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 161–170 of 215 papers

TitleStatusHype
Learning Data Teaching Strategies Via Knowledge Tracing—0
An Approach for Combining Multimodal Fusion and Neural Architecture Search Applied to Knowledge Tracing—0
Interpreting Deep Knowledge Tracing Model on EdNet Dataset—0
Deep Graph Memory Networks for Forgetting-Robust Knowledge Tracing—0
Consistency and Monotonicity Regularization for Neural Knowledge Tracing—0
On Representation Learning for Scientific News Articles Using Heterogeneous Knowledge Graphs—0
Temporal Cross-Effects in Knowledge Tracing—0
MUSE: Multi-Scale Temporal Features Evolution for Knowledge Tracing—0
LSTM-SAKT: LSTM-Encoded SAKT-like Transformer for Knowledge Tracing—0
On the Interpretability of Deep Learning Based Models for Knowledge Tracing—0
Show:102550
← PrevPage 17 of 22Next →
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