A modified item response model to detect and correct for cheating

This talk focuses on the identification of respondents with cheating behaviour to educational or psychometric tests. Cheating behaviour is often observed when some examinee with low ability level, tries to get correct responses (in some way or another) to get higher grades. This results usually in a response pattern that does not fit the underlying item response theory (IRT) model and severely affects the estimation of ability level. Until now, several indices of misfit have been proposed, and they seem accurate for detecting cheating (as well as other misfitting behaviours). Unfortunately, none of these indexes permit: (a) to determine which type of behaviour is encountered, and (b) to propose a corrected estimation of the examinee’s ability level.
The purpose of this talk is to present Raîche’s multidimensional model as an extension of the usual IRT models but incorporating additional person parameters to characterize misfitting behaviour. Emphasis is put on a simple model with personal pseudo-guessing variation to detect trends in cheating. Results from a simulation study indicate that, in the absence of cheating, the multidimensional model returns similar estimates than the traditional IRT models, while in the presence of cheating, the person pseudo-guessing parameter is an accurate index of misfit and the person ability estimates are less biased than its traditional counterpart.