AI Resources in Higher Education: What Instructors Need and How We Deliver

Abstract As generative AI reshapes higher education, instructors across the globe have become increasingly interested in integrating AI into the classroom, but they require trusted, timely, and relevant resources for such integration. To enable the development of an open educational resource (OER) that could be remixed and adapted to different teaching contexts and support inclusive access, this study examined what instructors want and need from an open resource on AI in teaching and learning in higher education and documented a process for developing professional development resources in a time of rapid technological change. This study employed a multiphase mixed-methods design. First, a statewide needs assessment survey was conducted with 149 instructors to identify needs, challenges, and priorities across diverse institutional and disciplinary contexts. Participants prioritized three core content domains for the resource—AI literacy, pedagogical strategies, and ethics—and favored interactive, adaptable, and open resources grounded in practical classroom applications. These findings were used to develop an OER prototype, on which 75 instructors provided feedback, affirming the utility of the resource and suggesting areas for further refinement. This study contributes an educator-informed process for translating instructors’ needs into the design and formative evaluation of an adaptable, openly licensed faculty development resource. This evidence-based, educator-driven approach demonstrates how those tasked with faculty development on AI can develop and refine timely resources that meet the needs of educators from diverse contexts, offering a flexible, scalable, and community-oriented pathway for bridging institutional resource gaps and advancing inclusive faculty development in the age of AI.