Abstract
This chapter engages information from the perspective of structural justice using a case study of learning analytics in higher education, drawing heavily on the “Drown the Bunnies” case at Mount St. Mary’s University in 2016. This case suggests the outlines of an increasingly common approach to promoting student “success” in higher education in which early academic and non-cognitive data, often from students at other universities, are used to build a student success prediction algorithm that uses a triage approach to intervention, targeting middling students while writing off those in most need of help as inefficient uses of resources. Most common ethics approaches—privacy, individualism, autonomy, and discrimination—capture at best only part of the issues in play here. Instead, I show that a full analysis of the “Drown the Bunnies” model requires understanding the ways that social structures perpetuate oppression and domination. Attention to more just organizational, politico-economic, and intellectual structures would greatly attenuate the likelihood of cases such as the Mount St. Mary’s University case, adding an important dimension to information justice. I conclude by contrasting the “Drown the Bunnies” model with an implementation of learning analytics at UVU, which did much better in part because of structural preconditions that support justice.
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- 1.
For the purpose of this paper I will use the terms “predictive analytics” to refer to predictive methods generally and “predictive student analytics” or simply “student analytics” to refer to such methods used in educational contexts. The term includes but is not limited to the narrower concept of “learning analytics,” which describes the use of such methods based on primarily academic behavioral and performance data to predict future academic performance and individuate course and program content.
- 2.
There are several higher education institutions in the United States with similar names. Mount St. Mary’s University, the object of this case study, is in Emmitsburg, Maryland. It should not be confused with Mount St. Mary’s College in Los Angeles, or Mount St. Mary College in Newburgh, New York.
- 3.
To some extent I must question whether they can be fully just; the simple act of acting on a statistical prediction seems inherently unjust in that it assumes that current conditions are permanent traits and therefore that individuals have little capacity to change themselves. That is, to my mind at least, antithetical to the entire purpose of education.
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Johnson, J.A. (2018). Structural Information Justice. In: Toward Information Justice. Public Administration and Information Technology, vol 33. Springer, Cham. https://doi.org/10.1007/978-3-319-70894-2_6
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