The Application of the Monte Carlo Approach to Cognitive Diagnostic Computerized Adaptive Testing With Content Constraints

Autor/inn/en	Mao, Xiuzhen; Xin, Tao
Titel	The Application of the Monte Carlo Approach to Cognitive Diagnostic Computerized Adaptive Testing With Content Constraints
Quelle	In: Applied Psychological Measurement, 37 (2013) 6, S.482-496 (15 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621613486015
Schlagwörter	Monte Carlo Methods; Cognitive Tests; Diagnostic Tests; Computer Assisted Testing; Adaptive Testing; Test Items; Item Banks; Selection + Suchen Sie Ihr Suchwort? Monte-Carlo-Methode; Kognitiver Fähigkeitstest; Diagnostic test; Diagnostischer Test; Test content; Testaufgabe; Auslese
Abstract	The Monte Carlo approach which has previously been implemented in traditional computerized adaptive testing (CAT) is applied here to cognitive diagnostic CAT to test the ability of this approach to address multiple content constraints. The performance of the Monte Carlo approach is compared with the performance of the modified maximum global discrimination index (MMGDI) method on simulations in which the only content constraint is on the number of items that measure each attribute. The results of the two simulation experiments show that (a) the Monte Carlo method fulfills all the test requirements and produces satisfactory measurement precision and item exposure results and (b) the Monte Carlo method outperforms the MMGDI method when the Monte Carlo method applies either the posterior-weighted Kullback-Leibler algorithm or the hybrid Kullback-Leibler information as the item selection index. Overall, the recovery rate of the knowledge states, the distribution of the item exposure, and the utilization rate of the item bank are improved when the Monte Carlo method is used. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10