1st CFA: FAIR4AIED - International Workshop on Fairness in Algorithmic Decision-Making for Education
Mirko Marras
International Workshop on Fairness in Algorithmic Decision-Making for Education to be held as part of the 27th International Conference on Artificial Intelligence in Education (AIED 2026) and the Festival of Learning
Workshop: 27 June 2026 - Seoul, Republic of Korea
https://fair4aied.github.io/2026/
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Important Dates
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Abstract submissions: May 15th, 2026
Notifications: May 27th, 2026
Workshop day: June 27, 2026 - Seoul, Republic of Korea
These deadlines refer to 23:59 in the AoE (Anywhere on Earth) time zone. Upon acceptance, authors will have approximately two weeks to prepare 1-3 slides for their lightning talk.
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Workshop Aims and Scope
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Education is being reshaped by AI: intelligent tutoring, risk detection, personalization, and unstructured learning with large language models are now commonplace. Ensuring fairness in educational AI remains difficult. Systems depend on algorithmic decisions and large data ecosystems that often under-represent diverse students; biases in data can be amplified into harm and discrimination; and rapid adoption of generative AI has added fairness and ethics questions that the field is still working through.
Researchers already pursue auditing, mitigation, fairness-aware modeling, bias detection in datasets, and fairness metrics for learning settings—yet this work is often fragmented across subcommunities and only loosely connected to broader fairness ideas from the machine learning community. This workshop aims to bridge those gaps through interdisciplinary dialogue and exchange among researchers, practitioners, and policymakers. Through presentations and a panel, we share practical experience, surface open questions, and connect fairness ideas to actionable strategies for real educational systems—especially as generative AI evolves—advancing socio-technical approaches that go beyond purely technical fixes.
We bring together researchers, practitioners, policymakers, and industry partners whose expertise is needed to put fairness and ethics at the center of AI-powered education.
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Workshop Topics
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We invite contributions via workshop abstracts or, for Festival of Learning presenters, fairness-focused talks tied to that work. Content should relate to fairness in algorithmic decision-making for education. Cross-cutting themes emphasized in the program include: defining fairness in educational contexts; identifying at-risk or marginalized groups; measurement, metrics, and evaluation; bias mitigation; transparency and reporting of fairness analyses; and auditing AIED systems—with attention to both outcome fairness and procedural fairness.
The following areas illustrate the scope (not an exhaustive list):
Fairness methods design and incorporation
Incorporating fairness principles across an AIED system
Ensuring fairness across the AIED system lifecycle
Integrating fairness with other AIED areas to provide complementary benefits
Fairness auditing and evaluation
Algorithmic auditing procedures in the context of AIED
Improving fairness metrics, definitions, and evaluation approaches in AIED
Strengthening mechanisms for long-term adherence to fairness in AIED
Fairness gaps and challenges identification
Identifying gaps and challenges in AIED regarding fairness
Exploring what we can do better concerning fairness as a research community
Challenges to improving fairness in practice
Methods for addressing these challenges in adopting fairness
Procedural Fairness
Operationalizing and studying procedural fairness across an AIED system
Gaps in current AIED research related to procedural fairness
Ensuring procedural fairness in AIED by identifying and addressing practical implementation challenges
Topics related to procedural fairness in education
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Submission Details
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Participant talks come from two sources:
Workshop abstracts. Authors may submit a 250-word abstract of their planned talk, written in English (references do not count toward the limit). Abstracts should be submitted using the submission form.
Festival of Learning presenters. Researchers who are presenting work at the Festival of Learning may request a short slot to speak specifically about fairness or ethical aspects of that work—whether fairness is the main contribution or an important angle that was not the paper’s primary focus. Contact the organizers to coordinate; capacity is limited and subject to the program schedule.
For workshop abstracts:
All abstract submissions will undergo a single-blind review process conducted by the organizers.
Submissions will be evaluated based on relevance, originality, significance, and clarity.
Accepted abstracts will be made available on the workshop website.
At least one author per accepted abstract must register for and attend the workshop to present.
Accepted abstracts are presented as short participant talks (5–7 minutes); see Program for Q&A format.
Presenters are responsible for preparing slides for their talk.
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Workshop Chairs
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Frank Stinar, University of Illinois Urbana–Champaign, USA
Chengyuan Yao, Columbia University, USA
Mirko Marras, University of Cagliari, Italy
Renzhe Yu, Columbia University, USA
Nigel Bosch, University of Illinois Urbana–Champaign, USA
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Contact
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For general enquiries on the workshop, please send an email to fsti...@illinois.edu
