What Gets Them Talking? Identifying Catalysts for Student Engagement Within a Computing Ethics Course

The expansion of undergraduate CS programs brings different forms of student identity, sociotechnical perspectives, and intersectionality into the classroom. These background factors affect student understanding of the world, and, consequently, their work in computing ethic classes. Instructors of computing ethics courses therefore must facilitate topics that are not only pertinent to modern technologies but that are also interesting for students from a range of backgrounds. In this work, we introduce a low-overhead, natural language processing tool that can assist instructors in extracting student talking points from over 600 discussion forum posts in a large-scale undergraduate computing ethics course. When compared to large language model approaches, this n-gram-based scripting tool is more effective in selecting popular quotes and summarizing course discussion. This tool is simple in implementation and can be easily adapted by instructors to prepare for classroom discussion.