  We develop T-SKIRT: a temporal, structured-knowledge, IRT-based method for
predicting student responses online. By explicitly accounting for student
learning and employing a structured, multidimensional representation of student
proficiencies, the model outperforms standard IRT-based methods on an online
response prediction task when applied to real responses collected from students
interacting with diverse pools of educational content.
