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Kim, Rae Yeong; Yoo, Yun Joo – Journal of Educational Measurement, 2023
In cognitive diagnostic models (CDMs), a set of fine-grained attributes is required to characterize complex problem solving and provide detailed diagnostic information about an examinee. However, it is challenging to ensure reliable estimation and control computational complexity when The test aims to identify the examinee's attribute profile in a…
Descriptors: Models, Diagnostic Tests, Adaptive Testing, Accuracy
Andrich, David; Marais, Ida – Journal of Educational Measurement, 2018
Even though guessing biases difficulty estimates as a function of item difficulty in the dichotomous Rasch model, assessment programs with tests which include multiple-choice items often construct scales using this model. Research has shown that when all items are multiple-choice, this bias can largely be eliminated. However, many assessments have…
Descriptors: Multiple Choice Tests, Test Items, Guessing (Tests), Test Bias
Hsu, Chia-Ling; Wang, Wen-Chung – Journal of Educational Measurement, 2015
Cognitive diagnosis models provide profile information about a set of latent binary attributes, whereas item response models yield a summary report on a latent continuous trait. To utilize the advantages of both models, higher order cognitive diagnosis models were developed in which information about both latent binary attributes and latent…
Descriptors: Computer Assisted Testing, Adaptive Testing, Models, Cognitive Measurement
Wise, Steven L.; Kingsbury, G. Gage – Journal of Educational Measurement, 2016
This study examined the utility of response time-based analyses in understanding the behavior of unmotivated test takers. For the data from an adaptive achievement test, patterns of observed rapid-guessing behavior and item response accuracy were compared to the behavior expected under several types of models that have been proposed to represent…
Descriptors: Achievement Tests, Student Motivation, Test Wiseness, Adaptive Testing
Finkelman, Matthew; Nering, Michael L.; Roussos, Louis A. – Journal of Educational Measurement, 2009
In computerized adaptive testing (CAT), ensuring the security of test items is a crucial practical consideration. A common approach to reducing item theft is to define maximum item exposure rates, i.e., to limit the proportion of examinees to whom a given item can be administered. Numerous methods for controlling exposure rates have been proposed…
Descriptors: Test Items, Adaptive Testing, Item Analysis, Item Response Theory

Luecht, Richard M.; Nungester, Ronald J. – Journal of Educational Measurement, 1998
Describes an integrated approach to test development and administration called computer-adaptive sequential testing (CAST). CAST incorporates adaptive testing methods with automated test assembly. Describes the CAST framework and demonstrates several applications using a medical-licensure example. (SLD)
Descriptors: Adaptive Testing, Automation, Computer Assisted Testing, Licensing Examinations (Professions)

Embretson, Susan E. – Journal of Educational Measurement, 1995
An extension of the multidimensional Rasch model for learning and change is presented that permits theories of processes and knowledge structures to be incorporated into the item response model. The extension resolves basic problems in measuring change and permits adaptive testing. The method is illustrated in a study of mathematical problem…
Descriptors: Adaptive Testing, Change, Individual Differences, Item Response Theory

Wang, Tianyou; Kolen, Michael J. – Journal of Educational Measurement, 2001
Reviews research literature on comparability issues in computerized adaptive testing (CAT) and synthesizes issues specific to comparability and test security. Develops a framework for evaluating comparability that contains three categories of criteria: (1) validity; (2) psychometric property/reliability; and (3) statistical assumption/test…
Descriptors: Adaptive Testing, Comparative Analysis, Computer Assisted Testing, Criteria