A similarity-based theory of controlling MCQ difficulty

Abstract

Several attempts have already been made to automate the generation of assessment questions. These attempts were mainly technical and lacked a theoretical backing. We explore psychological and educational theories to support the development of principled methods to generate questions and control their properties. We present a similarity-based theory to control the difficulty of multiple-choice questions and show its practicality and consistency with the psychological and educational theories.