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Daily Dashboard | University uses predictive analytics to increase retention rate Related reading: Evolving privacy law 'exciting' for IAPP Westin Scholar

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Researchers at The University of Arizona collect tracking data from student ID cards to analyze interactions and predict which students are most likely to drop out, Gizmodo reports. In a news release, the university explained that their analysis can predict a student’s likelihood to drop out 73 percent of the time, starting from day one of classes and improving over time. Lists of the most at-risk students are cultivated and sent to advisors twice a semester, who can then intervene and help improve the retention prospect if they choose. It is reported, however, that the student ID policy site does not disclose how data is used in monitoring and tracking student activity.
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