PEAF 2026 invites submissions on the pedagogical evaluation of automated feedback systems in educational settings. We particularly welcome submissions from early-stage work and position papers, and encourage shorter submissions within the page limit.

Submission Type

Extended Abstracts — up to 4 pages (including references).

Submissions may be work-in-progress or position papers. All accepted submissions will be published in CEUR-WS proceedings, a free open-source publishing service.

Topics

The workshop covers themes across the wider education domain. We welcome submissions on the following and other related topics:

  • Shared practical applications of education theory to evaluate the pedagogical quality of feedback, beyond accuracy
  • Methods for evaluating the pedagogical quality of feedback, including computable metrics and qualitative methods
  • How personalising feedback to the learner and to their preferences on how to interact with automated feedback can affect the pedagogical quality of the feedback
  • How culture and disciplines factor into the pedagogical quality of automated feedback, especially accounting for biases in generative AI tools
  • Ethical and societal considerations of automating feedback in education, including but not limited to fairness, bias and equity across learner populations, socialisation, sense of belonging, curiosity and critical thinking
  • How automated feedback impacts teaching and learning — including classroom activities, learning objectives, attitudes to learning, and societal and cultural changes

Formatting

Submissions must follow the CEUR-WS format.

How to Submit

Submissions must:

  1. Be extended abstracts of up to 4 pages (including references).
  2. Follow the CEUR-WS formatting template (see Formatting above).
  3. Be submitted as a single PDF.
  4. Not be under simultaneous review at another venue.

Submissions are handled via EasyChair: here.

Proceedings

All accepted submissions will be published in CEUR-WS proceedings — a free, open-access publishing service widely indexed in DBLP and Scopus.

Camera-ready instructions will be sent to authors upon acceptance notification.

Questions

Contact the organisers at m.messer@imperial.ac.uk.