SAKT uses self-attention to focus on relevant prior KCs for performance prediction and reports 4.43% average AUC improvement over DKT and DKVMN on real datasets.
On the Synthetic dataset, SAKT per- forms better than the competing approaches, achieving an AUC of 0.832 compared to 0.824 by DKT+
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A Self-Attentive model for Knowledge Tracing
SAKT uses self-attention to focus on relevant prior KCs for performance prediction and reports 4.43% average AUC improvement over DKT and DKVMN on real datasets.