Publications, Presentations & Grants

This paper presents the design, implementation, and outcomes of a faculty-focused micro-credential aimed at improving generative artificial intelligence (GenAI) literacy and ethical readiness among educators in higher education. Motivated by a disconnect between widespread student use of generative AI tools and limited faculty preparedness, the micro-credential offers a self-paced, modular course grounded in experiential learning and focused on responsible technology use.

Ahead of the Curve: What the Nation’s Largest University System Is Learning about AI” offers the key findings of a systemwide AI survey of students, faculty and staff that the CSU conducted in 2025 to understand how they perceive AI, use it, and what they need to engage with it effectively. With nearly 100,000 responses, the survey is the nation’s most comprehensive higher ed AI dataset.

Many educators have responded to AI's emergence with isolated, course-level changes. But students find this piecemeal approach confusing. This article calls for program-level integration of AI literacy across entire majors, advancing a systems-level framework for embedding AI readiness into degree learning outcomes, curricular maps, and ongoing improvement processes. It describes the ACORN Toolkit, which provides resources to support strategic, coherent, by-faculty-for-faculty whole-program AI-ready renovations.

Drawing on a 2024 student survey (n = 10,162) and 48 brief interviews, this paper explores how gender may influence attitudes toward GenAI, including perceptions of bias, trust, and educational impact. The analysis, framed within the context of public and post-conventional anthropology, highlights gendered differences in how students interpret GenAI’s risks and benefits, discusses how institutional tools such as surveys can shape what perspectives are made visible or overlooked, and offers concrete recommendations in support of effective and inclusive Gen AI implementation.

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.

This paper explores how AI tools are marketed to US college students and how students experience AI promotions. Many feel compelled to adopt AI to stay competitive, reflecting an internalized entrepreneurial imperative. Findings indicate a need for more open student-teacher exchange regarding AI, and marketing literacy education to support students in critically analyzing promotional strategies. Results are being used to update the AI micro-credential.

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.

Funded by the California State University (CSU) via the Artificial Intelligence Educational Innovations Challenge​ (AIEIC) award program, this project will develop a toolkit containing templates, worksheets, and activity guides to support intentional, faculty-led integration of AI at the curricular level. Designed for updating entire majors or programs, the ACORN Toolkit will help faculty embed AI competencies coherently and proactively — versus reactively or piecemeal, course-by-course. In doing so it will help faculty reduce gaps and redundancies, enhance program relevance for students, and boost workforce readiness. The ACORN Toolkit will be available at campuses across the CSU by Fall 2026.

In 2024, SDSU, UC San Diego, and the San Diego Community College District formed the Equitable AI Alliance to expand access to AI tools, training, and skill-building for students, faculty, and staff. The alliance promotes equitable AI education across institutions and was one of five projects awarded a $1.5 million AI Grand Challenge grant from the California Education Learning Lab under the Governor’s Office of Planning and Research.