RSCAT: Shadow-Test Approach to Computerized Adaptive Testing
As an advanced approach to computerized adaptive testing (CAT), shadow testing (van der Linden(2005) <doi:10.1007/0-387-29054-0>) dynamically assembles entire shadow tests as a part of selecting items throughout the testing process. Selecting items from shadow tests guarantees the compliance of all content constraints defined by the blueprint. 'RSCAT' is an R package for the shadow-test approach to CAT. The objective of 'RSCAT' is twofold: 1) Enhancing the effectiveness of shadow-test CAT simulation; 2) Contributing to the academic and scientific community for CAT research. RSCAT is currently designed for dichotomous items based on the three-parameter logistic (3PL) model.
| Version: | 1.1.3 |
| Depends: | R (≥ 3.4.0),rJava,shiny,shinycssloaders,shinyjs |
| Imports: | Metrics,ggplot2,gridExtra, grid, methods, stats, utils |
| Suggests: | testthat |
| Published: | 2021-10-12 |
| DOI: | 10.32614/CRAN.package.RSCAT |
| Author: | Bingnan Jiang [aut, cre], ACT, Inc. [cph] |
| Maintainer: | Bingnan Jiang <bnjiangece at gmail.com> |
| BugReports: | https://github.com/act-org/RSCAT/issues |
| License: | CC BY-NC 4.0 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | RSCAT results |
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