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Suh, Hongwook – ProQuest LLC, 2010
Response time has been regarded as an important source for investigating the relationship between human performance and response speed. It is important to examine the relationship between response time and item characteristics, especially in the perspective of the relationship between response time and various factors that affect examinee's…
Descriptors: Bayesian Statistics, Computation, Reaction Time, Item Response Theory
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Rudner, Lawrence M. – Practical Assessment, Research & Evaluation, 2009
This paper describes and evaluates the use of measurement decision theory (MDT) to classify examinees based on their item response patterns. The model has a simple framework that starts with the conditional probabilities of examinees in each category or mastery state responding correctly to each item. The presented evaluation investigates: (1) the…
Descriptors: Classification, Scoring, Item Response Theory, Measurement
Iseli, Markus R.; Koenig, Alan D.; Lee, John J.; Wainess, Richard – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2010
Assessment of complex task performance is crucial to evaluating personnel in critical job functions such as Navy damage control operations aboard ships. Games and simulations can be instrumental in this process, as they can present a broad range of complex scenarios without involving harm to people or property. However, "automatic"…
Descriptors: Performance Tests, Performance Based Assessment, Decision Making Skills, Military Training
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Rock, Donald A. – ETS Research Report Series, 2012
This paper provides a history of ETS's role in developing assessment instruments and psychometric procedures for measuring change in large-scale national assessments funded by the Longitudinal Studies branch of the National Center for Education Statistics. It documents the innovations developed during more than 30 years of working with…
Descriptors: Models, Educational Change, Longitudinal Studies, Educational Development
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Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
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Mariano, Louis T.; Junker, Brian W. – Journal of Educational and Behavioral Statistics, 2007
When constructed response test items are scored by more than one rater, the repeated ratings allow for the consideration of individual rater bias and variability in estimating student proficiency. Several hierarchical models based on item response theory have been introduced to model such effects. In this article, the authors demonstrate how these…
Descriptors: Test Items, Item Response Theory, Rating Scales, Scoring
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Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
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Sinharay, Sandip; Johnson, Matthew – ETS Research Report Series, 2005
"Item models" (LaDuca, Staples, Templeton, & Holzman, 1986) are classes from which it is possible to generate/produce items that are equivalent/isomorphic to other items from the same model (e.g., Bejar, 1996; Bejar, 2002). They have the potential to produce large number of high-quality items at reduced cost. This paper introduces…
Descriptors: Item Analysis, Test Items, Scoring, Psychometrics