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 51–60 of 215 papers

TitleStatusHype
Equity and Fairness of Bayesian Knowledge Tracing—0
Enhancing Deep Knowledge Tracing via Diffusion Models for Personalized Adaptive Learning—0
Deep Graph Memory Networks for Forgetting-Robust Knowledge Tracing—0
Analysis of Knowledge Tracing performance on synthesised student data—0
Dual-State Personalized Knowledge Tracing with Emotional Incorporation—0
Do we need to go Deep? Knowledge Tracing with Big Data—0
DBE-KT22: A Knowledge Tracing Dataset Based on Online Student Evaluation—0
Augmenting Interpretable Knowledge Tracing by Ability Attribute and Attention Mechanism—0
Deep Knowledge Tracing for Personalized Adaptive Learning at Historically Black Colleges and Universities—0
Dynamic Knowledge embedding and 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