
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…
Descriptors: Testing Problems, Scores, Educational Research, Longitudinal Studies
Stéphane Lavertu – Thomas B. Fordham Institute, 2024
For more than twenty-five years, public charter schools have served Ohio families and communities by providing quality educational options beyond the local school district. But it's no secret that we've also had a long-standing debate over whether increasing school choice impacts students who remain in traditional districts. In important--and…
Descriptors: Charter Schools, School Choice, Graduation Rate, Attendance Patterns
Heckman, James J.; Zhou, Jin – National Bureau of Economic Research, 2022
Empirical studies in the economics of education, the measurement of skill gaps, the impacts of interventions on skill formation, and the value-added literature rely on psychometrically validated test scores. Test scores are taken as measures of an invariant scale of human capital compared over time and people. We examine if conventional skill…
Descriptors: Scores, Mastery Learning, Measures (Individuals), Testing
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Andrew D. Ho – Journal of Educational and Behavioral Statistics, 2024
I review opportunities and threats that widely accessible Artificial Intelligence (AI)-powered services present for educational statistics and measurement. Algorithmic and computational advances continue to improve approaches to item generation, scale maintenance, test security, test scoring, and score reporting. Predictable misuses of AI for…
Descriptors: Artificial Intelligence, Measurement, Educational Assessment, Technology Uses in Education
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