SOTAVerified

Knowledge Tracing

Knowledge Tracing is the task of modelling student knowledge over time so that we can accurately predict how students will perform on future interactions. Improvement on this task means that resources can be suggested to students based on their individual needs, and content which is predicted to be too easy or too hard can be skipped or delayed.

Source: Deep Knowledge Tracing

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 76–100 of 215 papers

TitleStatusHype
Prerequisite Structure Discovery in Intelligent Tutoring SystemsCode0
No Length Left Behind: Enhancing Knowledge Tracing for Modeling Sequences of Excessive or Insufficient LengthsCode0
Cognition-Mode Aware Variational Representation Learning Framework for Knowledge TracingCode0
EKT: Exercise-aware Knowledge Tracing for Student Performance PredictionCode0
EdNet: A Large-Scale Hierarchical Dataset in EducationCode0
A Question-centric Multi-experts Contrastive Learning Framework for Improving the Accuracy and Interpretability of Deep Sequential Knowledge Tracing ModelsCode0
Dynamic Key-Value Memory Networks for Knowledge TracingCode0
Addressing Two Problems in Deep Knowledge Tracing via Prediction-Consistent RegularizationCode0
Knowledge Tracing Machines: Factorization Machines for Knowledge TracingCode0
Knowledge Relation Rank Enhanced Heterogeneous Learning Interaction Modeling for Neural Graph Forgetting Knowledge TracingCode0
Knowledge Tracing for Complex Problem Solving: Granular Rank-Based Tensor FactorizationCode0
Addressing Label Leakage in Knowledge Tracing ModelsCode0
Interpretable Knowledge Tracing via Response Influence-based Counterfactual ReasoningCode0
Improving Low-Resource Knowledge Tracing Tasks by Supervised Pre-training and Importance Mechanism Fine-tuningCode0
Explainable Few-shot Knowledge TracingCode0
Incorporating Features Learned by an Enhanced Deep Knowledge Tracing Model for STEM/Non-STEM Job PredictionCode0
Interpretable Knowledge Tracing with Multiscale State RepresentationCode0
Back to the Basics: Bayesian extensions of IRT outperform neural networks for proficiency estimationCode0
Personalized Exercise Recommendation with Semantically-Grounded Knowledge TracingCode0
Hierarchical Multi-Armed Bandits for the Concurrent Intelligent Tutoring of Concepts and Problems of Varying Difficulty LevelsCode0
Accuracy-aware Deep Knowledge Tracing with Knowledge State Vector LossCode0
Automated Knowledge Concept Annotation and Question Representation Learning for Knowledge TracingCode0
HiTSKT: A Hierarchical Transformer Model for Session-Aware Knowledge TracingCode0
Graph-based Knowledge Tracing: Modeling Student Proficiency Using Graph Neural NetworkCode0
Knowledge Query Network for Knowledge TracingCode0
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All datasetsEdNetAssistments

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SAKTAcc70.73—Unverified
2SAINT+AUC0.79—Unverified
3SAINTAUC0.78—Unverified
4PEBG+DKTAUC0.78—Unverified
5PEBG+DKVMNAUC0.78—Unverified
6DKVMNAUC0.77—Unverified
7DKTAUC0.76—Unverified
8GIKTAUC0.75—Unverified
#ModelMetricClaimedVerifiedStatus
1DKTAUC0.86—Unverified
2BKTAUC0.67—Unverified