Examines AI integration in sociology pedagogy, suggesting improved student engagement with algorithms.
Artificial intelligence (AI) is increasingly reshaping social life, yet AI literacy remains underdeveloped in undergraduate sociology. This article offers a sociology-forward framework for integrating AI into the curriculum. Drawing on Bourdieu’s theory of practice, it emphasizes experiential learning, justice-oriented instruction, and critical sociotechnical reflexivity. Using survey data from an upper-division Social Research Methods course at a public research university, I show that students quickly gained technical proficiency with AI tools, but deeper engagement with algorithmic power required explicit pedagogical scaffolding. I introduce “reflexive algorithmic capital” to describe the composite disposition students develop as they learn to interrogate AI’s symbolic authority, epistemic assumptions, and social consequences. Findings show how intentional pedagogy can help students connect AI to broader questions of inequality, legitimacy, and knowledge production, offering concrete strategies for preparing them to navigate and critically evaluate the algorithmic systems that organize academic, economic, and civic life.
No takes yet. Share an insight, caveat, or question.
Tamanna M. Shah (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: