RC Trust incubator project: Investigating the impact of AI-generated, adaptive prompts on students' understanding and learning of programming

Duration: 10/2024 -09/2025

Funded by:  UA Ruhr

Researchers: Prof. Dr. Nikol Rummel, Fabian Albers

Partners: Nils Köbis (Universität Duisburg-Essen), Irene Chounta (Universität Duisburg-Essen)

Externe Webseite:  https://rc-trust.ai/

Project description:

What is the optimal prompting condition in order to have an LLM generate hints that best help students understand and learn from compiler errors? How can we help students with exhibiting prompting behavior that leads to optimal tailored feedback/support from the LLM model? Working toward answering these research questions, we will enhance an interactive programming environment (e.g., Jupyter Notebook) with an AI student model that will allow us to monitor and model students’ knowledge state (Katz et al., 2021; Chounta, 2019).