“We're being tracked at all times”: Student perspectives of their privacy in relation to learning analytics in higher education

• Published in: Journal of the American Society for Information Science and Technology Vol. 71; no. 9; pp. 1044 - 1059
• Main Authors: Jones, Kyle M. L., Asher, Andrew, Goben, Abigail, Perry, Michael R., Salo, Dorothea, Briney, Kristin A., Robertshaw, M. Brooke
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.09.2020; Wiley Periodicals Inc
• Subjects: College students; Data analysis; Data mining; Ethics; Higher education; Higher education institutions; Informed consent; Intellectual property; Learning; Learning analytics; Mathematical analysis; Privacy; Students; Undergraduate Students; Undergraduate study
• ISSN: 2330-1635; 2330-1643
• DOI: 10.1002/asi.24358

Higher education institutions are continuing to develop their capacity for learning analytics (LA), which is a sociotechnical data‐mining and analytic practice. Institutions rarely inform their students about LA practices, and there exist significant privacy concerns. Without a clear student voice in the design of LA, institutions put themselves in an ethical gray area. To help fill this gap in practice and add to the growing literature on students' privacy perspectives, this study reports findings from over 100 interviews with undergraduate students at eight U.S. higher education institutions. Findings demonstrate that students lacked awareness of educational data‐mining and analytic practices, as well as the data on which they rely. Students see potential in LA, but they presented nuanced arguments about when and with whom data should be shared; they also expressed why informed consent was valuable and necessary. The study uncovered perspectives on institutional trust that were heretofore unknown, as well as what actions might violate that trust. Institutions must balance their desire to implement LA with their obligation to educate students about their analytic practices and treat them as partners in the design of analytic strategies reliant on student data in order to protect their intellectual privacy.