knowledge tracing consists in predicting the performance of some students on
new questions given their performance on previous questions, and can be a prior
step to optimizing assessment and learning. Deep knowledge tra
qDKT is a variant of deep knowledge tracing that models every learner's success probability on individual questions over time by incorporating graph Laplacian regularization and initialization scheme inspired by fastText algorithm, achieving state-of-the-art performance on predicting learner outcomes and serving as a baseline for new question-centric knowledge tracing models.