Deep and interesting questions sit underneath the well-worn question of “should we ban or embrace AI in first-year CS”. Early CS curricula have long embraced assumptions that now warrant reconsideration (e.g., that we should emphasize writing code over reading it). This talk highlights several assumptions and makes a concrete proposal: first-year computing courses can and should emphasize core software-engineering practices—such as specification, property-based testing, and code audits. We’ll explore this idea through both research literature and promising results from two experimental courses (one last spring for students with some CS background, and one this semester for novices). Ultimately, we hope to provide a research-based foundation for discussions about the affordances and pitfalls of agents in early computing education.
Kathi Fisler is faculty and Director of Undergraduate Studies for Computer Science at Brown University. Her CS journey has gone through multiple research areas (diagrammatic reasoning, formal methods for software design, software security, and the intersection of computing education and programming languages). Her work broadly focuses on understanding how people work with and within formal systems. She’s currently turning that theme towards understanding how to teach and learn around coding agents. Kathi has done substantial outreach work in CS and Data Science education for K-12 through the Bootstrap project and several state efforts to develop CS standards. She received SIGPLAN’s Distinguished Educator Award (along with Shriram Krishnamurthi) in 2023, and the ICER Lasting Impact award for her 2014 paper on using functional programming to teach the Rainfall problem. She enjoys jigsaw puzzles, a good hike, and great pizza.