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Özmen, Zeynep Medine; Güven, Bülent – Journal of Pedagogical Research, 2022
The present study aimed to remediate pre-service teachers' misconceptions about sampling distributions and to develop their conceptual understanding through the use of conceptual change texts (CCTs). The participants consisted of 84 pre-service teachers. To determine the pre-service teachers' conceptual understanding of sampling distributions, an…
Descriptors: Preservice Teachers, Mathematics Teachers, Sampling, Statistical Distributions
Xiao, Leifeng; Hau, Kit-Tai – Educational and Psychological Measurement, 2023
We examined the performance of coefficient alpha and its potential competitors (ordinal alpha, omega total, Revelle's omega total [omega RT], omega hierarchical [omega h], greatest lower bound [GLB], and coefficient "H") with continuous and discrete data having different types of non-normality. Results showed the estimation bias was…
Descriptors: Statistical Bias, Statistical Analysis, Likert Scales, Statistical Distributions
Jia-qi Zheng; Kwok-cheung Cheung; Pou-seong Sit – Scandinavian Journal of Educational Research, 2024
Several international large-scale assessments were conducted at the turn of the new century, and during the past two decades the Programme for International Student Assessment (PISA) completed seven cycles of assessment to facilitate practitioners' policy debates and governance. This study reviews PISA-related articles published in English and…
Descriptors: Achievement Tests, Foreign Countries, Secondary School Students, International Assessment
Shear, Benjamin R.; Reardon, Sean F. – Journal of Educational and Behavioral Statistics, 2021
This article describes an extension to the use of heteroskedastic ordered probit (HETOP) models to estimate latent distributional parameters from grouped, ordered-categorical data by pooling across multiple waves of data. We illustrate the method with aggregate proficiency data reporting the number of students in schools or districts scoring in…
Descriptors: Statistical Analysis, Computation, Regression (Statistics), Sample Size
Liqun Yin; Ummugul Bezirhan; Matthias von Davier – International Electronic Journal of Elementary Education, 2025
This paper introduces an approach that uses latent class analysis to identify cut scores (LCA-CS) and categorize respondents based on context scales derived from largescale assessments like PIRLS, TIMSS, and NAEP. Context scales use Likert scale items to measure latent constructs of interest and classify respondents into meaningful ordered…
Descriptors: Multivariate Analysis, Cutting Scores, Achievement Tests, Foreign Countries
Giada Spaccapanico Proietti; Mariagiulia Matteucci; Stefania Mignani; Bernard P. Veldkamp – Journal of Educational and Behavioral Statistics, 2024
Classical automated test assembly (ATA) methods assume fixed and known coefficients for the constraints and the objective function. This hypothesis is not true for the estimates of item response theory parameters, which are crucial elements in test assembly classical models. To account for uncertainty in ATA, we propose a chance-constrained…
Descriptors: Automation, Computer Assisted Testing, Ambiguity (Context), Item Response Theory
Qiao, Xin; Jiao, Hong; He, Qiwei – Journal of Educational Measurement, 2023
Multiple group modeling is one of the methods to address the measurement noninvariance issue. Traditional studies on multiple group modeling have mainly focused on item responses. In computer-based assessments, joint modeling of response times and action counts with item responses helps estimate the latent speed and action levels in addition to…
Descriptors: Multivariate Analysis, Models, Item Response Theory, Statistical Distributions
Shear, Benjamin R.; Reardon, Sean F. – Stanford Center for Education Policy Analysis, 2019
This paper describes a method for pooling grouped, ordered-categorical data across multiple waves to improve small-sample heteroskedastic ordered probit (HETOP) estimates of latent distributional parameters. We illustrate the method with aggregate proficiency data reporting the number of students in schools or districts scoring in each of a small…
Descriptors: Computation, Scores, Statistical Distributions, Sample Size
Karadavut, Tugba; Cohen, Allan S.; Kim, Seock-Ho – Measurement: Interdisciplinary Research and Perspectives, 2020
Mixture Rasch (MixRasch) models conventionally assume normal distributions for latent ability. Previous research has shown that the assumption of normality is often unmet in educational and psychological measurement. When normality is assumed, asymmetry in the actual latent ability distribution has been shown to result in extraction of spurious…
Descriptors: Item Response Theory, Ability, Statistical Distributions, Sample Size
Tong, Xin; Zhang, Zhiyong – Grantee Submission, 2020
Despite broad applications of growth curve models, few studies have dealt with a practical issue -- nonnormality of data. Previous studies have used Student's "t" distributions to remedy the nonnormal problems. In this study, robust distributional growth curve models are proposed from a semiparametric Bayesian perspective, in which…
Descriptors: Robustness (Statistics), Bayesian Statistics, Models, Error of Measurement
Kastberg, David; Murray, Gordon; Ferraro, David; Arieira, Carlos; Roey, Shep; Mamedova, Saida; Liao, Yuqi – National Center for Education Statistics, 2021
The Program for International Student Assessment Young Adult Follow-up Study (PISA YAFS) is a follow-up study with students who participated in PISA 2012 in the United States. The study is designed to measure how performance on PISA 2012 relates to subsequent measures of outcomes and skills of young adults on an online assessment, Education and…
Descriptors: Foreign Countries, Achievement Tests, Secondary School Students, Young Adults
Walzebug, Anke; Kasper, Daniel – Assessment in Education: Principles, Policy & Practice, 2018
In "Progress in International Reading Literacy Study" (PIRLS) educational inequalities are measured, amongst others, through the relationship between students' reading achievements and the home resource for learning (HRL) scale. By applying the partial credit model and using the WLE estimates for the person parameters it is accepted that…
Descriptors: Grade 4, Achievement Tests, Foreign Countries, International Assessment
Utibe, U. J.; Agwagah, U. N. – Journal of Education and Practice, 2015
This study investigated a decade of candidates' performances in NECO-SSCE mathematics in NIGERIA. A total of 9266459 valid results were collated for the study and analyzed for zones in the country. Already validated results of NECO for 2000 to 2009 were used for the study. Three research questions guided the conduct of the study. Results showed…
Descriptors: Foreign Countries, Mathematics Achievement, Academic Records, Scores
Reardon, Sean F.; Kalogrides, Demetra; Ho, Andrew D. – Stanford Center for Education Policy Analysis, 2017
There is no comprehensive database of U.S. district-level test scores that is comparable across states. We describe and evaluate a method for constructing such a database. First, we estimate linear, reliability-adjusted linking transformations from state test score scales to the scale of the National Assessment of Educational Progress (NAEP). We…
Descriptors: School Districts, Scores, Statistical Distributions, Database Design
Skaggs, Gary; Wilkins, Jesse L. M.; Hein, Serge F. – International Journal of Testing, 2016
The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying…
Descriptors: Achievement Tests, Foreign Countries, Elementary Secondary Education, Science Achievement