Author

F. Howar

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Book Open access Aug 2026

Exploring LLM-generated hints for students’ Error Recovery in programming

This paper explores how students in Higher Education use LLMs for programming and how learning environments should scaffold such support. We conducted a repeated-measures exploratory field study in two programming courses, a Bachelor’s and a Master’s level course, using a JupyterLab environment with LLM support. Studen...

Bibeg Limbu, Kai-Mao Sheng, Mona Münstermann et al. · Message Understanding Confer... · 0 citations

Open access Aug 2026

SLλ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${SL}^{\lambda }$$\end{document}: A Scalable Algorithm for Register

This article implements an effective and scalable register automata (RA) learning algorithm that significantly reduces the number of membership queries required for inferring models by up to an order of magnitude and achieves this by combining a tree-based cost-efficient data structure with mechanisms for computing sho...

Simon Dierl, P. Fiterău-Broştean, F. Howar et al. · Journal of automated reasoni... · 0 citations

Book Open access Aug 2026

Exploring LLM-generated hints for students’ Error Recovery in programming

Findings may indicate that LLM-supported programming environments should supply context-sensitive scaffolding, automatically providing the model with the learner’s code and error trace rather than relying on the learner to communicate that context.

Bibeg Limbu, Kaimao Sheng, Mona Münstermann et al. · Message Understanding Confer... · 0 citations