Guidelines for the Evolving Role of Generative AI in Introductory Programming Based on Emerging Practice

In the rapidly evolving Generative AI (GenAI) landscape, source code and natural language are being mixed and used in new ways. This presents opportunities for rethinking teaching practice in Introductory Programming (CS1) courses that includes, but goes beyond, assessment. In this paper we examine the reasons why and how instructors who are early adopters of GenAI are using it in their teaching, and why others are not. We also explore the changes and adaptations that are currently being made to practice. This is achieved by synthesizing insights from several recent studies that have collected primary data from introductory programming instructors who are teaching with, considering teaching with, or actively not teaching with GenAI. Due to the fast pace of GenAI development and adoption, the fixed-pace and cyclical nature of education, and the relatively slow pace of research (including ethical approvals) and publication cycles, research with primary data from instructors is only being published relatively recently. In computing education, there is not yet enough published research with primary data from CS1 instructors to warrant a systematic literature review, although in the next year this will likely be possible. Based on an analysis of the nascent research that has been published, we propose emerging and flexible guidelines on how CS1 instructors could adapt their practice based on what others have done so far. These guidelines highlight important factors to consider when integrating GenAI in CS1 courses, which for many is only beginning.