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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Johns, J., Mahadevan, S., & Woolf, B. (2006). Estimating student proficiency using an item response theory model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4053 LNCS, pp. 473–480). Springer Verlag. https://doi.org/10.1007/11774303_47
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