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
- Raha Moraffah (ORCID: https://orcid.org/0000-0002-6891-2925)
- Crystal H. Brown (ORCID: https://orcid.org/0000-0003-2300-6774)
- Oleg V. Pavlov (ORCID: https://orcid.org/0000-0001-6771-6677)
- Daniel N. Treku
- Patricia Agupusi
- Shamsnaz Bhada
- Stephen McCauley
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