Teaching and Learning AI from Course Design to Capstone Projects: Instructor Lessons and Student Reflections

Abstract

This session combines instructor perspective with student voice to share lessons from designing and teaching Sociology of Artificial Intelligence, a hands-on undergraduate course that explored sociological debates surrounding AI while offering applied training in AI tools for social science research. The instructor will briefly share the design strategy behind the course, including how it was structured as a bootcamp-style learning experience and incorporated topics such as prompt design, research applications, ethics, bias, hallucinations, privacy, transparency, and responsible AI use. The session will also highlight how students practiced AI-assisted research question development, critical engagement with AI scholarship, survey and interview design, qualitative coding, visualization, writing support, and custom AI assistants.

Two student co-presenters will reflect on their experience in the class, how their thinking about AI evolved over the semester, and how they approached their final capstone projects. In these projects, students identified a social problem and developed an AI-driven approach to address it, culminating in a live demo/presentation focused on functionality, potential social impact, limitations, and ethical reflection. This combination of course design and student perspective offers faculty an engaging and useful model for teaching with and about AI in intentional, critical, and student-centered ways.

Presenters