9:30 - 10:00: Optional and Informal: Gathering / Networking [Slides]
10:00 - 10:30: Introduction and Logistics
10:30 - 11:00: Coffee Break
11:00 - 11:30: Lightning Talks [Slides]
11:30 - 12:30: CSEDM presentations #1 (15 mins presentation + 4 minutes Q & A, Chair: Peter Brusilovsky)
Grouping and Differentiating Programming Exercises Using Minimal Programming Constructs. Ka Weng Pan, Bryn Jeffries and Irena Koprinska (University of Sydney) [Paper|Slides]
Investigating the Impact and Student Perceptions of Guided Parsons Problems for Learning Logic with Subgoals. Sutapa Dey Tithi, Xiaoyi Tian, Min Chi and Tiffany Barnes (NCSU) [Paper|Slides]
Example Explorers and Persistent Finishers: Exploring Student Practice Behaviors in a Python Practice System. Allison Poh, Anurata Prabha Hridi, Jordan Barria-Pineda, Peter Brusilovsky and Bita Akram (UMass, NCSU, UPitts) [Paper|Slides]
12:30 - 1:30: Lunch break
1:30 - 2:20: CSEDM presentations #2 (8/5 mins presentation + 4/2 minutes Q & A, Chair: Shan Zhang)
Exploring the Link between Cognitive Abilities and Data Science Skills using Alternative Raven’s Progressive Matrices. Farshid Farzan, Hasan Mashrique and Andrew M. Olney (UMemphis) [Paper|Slides]
Combining Log Data and Collaborative Dialogue Features to Predict Project Quality in Middle School AI Education. Conrad Borchers, Xiaoyi Tian, Kristy Elizabeth Boyer and Maya Israel (CMU, NCSU, UFL) [Paper|Slides]
Can Motivated Students Do More Activities? Arun Balajiee Lekshmi Narayanan, Michael Asher, Peter Brusilovsky and Paulo Carvalho (UPitts, CMU) [Paper|Slides]
AlgoAce: Retrieval-Augmented Generation for Assistance in Competitive Programming. Anav Agrawal and Jill-Jênn Vie (Inria) [Paper|Slides]
A Specification For CS Education Dataset Documentation. Samiha Marwan, Austin Cory Bart and Thomas Price (NCSU, UD) [Paper|Slides]
2:20 - 2:30: Short break
2:30 - 3:30: CSEDM presentations #3 (15 mins presentation + 4 minutes Q & A, Chair: Conrad Borchers)
Leveraging Large Language Models to Promote AI-Infused STEM Problem-Solving for Middle School Students. Ananya Rao, Krish Piryani, Shiyan Jiang, Tiffany Barnes, Jennifer Albert, Marnie Hill and Bita Akram (NCSU, UPenn, Citadel) [Paper|Slides]
Explainable AI in the Loop: An Instructor-Transformer Collaboration for Improving Explainability and Reliability of Feedback in Introductory Programming Classrooms. Muntasir Hoq, Bradford Mott, Seung Lee, Jessica Vandenberg, Narges Norouzi, James Lester and Bita Akram (NCSU, Cal) [Paper|Slides]
Reinforcement Learning for Programming Feedback: Aligning Small Language Models Without Human Preferences. Charles Koutcheme, Nicola Dainese and Arto Hellas (Aalto) [Paper|Slides]
3:30 - 3:50: Coffee break
3:50 - 4:50: Keynote: Supporting and Studying Student Learning From Feedback with LLMs in CS1. Ryan Baker, Maciej Pankiewicz
4:50 - 5:15: Wrap up + Future of CSEDM
Ryan Baker is Professor at the University of Pennsylvania (Adelaide University from September 2025), and Director of the Penn Center for Learning Analytics. Baker has developed models that can automatically detect student engagement in over a dozen online learning environments, and led the development of an observational protocol and app for field observation of student engagement that has been used by over 150 researchers in 7 countries. Predictive analytics models he helped develop have been used to benefit over two million students, over a hundred thousand people have taken MOOCs he ran, and he has coordinated longitudinal studies that spanned over a decade. Baker was the founding president of the International Educational Data Mining Society, is Associate Editor of the Journal of Educational Data Mining, was the first technical director of the Pittsburgh Science of Learning Center DataShop, currently serves as Co-Director of the JeepyTA project, and founded two Masters degree programs in Learning Analytics. Baker has co-authored published papers with over 500 colleagues and has been cited over 30,000 times.