We invite you to submit to the 10th CSEDM workshop, held at Festival of Learning 2026. The workshop will feature paper presentations and lively discussion. The paper deadline is May 8th, 2026 (abstract deadline May 1st).

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The 10th Educational Data Mining in Computer Science (CSEDM) Workshop

Part of Festival of Learning 2026

Date: June 27 or 28, 2026 (TBD)

Location: Seoul, Korea

Call for Papers: https://sites.google.com/view/csedm-workshop-edm26/call-for-papers

Submission Deadline: May 8th, 2026 (abstract deadline May 1st).

Submission Link in EasyChair: https://easychair.org/conferences/?conf=csedm2026

Format: In-person

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The objective of this workshop is to facilitate a discussion among our research community around Educational Data Mining (EDM) and AI in Computer Science Education. The workshop is meant to be an interdisciplinary event. Researchers, faculty and students are encouraged to share their data mining approaches, methodologies and experiences where AI is transforming the way students learn Computer Science (CS) skills. For more information, see our topics of interest.

We hope you'll contribute in three ways:

1. Research Papers (8 pages, excluding references) on AI and data mining being applied to computing education courses and data.

2. Position Papers or Work-in-progress Papers (6 pages, excluding references) on:

   1. Critical meta-reviews of CSEDM research and practice putting forward discussions of the vision and future research and practice directions for the CSEDM community.

   2. Original, unpublished work-in-progress papers (incomplete or ongoing work, ready for feedback, but not yet fully developed).

3. Descriptions of CS Tools/Datasets/Infrastructure (2 pages, excluding references), such as:

   1. Descriptions of shareable Computer Science (CS) datasets

   2. Descriptions of data mining / analytics approaches applied to specifically Computer Science datasets

   3. Case studies of collaboration where reproducible practices were used to integrate or compose two or more data analysis tools from different teams

   4. Descriptions of infrastructures that could collect and integrate data from multiple learning tools (e.g. forum posts, LMS activity and programming data)

CSEDM proceedings will be published online via CEUR (see last year's 2025 proceedings here).

For questions, please contact Shan Zhang <zhangshan@ufl.edu> and Yang Shi <yang.shi@usu.edu>.

Best,

CSEDM Organizers

Yang Shi

Shan Zhang

Peter Brusilovsky

Thomas Price

Bita Akram

Juho Leinonen

Andrew Lan

Paulo Carvalho

Ken Koedinger

Tiffany Barnes