mlsanityData to 14 Oct 2026

A Comprehensive Survey on Deep Learning Techniques in Educational Data Mining

arXiv 2309.04761 ↗First posted 9 Sep 2023cs.LG cs.CY cs.IRcited by 3

Not on the map. Why?

Abstract (arXiv)

Educational Data Mining (EDM) has emerged as a vital field of research, which harnesses the power of computational techniques to analyze educational data. With the increasing complexity and diversity of educational data, Deep Learning techniques have shown significant advantages in addressing the challenges associated with analyzing and modeling this data. This survey aims to systematically review the state-of-the-art in EDM with Deep Learning. We begin by providing a brief introduction to EDM and Deep Learning, highlighting their relevance in the context of modern education. Next, we present a detailed review of Deep Learning techniques applied in four typical educational scenarios, including knowledge tracing, student behavior detection, performance prediction, and personalized recommendation. Furthermore, a comprehensive overview of public datasets and processing tools for EDM is provided. We then analyze the practical challenges in EDM and propose targeted solutions. Finally, we point out emerging trends and future directions in this research area.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 33 of its 214 references that are in the map. First posted on arXiv 9 Sep 2023.

Builds on

33 of 214 references.

References · 33

  1. 2017Attention Is All You Needcited by 60,361
  2. 2019A Comprehensive Survey on Graph Neural Networkscited by 2,919
  3. 2016Equality of Opportunity in Supervised Learningcited by 2,007
  4. 2019Federated Learning: Challenges, Methods, and Future Directionscited by 1,538
  5. 2017Learning Important Features Through Propagating Activation Differencescited by 1,458
  6. 2017A Survey on Multi-Task Learningcited by 840
  7. 2020Graph Neural Networks in Recommender Systems: A Surveycited by 494
  8. 2021Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Surveycited by 463
  9. 2016Semi-supervised Knowledge Transfer for Deep Learning from Private Training Datacited by 348
  10. 2021ResMLP: Feedforward networks for image classification with data-efficient trainingcited by 339
  11. 2015Deep Knowledge Tracingcited by 332
  12. 2020Context-Aware Attentive Knowledge Tracingcited by 174
21 more
  1. 2019A Self-Attentive model for Knowledge Tracingcited by 172
  2. 2016Dynamic Key-Value Memory Networks for Knowledge Tracingcited by 171
  3. 2019EKT: Exercise-aware Knowledge Tracing for Student Performance Predictioncited by 109
  4. 2019EdNet: A Large-Scale Hierarchical Dataset in Educationcited by 108
  5. 2020A Survey of Deep Meta-Learningcited by 100
  6. 2023A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?cited by 84
  7. 2019Neural Cognitive Diagnosis for Intelligent Education Systemscited by 75
  8. 2020GIKT: A Graph-based Interaction Model for Knowledge Tracingcited by 51
  9. 2020BayLIME: Bayesian Local Interpretable Model-Agnostic Explanationscited by 51
  10. 2021Hybrid Contrastive Learning of Tri-Modal Representation for Multimodal Sentiment Analysiscited by 41
  11. 2019Exploiting Cognitive Structure for Adaptive Learningcited by 37
  12. 2021A Survey of Knowledge Tracing: Models, Variants, and Applicationscited by 30
  13. 2018Facial Expression Analysis under Partial Occlusion: A Surveycited by 28
  14. 2021DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNNcited by 19
  15. 2021A Survey on Reinforcement Learning for Recommender Systemscited by 18
  16. 2016Back to the Basics: Bayesian extensions of IRT outperform neural networks for proficiency estimationcited by 17
  17. 2022Online AutoML: An adaptive AutoML framework for online learningcited by 11
  18. 2022DGEKT: A Dual Graph Ensemble Learning Method for Knowledge Tracingcited by 9
  19. 2022No Task Left Behind: Multi-Task Learning of Knowledge Tracing and Option Tracing for Better Student Assessmentcited by 8
  20. 2021Learning Data Teaching Strategies Via Knowledge Tracingcited by 6
  21. 2023DKT-STDRL: Spatial and Temporal Representation Learning Enhanced Deep Knowledge Tracing for Learning Performance Predictioncited by 1

Built on by

Cited by year

Citing papers per year: 2024: 2; 2025: 1.

3 papers.

  1. 2025SVQA-R1: Reinforcing Spatial Reasoning in MLLMs via View-Consistent Reward Optimizationcited by 16
  2. 2024Evolutionary Reinforcement Learning: A Systematic Review and Future Directionscited by 4
  3. 2024A Review of Data Mining in Personalized Education: Current Trends and Future Prospectscited by 4