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 181–190 of 215 papers

TitleStatusHype
TutorLLM: Customizing Learning Recommendations with Knowledge Tracing and Retrieval-Augmented Generation—0
APGKT: Exploiting Associative Path on Skills Graph for Knowledge Tracing—0
A Comprehensive Survey on Deep Learning Techniques in Educational Data Mining—0
SAICL: Student Modelling with Interaction-level Auxiliary Contrastive Tasks for Knowledge Tracing and Dropout Prediction—0
Do we need to go Deep? Knowledge Tracing with Big Data—0
Dual-State Personalized Knowledge Tracing with Emotional Incorporation—0
Domain Generalizable Knowledge Tracing via Concept Aggregation and Relation-Based Attention—0
An Empirical Comparison of Deep Learning Models for Knowledge Tracing on Large-Scale Dataset—0
Dynamic Knowledge embedding and tracing—0
Domain Adaption for Knowledge 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