mlsanityData to 7 Oct 2026

Algorithmic Fairness in Education

arXiv 2007.05443 ↗First posted 10 Jul 2020cs.CY cs.AI cs.LGcited by 44

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Abstract (arXiv)

Data-driven predictive models are increasingly used in education to support students, instructors, and administrators. However, there are concerns about the fairness of the predictions and uses of these algorithmic systems. In this introduction to algorithmic fairness in education, we draw parallels to prior literature on educational access, bias, and discrimination, and we examine core components of algorithmic systems (measurement, model learning, and action) to identify sources of bias and discrimination in the process of developing and deploying these systems. Statistical, similarity-based, and causal notions of fairness are reviewed and contrasted in the way they apply in educational contexts. Recommendations for policy makers and developers of educational technology offer guidance for how to promote algorithmic fairness in education.

Key facts. Cited by 44 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Jul 2020.

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Citing papers per year: 2021: 5; 2022: 7; 2023: 13; 2024: 9; 2025: 5; 2026: 5.

44 papers.

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  1. 2023Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directionscited by 123
  2. 2023Large Language Models in Education: Vision and Opportunitiescited by 54
  3. 2024What's in a Name? Auditing Large Language Models for Race and Gender Biascited by 50
  4. 2023Bias and Fairness in Chatbots: An Overviewcited by 20
  5. 2023`It is currently hodgepodge'': Examining AI/ML Practitioners' Challenges during Co-production of Responsible AI Valuescited by 18
  6. 2025DrawEduMath: Evaluating Vision Language Models with Expert-Annotated Students' Hand-Drawn Math Imagescited by 17
  7. 2021Towards Equity and Algorithmic Fairness in Student Grade Predictioncited by 13
  8. 2022Mitigating Biases in Student Performance Prediction via Attention-Based Personalized Federated Learningcited by 13
  9. 2021Beyond "Fairness:" Structural (In)justice Lenses on AI for Educationcited by 12
  10. 2023Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approachcited by 12
  11. 2021Equity and Artificial Intelligence in Education: Will "AIEd" Amplify or Alleviate Inequities in Education?cited by 9
  12. 2023Cross-Institutional Transfer Learning for Educational Models: Implications for Model Performance, Fairness, and Equitycited by 9
32 more
  1. 2023Is Your Model "MADD"? A Novel Metric to Evaluate Algorithmic Fairness for Predictive Student Modelscited by 7
  2. 2024Survey of Computerized Adaptive Testing: A Machine Learning Perspectivecited by 6
  3. 2022Multi-Layer Personalized Federated Learning for Mitigating Biases in Student Predictive Analyticscited by 5
  4. 2023Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpointcited by 5
  5. 2023Bayesian Safe Policy Learning with Chance Constrained Optimization: Application to Military Security Assessment during the Vietnam Warcited by 4
  6. 2022Bias Discovery in Machine Learning Models for Mental Healthcited by 3
  7. 2023A review of clustering models in educational data science towards fairness-aware learningcited by 3
  8. 2024The Life Cycle of Large Language Models: A Review of Biases in Educationcited by 3
  9. 2024Collaborative Cognitive Diagnosis with Disentangled Representation Learning for Learner Modelingcited by 3
  10. 2021Predicting Early Dropout: Calibration and Algorithmic Fairness Considerationscited by 2
  11. 2022Equity and Fairness of Bayesian Knowledge Tracingcited by 2
  12. 2023Education in the age of Generative AI: Context and Recent Developmentscited by 2
  13. 2023Augmenting Holistic Review in University Admission using Natural Language Processing for Essays and Recommendation Letterscited by 1
  14. 2023Fairness Hub Technical Briefs: AUC Gapcited by 1
  15. 2024Deep Learning for Educational Data Sciencecited by 1
  16. 2024Evaluating Algorithmic Bias in Models for Predicting Academic Performance of Filipino Studentscited by 1
  17. 2025Toward Sufficient Statistical Power in Algorithmic Bias Assessment: A Test for ABROCAcited by 1
  18. 2026Optimizing LLM Annotation of Classroom Discourse through Multi-Agent Orchestrationcited by 1
  19. 2021Auditing the Imputation Effect on Fairness of Predictive Analytics in Higher Educationcited by 0
  20. 2022Fair Classification via Transformer Neural Networks: Case Study of an Educational Domaincited by 0
  21. 2022Ex-Ante Assessment of Discrimination in Datasetcited by 0
  22. 2022Towards Equalised Odds as Fairness Metric in Academic Performance Predictioncited by 0
  23. 2024FairTargetSim: An Interactive Simulator for Understanding and Explaining the Fairness Effects of Target Variable Definitioncited by 0
  24. 2024DispaRisk: Auditing Fairness Through Usable Informationcited by 0
  25. 2024A Fair Post-Processing Method based on the MADD Metric for Predictive Student Modelscited by 0
  26. 2025You Only Debias Once: Towards Flexible Accuracy-Fairness Trade-offs at Inference Timecited by 0
  27. 2025The Impact of Item-Writing Flaws on Difficulty and Discrimination in Item Response Theorycited by 0
  28. 2025Learning to Optimize Feedback for One Million Students: Insights from Multi-Armed and Contextual Bandits in Large-Scale Online Tutoringcited by 0
  29. 2026Fairness risk and its privacy-enabled solution in AI-driven robotic applicationscited by 0
  30. 2026Unheard in the Digital Age: Rethinking AI Bias and Speech Diversitycited by 0
  31. 2026Education-centered critical policy analysis of AI: Ghana's AI strategy as a casecited by 0
  32. 2026Accuracy Is Not Enough: A Cross-Architecture Audit of Demographic Bias in Deep Knowledge Tracingcited by 0