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Monday, November 7, 2016
Using Analytics to Find the Perfect College Student
Most people plugged into the college admissions game understand the stakes. We all know that students are evaluated on their grades, test scores, and so-called soft factors-like extracurricular activities and volunteer experience. What people might not know is that some colleges also rely on something else when measuring their candidates: analytics.
These are essentially data points recorded on students, based upon things like geography, race, family income, ethnicity, gender, and high school attended. The process of statistical analysis is beyond the scope of this blog, but using analytics to study people and their habits is nothing new. It is also potentially very valuable for colleges and universities.
Let's be honest-the idea that institutions are reducing human beings to data points isn't likely to sit well with people. At least at first glance. Predictive analysis is riddled inherent biases-take, for instance, the correlation between college graduation amongst students of color or students from low-income families. Colleges have a vested interest in making money and staying high in the rankings, so they are going to pick students likely to perform well.
Still, this doesn't mean that analytics can't be used in a positive way.
Colleges themselves can use analytics to track student performances. Some universities are becoming more invested in retaining their students rather than separating the wheat from the chaff. So when they see a freshman struggling with grades, they can approach and intervene, rather than tossing the student onto academic probation.
As tools of professional management, analytics can be enormously helpful in empowering colleges to better serve their student populations, by having a better understanding of demographics, financial need, and academic interests.
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