Computerized Adaptive Testing Using a Class of High-Order Item Response Theory Models

Autor/inn/en	Huang, Hung-Yu; Chen, Po-Hsi; Wang, Wen-Chung
Titel	Computerized Adaptive Testing Using a Class of High-Order Item Response Theory Models
Quelle	In: Applied Psychological Measurement, 36 (2012) 8, S.689-706 (18 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621612459552
Schlagwörter	Computer Assisted Testing; Adaptive Testing; Item Response Theory; Simulation; Test Items; Item Analysis; Selection; Item Banks + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Simulation program; Simulationsprogramm; Test content; Testaufgabe; Itemanalyse; Auslese
Abstract	In the human sciences, a common assumption is that latent traits have a hierarchical structure. Higher order item response theory models have been developed to account for this hierarchy. In this study, computerized adaptive testing (CAT) algorithms based on these kinds of models were implemented, and their performance under a variety of situations was examined using simulations. The results showed that the CAT algorithms were very effective. The progressive method for item selection, the Sympson and Hetter method with online and freeze procedure for item exposure control, and the multinomial model for content balancing can simultaneously maintain good measurement precision, item exposure control, content balance, test security, and pool usage. (Contains 3 tables and 2 figures.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10