Leveraging Big Data to Drive Student SuccessEdward Venit | Senior Director of the Student Success Collaborative, EAB
Though it’s a high priority for every administrator at every college and university across the country, student success is a somewhat nebulous concept. It’s hard to define and that has left postsecondary leaders struggling to define what it takes to achieve it. But it’s not impossible. Drawing on recent research as well as his work with the Student Success Collaborative, Ed Venit shares his thoughts on what student success means in the modern era and discusses the impact Big Data and analytics can have on delivering a student experience that drives success.
The EvoLLLution (Evo): What are some of the key lessons you and your colleagues learned from your research on the evolution of student success, which included the development of this infographic?
Ed Venit (EV): There were really three things we learned from doing this. The first was that, unlike biological evolution, nothing seems to go “extinct” in this space. We can go back to the 1970s to see the first pioneering work on “student integration” theory. The principles student success leaders talked about then are still embedded in a lot of the student engagement programs that you might see through a student affairs office or in a first-year experience initiative. Over time additional layers of practice have emerged. In the 1980s we saw schools targeting support to specific student populations, including traditionally underserved students. In the 1990s we saw more work on the transition to college and the first-year experience. Lots of technology came into play during the 2000s, like early warning systems. What’s interesting here is that these efforts seem to layer on top of one another, instead of new things replacing the old. The expansion of what folks consider to be important in this arena has meant that it’s now a big table with lots of people around it all representing different areas of the university.
Another big conclusion is that the rate of change seems to be accelerating. We noticed that because we saw a large number of practices enter the success space roughly around the same time. It was around 2010 and we linked it to the Great Recession, combined with some demographic trends. Colleges and universities are continuously welcoming more students from lower-income backgrounds, partially because there are more college-age, lower-income students than in the past—but also because of gains made in access and opportunity, which has been a positive development. Additionally, following the recession, more students need more financial support. In many cases, these students also require more support not just to go to school, but in order to succeed, and that has resulted in a proliferation of student success efforts post-recession as schools seek to serve previously underrepresented student groups.
The third conclusion was that if you take all these things together, student success is now a story of what some have called the “return on education”—not quite return on investment, but it’s similar. It’s a focus on making sure the student gets out of their postsecondary experience what they want. And for many students that’s making sure they graduate in the shortest amount of time at the least cost possible with a positive post-graduate outcome. Orienting your student success strategy around ROE is far different—and broader—than orienting around a single metric like first-year retention.
Evo: What were some of the motivations that have now pushed colleges and universities to focus more on success when 10 years ago that focus was opening the door on access?
EV: Schools are motivated to focus on success largely because of the demands of constituencies like parents and students, as well as funding bodies. But when you actually speak to institutions about it, they’ll tell you student success is not an economic imperative but a moral one. This is the right thing to do—we have to deliver on the promise to these students. And if you think about it, that’s a huge credit to higher education that that is the number one pressure here.
Evo: What are the lessons that higher education can learn from e-commerce leaders like Amazon and what are the limits to those lessons?
EV: There’s actually a tremendous amount higher education can learn from e-commerce leaders. Universities are making investments in self-service with resources like student portals where students can see all the information they need like forms, guidance, campus news etc. The issue is that a lot of online student portals are not mobile-friendly. And they’re often organized around the administration lines of the university, not really around student problems. There’s a user experience issue here. Amazon and many other successful online businesses are designed around us, the users. So much of our experience online now is just-in-time stuff. Think about how often your phone pings you to do stuff—attend a meeting, follow up with someone, something is trending on Twitter, whatever it may be, but it’s in-the-moment stuff. We can apply that principle to student success and say, hey, it’s the beginning of the term, you should go see your advisor, here’s all the information you need to set up that appointment. You’re heading towards the middle of term, time to start thinking about declaring a major and selecting some courses, here’s what you need to do about that. Maybe one day we’ll be able to say to a student, hi we know you’re in English 101 and we know you have a paper coming due soon, a week in advance we’re going to send you a nudge to go to the writing center to help yourself out and get some advice on that. We’re nowhere near that level of personalization yet or at the level of timeliness but it doesn’t feel that far off and it would mimic an experience that we have in every other aspect of our lives.
Evo: What role do you expect Big Data to play in student support initiatives over the next decade?
EV: There are a lot of different ways, but the most obvious one is that if you’re going to personalize and customize something you have to know something about the student. There’s a lot of data that we already have on students about their academic performance, their background, things along these lines. We also have data collected from the student specifically for purposes of pushing guidance, such as an engagement survey designed to learn a little bit about them or their preferences and needs. When we get further into the future you could see customization at the level of the course using data from the LMS. We might even see customizations based on student behaviors around campus as captured via swipe care or GPS data. These innovations might seem creepy, or even a bit like Big Brother, but really they just mimic the collection and use of data that is already happening in our lives, mostly to our benefit. Higher education is just now thinking about how to apply these marketing principles to the student success challenge.
Evo: Is there anything you’d like to add about the integration of Big Data and analytics into the delivery of student support and service?
EV: Big Data is not a panacea. It’s just another tool in the toolbox. And like any tool, you need to know how to use it correctly. At EAB, we believe strongly in change management as a necessary part of technology implementation. To explain why, let’s take the example of one of our predictive models meant to predict a student’s likelihood of graduation. If the model shows an advisor that a student has a 20-percent chance of succeeding, there are a lot of different ways to use that information, some good and some bad. We aren’t trying to “drown the bunnies,” and we definitely don’t want to create self-fulfilling prophecies. To avoid this, we need to train advisors, and the institution at large, on what a risk prediction means, how to interpret it, and how to intervene and communicate with at-risk students in a way that promotes their success rather than undermines it. People need to know that a prediction is just a forecast, it is not fate. Higher education is dealing with a lot of questions like these for the first time, which is why the philosophical conversations are just as important as the technological innovations.
This interview has been edited for length and clarity.
Author Perspective: Analyst