Estimating Student Proficiency Using an Item Response Theory Model

Item Response Theory (IRT) models were investigated as a tool for student modeling in an intelligent tutoring system (ITS). The models were tested using real data of high school students using the Wayang Outpost, a computer-based tutor for the mathematics portion of the Scholastic Aptitude Test (SAT). A cross-validation framework was developed and three metrics to measure prediction accuracy were compared. The trained models predicted with 72% accuracy whether a student would answer a multiple choice problem correctly.