Friday, April 17, 2026 from 10:30 am – 11:30 am
The updating of OER can be inconsistent or reactive, which may result in it not being informed by current research, disciplinary practice, and student needs. And when updates are made, ancillary materials such as quizzes, assignments, study guides, and instructional supports can become misaligned. How can AI as act as research and editorial support for OER updates? This session outlines a repeatable process faculty can adapt within their own courses and disciplines. Rather than treating AI as a content generator, the process centers on faculty judgment and disciplinary expertise. Faculty determine when review is needed, use AI to assist with scanning and synthesizing emerging scholarship, and then make informed decisions about revising core content, ancillaries, and related instructional materials. The focus is not on fixed timelines, but on an intentional workflow that supports academic accuracy, consistency, and sustainability across both primary materials and supporting assets. The approach emphasizes transparency, human-in-the-loop decision making, and responsible AI use, ensuring that updates strengthen rather than dilute the academic quality of the OER. Participants will leave with a practical framework for using AI to reduce the labor of updating OER and aligned instructional materials while maintaining faculty voice, pedagogical integrity, and curricular control. The session positions OER updating as an ongoing academic responsibility and a key component of sustainable ZTC efforts, rather than a one-time task completed at adoption.
Register for AI as Research and Editorial Support