Item Selection in Multidimensional Computerized Adaptive Testing--Gaining Information from Different Angles

Autor/inn/en	Wang, Chun; Chang, Hua-Hua
Titel	Item Selection in Multidimensional Computerized Adaptive Testing--Gaining Information from Different Angles
Quelle	In: Psychometrika, 76 (2011) 3, S.363-384 (22 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0033-3123
DOI	10.1007/s11336-011-9215-7
Schlagwörter	Psychological Testing; Adaptive Testing; Scientific Concepts; Item Analysis; Item Response Theory; Simulation; Educational Testing + Suchen Sie Ihr Suchwort? Psychological test; psychological tests; Psychological examination; Psychologischer Test; Itemanalyse; Item-Response-Theorie; Simulation program; Simulationsprogramm
Abstract	Over the past thirty years, obtaining diagnostic information from examinees' item responses has become an increasingly important feature of educational and psychological testing. The objective can be achieved by sequentially selecting multidimensional items to fit the class of latent traits being assessed, and therefore Multidimensional Computerized Adaptive Testing (MCAT) is one reasonable approach to such task. This study conducts a rigorous investigation on the relationships among four promising item selection methods: "D-optimality," "KL information index," "continuous entropy," and "mutual information." Some theoretical connections among the methods are demonstrated to show how information about the unknown vector theta can be gained from different perspectives. Two simulation studies were carried out to compare the performance of the four methods. The simulation results showed that "mutual information" not only improved the overall estimation accuracy but also yielded the smallest conditional mean squared error in most region of theta. In the end, the overlap rates were calculated to empirically show the similarity and difference among the four methods. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10