Developing Scalable Library Research Training: Search Protocols, Modular Learning, and AI-Assisted Support

University of California San Diego Library launched a project to transform health sciences library instruction – traditionally delivered in classroom settings – into a scalable, self-directed learning model that fosters independent research skill development. The project developed a structured search protocol to support systematic literature searches and library resource navigation. It follows a linear workflow, incorporating problem-solving actions, systematic search templates, an information needs taxonomy, and worked examples to support information retrieval. Unlike general library research guides, this protocol helps users apply search heuristics and methodologies to support System 1 (intuitive) and System 2 (analytical) problem-solving for more effective search strategy development. Its modular design enabled the development of instructional content in multiple formats, including videos, web-based guides, infographics, quizzes, and instructor resources, supporting diverse learning contexts. The structured protocol and modular learning content have been piloted in classrooms, where they received positive initial feedback. Beyond modular learning, the protocol serves as a foundation for AI-assisted research support. It was used to configure a custom GPT chatbot, guiding users stepwise through systematic search query development. Initial tests showed promise, but challenges in enforcing workflows and maintaining response consistency highlight the need for refinements to enhance AI-guided research assistance. Future plans include assessing learner engagement and instructional effectiveness through user analytics and feedback to refine instructional strategies. This project establishes a scalable model for library research training and serves as a foundation for broader AI-assisted research support.Presentation for CNI Spring 2025 Pre-Recorded Project Briefing Series https://www.cni.org/topics/information-access-retrieval/developing-scalable-library-research-training