A Framework for AI-Integrated Pedagogy in Computer Science

Abstract

Artificial intelligence is no longer a future concern — it is already embedded in how we work, learn, and teach. In academia alone, the shift is visible on both sides of the classroom. Students are using tools like ChatGPT and Claude to summarize lecture notes, condense slides, and navigate assignments. Faculty are using AI to refresh course materials, design assessments, and streamline administrative tasks. In computer science specifically, this adoption runs even deeper: GitHub Copilot assists with code generation and debugging, while Google Colab's integrated AI allows students to describe a problem in plain language and receive working code in return. The CS community is already living inside an AI-augmented workflow — yet meaningful questions remain about what this means for the overall educational experience, for both students and the educators who guide them. This poster presents a framework for integrating AI effectively and responsibly into CS education — though the principles offered extend to other disciplines as well. We examine three dimensions: the tools and technologies that genuinely support student learning; practical guidance for educators on how to incorporate AI into their teaching without surrendering creativity or becoming dependent on it; and the foundational principles of good teaching that remain relevant regardless of technological change. Our central argument is that balance, not prohibition, is the most constructive response to AI in the classroom. Through current adoption statistics and actionable guidelines, this poster aims to show not just that AI integration is happening — but how it can be done well.

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