Substitution vs. Collaboration: How Faculty Conceptions of Human-AI Relationships Shape Pedagogical Choices
In this study, we've attempted to nudge the focus of discussion from what faculty do with AI to the underlying belief systems where those choices are crystallized--in particular, demonstrating how tacitly held paradigms about human-technology relationships shape pedagogical design. For educational leaders, the key insight is that AI enters a space already dense with beliefs about technology, power, and collaboration—meaning effective support requires surfacing these frameworks, not just offering best practices.
Our study (IRB#2035233-1) examines how instructors navigate the impacts of Generative AI on college writing as they adapt to technological paradigm shift. Through surveys and focus groups involving 178 faculty across 16 institutions, we document how AI changes the writing they assign and the extent to which they welcome or resist these changes. Our key finding: instructional choices are shaped by powerful, but seemingly unconscious (Turel and Kalhan, 2023), assumptions about how humans and machines will coexist. Faculty adopting a substitution paradigm (“If AI can do summaries, students won't”) make different choices from those adopting a collaborative paradigm (“AI is good at summaries; so, use AI to coach students to summarize”). While AI-pedagogy scholarship recognizes that teaching and learning are inherently relational and that interpersonal trust networks been fundamentally disrupted by the emergence of Generative AI (Blackwell-Starnes, 2025; Luo, 2024; Ryan 2025; Winthrop, 2025), it is less aware that we and our students also exist in relation to AI itself. By mapping out these relational models, we make visible the full spectrum of human-AI possibilities, while redirecting pedagogical attention toward the underlying frameworks where choices are crystallized.