out new ways to diversify revenues. Concurrently, universities are struggling with losing students after their freshman year. Using student data and data analytics to predict which students are at risk of dropping out seems like an easy solution to the problem. Once identified through data mining, universities can target these at-risk students to retain them. In doing so, the university ensures it does not lose tuition from those at-risk students. However, universities fail to consider the privacy concerns that arise by bringing big data to college campuses. Student autonomy and student choice suffer from the use of big data at a university. The use of big data then creates an environment of surveillance, which impacts students' learning. Further, big data impairs students' ability to innovate. Privacy violations contravene a university's mission and purpose; thus, privacy harms are something universities should care about. Universities could self-regulate to protect student privacy, but this seems unlikely because universities have no incentive to stop data mining. Additionally, the current regulatory regime is unprepared to address the harms caused by big data. The shortcomings of the federal statutory regime are particularly salient when contrasted with other regimes, such as the California Consumer Privacy Act and the European Union's General Data Privacy Regulations. This Note proposes ways to fix the current regulatory regime, along with recommending new legislation that would provide privacy to students.
University Use of Big Data Surveillance and Student Privacy,
48 Fla. St. U. L. Rev.