The most common approach to modelling item discrimination and guessing for multiple-choice questions is the three parameter logistic (3PL) model. However, proponents of Rasch models generally avoid using the 3PL model because to model guessing entails sacrificing the distinctive property and advantages of Rasch models. One approach to dealing with guessing based on the application of Rasch models is to omit responses in which guessing appears to play a significant role. However, this approach entails loss of information and it does not account for variable item discrimination. It has been shown, though, that provided specific constraints are met, it is possible to parameterize discrimination while preserving the distinctive property of Rasch models. This article proposes an approach that uses Rasch models to account for guessing on standard multiple-choice items simply by treating it as a source of low item discrimination. Technical considerations are noted although a detailed examination of such considerations is beyond the scope of this article.
|Journal||Journal of Applied Measurement|
|Publication status||Published - 2015|