Artificial Intelligence and the Sociological Imagination: Cultivating Reflexive Algorithmic Capital through Sociology Pedagogy

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.

Authors

Institutions

Publication Details

Journal
Teaching Sociology
Published
2026-08-03
DOI
https://doi.org/10.1177/0092055x261469146
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial Intelligence and the Sociological Imagination: Cultivating Reflexive Algorithmic Capital through Sociology Pedagogy

Tamanna M. Shah
Teaching Sociology
Computational and Text Analysis Methods
article

Artificial Intelligence and the Sociological Imagination: Cultivating Reflexive Algorithmic Capital through Sociology Pedagogy

Tamanna M. Shah
article en

Abstract

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.

Teaching Sociology
Ohio University (US)
Quality Education
Openalex Percentile: Top 3%
Computational and Text Analysis Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.