In the Self-Attentive Knowledge Tracing model, past exercise interactions serve as keys and the upcoming exercise serves as the query. The authors visualized the resulting attention weights to examine which past interactions were most relevant to each prediction. They reported that exercises grouped by tag and that the model identified relationships between same-tag exercises even when those exercises were far apart in the interaction sequence.