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van der Linden, Wim J.; Boekkooi-Timminga, Ellen – 1987
A "maximin" model for item response theory based test design is proposed. In this model only the relative shape of the target test information function is specified. It serves as a constraint subject to which a linear programming algorithm maximizes the information in the test. In the practice of test construction there may be several…
Descriptors: Algorithms, Foreign Countries, Item Banks, Latent Trait Theory
Choppin, Bruce – 1982
On well-constructed multiple-choice tests, the most serious threat to measurement is not variation in item discrimination, but the guessing behavior that may be adopted by some students. Ways of ameliorating the effects of guessing are discussed, especially for problems in latent trait models. A new item response model, including an item parameter…
Descriptors: Ability, Algorithms, Guessing (Tests), Item Analysis
Peer reviewed Peer reviewed
Wainer, Howard; Lewis, Charles – Journal of Educational Measurement, 1990
Three different applications of the testlet concept are presented, and the psychometric models most suitable for each application are described. Difficulties that testlets can help overcome include (1) context effects; (2) item ordering; and (3) content balancing. Implications for test construction are discussed. (SLD)
Descriptors: Algorithms, Computer Assisted Testing, Elementary Secondary Education, Item Response Theory
Wainer, Howard; Kiely, Gerard L. – 1986
Recent experience with the Computerized Adaptive Test (CAT) has raised a number of concerns about its practical applications. The concerns are principally involved with the concept of having the computer construct the test from a precalibrated item pool, and substituting statistical characteristics for the test developer's skills. Problems with…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Construct Validity