In this article we considered the complexities of "making moral decisions when resources are limited" (e.g. Joynt & Gomersall, 2005). The effective allocation of increasingly limited resources, although not new (e.g. Hartley, 1995), challenges higher education institutions to take concerns regarding student failure and dropout seriously. Institutions increasingly rely on the analysis of data through algorithms to determine students' chances on success, or risk of dropout and allocating resources according to a system of triage. Students are classified in different categories based on an assessment of their educational risk and the cost of increasing or ensuring their chances on success.
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