A Layered Strategy for Integrating Generative AI into Practice-led Computer Programming Education

Paul Craig, Thomas Selig, Ling Wang

Research output: Contribution to journalArticlepeer-review

Abstract

Recent developments in Generative AI (GAI) have made skills in AI-assisted programming essential for graduates. In order to accommodate these changes we have developed a layered strategy to integrate GAI into undergraduate computer programming education while maintaining foundational coding competencies. This paper reflects on our strategy development process via Kolb’s experimental learning reflective framework, drawing on scaffoled learning and constructive alignment. We discuss challenges, stakeholder feedback, and iterative refinements to our framework to offer an insight into the challenging process of integrating GAI into learning and teaching strategy.
Original languageEnglish
JournalDeveloping Academic Practice
Publication statusSubmitted - 2025

Keywords

  • Generative AI (GAI), Reflective Practice, Scaffolded Learning

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