The New York Times recently published an article describing the decisions of universities to employ data analytics as a tool to monitor the activity of students more closely. These universities, which included Ball State University, Arizona State University and Georgia State University intend to use an individual student’s data to examine his or her class attendance, gauge engagement in extracurricular activities or help students stay on course toward achieving their degree. For example, Ball State specialists call or e-mail students who have stopped “swiping” into their typical activities. While there is potential in this technology to create a more personalized student experience, if the University were to implement a similar system, they should be aware of concerns regarding its possible invasiveness into students’ lives.

Data collection offers a comprehensive way to support students. For students with lower socioeconomic status, a focus of some universities’ efforts, this means more individualized attention, as universities can flag students and check in with them throughout their college career. Keeping in touch and emphasizing relevant resources for academic achievement can help low-income students stay on track. In fact, the graduation rate of lower-income students at Arizona State has already significantly increased in the past three years. This system may prove helpful to other students as well, especially larger schools like the University where students can feel lost and disconnected. Reminders provided through this system could help all students remain active and focused on their studies.

Big data can play a critical role in recognizing aggregate student behavior through collection in a centralized manner. Universities already have access to dining habits and gym visits. However, these systems are separate from one another. The recently developed systems allow for more comprehensive information to be analyzed from a single pool of data. This, in turn, offers a huge variety of benefits, not only in drawing correlations between student behaviors and making findings available to students themselves, but also in using the information to fine-tune academic and other university-led services. For example, generally poor attendance and grades in a certain class could signal further investigation into the course. Measuring the times students visit services like gyms could prompt opening for different hours to accommodate these trends.

The University should consider using these new tools to assess the student body as a whole. However, the University should be wary of targeting students and contacting them individually, as other institutions have been doing. The more personalized aspects of the new systems can quickly turn into privacy violations, and calls could seem intrusive or accusatory to many students. These systems leave ample opportunity for misunderstandings as well. For instance, if a student stops attending lectures because they prefer to study at home, or if they drop out of a club whose meetings they previously attended, it should not necessarily be the responsibility of the University to dictate how the student shapes their academic experience.

If the University decides to implement similar strategies to those of Ball State, they should use less invasive techniques to identify students who are in need of support. An alternative to direct phone calls could be group e-mails encouraging students to come to advising appointments, as well as other reminders to nudge students toward extracurricular involvement. It’s also important to recognize higher education is a service students pay for, and if they do not wish to be approached by staff, they should have the choice to opt out of the program. Lastly, the University should consider the significant monetary investments required to process this data. If less expensive avenues exist to directly aid students, those should be taken into account first.

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