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Paper submission deadline extended to 15th of June2025
In the 26th International Conference on Artificial Intelligence in Education
(AIED 2025)
on July 22, 2025, between 9:00h - 13:00h
Palermo, Italy
This year, we are pleased to announce the collaboration between the XAI-Ed workshop and the 2nd Human-Centric eXplainable AI in Education (HEXED) workshop, which will be held in conjunction with the Educational Data Mining (EDM) 2025 conference, which is jointly located this year with AIED in Palermo.
This partnership reflects a shared commitment to advancing the field of XAI within educational contexts. Therefore, we strongly encourage participants in XAI-Ed to consider attending HEXED workshop to get a thorough complement to the content of XAI-Ed.
In support of this collaborative spirit, XAI-Ed and HEXED will jointly publish their workshop proceedings, promoting further integration and dialogue across both communities in addressing the evolving needs and challenges in human-centered, and pedagogy-founded XAI for education.
Why XAI-Ed Workshop
As educational technology evolves, integrating Artificial Intelligence (AI) into Technology-Enhanced Learning (TEL), Educational technologies (EdTech), and AI in Education (AIED) offers significant potential for learning and the educational stakeholders. However, the opacity of many AI systems complicates the interpretation of their decision making processes, and their predictions of, e.g., personalized learning recommendations. Explainable AI (XAI) addresses this challenge by providing insights into how AI algorithms arrive at their predictions, thereby enabling stakeholders to make more informed decisions. This workshop will explore the convergence of XAI with AIED, TEL, and EdTech in general, aiming to empower learners and educators through transparent and understandable insights into the inner workings of AI algorithms.
As educational technology evolves, integrating Artificial Intelligence (AI) into Technology-Enhanced Learning (TEL), Educational technologies (EdTech), and AI in Education (AIED) offers significant potential for learning and the educational stakeholders. However, the opacity of many AI systems complicates the interpretation of their decision making processes, and their predictions of, e.g., personalized learning recommendations. Explainable AI (XAI) addresses this challenge by providing insights into how AI algorithms arrive at their predictions, thereby enabling stakeholders to make more informed decisions. This workshop will explore the convergence of XAI with AIED, TEL, and EdTech in general, aiming to empower learners and educators through transparent and understandable insights into the inner workings of AI algorithms.
Although the recent advances within the AIED community underscored the growing demand for explainable and transparent AI systems, the focus has mainly been on the technical side of XAI, leaving a strong need for addressing the pedagogical aspects of XAI in education. Those are not only limited to the pedagogical foundations of XAI but also include the actual learning value from implementing XAI, how this value aligns with learning theories, and how XAI’s ability to achieve it can be evaluated. In educational contexts, where learner autonomy and agency are essential for a fair, learner-centered process, XAI is expected to provide meaningful explanations for algorithmic predictions. Successfully implementing XAI in EdTech and AIED, therefore, requires a robust understanding of its pedagogical foundations, technical realization, regulatory limitations, and the perspectives of the educational stakeholders, including learners, educators, developers, and institutions.
Although the recent advances within the AIED community underscored the growing demand for explainable and transparent AI systems, the focus has mainly been on the technical side of XAI, leaving a strong need for addressing the pedagogical aspects of XAI in education. Those are not only limited to the pedagogical foundations of XAI but also include the actual learning value from implementing XAI, how this value aligns with learning theories, and how XAI’s ability to achieve it can be evaluated. In educational contexts, where learner autonomy and agency are essential for a fair, learner-centered process, XAI is expected to provide meaningful explanations for algorithmic predictions. Successfully implementing XAI in EdTech and AIED, therefore, requires a robust understanding of its pedagogical foundations, technical realization, regulatory limitations, and the perspectives of the educational stakeholders, including learners, educators, developers, and institutions.
Workshop Goals
Foster interdisciplinary dialogue on XAI in education.
Promote the design and implementation of XAI with strong pedagogical foundations.
Encourage user-centered co-design between technical, educational, and regulatory stakeholders, to empower learners and educators through transparent AI decision-making.
Share tools, methods, and evaluation strategies for implementing XAI.
Address ethical and legal considerations in XAI for education.
📢 Call for Papers
The second annual XAI-Ed Workshop explores the intersection of Explainable AI (XAI), education, and human-centered design, with a strong focus on pedagogical foundations, stakeholder agency, ethical implications, and interdisciplinary collaboration.
The second annual XAI-Ed Workshop explores the intersection of Explainable AI (XAI), education, and human-centered design, with a strong focus on pedagogical foundations, stakeholder agency, ethical implications, and interdisciplinary collaboration.
We invite contributions that investigate, design, or critique the role of XAI in educational contexts, especially those that address:
We invite contributions that investigate, design, or critique the role of XAI in educational contexts, especially those that address:
- Pedagogical and learning-theory foundations for XAI
- Human-centered and stakeholder-driven XAI design
- Tools, methods, and frameworks for XAI in education
- Ethical, legal, and societal considerations (e.g., European AI Act)
- Evaluation and real-world deployment of XAI systems in EdTech/AIED
Submission Categories
Submission Categories
We welcome the following types of contributions:
We welcome the following types of contributions:
- Full Research Papers (6–10 pages, including references)
Original research with completed results and rigorous evaluation.
Original research with completed results and rigorous evaluation.
- Short Papers (3–5 pages, including references)
Including but not limited to:
Including but not limited to:
- Work-in-progress
- Practitioner reports
- Conceptual or theoretical contributions
- Positional papers
All submissions must be written in English, double column, double-blind, PDF format preferred.
All submissions must be written in English, double column, double-blind, PDF format preferred.
Target Audience
Target Audience
We encourage submissions from a wide range of disciplines including (but not limited to):
We encourage submissions from a wide range of disciplines including (but not limited to):
AI in Education, Learning Sciences, HCI, Learning Analytics, Educational Technology, Ethics, Policy, and Law. Contributions from both academic and practitioner communities are highly welcomed.
AI in Education, Learning Sciences, HCI, Learning Analytics, Educational Technology, Ethics, Policy, and Law. Contributions from both academic and practitioner communities are highly welcomed.
Submission
Submission
All submissions are made through EasyChair. Submission URL: https://easychair.org/conferences?conf=xaied2025
All submissions are made through EasyChair. Submission URL: https://easychair.org/conferences?conf=xaied2025
While we encourage participant submissions, we will also have a variety of activities and other opportunities for contribution during the workshop itself. Presentation of the submissions will only be a portion of the workshop, as we plan to keep participants engaged and contributing through other ways during the workshop, along with plans to have multiple artifacts created during the workshop.
While we encourage participant submissions, we will also have a variety of activities and other opportunities for contribution during the workshop itself. Presentation of the submissions will only be a portion of the workshop, as we plan to keep participants engaged and contributing through other ways during the workshop, along with plans to have multiple artifacts created during the workshop.
Important Dates
Important Dates
- Paper submission deadline: June 15, 2025 (extended) May 31, 2025
- Notification of acceptance: June 15-30, 2025
- Camera-ready deadline: July 20, 2025
- Workshop date: 22 July, 2025
(All submission deadlines are on 23:59 AoE time)
Workshop Proceedings
Workshop Proceedings
Submitted papers will be peer-reviewed (at least two reviews per paper). All accepted and presented papers will be submitted for publishing as open-access CEUR Workshop Proceedings, by CEUR-WS.org
Submitted papers will be peer-reviewed (at least two reviews per paper). All accepted and presented papers will be submitted for publishing as open-access CEUR Workshop Proceedings, by CEUR-WS.org
Workshop Schedule and Activities
- Welcome & Overview
- Presentation on XAI principles in education
- Discussion on stakeholder roles and contexts
- Paper presentations
- Break
- Presentation on methods and tools
- Discussion on challenges and opportunities
- Hands-on group activity with XAI tools
- Group and open discussion on design, ethics, and future directions
- Closing & reflection
Workshop Organizers
Program Committee
Olga Viberg, KTH Royal Institute of Technology.
Paul Prinsloo, University of South Africa.
Gabriella Casalino, University of Bari Aldo Moro.
Irene-Angelica Chounta, University of Duisburg-Essen.
Francisco Javier Bellas, Universidade da Coruña.
Jordan Barría Pineda, University of Pittsburgh.
Yifei Gao, University College London.
Venue
The XAI-Ed workshop will be held within the AIED2025 conference at the Conference Venue of the University of Palermo, Palermo, Italy.
Let us know if you'll be attending! (optional)
Let us know if you'll be attending! (optional)
We would like to know more about you, to ensure that the workshop meets your goals and expectations.
Contact
For any question or inquiry, do not hesitate to contact us via:
Hasan Abu-Rasheed: rasheed@studiumdigitale.uni-frankfurt.de
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