Learning analytics is the “measurement, collection, analysis, and reporting of [student and other data] for the purposes of understanding and optimizing learning and the environments in which it occurs.” Institutions and their libraries are adopting learning analytics technologies and methods to better understand these questions about student learning: What is happening?, Why did it happen?, What is likely to happen?, and What should we do about what could happen in the future? These questions are important to academic libraries due to increasing pressures to demonstrate a return on investment, relevancy, impact and contributions to the overarching concept of student success. The efficacy of learning analytics depends in part on an institution’s ability to connect campus information systems—including those under the purview of libraries—to aggregate and analyze student data. As institutions continue to surface granular data and information about student life, the risk to student privacy grows and the tension on professional ethics commitments increases.
Librarians protect user privacy and intellectual freedom, and the profession has historically been averse to any type of sociotechnical practice that tracks user behaviors in information systems. Given the movement towards learning analytics and, potentially, away from these ethical stances, a need has emerged to research issues related to data ethics, information privacy, and policy, among other things. On key to answering these questions is discovering how students perceive these practices and how they impact their privacy. This is the approach our research has taken.Our research team is comprised of collaborators at Indiana University-Indianapolis (IUPUI), the University of Wisconsin-Madison, the University of Wisconsin-Milwaukee, the University of Illinois at Chicago, Northwestern University, Oregon State University, and Indiana University-Bloomington. Together we are in the midst of a three-year project investigating student privacy and learning analytics.
Our presentation will detail findings from the first phase of our research. During this phase, the team interviewed a diverse sample of over 100 students at eight institutions. Our questions centered around five themes:
1) Privacy: Questions regarding common conceptions of privacy as they relate to learning analytics generally
2) Data sharing and use: Questions regarding data sharing and use practices that drive learning analytics
3) Data protections: Questions regarding how data is managed and protected for the purposes of learning analytics
4) Awareness of and reactions to learning analytics: Questions regarding whether or not and how students are aware of learning analytics and to what degree they are aware
5) Libraries and learning analytics: Questions regarding library participation in learning analytics initiatives
Specific to this presentation, we will highlight findings from themes two and three, focusing on student perspectives of their privacy regarding individual and aggregate data sharing, use, and management. Extrapolating from this data, we will make recommendations regarding information policy, data security, and data practices to help participants engage in conversations in these areas at their organization. While this presentation will most likely inform academic librarians, any library—especially school and private libraries—will benefit from this presentation if they engage in instruction.
To find out more about this project, visit datadoubles.org or follow the team on Twitter using @datadoubles. The hashtag for this presentation is #DataDoublesALA19
This project was made possible in part by the Institute of Museum and Library Services (LG-96-18-0044-18).
ALA Unit/Subunit: LITA
Meeting Type: Program
Cost: Included with full conference registration.