A New Stopping Rule for Computerized Adaptive Testing

Autor/inn/en	Choi, Seung W.; Grady, Matthew W.; Dodd, Barbara G.
Titel	A New Stopping Rule for Computerized Adaptive Testing
Quelle	In: Educational and Psychological Measurement, 71 (2011) 1, S.37-53 (17 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164410387338
Schlagwörter	Item Banks; Adaptive Testing; Computer Assisted Testing; Evaluation Methods; Predictive Measurement; Comparative Analysis
Abstract	The goal of the current study was to introduce a new stopping rule for computerized adaptive testing (CAT). The predicted standard error reduction (PSER) stopping rule uses the predictive posterior variance to determine the reduction in standard error that would result from the administration of additional items. The performance of the PSER was compared with that of the minimum standard error stopping rule and a modified version of the minimum information stopping rule in a series of simulated adaptive tests, drawn from a number of item pools. Results indicate that the PSER makes efficient use of CAT item pools, administering fewer items when predictive gains in information are small and increasing measurement precision when information is abundant. (Contains 4 figures and 4 tables.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10