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 191–200 of 215 papers

TitleStatusHype
Second Language Acquisition Modeling—0
Set-to-Sequence Ranking-based Concept-aware Learning Path Recommendation—0
Enhancing Deep Knowledge Tracing via Diffusion Models for Personalized Adaptive Learning—0
Enhancing Deep Knowledge Tracing with Auxiliary Tasks—0
DKT-STDRL: Spatial and Temporal Representation Learning Enhanced Deep Knowledge Tracing for Learning Performance Prediction—0
Difficulty-Focused Contrastive Learning for Knowledge Tracing with a Large Language Model-Based Difficulty Prediction—0
Equity and Fairness of Bayesian Knowledge Tracing—0
Differentiating Student Feedbacks for Knowledge Tracing—0
Exercise Hierarchical Feature Enhanced Knowledge Tracing—0
simpleKT: A Simple But Tough-to-Beat Baseline for Knowledge Tracing—0
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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