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 51–60 of 215 papers

TitleStatusHype
Augmenting Knowledge Tracing by Considering Forgetting Behavior—0
Enhancing Deep Knowledge Tracing with Auxiliary Tasks—0
Augmenting Interpretable Knowledge Tracing by Ability Attribute and Attention Mechanism—0
Deep Graph Memory Networks for Forgetting-Robust Knowledge Tracing—0
Analysis of Knowledge Tracing performance on synthesised student data—0
Enhancing Deep Knowledge Tracing via Diffusion Models for Personalized Adaptive Learning—0
Do we need to go Deep? Knowledge Tracing with Big Data—0
Knowledge Tracing with Sequential Key-Value Memory Networks—0
Deep Knowledge Tracing for Personalized Adaptive Learning at Historically Black Colleges and Universities—0
Dual-State Personalized Knowledge Tracing with Emotional Incorporation—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