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Qian, Xiaoyu; Nandakumar, Ratna; Glutting, Joseoph; Ford, Danielle; Fifield, Steve – ETS Research Report Series, 2017
In this study, we investigated gender and minority achievement gaps on 8th-grade science items employing a multilevel item response methodology. Both gaps were wider on physics and earth science items than on biology and chemistry items. Larger gender gaps were found on items with specific topics favoring male students than other items, for…
Descriptors: Item Analysis, Gender Differences, Achievement Gap, Grade 8
Almond, Russell G.; Mulder, Joris; Hemat, Lisa A.; Yan, Duanli – ETS Research Report Series, 2006
Bayesian network models offer a large degree of flexibility for modeling dependence among observables (item outcome variables) from the same task that may be dependent. This paper explores four design patterns for modeling locally dependent observations from the same task: (1) No context--Ignore dependence among observables; (2) Compensatory…
Descriptors: Bayesian Statistics, Networks, Models, Design
Hartz, Sarah; Roussos, Louis – ETS Research Report Series, 2008
This paper presents the development of the fusion model skills diagnosis system (fusion model system), which can help integrate standardized testing into the learning process with both skills-level examinee parameters for modeling examinee skill mastery and skills-level item parameters, giving information about the diagnostic power of the test.…
Descriptors: Skill Development, Educational Diagnosis, Theory Practice Relationship, Standardized Tests
Wang, Xiaohui; Bradlow, Eric T.; Wainer, Howard – ETS Research Report Series, 2005
SCORIGHT is a very general computer program for scoring tests. It models tests that are made up of dichotomously or polytomously rated items or any kind of combination of the two through the use of a generalized item response theory (IRT) formulation. The items can be presented independently or grouped into clumps of allied items (testlets) or in…
Descriptors: Computer Assisted Testing, Statistical Analysis, Test Items, Bayesian Statistics
Johnson, Matthew S.; Jenkins, Frank – ETS Research Report Series, 2005
Large-scale educational assessments such as the National Assessment of Educational Progress (NAEP) sample examinees to whom an exam will be administered. In most situations the sampling design is not a simple random sample and must be accounted for in the estimating model. After reviewing the current operational estimation procedure for NAEP, this…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, National Competency Tests, Sampling