Call for Papers

Workshop Scope

This edition of XAI-Ed 2026 seeks to consolidate methodological, theoretical, and empirical perspectives on explainability in education. We aim to complement technical implementations with shared frameworks that integrate explainability into pedagogical design, stakeholder engagement, and institutional decision-making.

The workshop encourages contributions that:

• Theorize the role of explainability in supporting learning processes, reflection, and teacher facilitation;
• Investigate methods, data representations, and visualization approaches that enhance interpretability;
• Evaluate the usefulness and faithfulness of explanations from multiple stakeholder perspectives;
• Explore the intersection of large language models (LLMs), generative AI, and explainable learning analytics;
• Discuss the ethical, legal, and policy dimensions of transparency and accountability in educational AI.

Through paper presentations, interactive sessions, and collective discussion, XAI-Ed 2026 aims to build a coherent research agenda for explainability as a cornerstone of human-centered, trustworthy learning analytics.

Topics of Interest

Submissions may address (but are not limited to):

• Explainability and transparency in learning analytics
• Evaluation metrics and frameworks for educational XAI/XLA
• Pedagogical and cognitive foundations of explanations
• Stakeholder-sensitive explanation design and user evaluation
• Fairness, bias, and accountability in AI-enabled LA systems
• Institutional and policy challenges in adopting XAI and XLA
• Ethical, legal, and regulatory aspects of transparency and explainability in LA
• Role of LLMs and generative AI in supporting explainability and learner reflection in LA
• Case studies, prototypes, and empirical findings demonstrating XAI/XLA in educational contexts

Submission Types

• Full Research Papers (6–10 pages): Novel empirical results, methods, frameworks, systems, or datasets related to XAI/XLA.
• Short Papers (4–6 pages): Including work in progress, positional papers, conceptual frameworks, theoretical perspectives, and practitioner reports.

Page limits include references. Optional appendices (e.g., instruments, algorithms, dataset details) do not count toward the limit but will be treated as supplementary (reviewers are not required to read them).

Formatting & Submission

• All submissions should be PDF file using the workshop’s template. An Overleaf project is available for LaTeX users here. Simply make a copy of the project (“Menu” > “Copy Project”). Alternatively, you can download an offline version here. This download also includes ODT (LibreOffice) and DOCX (Microsoft Word) template files.
• Submissions must be anonymous for double-blind review. Remove all author names and identifying information (e.g., grant numbers), and refer to prior work in the third person (e.g., “Previously, Smith et al. did … [1]” rather than “In our prior work [1]”).
• Submissions are to be made via XAI-Ed 2026 Workshop on EasyChair.

Submission link: https://easychair.org/conferences/?conf=xaied2026

Important Dates (AoE)

All submission deadlines are 23:59 AoE time.

Review & Presentation

• Double-blind peer review by the program committee.

• All submissions will be reviewed by at least two members of the program committee.

  Evaluation will consider:

  • Relevance to XAI-Ed and LAK 2026 themes;
  • Originality, rigor, and clarity;
  • Theoretical and methodological soundness;
  • Ethical awareness and stakeholder relevance;
  • Contribution to understanding or advancing explainability in education.

• Presentation format: Poster-style sessions with spotlight talks to maximize interaction.

Proceedings

Accepted papers will be submitted for publication in open-access CEUR-WS proceedings.

Please note that workshop papers are not published as part of the LAK 2026 Companion Proceedings.

Contact

• Submission and CfP (EasyChair): https://easychair.org/conferences/?conf=xaied2026
• General inquiries: rasheed@sd.uni-frankfurt.de