Library Analytics Case Study: Informing and Transforming Library Instruction Programs

Abstract

This session was presented at the CNI Fall 2017 Membership Meeting.

As the use and application of analytics mature, so do opportunities for libraries to better understand how data can inform decision-making practices, identify literacy needs, and increase user interactions with library services. At the University of Michigan Library, we are engaged in a variety of assessment activities, from surveys to rubrics to focus groups. Library analytics offer us another method to further engage in assessing our impact on learning and strengthening opportunities to share our expertise with the campus. Given data complexities (access, storage, analysis), policy implications (privacy, IRB), and the emergent nature of analytics, we launched a specific experiment to test the question of how library analytics could transform our instruction program. We scoped an experiment around existing data from the library instruction request system and the University data warehouse. What we learned has direct implications for our program planning (demographics, sequencing, curriculum development), resource allocation, and delivery of library instruction. This session will provide an overview of our experiment, dive into the challenges we faced, outline our methodology, highlight preliminary results, and invite attendees to envision experiments for their own campus.

https://ld4l.org/

Presentation​