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Download full textSamejima, Fumiko – 1998
Item response theory (IRT) has been adapted as the theoretical foundation of computerized adaptive testing (CAT) for several decades. In applying IRT to CAT, there are certain considerations that are essential, and yet tend to be neglected. These essential issues are addressed in this paper, and then several ways of eliminating noise and bias in…
Descriptors: Ability, Adaptive Testing, Estimation (Mathematics), Item Response Theory
Roussos, Louis; Nandakumar, Ratna; Cwikla, Julie – 2000
CATSIB is a differential item functioning (DIF) assessment methodology for computerized adaptive test (CAT) data. Kernel smoothing (KS) is a technique for nonparametric estimation of item response functions. In this study an attempt has been made to develop a more efficient DIF procedure for CAT data, KS-CATSIB, by combining CATSIB with kernel…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Bias, Item Response Theory
Yan, Duanli; Lewis, Charles; Stocking, Martha – 1998
It is unrealistic to suppose that standard item response theory (IRT) models will be appropriate for all new and currently considered computer-based tests. In addition to developing new models, researchers will need to give some attention to the possibility of constructing and analyzing new tests without the aid of strong models. Computerized…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Item Response Theory
