Conference Agenda

This paper examines how Generative AI coding tools impact computer science education and describes instructional experiments conducted across several courses that inform the design of a new Special Topics course, Software Development in the GenAI Era. The newly designed course introduces students to the evolving landscape of AI-assisted development through five modules: The Stochastic Engine, Prompt & Context Engineering, Vibe Coding, Agentic Coding, and Specification-Driven Development. Drawing from classroom experiences, the paper highlights how students respond to AI tools, where they benefit most, and where they struggle with the verification and documentation practices required for responsible AI use. The goal is to offer a practical, evidence-based framework for preparing students to become architects and supervisors of AI-driven software systems, equipped with the foundational CS knowledge and modern AI-native skills needed in today’s rapidly evolving development environment.

The era of GenAI began with the release of ChatGPT 3.5 in November 2022. GenAI systems that can generate passable code for undergraduate-level programming-focused courses require a shift in faculty mindset in what is taught in programming-focused courses and in how student learning is assessed. Rather than trying to create assignments that the current GenAI systems cannot easily generate code for, this paper suggests approaching the GenAI era by updating assessments of student learning and incorporating GenAI into the coursework. Small class sizes at small colleges provide an excellent environment for experimenting with new pedagogical approaches.