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 131–140 of 215 papers

TitleStatusHype
Using Deep Reinforcement Learning to Train and Evaluate Instructional Sequencing Policies for an Intelligent Tutoring System—0
DBE-KT22: A Knowledge Tracing Dataset Based on Online Student Evaluation—0
Language Model Can Do Knowledge Tracing: Simple but Effective Method to Integrate Language Model and Knowledge Tracing Task—0
DASKT: A Dynamic Affect Simulation Method for Knowledge Tracing—0
Consistency and Monotonicity Regularization for Neural Knowledge Tracing—0
Learning Data Teaching Strategies Via Knowledge Tracing—0
CogGen: A Learner-Centered Generative AI Architecture for Intelligent Tutoring with Programming Video—0
Learning states enhanced knowledge tracing: Simulating the diversity in real-world learning process—0
Learning Structure and Knowledge Aware Representation with Large Language Models for Concept Recommendation—0
Learning to Love Edge Cases in Formative Math Assessment: Using the AMMORE Dataset and Chain-of-Thought Prompting to Improve Grading Accuracy—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