Stable and Faithful Explanations for Knowledge Tracing

arXiv:2609.28502 · cs.LG · Submitted 2026-09-15 · Read on arXiv

cs.LG

Submitted: 2026-09-15

Updated: 2026-09-15

Terminology

• AUC — 34× in this paper · explained in 2 episodes
• Ablation — 24× in this paper · explained in 1 episode
• Accuracy — 23× in this paper · explained in 1 episode
• Benchmark — 10× in this paper · explained in 2 episodes
• Interpretability — 8× in this paper · explained in 15 episodes
• Shapley values — 8× in this paper · explained in 2 episodes
• Embeddings — 6× in this paper · explained in 2 episodes
• Explainability — 6× in this paper · explained in 3 episodes
• Calibration — 4× in this paper · explained in 7 episodes
• SHAP values — 4× in this paper · explained in 2 episodes
• Deep Knowledge Tracing — 3× in this paper
• Generalization — 3× in this paper · explained in 13 episodes
• Redundancy — 3× in this paper · explained in 2 episodes
• Scaffolding — 3× in this paper · explained in 3 episodes
• Attention Mechanism — 2× in this paper · explained in 3 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Adversarial Model — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Axioms — 1× in this paper · explained in 2 episodes
• Bayesian Knowledge Tracing — 1× in this paper
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• Knowledge Tracing Models — 1× in this paper · explained in 2 episodes
• Metacognition — 1× in this paper · explained in 5 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Predictive Modeling — 1× in this paper · explained in 2 episodes
• Procedural Knowledge — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• Self-Attentive Knowledge Tracing — 1× in this paper
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• simpleKT: A Simple But Tough-to-Beat Baseline for Knowledge Tracing
• Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs
• Captum: A unified and generic model interpretability library for PyTorch
• True to the Model or True to the Data?

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