Building On-Ramps to Student Success

By Carlo Salerno

Vice President, Data Analytics, Strada Education Network


Postsecondary training is an expensive proposition without a guaranteed payoff. To make matters worse, many students find themselves in the position of making large financial investments and never completing a degree, a near worst-case scenario that often leaves individuals with lots of debt and no credential to earn the wages needed to pay back those borrowed dollars.

Success requires earning the kinds of certificates and degrees employers value, which is why federal and state policy has gradually moved away from facilitating access and toward supporting completion. Much of the effort, though, has gone into making institutional accountability more robust, which really is only half the battle. Success starts with ensuring a good fit between what prospective students want and what institutions offer.

How do we help prospective and current students make sensible choices that reflect their aspirations and abilities? We do it with the data, but most importantly, we do it with the right kind of data.

Yes, consumers need more transparent data about college costs. But, as I shared during a panel discussion at the ASU + GSV Summit this spring, what they sorely need is much better information about the economic returns a degree can yield.

Accessing the right data

Many service sectors, for example, rely on consumer satisfaction feedback to help guide choices and improve offerings — just think of resources like Yelp! or Consumer Reports. While college rankings and ratings certainly are not in short supply, they often end up being measures of what methodologists think good schools should be like, rather than what actual users believe was a good or bad investment. What’s more, they don’t really distinguish between nonselective institutions or those with a more vocational bent, like the nation’s community colleges and technical schools that enroll about half of all students today.

Even where there is reputable data, such as the U.S. Department of Education’s College Scorecard, it’s clear there are challenges. Look up Grand Valley State University in Michigan, for example, and you’ll find an institution where the net cost of a bachelor’s degree can run anywhere from $67,000 to almost $100,000, and former students (only those who received federal aid) earn just less than $40,000 a year a full decade after they’ve left. Is that a good deal? Are those good wages? It’s hard to tell, since we’re talking about a school that at any given time enrolls more than 20,000 students and offers more than 190 different academic programs.

Consumers need program-level wage and career data. They also need to know what starting salaries look like, in addition to mid- and late-career earnings, if we’re going to reasonably expect them to properly value an investment that can potentially bear out over a 30-plus year career. What does the average worker earn in the student’s desired field? What does someone who’s in the 25th or 95th percentile earn? Is the student looking to enter a high-demand field, or one that’s already flooded with hundreds of thousands of other people who have degrees and highly valued work experience?

Finding the right pathway

From constructing a building, to training to become a world-class athlete, to building a rewarding, lifelong career, a good foundation matters. At the end of the day, people choose where to study, what to study, and what degree to pursue. In the absence of good data, the lifelong investment choices we expect consumers to make end up resting instead on an unstable foundation of piecemeal data, anecdotes and romanticized beliefs about career options and opportunities.

Giving people the right tools to make sensible choices that meet their uniquely personal circumstances is a laudable goal. Whether it’s policymakers, pundits or the public, we should continually look for better ways to leverage data to help education consumers help themselves.