This paper investigates how different types of feedback interact with individual learner characteristics, such as gender and self-assessed experience and potentially impact performance, perceptions and hint-request behavior in programming education. To that end, we conducted a mixed-methods exploratory study in a highe...
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...
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.
