Generative AI for education (GAIED): Advances, opportunities, and challenges

P Denny, S Gulwani, NT Heffernan, T Käser… - arxiv preprint arxiv …, 2024 - arxiv.org
This survey article has grown out of the GAIED (pronounced" guide") workshop organized by
the authors at the NeurIPS 2023 conference. We organized the GAIED workshop as part of a …

Evaluating language models for generating and judging programming feedback

C Koutcheme, N Dainese, S Sarsa, A Hellas… - Proceedings of the 56th …, 2025 - dl.acm.org
The emergence of large language models (LLMs) has transformed research and practice
across a wide range of domains. Within the computing education research (CER) domain …

Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation

N Kotalwar, A Gotovos, A Singla - arxiv preprint arxiv:2406.05053, 2024 - arxiv.org
Generative AI and large language models hold great promise in enhancing programming
education by generating individualized feedback and hints for learners. Recent works have …

Propagating Large Language Models Programming Feedback

C Koutcheme, A Hellas - Proceedings of the Eleventh ACM Conference …, 2024 - dl.acm.org
Large language models (LLMs) such as GPT-4 have emerged as promising tools for
providing programming feedback. However, effective deployment of LLMs in massive …

[PDF][PDF] Toward diagnosis of semantic errors in Python programming platforms for beginners

B Kirouchenassamy, A Yessad, S Jolivet, V Luengo - researchgate.net
Reliable semantic error analysis of student codes can be used to improve both the learning
and teaching experience, through a better understanding of students' codes. We propose a …

Simulated Interactive Debugging

Y Noller, E Chandra, S HC, K Choo, C Jegourel… - arxiv preprint arxiv …, 2025 - arxiv.org
Debugging software, ie, the localization of faults and their repair, is a main activity in
software engineering. Therefore, effective and efficient debugging is one of the core skills a …