Crystal H. Brown, Patricia Agupusi, Shamsnaz Bhada, Stephen McCauley, Daniel N. Treku, Raha Moraffah, Oleg V. Pavlov · Systems 2026 · 2026
DOI: 10.3390/systems14091055
Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).
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.
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