Reference : An overview of the CAT: framework, R package, and applications
Scientific congresses and symposiums : Unpublished conference
Physical, chemical, mathematical & earth Sciences : Mathematics
http://hdl.handle.net/2268/112051
An overview of the CAT: framework, R package, and applications
English
Magis, David mailto [Université de Liège - ULg > Département de mathématique > Statistique mathématique >]
12-Mar-2012
No
Yes
National
Biweekly seminar
12 mars 2012
Department of Psychological Methods, University of Amsterdam
Amsterdam
Pays-Bas
[en] Computerized adaptive testing (CAT) is an efficient method to administer psychometric or educational tests and questionnaires. Unlike the standard fixed (“paper-and-pencil”) tests, items in a CAT are iteratively and optimally selected within a bank of available items, on the basis of previously administered items and the current ability estimate of the examinee. This general approach has several assets with respect to fixed tests: it reduces the risk of fraud, it allows for individualized questionnaires according to the examinee’s ability level, and fewer items must be administered to reach the same level of precision in the ability estimates.
The purpose of this talk is threefold. First, a general overview of CAT is proposed and its main principles are quickly outlined. Second, a recently developed R package, called catR, is briefly presented and its functionalities are described. Finally, two applications are discussed. The first application is a live demonstration of catR, by using its by-default item bank about English aptitude assessment, and several CAT options. The second application focuses on the on-line testing platform Concerto, a web interface for the development and testing of CAT sessions that uses catR as underlying computational package.
The R package catR was jointly developed with Gilles Raîche (Université du Québec à Montréal, Canada). The platform Concerto is under development by The Psychometrics Centre (Cambridge University, UK) under the supervision of Michal Kosinski and John Rust.
http://hdl.handle.net/2268/112051

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