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 71–80 of 215 papers

TitleStatusHype
Towards Modeling Learner Performance with Large Language ModelsCode0
A Review of Data Mining in Personalized Education: Current Trends and Future Prospects—0
KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students—0
Analysis of Knowledge Tracing performance on synthesised student data—0
Prerequisite Structure Discovery in Intelligent Tutoring SystemsCode0
Parametric Constraints for Bayesian Knowledge Tracing from First Principles—0
Difficulty-Focused Contrastive Learning for Knowledge Tracing with a Large Language Model-Based Difficulty Prediction—0
On the verification of Embeddings using Hybrid Markov Logic—0
Interpretable Knowledge Tracing via Response Influence-based Counterfactual ReasoningCode0
Knowledge Tracing Challenge: Optimal Activity Sequencing for Students—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