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Proposes Phase-Aware Knowledge Tracing (PAKT), a framework that decomposes student interactions into ability and proficiency phases, using a multi-branch Transformer to model phase-specific and holistic knowledge states, achieving consistent improvements over baselines on six benchmarks.
This paper introduces the Unified Behavioral Prediction and Calibration Analysis Pipeline (UBP-CAP), an integrated framework linking student performance prediction, calibration error calculation, and variance decomposition of metacognitive misalignment. Evaluated on a dataset of 1,195 interaction records, the pipeline identifies key predictors of correctness and reveals that metacognitive calibration is primarily situational rather than a stable trait.