The interpretations of test scores in secure, high-stakes environments are dependent on several assumptions, one of which is that examinee responses to items are independent and no enemy items are included on the same forms. This paper documents the development and implementation of a C#-based application that uses Natural Language Processing…

In recent years, Automatic Item Generation (AIG) has increasingly shifted from theoretical research to operational implementation, a shift raising some unforeseen practical challenges. Specifically, generating high-quality answer choices presents several challenges such as ensuring that answer choices blend in nicely together for all possible item…