XAI-Ed@LAK2027: Explainable AI in Education at the Learning Analytics and Knowledge Conference 2027 Recife, Brazil, March 8-9, 2027

Actionable Explainable AI to Enhance Learning and Teaching
The 4th International Workshop on Explainable AI in Education, held with the 17th International Conference on Learning Analytics & Knowledge (LAK27)

XAI-Ed @ LAK27 is a full-day workshop on what explanations from AI and learning analytics systems actually do in education. In education, the quality of an explanation is still judged mostly by model-side proxies, such as fidelity or agreement between explainers. Turning insight into action is still one of the hardest steps in the analytics cycle. This fourth edition of the XAI-Ed series focuses on that gap through two questions:

How do explanations influence learning processes and learning outcomes?
How do explanations help differently positioned stakeholders (students, teachers, parents and caregivers, and educational leaders) take action?
Equity, fairness and transparency run through both questions, because explanations decide who can scrutinise, contest or act on automated inferences. The day combines paper and demonstration sessions with two hands-on design activities and a cross-stakeholder panel. All of them work from a shared scenario pack. Together they will produce a shared framework and a research agenda for actionable explainable learning analytics.

Submission Guidelines

All papers must be original and not under review at another journal or conference at the same time. All submissions must be in English and anonymised for double-blind review. Each paper will be reviewed by at least two members of the programme committee. We welcome the following categories:

• Full papers (6–10 pages) describing original empirical studies, methods, frameworks, systems or datasets on explainability in education and learning analytics.
• Short papers and posters (4–6 pages) describing work in progress, position papers, conceptual or theoretical contributions, and practitioner reports.
• Demonstrations (4–6 pages) describing explainable systems, tools or interfaces, to be shown live during the papers and demo carousel

Page limits include references. Papers must use the workshop template and be submitted through [submission system].

Important dates (all deadlines 23:59 AoE)

• Submission deadline: 4 December 2026
• Notification of acceptance: 18 December 2026
• Camera-ready version: 28 February 2027
• Workshop: 8/9 March 2027 (exact day TBA)

List of Topics

• Effects of explanations on learning processes, self-regulated learning and learning outcomes
• Theoretically grounded explanation, linking XAI and explainable learning analytics (XLA) to learning theory and learning design
• Actionability of explanations and the path from explanation to educational intervention
• Multi-step and co-constructed explanations with stakeholders (social XAI and XLA)
• Explanation design for different stakeholders, and how inferences are communicated
• Explainability of LLM-based systems, including faithfulness and calibrated reliance
• Interpretable models for learner modelling, knowledge tracing and success prediction
• Fairness auditing, explanatory equity and contestability of automated inferences
• Evaluation frameworks for XLA, and governance and institutional adoption of explainability

Committees

Program Committee

• TBA

Organizing Committee

• Hasan Abu-Rasheed, Goethe University Frankfurt, Germany
• Jakub Kuzilek, FernUniversität in Hagen, Germany
• Luc Paquette, University of Illinois, USA
• Benjamin Paaßen, Bielefeld University, Germany
• Qianhui (Sophie) Liu, University of Houston, USA
• Hassan Khosravi, The University of Queensland, Australia
• Jeroen Ooge, Utrecht University, Netherlands
• Tanja Käser, EPFL, Switzerland
• Mutlu Cukurova, University College London, United Kingdom
• Christian Weber, University of Siegen, Germany
• Vinitra Swamy, Scholé AI, Switzerland

Publication

XAI-Ed @ LAK27 proceedings will submitted for publishing as open-access CEUR-WS proceedings. Workshop papers are not part of the LAK27 Companion Proceedings.

Venue

The workshop will be held in Recife, Brazil, in March 2027 as a full-day pre-conference workshop at LAK27, the 17th International Conference on Learning Analytics and Knowledge. Attending the workshop requires registration for the main conference.

Contact

All questions about submissions can be emailed to: rasheed@sd.uni-frankfurt.de