Abstract
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.
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Johns, J., Mahadevan, S., Woolf, B. (2006). Estimating Student Proficiency Using an Item Response Theory Model. In: Ikeda, M., Ashley, K.D., Chan, TW. (eds) Intelligent Tutoring Systems. ITS 2006. Lecture Notes in Computer Science, vol 4053. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11774303_47
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DOI: https://doi.org/10.1007/11774303_47
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