The following article was recently shared on SSRN.
Title
Authors
Kyle M. L. Jones
Indiana University-Indianapolis (IUPUI)
Alan Rubel
University of Wisconsin, Madison – Information School; University of Wisconsin, Madison – Program in Legal Studies
Ellen LeClere
iSchool, University of Wisconsin, Madison
Source
via SSRN
December 16, 2019
Forthcoming: Journal of the Association for Information Science and Technology
Abstract
Higher education institutions are mining and analyzing student data to effect educational, political, and managerial outcomes. Done under the banner of “learning analytics,” this work can—and often does—surface sensitive data and information about, inter alia, a student’s demographics, academic performance, offline and online movements, physical fitness, mental wellbeing, and social network. With these data, institutions and third parties are able to describe student life, predict future behaviors, and intervene to address academic or other barriers to student success (however defined). Learning analytics, consequently, raise serious issues concerning student privacy, autonomy, and the appropriate flow of student data. We argue that issues around privacy lead to valid questions about the degree to which students should trust their institution to use learning analytics data and other artifacts (algorithms, predictive scores) with their interests in mind. We argue that higher education institutions are paradigms of information fiduciaries. As such, colleges and universities have a special responsibility to their students. In this article, we use the information fiduciary concept to analyze cases when learning analytics violate an institution’s responsibility to its students.
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