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 151–160 of 215 papers

TitleStatusHype
APGKT: Exploiting Associative Path on Skills Graph for Knowledge Tracing—0
DBE-KT22: A Knowledge Tracing Dataset Based on Online Student Evaluation—0
Equity and Fairness of Bayesian Knowledge Tracing—0
No Task Left Behind: Multi-Task Learning of Knowledge Tracing and Option Tracing for Better Student Assessment—0
Bi-CLKT: Bi-Graph Contrastive Learning based Knowledge Tracing—0
Knowledge Tracing: A Survey—0
Incremental Knowledge Tracing from Multiple Schools—0
Empirical Evaluation of Deep Learning Models for Knowledge Tracing: Of Hyperparameters and Metrics on Performance and Replicability—0
Masked Deep Q-Recommender for Effective Question Scheduling—0
Programming Knowledge Tracing: A Comprehensive Dataset and A New Model—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