Assessing library contributions to university outcomes: the need for individual student level data

Purpose - The purpose of this paper is to suggest move beyond examining the impact of the library from the library's perspective but rather to collaborate with university-wide assessment efforts to determine the impact of the library from the student's perspective, the instructor's perspective, or the researcher's perspective.Design methodology approach - A limited number of studies have been conducted in an attempt to determine the impact of the use of the library's physical or electronic resources, reference services, and the library as place. Considerably more studies have been prepared that have examined library instruction programs and information literacy programs although the results paint a very mixed picture. A majority of the evaluation efforts for information literacy programs have used opinion surveys, skills testing, and observed actual behavior using rubrics and other methods. A consistent criticism of such studies has been the small sample size and the lack of replication of such studies. Clearly an approach that collaborates with the university's assessment efforts and allows the library to determine the correlation levels between use of a library collection or service and a desired university outcome will be welcome by all academic libraries.Findings - The suggested approach is to combine library usage data with university data. In the best of worlds the library data would be combined with both indirect measures of learning (such as student persistence, graduation rates) as well as direct measures of student learning such as the Collegiate Learning Assessment, Collegiate Assessment of Academic Proficiency, and the Measure of Academic Proficiency and Progress. If university libraries were to embark on a coordinated program of data analysis then the results would have greater credibility and impact within the university.Practical implications - The paper provides a set of recommendations for combining library data (where the identification of each user is preserved) with institutional performance and demographic data for each user (after which the unique identification information can be eliminated so as to preserve the privacy and confidentiality rights of the user). The resulting large data set can be then used to explore possible relationships between use of library services and important outcomes - student success, student retention, graduation rates, and so forth that is necessary in order to demonstrate the value of the academic librar