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Ramon Barrada, Juan; Veldkamp, Bernard P.; Olea, Julio – Applied Psychological Measurement, 2009
Computerized adaptive testing is subject to security problems, as the item bank content remains operative over long periods and administration time is flexible for examinees. Spreading the content of a part of the item bank could lead to an overestimation of the examinees' trait level. The most common way of reducing this risk is to impose a…
Descriptors: Item Banks, Adaptive Testing, Item Analysis, Psychometrics
Kirisci, Levent; Hsu, Tse-Chi – 1992
A predictive adaptive testing (PAT) strategy was developed based on statistical predictive analysis, and its feasibility was studied by comparing PAT performance to those of the Flexilevel, Bayesian modal, and expected a posteriori (EAP) strategies in a simulated environment. The proposed adaptive test is based on the idea of using item difficulty…
Descriptors: Adaptive Testing, Bayesian Statistics, Comparative Analysis, Computer Assisted Testing
Xiao, Beiling – 1990
Dichotomous search strategies (DSSs) for computerized adaptive testing are similar to golden section search strategies (GSSSs). Each middle point of successive search regions is a testing point. After each item is administered, the subject's obtained score is compared with the expected score at successive testing points. If the subject's obtained…
Descriptors: Ability Identification, Adaptive Testing, Computer Assisted Testing, Equations (Mathematics)
Patience, Wayne M.; Reckase, Mark D. – 1979
An experiment was performed with computer-generated data to investigate some of the operational characteristics of tailored testing as they are related to various provisions of the computer program and item pool. With respect to the computer program, two characteristics were varied: the size of the step of increase or decrease in item difficulty…
Descriptors: Adaptive Testing, Computer Assisted Testing, Difficulty Level, Error of Measurement
Tatsuoka, Kikumi K.; Tatsuoka, Maurice M. – 1985
The study examines the rule space model, a probabilistic model capable of measuring cognitive skill acquisition and of diagnosing erroneous rules of operation in a procedural domain. The model involves two important components: (1) determination of a set of bug distributions (bug density functions representing clusters around the rules); and (2)…
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Assisted Testing, Computer Software