Reassessing Assessment: Student Privacy and Library Data Use In Learning Analytics

This session will present the results of research analyzing the privacy policies of academic libraries and institutions in the Big Ten Academic Alliance, a consortium of 18 large, research-intensive universities in the U.S., in light of the growing use of predictive learning analytics. Learning analytics is defined as “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs” (Siemens & Long, 2011). Academic libraries are turning to learning analytics in an attempt to prove their value to their institutions, applying these analytics to their user data to try to demonstrate a connection between the use of library resources and student success (Oakleaf, 2018). Student use of library spaces, computer activity, digital resources accessed, and books checked out can be associated with an individual student’s grades, retention, and on-time graduation. Some librarians view this as a controversial invasion of student privacy (Jones, 2019), yet these opinions are countered by those who argue that the use of library data in learning analytics can provide correlational evidence demonstrating the library’s contribution to positive student outcomes (Oakleaf, 2018). Before this can happen, however, librarians will need to revise their view of privacy such that it is acceptable for them to use personally identified library records in student data analysis (Oakleaf, 2018).

This project critically explores how higher education institutions and their libraries use student data to predict student success, and how this may affect future interpretations of user privacy in libraries. Participants will gain knowledge of how student data is being used in learning analytics, and why library privacy policies should be revisited to address the possible use of identified user data in library assessment and institutional analysis. Markers of strong privacy policies also will be introduced.