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An Investigation of the Nature and Consequence of the Relationship between IRT Difficulty and Discrimination
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Sweeney, Sandra M.; Sinharay, Sandip; Johnson, Matthew S.; Steinhauer, Eric W. – Educational Measurement: Issues and Practice, 2022
The focus of this paper is on the empirical relationship between item difficulty and item discrimination. Two studies--an empirical investigation and a simulation study--were conducted to examine the association between item difficulty and item discrimination under classical test theory and item response theory (IRT), and the effects of the…
Descriptors: Correlation, Item Response Theory, Item Analysis, Difficulty Level
Combining Process Information and Item Response Modeling to Estimate Problem-Solving Ability
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Xiao, Yue; Veldkamp, Bernard; Liu, Hongyun – Educational Measurement: Issues and Practice, 2022
The action sequences of respondents in problem-solving tasks reflect rich and detailed information about their performance, including differences in problem-solving ability, even if item scores are equal. It is therefore not sufficient to infer individual problem-solving skills based solely on item scores. This study is a preliminary attempt to…
Descriptors: Problem Solving, Item Response Theory, Scores, Item Analysis
A Special Case of Brennan's Index for Tests That Aim to Select a Limited Number of Students: A Monte Carlo Simulation Study
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Arikan, Serkan; Aybek, Eren Can – Educational Measurement: Issues and Practice, 2022
Many scholars compared various item discrimination indices in real or simulated data. Item discrimination indices, such as item-total correlation, item-rest correlation, and IRT item discrimination parameter, provide information about individual differences among all participants. However, there are tests that aim to select a very limited number…
Descriptors: Monte Carlo Methods, Item Analysis, Correlation, Individual Differences
Digital Module 08: Foundations of Operational Item Analysis https://ncme.elevate.commpartners.com
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Yoo, Hanwook; Hambleton, Ronald K. – Educational Measurement: Issues and Practice, 2019
Item analysis is an integral part of operational test development and is typically conducted within two popular statistical frameworks: classical test theory (CTT) and item response theory (IRT). In this digital ITEMS module, Hanwook Yoo and Ronald K. Hambleton provide an accessible overview of operational item analysis approaches within these…
Descriptors: Item Analysis, Item Response Theory, Guidelines, Test Construction
Improving the Measurement of School Climate Using Item Response Theory
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Sarah Lindstrom Johnson; Ray E. Reichenberg; Kathan Shukla; Tracy E. Waasdorp; Catherine P. Bradshaw – Educational Measurement: Issues and Practice, 2019
The U.S. government has become increasingly focused on school climate, as recently evidenced by its inclusion as an accountability indicator in the Every Student Succeeds Act. Yet, there remains considerable variability in both conceptualizing and measuring school climate. To better inform the research and practice related to school climate and…
Descriptors: Item Response Theory, Educational Environment, Accountability, Educational Legislation
Exploring the Logic of Tatsuoka's Rule-Space Model for Test Development and Analysis. An NCME Instructional Module.
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Gierl, Mark J.; Leighton, Jacqueline P.; Hunka, Stephen M. – Educational Measurement: Issues and Practice, 2000
Discusses the logic of the rule-space model (K. Tatsuoka, 1983) as it applies to test development and analysis. The rule-space model is a statistical method for classifying examinees' test item responses into a set of attribute-mastery patterns associated with different cognitive skills. Directs readers to a tutorial that may be downloaded. (SLD)
Descriptors: Item Analysis, Item Response Theory, Test Construction, Test Items