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 1–10 of 215 papers

TitleStatusHype
Personalized Exercise Recommendation with Semantically-Grounded Knowledge TracingCode0
CogGen: A Learner-Centered Generative AI Architecture for Intelligent Tutoring with Programming Video—0
A Hierarchical Probabilistic Framework for Incremental Knowledge Tracing in Classroom SettingsCode0
Denoising Programming Knowledge Tracing with a Code Graph-based Tuning Adaptor—0
Hierarchical Bayesian Knowledge Tracing in Undergraduate Engineering Education—0
Cuff-KT: Tackling Learners' Real-time Learning Pattern Adjustment via Tuning-Free Knowledge State Guided Model UpdatingCode0
KnowTrace: Bootstrapping Iterative Retrieval-Augmented Generation with Structured Knowledge TracingCode1
Pedagogy-R1: Pedagogically-Aligned Reasoning Model with Balanced Educational Benchmark—0
Personalized Student Knowledge Modeling for Future Learning Resource PredictionCode0
Contrastive Cross-Course Knowledge Tracing via Concept Graph Guided Knowledge TransferCode0
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All datasetsEdNetAssistments

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DKTAUC0.86—Unverified
2BKTAUC0.67—Unverified