Traditional methods of collecting information from test-takers on multiple choice tests most often involve the dichotomization of individuals into groups based on a simple correct/incorrect criterion. In doing so, information that would further differentiate individuals on ability is lost. This paper shows, though a number of simulations and human subject collections, that this information can be collected and utilized in order to make tests generally more efficient.
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