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 |
Documentation:
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