Ruheng Xia

AMDKT: An Interpretable Dual-Stream Transformer for Knowledge Tracing via Student Proficiency–Item Competency Matching (SPIM)

AMDKT is proposed, an interpretable dual-stream Transformer model grounded in the Student Proficiency–Item Competency Matching (SPIM) mechanism that achieves AUC performance comparable to the state-of-the-art AKT model, and obtains statistically superior results against DKT, DKVMN, DEEP-IRT, and DIMKT on most datasets.