Developing an Engaging Learning Experience in AI for Science for Interdisciplinary Students

This proposed project seeks to make advanced AI research topics more engaging and accessible to students from computer science and other science and engineering disciplines through innovative teaching methods, like role-playing and problem-solving. The project’s primary goal is to enrich the educational experience of interdisciplinary students, fostering peer interactions and enhancing their ability to critically analyze and apply AI methods to real-world scientific problems. The AI for Science course, initially delivered in Fall 2024, received high evaluation scores for both course and instructor excellence, with a notable enrollment of over 30% from various non-CS and ECE disciplines. This indicates the course’s success in consolidating state-of-the-art AI material for a diverse audience.

Building on the positive reception of group paper presentations in the course’s first offering, future iterations will emphasize peer learning by increasing interactions among students from different academic backgrounds. The project introduces two key innovations: structured role-playing sessions building upon the previous paper presentations, and entirely new problem-solving sessions. These strategies aim to deepen students’ understanding and engagement, leveraging the diverse perspectives brought by participants from fields such as Physics, Biomedical Engineering, Civil Engineering, Mechanical and Aerospace Engineering, and Climate Sciences.

Project Team

Funding

This team was awarded $10000 in funding in Spring 2025.