Random Generation of Response Patterns under Computerized Adaptive Testing with the<i>R</i>Package<b>catR</b>

Magis, David; Raîche, Gilles

doi:10.18637/jss.v048.i08

Cited by 94 publications

(98 citation statements)

References 46 publications

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“…Concerto 3 (Scalise & Allen, 2015) is the most flexible platform to that respect. It is designed for stand-alone deployment and uses the catR-library (Magis & Raîche, 2012), which offers different IRT testing strategies, several methods for next item selection, and three stopping rules. Tests and items can be designed by specifying HTML-templates using a drag-and-drop editor.…”

Section: Platforms For Web-based Delivery Of Catmentioning

confidence: 99%

A flexible online platform for computerized adaptive testing

Oppl

Reisinger

Eckmaier

et al. 2017

Int J Educ Technol High Educ

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Computerized Adaptive Testing (CAT) is a field of research originating in psychometrics that has been adopted in the last years for formative and summative assessment activities in educational settings in general and in online learning in particular. While a variety of platforms is available for designing and deploying CAT the challenge of providing the flexibility in test and item design required for domain-specific assessment formats in education has hardly been addressed so far. The present article introduces a software architecture to fill this gap and enable the development of fully customizable CAT tools with respect to domain-specific item design and visualization as well as deployed CAT algorithms. A prototypical implementation of the architecture and a set of domain-specific item types are presented to demonstrate the feasibility of the proposed approach and outline future directions of development and research.

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Section: Platforms For Web-based Delivery Of Catmentioning

confidence: 99%

A flexible online platform for computerized adaptive testing

Oppl

Reisinger

Eckmaier

et al. 2017

Int J Educ Technol High Educ

View full text Add to dashboard Cite

show abstract

“…Criteria applicable to both unidimensional and multidimensional adaptive tests are the "KL" and "KLn" method for the point-wise Kullback-Leibler divergence and the point-wise Kullback-Leibler with a decreasing delta value (∆ · √ n, where n is the number of items previous answered), respectively, "IKLP" and "IKL" for the integration based Kullback-Leibler criteria with and without the prior density weight, and "IKLn" and "IKLPn" for the √ n sequentially weighted counter-parts of the integration criteria (Chang and Ying 1996). Possible inputs for unidimensional adaptive tests include "MI" for the maximum information criteria, "MEPV" for minimum expected posterior variance, "MLWI" for maximum-likelihood with weighted information, "MPWI" for maximum posterior weighted information, and "MEI" for maximum expected information (see Magis and Raîche 2012, and the references therein for further elaboration of these methods).…”

Section: Gui Inputs For Mirtcat()mentioning

confidence: 99%

“…Several criteria have been proposed for unidimensional CATs to select optimal items for ability and classification designs, many of which have been implemented in unidimensional CAT software in R (e.g., see Magis and Raîche 2012). Fewer MCAT criteria have been proposed in the literature, though a small number of criteria are available.…”

Section: Introductionmentioning

confidence: 99%

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Generating Adaptive and Non-Adaptive Test Interfaces for Multidimensional Item Response Theory Applications

Chalmers¹

2016

J. Stat. Soft.

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Computerized adaptive testing (CAT) is a powerful technique to help improve measurement precision and reduce the total number of items required in educational, psychological, and medical tests. In CATs, tailored test forms are progressively constructed by capitalizing on information available from responses to previous items. CAT applications primarily have relied on unidimensional item response theory (IRT) to help select which items should be administered during the session. However, multidimensional CATs may be constructed to improve measurement precision and further reduce the number of items required to measure multiple traits simultaneously.A small selection of CAT simulation packages exist for the R environment; namely, catR (Magis and Raîche 2012), catIrt (Nydick 2014), and MAT (Choi and King 2014). However, the ability to generate graphical user interfaces for administering CATs in realtime has not been implemented in R to date, support for multidimensional CATs have been limited to the multidimensional three-parameter logistic model, and CAT designs were required to contain IRT models from the same modeling family. This article describes a new R package for implementing unidimensional and multidimensional CATs using a wide variety of IRT models, which can be unique for each respective test item, and demonstrates how graphical user interfaces and Monte Carlo simulation designs can be constructed with the mirtCAT package.

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“…Several technical details are also included in Appendix A. The package itself will not be described again, so we refer the interested reader to Magis and Raîche (2012) for more details.…”

Section: Introductionmentioning

confidence: 99%

Computerized Adaptive Testing with R: Recent Updates of the Package catR

Magis

Barrada²

2017

J. Stat. Soft.

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The purpose of this paper is to list the recent updates of the R package catR. This package allows for generating response patterns under a computerized adaptive testing (CAT) framework with underlying item response theory (IRT) models. Among the most important updates, well-known polytomous IRT models are now supported by catR; several item selection rules have been added; and it is now possible to perform post-hoc simulations. Some functions were also rewritten or withdrawn to improve the usefulness and performances of the package.

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Random Generation of Response Patterns under Computerized Adaptive Testing with theRPackagecatR

Cited by 94 publications

References 46 publications

A flexible online platform for computerized adaptive testing

A flexible online platform for computerized adaptive testing

Generating Adaptive and Non-Adaptive Test Interfaces for Multidimensional Item Response Theory Applications

Computerized Adaptive Testing with R: Recent Updates of the Package catR

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