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 141–150 of 215 papers

TitleStatusHype
Towards Robust Knowledge Tracing Models via k-Sparse Attention—0
Leveraging Skill-to-Skill Supervision for Knowledge Tracing—0
LLM-driven Effective Knowledge Tracing by Integrating Dual-channel Difficulty—0
LSTM-SAKT: LSTM-Encoded SAKT-like Transformer for Knowledge Tracing—0
Mamba4KT:An Efficient and Effective Mamba-based Knowledge Tracing Model—0
Masked Deep Q-Recommender for Effective Question Scheduling—0
CLUF: a Neural Model for Second Language Acquisition Modeling—0
Deep Trustworthy Knowledge Tracing—0
CLST: Cold-Start Mitigation in Knowledge Tracing by Aligning a Generative Language Model as a Students' Knowledge Tracer—0
BKT-LSTM: Efficient Student Modeling for knowledge tracing and student performance prediction—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