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No Child Left Behind Act 20011
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Sijia Huang; Dubravka Svetina Valdivia – Educational and Psychological Measurement, 2024
Identifying items with differential item functioning (DIF) in an assessment is a crucial step for achieving equitable measurement. One critical issue that has not been fully addressed with existing studies is how DIF items can be detected when data are multilevel. In the present study, we introduced a Lord's Wald X[superscript 2] test-based…
Descriptors: Item Analysis, Item Response Theory, Algorithms, Accuracy
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Albano, Anthony D.; Cai, Liuhan; Lease, Erin M.; McConnell, Scott R. – Journal of Educational Measurement, 2019
Studies have shown that item difficulty can vary significantly based on the context of an item within a test form. In particular, item position may be associated with practice and fatigue effects that influence item parameter estimation. The purpose of this research was to examine the relevance of item position specifically for assessments used in…
Descriptors: Test Items, Computer Assisted Testing, Item Analysis, Difficulty Level
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Aydin, Burak; Leite, Walter L.; Algina, James – Educational and Psychological Measurement, 2016
We investigated methods of including covariates in two-level models for cluster randomized trials to increase power to detect the treatment effect. We compared multilevel models that included either an observed cluster mean or a latent cluster mean as a covariate, as well as the effect of including Level 1 deviation scores in the model. A Monte…
Descriptors: Error of Measurement, Predictor Variables, Randomized Controlled Trials, Experimental Groups
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Mohr-Schroeder, Margaret; Ronau, Robert N.; Peters, Susan; Lee, Carl W.; Bush, William S. – Journal for Research in Mathematics Education, 2017
This article describes the development and validation of two forms of the Geometry Assessments for Secondary Teachers (GAST), which were designed to assess teachers' knowledge for teaching geometry. Both forms were developed by teams of mathematicians, mathematics educators, psychometricians, and secondary classroom geometry teachers. Predictive…
Descriptors: Predictor Variables, Academic Achievement, Mathematics Instruction, Geometry
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Adams, Raymond J.; Lietz, Petra; Berezner, Alla – Large-scale Assessments in Education, 2013
Background: While rotated test booklets have been employed in large-scale assessments to increase the content coverage of the assessments, rotation has not yet been applied to the context questionnaires administered to respondents. Methods: This paper describes the development of a methodology that uses rotated context questionnaires in…
Descriptors: Questionnaires, Item Response Theory, Foreign Countries, Achievement Tests
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Lee, Jaekyung; Liu, Xiaoyan; Amo, Laura Casey; Wang, Weichun Leilani – Educational Policy, 2014
Drawing on national and state assessment datasets in reading and math, this study tested "external" versus "internal" standards-based education models. The goal was to understand whether and how student performance standards work in multilayered school systems under No Child Left Behind Act of 2001 (NCLB). Under the…
Descriptors: State Standards, Academic Standards, Student Evaluation, Academic Achievement
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Jiao, Hong; Wang, Shudong; He, Wei – Journal of Educational Measurement, 2013
This study demonstrated the equivalence between the Rasch testlet model and the three-level one-parameter testlet model and explored the Markov Chain Monte Carlo (MCMC) method for model parameter estimation in WINBUGS. The estimation accuracy from the MCMC method was compared with those from the marginalized maximum likelihood estimation (MMLE)…
Descriptors: Computation, Item Response Theory, Models, Monte Carlo Methods
Jeon, Minjeong – ProQuest LLC, 2012
Maximum likelihood (ML) estimation of generalized linear mixed models (GLMMs) is technically challenging because of the intractable likelihoods that involve high dimensional integrations over random effects. The problem is magnified when the random effects have a crossed design and thus the data cannot be reduced to small independent clusters. A…
Descriptors: Hierarchical Linear Modeling, Computation, Measurement, Maximum Likelihood Statistics
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Huang, Hung-Yu; Wang, Wen-Chung – Educational and Psychological Measurement, 2014
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
Descriptors: Item Response Theory, Hierarchical Linear Modeling, Computation, Test Reliability
Thomas, Matthew – ProQuest LLC, 2013
This dissertation examines the relationship between an instructional style called Interactive-Engagement (IE) and gains on a measure of conceptual knowledge called the Calculus Concept Inventory (CCI). The data comes from two semesters of introductory calculus courses (Fall 2010 and Spring 2011), consisting of a total of 482 students from the…
Descriptors: Introductory Courses, Calculus, Mathematics Instruction, Teaching Styles
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Yen, Wendy M.; Lall, Venessa F.; Monfils, Lora – ETS Research Report Series, 2012
Alternatives to vertical scales are compared for measuring longitudinal academic growth and for producing school-level growth measures. The alternatives examined were empirical cross-grade regression, ordinary least squares and logistic regression, and multilevel models. The student data used for the comparisons were Arabic Grades 4 to 10 in…
Descriptors: Foreign Countries, Scaling, Item Response Theory, Test Interpretation
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von Davier, Matthias – ETS Research Report Series, 2007
This paper introduces multilevel extensions for the general diagnostic model (GDM) following recent developments on extensions of latent class analysis (LCA) to hierarchical models. The GDM is based on LCA as well as discrete latent trait models and may be viewed as a general modeling framework for conrmatory multidimensional item response models.…
Descriptors: Multivariate Analysis, Models, Item Response Theory, Probability