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

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Showing 141–150 of 215 papers

TitleStatusHype
Enhancing Deep Knowledge Tracing with Auxiliary Tasks—0
simpleKT: A Simple But Tough-to-Beat Baseline for Knowledge Tracing—0
Augmenting Interpretable Knowledge Tracing by Ability Attribute and Attention Mechanism—0
Transition-Aware Multi-Activity Knowledge TracingCode0
HiTSKT: A Hierarchical Transformer Model for Session-Aware Knowledge TracingCode0
Differentiating Student Feedbacks for Knowledge Tracing—0
Multi-Layer Personalized Federated Learning for Mitigating Biases in Student Predictive Analytics—0
DAGKT: Difficulty and Attempts Boosted Graph-based Knowledge TracingCode0
SAICL: Student Modelling with Interaction-level Auxiliary Contrastive Tasks for Knowledge Tracing and Dropout Prediction—0
Knowledge Tracing for Complex Problem Solving: Granular Rank-Based Tensor FactorizationCode0
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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