Publication

Partnering with AI: A pedagogical feedback system for LLM integration into programming education

Niklas Scholz, Manh Hung Nguyen, Adish Singla, Tomohiro Nagashima

ECTEL2025 · 2025

@inproceedings{scholz2025partnering,
  title     = {Partnering with AI: A pedagogical feedback system for LLM integration into programming education},
  author    = {Niklas Scholz and Manh Hung Nguyen and Adish Singla and Tomohiro Nagashima},
  booktitle = {ECTEL2025},
  year      = {2025},
  doi       = {10.1007/978-3-032-03873-9_31},
}

Abstract

Feedback is essential for effective learning, yet providing timely, pedagogically-sound feedback remains challenging. With the rise of large language models (LLMs), research has turned to automated feedback in programming education. However, prior work often overlooks key feedback adaptation criteria, such as student performance. We present a novel multi-agent LLM feedback framework, derived from established feedback models and input from school teachers. We implemented a learning platform for Python programming with LLM-based feedback based on the framework and evaluated its effectiveness with eight computer science teachers. Results show that teachers considered our feedback pedagogically sound, comprehensive, and effective in supporting student learning. However, we also found major challenges, including the adaptation of feedback to classroom contexts, which underscores the importance of involving human teachers in the feedback-giving process.