The Influence of Item Calibration Error on Variable-Length Computerized Adaptive Testing

Autor/inn/en	Patton, Jeffrey M.; Cheng, Ying; Yuan, Ke-Hai; Diao, Qi
Titel	The Influence of Item Calibration Error on Variable-Length Computerized Adaptive Testing
Quelle	In: Applied Psychological Measurement, 37 (2013) 1, S.24-40 (17 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621612461727
Schlagwörter	Adaptive Testing; Computer Assisted Testing; Test Length; Ability; Test Items; Accuracy; Classification; Simulation + Suchen Sie Ihr Suchwort? Fähigkeit; Fertigkeit; Test content; Testaufgabe; Classification system; Klassifikation; Klassifikationssystem; Simulation program; Simulationsprogramm
Abstract	Variable-length computerized adaptive testing (VL-CAT) allows both items and test length to be "tailored" to examinees, thereby achieving the measurement goal (e.g., scoring precision or classification) with as few items as possible. Several popular test termination rules depend on the standard error of the ability estimate, which in turn depends on the item parameter values. However, items are chosen on the basis of their parameter estimates, and capitalization on chance may occur. In this article, the authors investigated the effects of capitalization on chance on test length and classification accuracy in several VL-CAT simulations. The results confirm that capitalization on chance occurs in VL-CAT and has complex effects on test length, ability estimation, and classification accuracy. These results have important implications for the design and implementation of VL-CATs. (Contains 6 figures and 4 tables.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10