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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
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
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
Becker, Betsy Jane – 1986
This paper discusses distribution theory and power computations for four common "tests of combined significance." These tests are calculated using one-sided sample probabilities or p values from independent studies (or hypothesis tests), and provide an overall significance level for the series of results. Noncentral asymptotic sampling…
Descriptors: Achievement Tests, Correlation, Effect Size, Hypothesis Testing