Teaching with and About Artificial Intelligence: An Interdisciplinary Convergence–Divergence Framework for AI Literacy in Higher Education

Artificial intelligence is a rapidly evolving technology whose capabilities are expanding quickly, leaving instructors across higher education to determine how to integrate it into teaching with little shared guidance. This paper reports on a Faculty Learning Community comprising seven faculty members from computer science, management information systems, systems engineering, economics, development studies, political science, and geography at a technological university in the northeastern United States. Through collaborative autoethnography, the group developed a convergence-divergence framework for AI-integrated pedagogy, visualized as a daisy: a shared core of AI literacy, ethical and risk awareness, and governance frameworks, surrounded by discipline-specific petals reflecting each field's distinct conceptualization and application of AI. Seven disciplinary vignettes illustrate the framework in practice, revealing a common pattern across disciplines: AI tools offer possibilities and efficiencies while simultaneously obscuring risks and reproducing biases that require deliberate human attention. Drawing on ecological systems theory, the framework offers faculty a multi-level structure for designing AI-integrated courses that honor both shared foundations and disciplinary authenticity.

Authors

Publication Details

Journal
Systems
Published
2026-09-01
DOI
https://doi.org/10.3390/systems14091055
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Teaching with and About Artificial Intelligence: An Interdisciplinary Convergence–Divergence Framework for AI Literacy in Higher Education

Raha Moraffah, Crystal H. Brown, Oleg V. Pavlov, Daniel N. Treku et al.
Systems
Ethics and Social Impacts of AI
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Teaching with and About Artificial Intelligence: An Interdisciplinary Convergence–Divergence Framework for AI Literacy in Higher Education

Raha Moraffah, Crystal H. Brown, Oleg V. Pavlov, Daniel N. Treku, Patricia Agupusi, Shamsnaz Bhada, Stephen McCauley
article en

Abstract

Artificial intelligence is a rapidly evolving technology whose capabilities are expanding quickly, leaving instructors across higher education to determine how to integrate it into teaching with little shared guidance. This paper reports on a Faculty Learning Community comprising seven faculty members from computer science, management information systems, systems engineering, economics, development studies, political science, and geography at a technological university in the northeastern United States. Through collaborative autoethnography, the group developed a convergence-divergence framework for AI-integrated pedagogy, visualized as a daisy: a shared core of AI literacy, ethical and risk awareness, and governance frameworks, surrounded by discipline-specific petals reflecting each field's distinct conceptualization and application of AI. Seven disciplinary vignettes illustrate the framework in practice, revealing a common pattern across disciplines: AI tools offer possibilities and efficiencies while simultaneously obscuring risks and reproducing biases that require deliberate human attention. Drawing on ecological systems theory, the framework offers faculty a multi-level structure for designing AI-integrated courses that honor both shared foundations and disciplinary authenticity.

SystemsVol. 14(9)
Quality Education
Openalex Percentile: Top 31%
Ethics and Social Impacts of AI
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