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Biancarosa, Gina; Kennedy, Patrick C.; Carlson, Sarah E.; Yoon, HyeonJin; Seipel, Ben; Liu, Bowen; Davison, Mark L. – Educational and Psychological Measurement, 2019
Prior research suggests that subscores from a single achievement test seldom add value over a single total score. Such scores typically correspond to subcontent areas in the total content domain, but content subdomains might not provide a sound basis for subscores. Using scores on an inferential reading comprehension test from 625 third, fourth,…
Descriptors: Scores, Scoring, Achievement Tests, Grade 3
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Konstantopoulos, Spyros; Li, Wei; Miller, Shazia R.; van der Ploeg, Arie – Educational and Psychological Measurement, 2016
We use data from a large-scale experiment conducted in Indiana in 2009-2010 to examine the impact of two interim assessment programs (mCLASS and Acuity) across the mathematics and reading achievement distributions. Specifically, we focus on whether the use of interim assessments has a particularly strong effect on improving outcomes for low…
Descriptors: Educational Assessment, Mathematics Achievement, Reading Achievement, Regression (Statistics)
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Williams, Ryan T.; Swanlund, Andrew; Miller, Shazia; Konstantopoulos, Spyros; Eno, Jared; van der Ploeg, Arie; Meyers, Coby – Educational and Psychological Measurement, 2014
This study operationalizes four measures of instructional differentiation: one for Grade 2 English language arts (ELA), one for Grade 2 mathematics, one for Grade 5 ELA, and one for Grade 5 mathematics. Our study evaluates their measurement properties of each measure in a large field experiment: the Indiana Diagnostic Assessment Tools Study, which…
Descriptors: Individualized Instruction, Grade 2, Grade 5, English Instruction
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Magis, David; Facon, Bruno – Educational and Psychological Measurement, 2013
Item purification is an iterative process that is often advocated as improving the identification of items affected by differential item functioning (DIF). With test-score-based DIF detection methods, item purification iteratively removes the items currently flagged as DIF from the test scores to get purified sets of items, unaffected by DIF. The…
Descriptors: Test Bias, Test Items, Statistical Analysis, Error of Measurement
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Skinner, Ellen; Pitzer, Jennifer; Steele, Joel – Educational and Psychological Measurement, 2013
A study was designed to examine a multidimensional measure of children's coping in the academic domain as part of a larger model of motivational resilience. Using items tapping multiple ways of dealing with academic problems, including five adaptive ways (strategizing, help-seeking, comfort-seeking, self-encouragement, and commitment) and six…
Descriptors: Coping, Resilience (Psychology), Student Motivation, Student Adjustment
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Finch, W. Holmes; Hernández Finch, Maria E. – Educational and Psychological Measurement, 2013
The assessment of test data for the presence of differential item functioning (DIF) is a key component of instrument development and validation. Among the many methods that have been used successfully in such analyses is the mixture modeling approach. Using this approach to identify the presence of DIF has been touted as potentially superior for…
Descriptors: Learning Disabilities, Testing Accommodations, Test Bias, Item Response Theory
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Skaggs, Gary; Hein, Serge F. – Educational and Psychological Measurement, 2011
Judgmental standard setting methods have been criticized for the cognitive complexity of the judgment task that panelists are asked to complete. This study compared two methods designed to reduce this complexity: the yes/no method and the single-passage bookmark method. Two mock standard setting panel meetings were convened, one for each method,…
Descriptors: Standard Setting (Scoring), Methods, Cutting Scores, Experienced Teachers
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Palardy, Gregory J. – Educational and Psychological Measurement, 2010
This article examines the multilevel linear crossed random effects growth model for estimating teacher and school effects from repeated measurements of student achievement. Results suggest that even a small degree of unmodeled nonlinearity can result in a substantial upward bias in the magnitude of the teacher effect, which raises concerns about…
Descriptors: Computation, Models, Statistical Analysis, Academic Achievement