The use of the Bayes factor to identify students who guess at random
The available methods that permit detecting students who guess at random in learning assessment tests present many limits. For example, person-fit indexes need generally large data matrices and can be used only to detect if a student responds in accordance to a measurement model (e.g., Rasch models). In this paper, we will present a new approach to identify students who guess at random in learning assessment tests. After discussing limits of some existing methods, we will expose the technical details of the use of the Bayes factor to evaluate a number of informative hypotheses (Hoijtink, 2012 ; Hoijtink, Klugkist and Boelen, 2008). Next, we will apply this Bayes factor to a simulation study and real data sets for illustration purposes. Our result shows that the Bayes factor is a promising way to detect students who guess at random in learning assessment tests.