Publications, Presentations & Grants

Instead of allowing tech companies to set the agenda, higher education must actively shape how generative AI is adopted. Drawing on large-scale research at SDSU, the call for coherent, program-level AI plans, better modeling of responsible AI use, and meaningful funding to support curricular redesign and faculty development. Ultimately, they warn that, because opting out is impossible at this point, universities must assert control, build balanced partnerships with industry, and ensure AI strengthens rather than weakens critical thinking and educational integrity.

Given the documented divergence between AI developers’ and educators’ views of AI’s potential harms and benefits, educators must work closely with vendors to develop business plans and ensure the quality and integrity of AI models. Educators must also contribute expert testimony and data to support AI legislation; and there is much we can do in the classroom as well, pending funding. More consistent approaches to AI within majors to increase students’ sense of coherence and more instruction on what legitimate AI use looks like are crucial. If higher education doesn’t set the terms for our incorporation of AI, the costs of lost learning and intellectual downskilling will be catastrophic.

How do US undergraduates engage with GenAI in learning? Drawing on 8,500 surveys and student interviews, we found two approaches: process-oriented, ethically engaged, co-regulating “AI learners,” and product-focused, efficiency-driven “AI users.” Becoming an “AI learner” depended less on individual student traits than faculty modeling, disciplinary norms, and institutional support. Relevant strategies for AI-integrated instruction and student-centered faculty development are described.