portal:: Libraries and the Academy 2020 Johns Hopkins University Press Award for Best Article

The Best Article Award Committee has announced the selection of "'Just Because You Can Doesn't Mean You Should': Practitioner Perceptions of Learning Analytics Ethics" as recipient of the 2019 Johns Hopkins University Press Award for the best article featured in portal: Libraries and the Academy during 2019. Written by Kyle M. L. Jones, the article appears in volume 19, number 3 (2019), pages 407–28 and can be accessed at https://muse.jhu.edu/article/729196.

As noted in the committee's report, this timely and well-written essay uses qualitative research to address ethical issues regarding learning analytics, the gathering and analysis of a wide range of data about students to assess their academic progress and improve their educational outcomes. The article provides valuable context for the uptake of learning analytics in academic libraries in response to findings and recommendations from the Association of College and Research Libraries (ACRL) 2010 publication The Value of Academic Libraries: A Comprehensive Research Review and Report by Megan Oak-leaf. Learning analytics is a topic of growing importance for libraries as they attempt to demonstrate their role in student success and their value to higher education.

Members of the portal Editorial Board called Jones's essay "a good introduction to the ethical questions surrounding learning analytics" and "an important contribution to the literature." Jones raises important questions, including whether assessment findings justify potentially compromising student privacy and whether the information libraries gather by using learning analytics is worth the ethical dilemmas that doing so can create. The article suggests that institutional review boards may lack familiarity with the emerging issues of data ethics, which may result in overly lenient examination of library learning analytics research. It theorizes that current learning analytics practice may not be consistently guided by the American Library Association (ALA) Code of Ethics. This inconsistency has fueled heated debate, particularly in discussions of data ethics. Jones also offers practical and actionable suggestions for how libraries might navigate these challenging waters.

Comments from the board consistently noted the timeliness of this topic and Jones's balanced and thoughtful treatment. One member observed that Jones's essay "demonstrates, through a literature review, analysis of current practice, a focus on professional ethics for librarians (especially user privacy), and methodologically sound interviews with library practitioners, just how much of an ethical minefield [learning analytics] is for academic libraries." Another called the essay "an effective article for me to point to for others to read and join the conversation locally." Still another said, "This is a conversation that needs to happen."

Kyle M. L. Jones is an assistant professor in the Department of Library and Information Science in the School of Informatics and Computing at Indiana University–Purdue University, Indianapolis. His research primarily focuses on student privacy issues that emerge from mining sensitive or confidential student data and information, which institutions use to match courses and majors to students' interests, to support interpersonal relationships, and to improve learning outcomes. His secondary research interest concentrates on emerging educational technologies and their efficacy in library and information science (LIS) graduate programs and for LIS professional development. Jones is currently coprincipal investigator for two Institute of Museum and Library Services (IMLS) research grants: the first to investigate faculty perspectives of student privacy and their practices in relation to learning analytics, and the second to develop continuing education for academic library practitioners to address student privacy and deal with the emerging ethical issues of learning analytics. He teaches courses on database design and information policy, and publishes extensively on the topics of student confidentiality and data ethics with respect to library learning analytics.

Articles selected for portal's Best Article Award are chosen through a multistep process by which Editorial Board members nominate a pool of articles from each volume. The entire board then votes on a short list of the most nominated articles. Criteria used in the selection process examine the quality of the research methodology; the extent to which the article places library issues in a broader academic or higher education context; the degree to which...