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A New Stopping Rule for Computerized Adaptive Testing

Bibliographic Data

ID20283249
AuthorsSeung W Choi (0000-0003-4777-5420, Northwestern University Feinberg School of Medicine, Chicago, IL, USA,, corresponding author), Matthew W Grady (University of Texas at Austin, Austin, TX, USA), Barbara G Dodd (University of Texas at Austin, Austin, TX, USA)
Year2011
Volume71
Issue1
Pages37-53
Publication date2011-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEducational and Psychological Measurement (JOURNAL)
Journal identifiersISSN: 0013-1644 • E-ISSN: 1552-3888
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/0013164410387338
PMID21278821
PMCIDPMC3028267
OpenAlexW2153733797
LanguageEN
Citations received8
References cited12

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

Computerized adaptive testing · Econometrics · Psychometrics · Reliability engineering · Statistics · Computer Science · Engineering · Mathematics · Psychology · Psychometric Methodologies and Testing · Statistical Methods in Clinical Trials · VLSI and Analog Circuit Testing

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Unique citing works8
Citations per year0.67
Citation span2014 - 2026 (13)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 6

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