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Deep Knowledge Tracing and Dynamic Student Classification for Knowledge Tracing

arXiv 1809.08713 ↗First posted 24 Sep 2018cs.AIcited by 23

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Abstract (arXiv)

In Intelligent Tutoring System (ITS), tracing the student's knowledge state during learning has been studied for several decades in order to provide more supportive learning instructions. In this paper, we propose a novel model for knowledge tracing that i) captures students' learning ability and dynamically assigns students into distinct groups with similar ability at regular time intervals, and ii) combines this information with a Recurrent Neural Network architecture known as Deep Knowledge Tracing. Experimental results confirm that the proposed model is significantly better at predicting student performance than well known state-of-the-art techniques for student modelling.

Key facts. Cited by 23 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Sep 2018.

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Citing papers per year: 2021: 5; 2022: 3; 2023: 7; 2024: 3; 2025: 3; 2026: 2.

23 papers.

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  1. 2022Knowledge Tracing: A Surveycited by 77
  2. 2022pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Modelscited by 52
  3. 2023simpleKT: A Simple But Tough-to-Beat Baseline for Knowledge Tracingcited by 47
  4. 2024EduAgent: Generative Student Agents in Learningcited by 42
  5. 2023Improving Interpretability of Deep Sequential Knowledge Tracing Models with Question-centric Cognitive Representationscited by 32
  6. 2021Enhancing Knowledge Tracing via Adversarial Trainingcited by 31
  7. 2021A Survey of Knowledge Tracing: Models, Variants, and Applicationscited by 30
  8. 2023Enhancing Deep Knowledge Tracing with Auxiliary Taskscited by 24
  9. 2021Quality meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testingcited by 17
  10. 2021Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relationscited by 14
  11. 2023Forgetting-aware Linear Bias for Attentive Knowledge Tracingcited by 13
  12. 2024A Question-centric Multi-experts Contrastive Learning Framework for Improving the Accuracy and Interpretability of Deep Sequential Knowledge Tracing Modelscited by 5
11 more
  1. 2025DKT2: Revisiting Applicable and Comprehensive Knowledge Tracing in Large-Scale Datacited by 4
  2. 2024Cross-domain-aware Worker Selection with Training for Crowdsourced Annotationcited by 2
  3. 2021Interpreting Deep Knowledge Tracing Model on EdNet Datasetcited by 1
  4. 2022DAGKT: Difficulty and Attempts Boosted Graph-based Knowledge Tracingcited by 1
  5. 2026Neural-Symbolic Knowledge Tracing: Injecting Educational Knowledge into Deep Learning for Responsible Learner Modellingcited by 1
  6. 2023Augmenting Interpretable Knowledge Tracing by Ability Attribute and Attention Mechanismcited by 0
  7. 2023Imputing Knowledge Tracing Data with Subject-Based Training via LSTM Variational Autoencoders Frameworkscited by 0
  8. 2023Deep Knowledge Tracing is an implicit dynamic multidimensional item response theory modelcited by 0
  9. 2025Survey of Loss Augmented Knowledge Tracingcited by 0
  10. 2025Enhanced Interpretable Knowledge Tracing for Students Performance Prediction with Human understandable Feature Spacecited by 0
  11. 2026MBP-KT: Learning Global Collaborative Information from Meta-Behavioral Pattern for Enhanced Knowledge Tracingcited by 0