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Knowledge Tracing
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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
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
CogGen: A Learner-Centered Generative AI Architecture for Intelligent Tutoring with Programming Video
A Hierarchical Probabilistic Framework for Incremental Knowledge Tracing in Classroom Settings
Denoising Programming Knowledge Tracing with a Code Graph-based Tuning Adaptor
Hierarchical Bayesian Knowledge Tracing in Undergraduate Engineering Education
Cuff-KT: Tackling Learners' Real-time Learning Pattern Adjustment via Tuning-Free Knowledge State Guided Model Updating
KnowTrace: Bootstrapping Iterative Retrieval-Augmented Generation with Structured Knowledge Tracing
Pedagogy-R1: Pedagogically-Aligned Reasoning Model with Balanced Educational Benchmark
Personalized Student Knowledge Modeling for Future Learning Resource Prediction
Contrastive Cross-Course Knowledge Tracing via Concept Graph Guided Knowledge Transfer
Survey of Loss Augmented Knowledge Tracing
RouterKT: Mixture-of-Experts for Knowledge Tracing
AdvKT: An Adversarial Multi-Step Training Framework for Knowledge Tracing
Improving Question Embeddings with Cognitiv Representation Optimization for Knowledge Tracing
UniEDU: A Unified Language and Vision Assistant for Education Applications
Disentangled Knowledge Tracing for Alleviating Cognitive Bias
LLM-driven Effective Knowledge Tracing by Integrating Dual-channel Difficulty
Automated Knowledge Component Generation and Knowledge Tracing for Coding Problems
Training Turn-by-Turn Verifiers for Dialogue Tutoring Agents: The Curious Case of LLMs as Your Coding Tutors
AAKT: Enhancing Knowledge Tracing with Alternate Autoregressive Modeling
Revisiting Applicable and Comprehensive Knowledge Tracing in Large-Scale Data
Knowledge Tracing in Programming Education Integrating Students' Questions
TutorLLM: Customizing Learning Recommendations with Knowledge Tracing and Retrieval-Augmented Generation
DASKT: A Dynamic Affect Simulation Method for Knowledge Tracing
Sparse Binary Representation Learning for Knowledge Tracing
Tracking student skills real-time through a continuous-variable dynamic Bayesian network
Uncertainty-aware Knowledge Tracing
Advancing Personalized Learning Analysis via an Innovative Domain Knowledge Informed Attention-based Knowledge Tracing Method
Learning states enhanced knowledge tracing: Simulating the diversity in real-world learning process
Fair Knowledge Tracing in Second Language Acquisition
Not All Options Are Created Equal: Textual Option Weighting for Token-Efficient LLM-Based Knowledge Tracing
Automated Knowledge Concept Annotation and Question Representation Learning for Knowledge Tracing
Deep Knowledge Tracing for Personalized Adaptive Learning at Historically Black Colleges and Universities
Using Large Multimodal Models to Extract Knowledge Components for Knowledge Tracing from Multimedia Question Information
Test Case-Informed Knowledge Tracing for Open-ended Coding Tasks
Learning to Love Edge Cases in Formative Math Assessment: Using the AMMORE Dataset and Chain-of-Thought Prompting to Improve Grading Accuracy
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