| Vol-4019 urn:nbn:de:0074-4019-X Copyright © 2025 for the individual papers by the papers' authors. Copyright © 2025 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# CSEDM 2025
9th Educational Data Mining in Computer Science Education (CSEDM) Workshop

### Proceedings of 9th Educational Data Mining in Computer Science Education (CSEDM) Workshop
co-located with the 18th Educational Data Mining Conference (EDM 2025)

### Palermo, Sicily, Italy, July 20, 2025.

Edited by

### Bita Akram (1)
Yang Shi (2)
Peter Brusilovsky (3)
Thomas Price (1)
Ken Koedinger (4)
Paulo Carvalho (4)
Shan Zhang (5)
Andrew Lan (6)
Juho Leinonen (7)

(1) North Carolina State University, Department of Computer Science, Raleigh, NC, USA.
(2) Utah State University, School of Computing, Logan, UT, USA.
(3) University of Pittsburgh, School of Computing and Information, Pittsburgh, PA, USA
(4) Carnegie Mellon University, Human-Computer Interaction Institute, Pittsburgh, PA, USA
(5) University of Florida, School of Teaching and Learning, Gainesville, FL, USA.
(6) UMass Amherst, Manning College of Information and Computer Sciences, Amherst, MA, USA
(7) Aalto University, School of Electrical Engineering, Espoo, Finland

## Table of Contents

### Preface

- Preface
  Bita Akram, Yang Shi, Peter Brusilovsky, Thomas Price, Ken Koedinger, Paulo Carvalho, Shan Zhang, Andrew Lan, Juho Leinonen
  Summary: There were 17 papers submitted for peer-review to this workshop. Out of these, 6 papers were accepted to the research papers track, 3 to the position papers or work-in-progress track and 2 to the description track.

### Full Papers

- Reinforcement Learning for Programming Feedback: Aligning Small Language Models Without Human Preferences
  Charles Koutcheme, Nicola Dainese, Arto Hellas
- Investigating the Impact and Student Perceptions of Guided Parsons Problems for Learning Logic with Subgoals
  Sutapa Dey Tithi, Xiaoyi Tian, Min Chi, Tiffany Barnes
- Grouping and Differentiating Programming Exercises Using Minimal Programming Constructs
  Ka Weng Pan, Bryn Jeffries, Irena Koprinska
- 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, Bita Akram
- Example Explorers and Persistent Finishers: Exploring Student Practice Behaviors in a Python Practice System
  Allison Poh, Anurata Prabha Hridi, Jordan Barria-Pineda, Peter Brusilovsky, Bita Akram
- 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, Bita Akram

### Short Papers

- Exploring the Link between Cognitive Abilities and Data Science Skills using Alternative Raven's Progressive Matrices
  Farshid Farzan, Hasan Mashrique, Andrew M. Olney
- Can Motivated Students Do More Activities?
  Arun-Balajiee Lekshmi-Narayanan, Michael W. Asher, Peter Brusilovsky, Paulo F. Carvalho
- Combining Log Data and Collaborative Dialogue Features to Predict Project Quality in Middle School AI Education
  Conrad Borchers, Xiaoyi Tian, Kristy Elizabeth Boyer, Maya Israel

### Descriptions

- A Specification For CS Education Dataset Documentation
  Samiha Marwan, Austin C. Bart, Thomas W. Price
- AlgoAce: Retrieval-Augmented Generation for Assistance in Competitive Programming
  Anav Agrawal, Jill-Jênn Vie

2025-08-16: submitted by Shan Zhang, metadata incl. bibliographic data published under Creative Commons CC0
2025-09-01: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|