# Deep Knowledge Tracing and Dynamic Student Classification for Knowledge Tracing

arXiv: https://arxiv.org/abs/1809.08713 · HTML: https://mlsanity.com/paper/1809.08713/

## Key facts

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

## Built on by (most cited first, 23 of 23)

- [Knowledge Tracing: A Survey](https://mlsanity.com/paper/2201.06953/) (2022)
- [pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models](https://mlsanity.com/paper/2206.11460/) (2022)
- [simpleKT: A Simple But Tough-to-Beat Baseline for Knowledge Tracing](https://mlsanity.com/paper/2302.06881/) (2023)
- [EduAgent: Generative Student Agents in Learning](https://mlsanity.com/paper/2404.07963/) (2024)
- [Improving Interpretability of Deep Sequential Knowledge Tracing Models with Question-centric Cognitive Representations](https://mlsanity.com/paper/2302.06885/) (2023)
- [Enhancing Knowledge Tracing via Adversarial Training](https://mlsanity.com/paper/2108.04430/) (2021)
- [A Survey of Knowledge Tracing: Models, Variants, and Applications](https://mlsanity.com/paper/2105.15106/) (2021)
- [Enhancing Deep Knowledge Tracing with Auxiliary Tasks](https://mlsanity.com/paper/2302.07942/) (2023)
- [Quality meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing](https://mlsanity.com/paper/2101.05986/) (2021)
- [Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations](https://mlsanity.com/paper/2112.11209/) (2021)
- [Forgetting-aware Linear Bias for Attentive Knowledge Tracing](https://mlsanity.com/paper/2309.14796/) (2023)
- [A Question-centric Multi-experts Contrastive Learning Framework for Improving the Accuracy and Interpretability of Deep Sequential Knowledge Tracing Models](https://mlsanity.com/paper/2403.07322/) (2024)
- [DKT2: Revisiting Applicable and Comprehensive Knowledge Tracing in Large-Scale Data](https://mlsanity.com/paper/2501.14256/) (2025)
- [Cross-domain-aware Worker Selection with Training for Crowdsourced Annotation](https://mlsanity.com/paper/2406.06977/) (2024)
- [Interpreting Deep Knowledge Tracing Model on EdNet Dataset](https://mlsanity.com/paper/2111.00419/) (2021)
- [DAGKT: Difficulty and Attempts Boosted Graph-based Knowledge Tracing](https://mlsanity.com/paper/2210.15470/) (2022)
- [Neural-Symbolic Knowledge Tracing: Injecting Educational Knowledge into Deep Learning for Responsible Learner Modelling](https://mlsanity.com/paper/2604.08263/) (2026)
- [Augmenting Interpretable Knowledge Tracing by Ability Attribute and Attention Mechanism](https://mlsanity.com/paper/2302.02146/) (2023)
- [Imputing Knowledge Tracing Data with Subject-Based Training via LSTM Variational Autoencoders Frameworks](https://mlsanity.com/paper/2302.12910/) (2023)
- [Deep Knowledge Tracing is an implicit dynamic multidimensional item response theory model](https://mlsanity.com/paper/2309.12334/) (2023)
- [Survey of Loss Augmented Knowledge Tracing](https://mlsanity.com/paper/2504.15163/) (2025)
- [Enhanced Interpretable Knowledge Tracing for Students Performance Prediction with Human understandable Feature Space](https://mlsanity.com/paper/2509.18231/) (2025)
- [MBP-KT: Learning Global Collaborative Information from Meta-Behavioral Pattern for Enhanced Knowledge Tracing](https://mlsanity.com/paper/2605.08697/) (2026)

## 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.