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 171–180 of 215 papers

TitleStatusHype
Do we need to go Deep? Knowledge Tracing with Big Data—0
An Empirical Comparison of Deep Learning Models for Knowledge Tracing on Large-Scale Dataset—0
Using Deep Reinforcement Learning to Train and Evaluate Instructional Sequencing Policies for an Intelligent Tutoring System—0
BKT-LSTM: Efficient Student Modeling for knowledge tracing and student performance prediction—0
Explainable Knowledge Tracing Models for Big Data: Is Ensembling an Answer?—0
Exercise Hierarchical Feature Enhanced Knowledge Tracing—0
Accuracy-aware Deep Knowledge Tracing with Knowledge State Vector LossCode0
Deep Knowledge Tracing with Learning Curves—0
HGKT: Introducing Hierarchical Exercise Graph for Knowledge Tracing—0
qDKT: Question-centric Deep 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