The Value of Academic Libraries: Library Services as a Predictor of Student Retention

Abstract

This study examined the predictive relationship between library use by individual students and their retention status in university settings. The methodology builds on a small number of previous studies to examine library use at the individual level to determine if use of specific library services is predictive of retention for freshmen and sophomores. Binary logistic regression yielded results that indicate a strong positive predictive relationship between library use of any kind with both freshmen and sophomore retention. These results suggest that academic libraries add value to institutional retention efforts. tudent retention is an increasingly critical issue for institutions of higher education, with far-reaching effects on many other areas of life, including the well-being of students and society. Institutions of higher education face greater calls for accountability regarding different performance metrics, among them student retention and completion of degree programs. State legislatures and higher education coordinating agencies increasingly connect state funding with graduation rates.1 Institutions of higher education are often pressured to keep costs contained, while serving more students who lack the skills necessary to succeed in college. Frequent limitations to increases in tuition as a means of offsetting lost state appropriations lead to both enrollment and retention as high-stakes endeavors, not just for university administrators but also for students and society.2 Seidman provided a clear summary of the wide-ranging impact of student dropout:Attrition results in a severe loss of resources by society, by students, and by colleges that spend to provide programs and services to help retain and graduate students. When a student leaves college prematurely, any debt incurred must be repaid, despite the failure to graduate, and the college loses future funding in the form of tuition and fees and auxiliary services (bookstore, food service, and so forth) generated over time. The surrounding college community that supports the college, restaurants, movie theaters, and so on, also suffers an adverse economic impact when students leave. In addition, students may be turned off to the educational system in general, never returning to benefit from educational opportunities that may have helped with job

Data Management Practices in Academic Library Learning Analytics: A Critical Review

“…A significant number of studies, 46 of the 54 examined, imply transferring individual-level data between the library and a central university office (Allison, 2015;Black & Murphy, 2017;Bowles-Terry, 2012;Çetin & Howard, 2016;Collins & Stone, 2014;Coulter, Clarke, & Scamman, 2007;Cox & Jantti, 2012a, 2012bde Jager et al, 2018;Fransen & Peterson, 2016;Goodall & Pattern, 2011;Haddow, 2013;Haddow & Joseph, 2010;Jantti, 2016;Jantti & Cox, 2013;J. L. Jones, 2010;Kot & Jones, 2015;LeMaistre, 2015;LeMaistre et al, 2018;Massengale, Piotrowski, & Savage, 2016;McCarthy, 2017;Montenegro et al, 2016;Murray et al, 2016;Nackerud et al, 2012Nackerud et al, , 2013Odeh, 2012;Pepper & Jantti, 2015;Renaud et al, 2015;Scarletto et al, 2013;Scott, 2014;Soria et al, 2014Soria et al, , 2017aSoria et al, , 2017bSoria et al, , 2013Soria et al, , 2015Squibb & Mikkelsen, 2016;Stemmer & Mahan, 2015Stone, Pattern, & Ramsden, 2012;Thorpe et al, 2016;…”

“…Library analytics projects span a range of practices with respect to data minimization. Eight projects encompass a particularly wide range of data collection (Kot & Jones, 2015;Massengale, Piotrowski, & Savage, 2016;Murray et al, 2016;Nackerud et al, 2013;Soria et al, 2014Soria et al, , 2017aSoria et al, , 2013Soria et al, , 2015. One expansive example is Massengale et al (2016), in which library data was collected on "students physically entering the building, students receiving instruction from a librarian, students visiting the Research Help Office (RHO), students checking out laptops, students using interlibrary loan, students reserving study rooms, students placing requests for 3-D printer usage, and students accessing our online resources" (p. 230).…”

“…Most projects are in between these two extremes, though many studies described a wish to have more specific data or overall more data for analysis (Çetin & Howard, 2016;B. Cox & Jantti, 2012a;Haddow, 2013;Murray et al, 2016;Pepper & Jantti, 2015;Samson, 2014;.…”

“…L. Jones, 2010;Renaud et al, 2015;Scarletto et al, 2013) but there is no published evidence that these patrons are informed of the full use of their ID data and its potential hazards. Another three studies use the strategy of collecting IDs by always requiring user authentication for access to electronic resources (Cherry et al, 2013;Massengale et al, 2016;Murray et al, 2016), but this does not equate with informed consent either when the data is being used for the secondary analysis purpose. Analyses of space usage raise similar issues (Kome, 2017; "Measure the Future -Libraries & Open Hardware, " n.d.).…”

Embracing the Generalized Propensity Score Method: Measuring the Effect of Library Usage on First-Time-In-College Student Academic Success

“…Nine recent studies examined by the authors found that a combination of library space, instruction, and resource usage by FTIC students was positively associated with retention, GPA, or both (Kot & Jones, 2015;Soria et al, 2013Soria et al, , 2014Soria et al, , 2017aSoria et al, , 2017bHaddow, 2013;Murray, Ireland, & Hackathorn, 2016;Stemmer & Mahan, 2016;Stone & Ramsden, 2012). Note that of the studies examined, most focused on library space and resource usage effects on student outcomes which included workstation logins, study room usage, e-resources and print books usage, interactions with library personnel, use of ILL and reference, and other similar resources.…”