Teaching Programming in the Age of AI: Pedagogical Strategies for Computational Sociology
TL;DR
It is argued that programming should be treated not only as a technical skill but also as a sociological practice that enables students to fully participate in computational inquiry while engaging critically and ethically.
Abstract
As programming becomes increasingly central to sociological research and education, the rise of artificial intelligence (AI) presents both opportunities and challenges for instructors. AI tools such as ChatGPT and GitHub Copilot are transforming how students approach coding, raising important questions about what programming competencies matter most, how they should be taught, and how learning should be assessed. Drawing on emerging research, this conversation article examines the capabilities and limitations of AI tools and considers AI’s impact on student learning and skill development. We outline sociologically grounded learning goals that emphasize both technical fluency and critical judgment. We then offer evidence-informed strategies for incorporating active learning, developing metacognitive skills, and designing assessments suited to an AI-enhanced educational environment. Throughout, we argue that programming should be treated not only as a technical skill but also as a sociological practice that enables students to fully participate in computational inquiry while engaging critically and ethically.