Recent advances and improvements in computerized adaptive testing with the R package catR

The purpose of this talk is to present recent advances and developments of the R package catR. This package allows for random generation of response patterns under computerized adaptive testing (CAT) and holds various options to select the first items, estimate ability, select the next item, stop the test and return final results. Two main improvements were realized. First, several rules for next item selection were added, among others, Kullback- Leibler, progressive and proportional methods. Second, catR was limited to dichotomous IRT models so far. The most recent update allows
now for several polytomous IRT models, such as partial and generalized partial credit model, graded and modified graded response models, rating scale model, and nominal response model. All improvements will be shortly presented, both from a theoretical point of view and in terms of practical implementation in catR. If possible, several illustrative examples will be displayed in a short live demonstration of catR.