We invite original, unpublished research contributions presenting novel findings, methods, or theoretical frameworks on the responsible use of AI in education.
Full papers should present original, mature, and unpublished research that makes a significant contribution to the field of AI in education. Submissions must not be currently under review elsewhere.
Papers must be written in English and formatted according to the Springer LNCS style.Full papers are limited to a minimum of 11 pages and a maximum of 15 pages (references, figures, tables, proofs, appendixes, acknowledgments, and any other content count toward the page limit).
Submissions must be anonymized for double-blind review. Author names, affiliations, and any self-identifying references must be removed from the manuscript.
Each submission will be reviewed by at least 3 members of the Program Committee. Papers will be evaluated on the basis of originality, significance, technical quality, and clarity of presentation.
Please submit via CMT — select the WAILS 2026 Full and Short Papers track at submission.
Accepted papers will be published by Springer in the Lecture Notes in Computer Science (LNCS) series and indexed in DBLP, Google Scholar, and Scopus.
The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.