America’s community colleges promise more than an affordable pathway to a bachelor’s degree. Pupils pay substantially less for the first couple of years of college, transfer to a four-year college, then earn their diploma in the same amount of time.
That’s the theory, at least. Most community college students— over 80 percent of them — enter with the intention to transfer, but just 20 percent actually do so within five years of entering college. Even when students are made aware of these odds, it has not proved a deterrent from enrolling — and dropping out — of community colleges across America. This divide represents a classic case that behavioralists call an intention-action gap.
So, why do four out of five community college students who plan on transferring end up failing to do so? Put yourself in the shoes of a 20-something-year-old community college student. You’ve worked hard for the past few years, making credits and paying much less tuition than you would have in the event that you had enrolled instantly in a four-year college or university. Nevertheless, now you want to transfer colleges to make certain that you can complete your bachelor’s degree. How do you figure out where to go? Ideally, you would like to find a college that will take as many of your credits as possible, where you’re most likely to graduate from, and where the degree you eventually earn will actually count for something in the real-world workforce.
A college counselor might be able to help you figure this out, but most community colleges have at least 1,000 other students assigned the same counselor, so students often complain that the advice they receive from college counselors aren’t specific to their academic goals.
So, where does Big Data come into the equation? The combination of Big Data and behavioral insights is certainly one of the most interesting uses for Big Data analytics that we’ve seen lately. Now, Big Data is making it possible to help students navigate these complex decisions like only Big Data can, allowing them to successfully follow through with their initial academic goals. Big Data analytics now allow college administrators to identify where students will be most successful academically and suggest the best transfer that they could hope for.
Big Data has the potential to contribute to the next generation of behavioral science advances in education. These strategies provided by Big Data can help people overcome complex identity problems, such as the decision to transfer, by utilizing Big Data technology to give personalized information about educational pathways that both build on the students’ prior experience and career in which they are most likely to succeed in the future.
While it may seem as novel as a “choose your own adventure” book, many students, including those at University of California, have already put their future firmly in the hands of Big Data and aligned their college careers with Big Data’s predicted outcome.
In a single study, scientists used college-level academic achievement Big Data from the College Board and publicly available information on college traits to send high-achieving, low-income students semi-customized packets of some of the best universities and colleges where students had a good chance of being admitted considering their academic performance.
That’s just the beginning. The real potential behind utilizing Big Data at college institutions is having the computer-generated results optimized for the personalization of each and every student, then automatically analyzed, printed and mailed out to universities in lieu of students actually filling out applications. This new application for Big Data in the education arena will be just the first of many advances on the way.
This new application for Big Data in the education arena will be the first of many innovative advances that focus on using Big Data analytics to make the lives of students — and college administrators — easier. But not everyone is happy with this.
Many college students are in opposition of having their academic fate determined by Big Data, saying that it removes their freedom of choice in the matter, despite what the statistics say. It will still be years, decades even, before the ongoing case studies yield any sort of results that will be used to make a decision.