This session shares the ONE List, a tagging framework developed at the University of Nebraska Omaha to make visible the authority signals often missing from OER discovery systems: author credentials, publisher type, editorial oversight, revision history, accessibility features, and more. Grounded in information literacy and the ACRL frame “Authority Is Constructed and Contextual," this project aims to develop an objective system for categorizing OER according to standard notions of publishing authority through application of relevant metadata. This provides potential faculty adopters with ready markers of publishing authority when scanning for materials. The session will also discuss a newer phase of the work: investigating the feasibility of AI assistants in a human-in-the-loop workflow to assist with tagging while preserving transparency, evidence, and librarian review. Attendees will leave with a practical model for improving OER discoverability, trust, and adoption support.
It is not claimed that this system should be the primary method for categorizing and recommending OER to potential adopters, nor that traditional notions of publishing authority are the exclusive qualifiers of potential source quality. Rather, this presents a way to promote objective categorization, address common adopter concerns, reward the existence of still-important publishing attributes, and ultimately improve the toolkits we use in adoption and promotion.
Attendees of this session will be able to:- Identify common metadata gaps that may be initial barriers to OER adoption.
- Describe how an objective tagging attribute framework can surface markers of academic authority.
- Apply fundamental information literacy tenets to OER discovery and selection.
- Adapt key elements of the ONE List model to local OER, library, or instructional design workflows.
- Evaluate the benefits and limits of using human-in-the-loop AI to support metadata creation in open education settings (this portion of the project is still in-progress).
