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In 2016, the Florida Virtual Campus (FLVC) administered a state-wide survey to higher education students to examine how the cost of textbooks impacted their education, purchasing behaviors, and academic success. More than 22,000 students responded to the invitation, and the FLVC ultimately reported that “the high cost of textbooks is forcing many Florida higher education students to make decisions that compromise their academic success.” Survey responses specific to the home institution, University of Central Florida (UCF), revealed that of the 1,975 UCF students who completed the survey, 53% “frequently” or “occasionally” had not purchased a textbook due to cost, and 19% attributed obtaining a poor course grade to not having the textbook. This environment served as an impetus for librarians and instructional designers to begin collaborating to promote and facilitate adoption of affordable textbook alternatives. On another front, in 2014 the Florida Board of Governors (BOG) approved the Performance Based Funding (PBF) Model, which is designed to reward excellence or improvement across ten different metrics. Metrics are most closely associated with what is traditionally thought of as student success indicators, such as graduation and retention rates, degrees awarded in areas of strategic emphasis or without excess hours, and average cost to the student. Since inception of the PBF model, UCF has received over $330 million in recurring base and performance based funding, which comprises a significant portion of the institutional budget. The “cost to attend college” metric is based on tuition and fees, books and supplies, and financial aid provided to the student. The cost of books and supplies as calculated by the College Board served as a proxy until last fall, when a new methodology was approved. The current books and supplies sub-metric is now calculated using bookstore information and the percentage of open access use. Data related to affordable adoptions has been tracked since 2016, consisting of faculty name and college, course information, year and semester of adoption, type of adoption, cost of the traditional text, and savings calculated as new cost of the old textbook by number of student enrollments. These efforts also have been assessed using the COUP Framework for Evaluating OER, with results of the study widely disseminated across campus. The COUP Framework suggests various methods for assessing impact of affordable textbooks, covering cost savings, student academic outcomes, student use of the OER, and perceptions of the resource. The Institutional Effectiveness office was aware of this work and consequently asked the author to submit textbook affordability metrics in support of the “cost of books and supplies” PBF sub-metric. Session attendees will learn of the FL PBF model (a widely adopted model nation-wide), different methods used to facilitate adoptions of affordable textbooks at UCF, internal data collection procedures, and how the program was assessed using the COUP Framework and disseminated widely, in turn positioning the library and its sister online learning unit to be key entities in supporting student success and providing institutional funding metrics.

Purpose: Libraries rely on statistics to capture who their patrons are and what resources they use. Vendor-provided statistics, such as how many times a e-resource was accessed, may provide some insights about our patrons. However, they do not capture all aspects of patron behavior. This presentation explores how local evidence obtained from an EZproxy server can be utilized to illustrate a broader picture of patron behaviors. This local evidence, in combination with research evidence and librarian expertise, form the basis for the decision making approach for evidence-based assessment.

Approach: The University of Hawai‘i at Mãnoa Library for a land-, sea-, and space-grant research institution requires almost all of its patrons to be authenticated through an EZproxy server in order to access e-resources. Using EZproxy log data captured from July 2016 to June 2017 at the point of entry, this presentation will answer who is accessing resources, what resources are being used, and where and when they are accessing resources.

Findings: By analyzing around 350,000 entry points, differences in behavior between undergraduate students, graduate students and faculty members were determined: time and day, location, and databases or resources. Repeated access to particular articles or books by a single user still needs to be evaluated.

Practical implications or value: Analyzing statistics such as when and where users access e-resources may help library staff determine when staff assistance is needed and what patron groups may require addition or modified support services to encourage and facilitate use, and usage by patrons who access the same resource. Also, analyzing patron access to e-resources can clarify some aspects of patron behaviors such as which patrons access the same resource (e.g., article or e-book) multiple times, which can be used to determine if vendor-provided statistics are inflated. This may ultimately influence the decision making process in managing e-resources.

The growing expenditure on electronic resources has become a new norm for academic libraries. It is crucial for library administration to measure the impact of such investment consistently and persistently, and then develop collections strategy. Big data technology provides such an arena for management to gain insights through meaningful data and allow libraries to optimize collection operations in real time. The purpose of this study is to assess the implied value of a research library by analyzing resource-use data with BigQuery—a cloud-based data warehouse. The authors develop a systematic approach to process structured data including e-resource usage and interlibrary loan transactions, and then analyze the data in BigQuery. Meanwhile, Google Data Studio is utilized to visualize the results. The findings of this study not only manifest the implied value of the research library but also offer an innovative approach to predict the future collection needs. The methodology employed in the study also provides a new opportunity for libraries to adopt big data technology and artificial intelligence to tackle intricate problems and make smart and informed decisions in this big data era.