Computer adaptive testing is an important research field in educational measurement, and simulation studies play a critically important role in CAT development and evaluation. Both Monte Carlo and Post Hoc simulations are frequently used in CAT studies in order to investigate the effects of different factors on test efficiency and to compare different test designs. Although there are several softwares for CAT simulations, R is preferred since it includes many free packages and gives researchers opportunity to write their own functions according to their own requirements besides being free. The purpose of this study is to make an introduction and demonstration of how to use catR package in CAT simulations. Different examples were provided in the context of this study and R codes were presented with explanations. Then, the output files were briefly explained. It is thought that this paper is helpful for the researchers who are interested in CAT simulations.Computer adaptive testing is an important research field in educational measurement, and simulation studies play a critically important role in CAT development and evaluation. Both Monte Carlo and Post Hoc simulations are frequently used in CAT studies in order to investigate the effects of different factors on test efficiency and to compare different test designs. Although there are several softwares for CAT simulations, R is preferred since it includes many free packages and gives researchers opportunity to write their own functions according to their own requirements besides being free. The purpose of this study is to make an introduction and demonstration of how to use catR package in CAT simulations. Different examples were provided in the context of this study and R codes were presented with explanations. Then, the output files were briefly explained. It is thought that this paper is helpful for the researchers who are interested in CAT simulations.
CITATION STYLE
ERDEM KARA, B. (2019). Computer Adaptive Testing Simulations in R. International Journal of Assessment Tools in Education, 6(5), 44–56. https://doi.org/10.21449/ijate.621157
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