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Stephen G. Sireci; Javier Suárez-Álvarez; April L. Zenisky; Maria Elena Oliveri – Educational Measurement: Issues and Practice, 2024
The goal in personalized assessment is to best fit the needs of each individual test taker, given the assessment purposes. Design-in-Real-Time (DIRTy) assessment reflects the progressive evolution in testing from a single test, to an adaptive test, to an adaptive assessment "system." In this article, we lay the foundation for DIRTy…
Descriptors: Educational Assessment, Student Needs, Test Format, Test Construction
Sidener, David W. – Analysis of Verbal Behavior, 2006
The following paper describes Lowenkron's model of joint (stimulus) control. Joint control is described as a means of accounting for performances, especially generalized performances, for which a history of contingency control does not provide an adequate account. Examples are provided to illustrate instances in which joint control may facilitate…
Descriptors: Stimuli, Performance, Adaptive Testing, Models
Peer reviewedVeerkamp, Wim J. J. – Journal of Educational and Behavioral Statistics, 2000
Showed how Taylor approximation can be used to generate a linear approximation to a logistic item characteristic curve and a linear ability estimator. Demonstrated how, for a specific simulation, this could result in the special case of a Robbins-Monro item selection procedure for adaptive testing. (SLD)
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Selection
Peer reviewedChang, Hua-Hua; Ying, Zhiliang – Applied Psychological Measurement, 1999
Proposes a new multistage adaptive-testing procedure that factors the discrimination parameter (alpha) into the item-selection process. Simulation studies indicate that the new strategy results in tests that are well-balanced, with respect to item exposure, and efficient. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Selection
van der Linden, Wim J.; Scrams, David J.; Schnipke, Deborah L. – 2003
This paper proposes an item selection algorithm that can be used to neutralize the effect of time limits in computer adaptive testing. The method is based on a statistical model for the response-time distributions of the test takers on the items in the pool that is updated each time a new item has been administered. Predictions from the model are…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Linear Programming
Peer reviewedvan der Linden, Wim J.; Scrams, David J.; Schnipke, Deborah L. – Applied Psychological Measurement, 1999
Proposes an item-selection algorithm for neutralizing the differential effects of time limits on computerized adaptive test scores. Uses a statistical model for distributions of examinees' response times on items in a bank that is updated each time an item is administered. Demonstrates the method using an item bank from the Armed Services…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Item Banks
Thommen, John D. – 1992
Testbanking provides teachers with an effective, low-cost, time-saving opportunity to improve the testing aspect of their classes. Testbanking, which involves the use of a testbank program and a computer, allows teachers to develop and generate tests and test-forms with a minimum of effort. Teachers who test using true and false, multiple choice,…
Descriptors: Adaptive Testing, Classroom Techniques, Community Colleges, Computer Assisted Testing
Stufflebeam, Daniel L. – 1985
A consortium of four institutions, based at Western Michigan University, was to plan a Research and Development Center on Student Testing, Evaluation, and Standards Setting. The four consortium sites are Boston College, the Dallas Independent School District, the University of Kansas, and Western Michigan University. This report is a final…
Descriptors: Academic Standards, Adaptive Testing, Computer Assisted Testing, Consortia

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