Introducing a Computerized Figural Memory Test Based on Automatic Item Generation: An Analysis With the Rasch Poisson Counts Model

Abstract

An automatic item generator for figural memory test items called figumem was developed. It is available in R. A cognitive model allowed the generation of hypothetically parallel items within three difficulty levels determined by visual information load. In a pilot study, participants solved three items for each level of visual load. Within an item response theory approach, the Rasch Poisson counts model and modifications of it were fitted to the data. Results showed overall satisfying fit. Visual information load explained most of the variance in item difficulty. Differences in difficulty between items of the same family were comparatively low, displaying the utility of the item generator for the creation of parallel test forms. Implications, limitations, and suggestions for the use and extensions of figumem are discussed.