Introduction

WAILS 2026 is the 3rd edition of the Workshop on Artificial Intelligence with and for Learning Sciences. Building on two successful editions (Salerno 2024, Cagliari 2025), this year focuses on the responsible, ethical, inclusive, and equitable use of AI in educational contexts. If AI makes learning easier, are we still learning or merely optimizing task completion? AI systems can support reasoning, creativity, and decision-making. Yet they can also obscure understanding, reinforce bias, and reduce cognitive effort. WAILS 2026 is grounded in a simple premise:

AI should not replace thinking, it should make thinking more visible, critical, and meaningful.

We invite the community to critically examine and shape the role of AI in education through evidence, design, and theory. The accepted papers are going to be published by Springer into an LNCS post-workshop proceedings volume, and submitted for indexing to DBLP, Google Scholar, and Scopus.

Location
Sorbonne Université - Campus Pierre et Marie Curie
Paris (France)



Topics
WAILS 2026 welcomes contributions from a wide range of disciplines, including computer science, education, cognitive science, psychology, sociology, ethics, economics, and human-computer interaction. Topics of interest include, but are not limited to:

Responsible AI in Education
• Transparency, explainability, and accountability in AI-powered learning systems
• Communicating AI limitations (e.g., hallucinations, uncertainty) to users
• Large language models in educational contexts
• Privacy, data protection, and governance of student data
• Learning analytics and educational data mining
• Ethical frameworks and governance for AI in education
• AI policy and regulation in educational institutions
• Designing systems that make risks visible, interpretable, and actionable

Equity, Fairness & Inclusion
• Bias detection, measurement, and mitigation in educational AI
• Inclusive and accessible AI-supported learning environments
• Addressing inequalities in access, representation, and AI literacy
• AI for supporting diverse and underserved learners
• Sociological and cultural factors in AI adoption across educational contexts
• Digital divide and unequal access to AI-powered tools
• Gender, race, and disability bias in AI-powered learning systems
• Community-based and participatory approaches to equitable AI design

Human-Centered AI
• Learner agency vs. over-reliance and automation bias
• Cognitive impacts of AI use (e.g., shallow learning, reduced effort, illusion of understanding)
• Intelligent tutoring systems and conversational agents
• Evolving teacher roles: augmentation, adaptation, or deskilling
• Designing for reflection, reasoning, and metacognition
• Cognitive science and psychological dimensions of AI-supported learning
• Student wellbeing and mental health in AI-mediated learning
• Adaptive and personalized learning environments

Serious Games & Inclusive Learning
• AI-enhanced serious games for education and training
• Game-based approaches for AI literacy and critical thinking
• Serious games for social-emotional learning and inclusion
• Participatory design of serious games with marginalized communities
• Narrative and storytelling in AI-driven educational games
• Emotional and motivational dimensions of game-based learning
• AI-generated content in serious games: opportunities and risks
• Accessibility and universal design in serious games
• Transfer of learning from game-based to real-world contexts

Interdisciplinary & Social Perspectives
• Sociological and psychological dimensions of AI in education
• Cognitive science approaches to AI-supported learning
• Economic and policy implications of AI adoption in education
• Cultural and contextual factors in AI-enhanced learning environments
• AI and the future of educational institutions
• Philosophical and ethical dimensions of AI in education
• Cross-cultural perspectives on AI-supported learning
• AI and educational equity from a policy perspective

Teaching AI
• Teaching AI literacy across formal and informal learning contexts
• Curriculum design for responsible AI education
• Teaching AI concepts across disciplines and age groups
• Pedagogical approaches to explaining AI limitations and risks
• Teacher training and professional development for AI-integrated classrooms
• Assessing student understanding of AI systems and their societal impact
• Evaluating the effectiveness of AI education programs and interventions
• Student and teacher perceptions of AI: trust, fear, and agency






Submission

Platform

Papers must be written in English and submitted electronically in a PDF format, through the CMT submission system, by selecting the type “Full Paper/Short Paper” or “Doctoral Consortium” based on their length. The link to the submission system will be available soon.

Format

We encourage three types of submissions (reviewers will comment on whether the size is appropriate for each contribution), in the Springer single-column format.

Fullpapers (11 to 15 pages at most; references, figures, tables, proofs, appendixes, acknowledgments, and any other content count toward the page limit) should report on substantial contributions of lasting value. They should reflect innovations or studies and have a more thorough discussion of related work.
Short papers (6 to 10 pages at most; references, figures, tables, proofs, appendixes, acknowledgments, and any other content count toward the page limit) typically discuss exciting new work that is not yet mature enough for a long paper – they are complete reports on a smaller or simpler-to-describe but complete research work on advances that can be described, set into context, and evaluated concisely. Note that novel but significant proposals will be considered for acceptance despite not having gone through sufficient experimental validation.
Doctoral Consortium ( 6 pages at most; references, figures, tables, proofs, appendixes, acknowledgments, and any other content count toward the page limit) invites doctoral students to present their research to experienced scholars who will provide constructive feedback and guidance. Students are encouraged to participate if they are at least six months from completing their dissertation and have identified a research area or dissertation topic. Submissions should consist of a concise paper outlining the candidate’s doctoral research. Papers are expected to clearly describe the research problem and motivation, situate the work within relevant literature, and present the proposed approach or methodology.


Templates

Following the Springer publication workflow, authors should submit manuscripts for review in the Springer single-column format. Instructions for authors are given below:
- Latex
- Overleaf
- Word

Non-anonymity

Submissions for “Full Paper” and “Short Paper” must be anonymized for double-blind review. Author names, affiliations, and any self-identifying references must be removed from the manuscript.
Submissions for the “Doctoral Consortium” are not anonymized; the student's name and affiliation should be included in the paper.


Submission policy

WAILS has a no dual submission policy, which is why submitted manuscripts must not be simultaneously under review nor submitted for review elsewhere whilst under consideration for WAILS. A violation of this concurrent submission policy will be deemed a serious infraction of scientific ethics, and appropriate measures will be implemented in response.

Ethical and human subjects considerations

WAILS expects papers to include a discussion of the ethical considerations, as well as the impact of the presented work and/or its intended application, where appropriate. WAILS further expects all the authors to comply with ethical standards and regulatory guidelines associated with human subjects research, including research involving human participants and research using personally identifiable data. Papers reporting on such human subjects research must include a statement identifying any regulatory review the research is subject to (and identifying the form of approval provided), or explaining the lack of required review.

Review Process & Camera-Ready Submission

Review process

Reviewers will evaluate papers based on their significance, originality, rigor, and contribution to the field. Papers that are out of scope, incomplete, or lack sufficient evidence to support the basic claims, may be rejected without full review. Furthermore, reviewers will be asked to comment on whether the length is appropriate for the contribution.

Camera-ready information

The accepted papers will be subject to further revision to meet the requirements of the camera-ready format required by Springer. We recommend the usage of LaTeX/Overleaf to minimize the extent of reformatting. Users of the Word template must use either the version for Microsoft Word for Windows, Macintosh Office 2011, or Macintosh Office 2016 (other formats like Open Office are not admitted) to avoid incompatibility issues. Instructions for preparing the camera-ready versions of accepted papers will be provided after acceptance. Camera-ready versions of accepted papers will be submitted via CMT.

Registration and Presentation Policy

Each accepted paper must be accompanied by a full author registration, completed by the early registration deadline. Each accepted paper must be presented in person to be included in the proceedings, published by Springer and available via the SpringerLink Digital Library. The official publication date is when the proceedings are made available online by Springer.

General Chairs
Angelica Lo Duca, Francesca Maridina Malloci, Daniela Rotelli