Taking a fresh look: Reviewing and classifying reference statistics for data-driven decision making

Abstract

This article describes the results of an extensive review of reference transactions from multiple service points at the University of Utah's J. Willard Marriott Library. The review enabled us to better understand the types of questions asked at our service points and resulted in a new set of codes for categorizing reference transactions that focus on recording the kinds of expertise needed to answer each question. We describe the differences between our model and other scales for collecting reference questions. Our method for reviewing reference transactions and developing new codes may be useful to other libraries interested in updating how they collect reference statistics.