Right now, measurements tell us what happened; they don’t tell us what it was worth.
In my last piece, I shared my vision for what learning mobility makes possible: a world where every person’s learning will open more doors than it closes and will compound in real economic value over time. But how do we go about measuring against that vision?
We have a lot of data that describes what is happening in education, less about why it’s happening, and what happens next.
Take the growth in high school students taking college courses. I understand why we point to increased participation as progress, but participation is not the outcome I’m most interested in. I want to know what happens to those students and the knowledge, skills, and credits they gain from those courses.
When that student eventually enrolls in college, do their dual enrollment credits actually apply to the program they choose? Did taking those courses save the student time or money? Did they create more options? If not, then I think we have to be careful about celebrating the participation number without understanding what it produced.
Learning mobility:
The ability of an individual to have their knowledge, skills, and competencies recognized across contexts and geographies, including from learning providers and employers, such that what they have learned is visible, portable, trusted, consented-to and usable toward ongoing educational and employment opportunities.
The same is true when we hear that a large share of students transfer and change colleges. Changing institutions is not inherently good or bad, but we lack the ability to really investigate why students are making those changes. Likewise for the enormous number of people who went to college but never earned a credential. We’re beginning to dig deeper into the reasons, but when something is happening at this scale, we cannot put all the analytical burden on the individual. We also have to look at the institutions, financing, information, incentives, and choices around students. We have to ask just how well the education market is actually working. I worry that while we try and figure out how to measure this, the court of public opinion is doing the measuring.
Credit loss is one example of a much larger issue I’m interested in: when learning that has value in one setting loses some or all of that value when a person’s circumstances change. In higher education, we can see the loss pretty clearly. Someone paid for those credits and spent time earning them; taxpayers may have subsidized them, and there may be debt, forgone wages, or time away from family attached to them. But learning mobility asks us to look beyond credit and ask where else this happens. It can happen with academic credit, but it can also happen with learning acquired through work, training, military service, certifications, and other experiences. I want us to understand where that value is being lost, why it is happening, and what it is costing people and the economy.
All of this makes me think we need a different way of measuring progress.
We’re very good at counting activity: enrollment, credits, credentials, transfers, programs. We’re getting better at measuring value, in terms of the wages that a credential unlocks. Those numbers are important, but, again: they only tell us what happened, they don’t tell us what it was worth. That’s why I think we need a different vocabulary for progress. I have been thinking about three things in particular: utility, friction, and optionality.
By utility, I mean whether someone can actually use what they have learned.
AN EXAMPLE:
“With 1.8M unique credentials from over 130,000 providers, employers face a real challenge understanding what each one represents.”
An example: When employers are asked what they think about “microcredentials,” 96% say they strengthen a candidate’s application. That suggests the learning they represent has value. But when Burning Glass actually looked at hiring at 1,000+ large employers, they found almost no relationship between asking for these credentials in a job posting and actually hiring people who hold them. And when Burning Glass and AEI tested more than 23,000 credentials against the career histories of 65 million Americans, only about one in eight credentials produced a wage gain the earner wouldn’t have seen anyway. To me, that points to a learning mobility problem. The learning may be real and documented, but that doesn’t mean it will be understood, assessed, or applied when someone tries to use it in a new context. With 1.8M unique credentials from over 130,000 providers, employers face a real challenge understanding what each one represents; learners face an equal challenge knowing where what they have learned will actually create value. That’s a barrier to utility.
By friction, I mean what it costs them in time, money, repetition, bureaucracy, or lost opportunity when they try to progress.
Consider a learner who completes a low-cost, college-level course through a nontraditional provider. The course has been independently evaluated and recommended for college credit, but that doesn’t guarantee that every institution will accept or apply it toward a degree. Even if the provider does their best to forge articulation agreements, they can’t make every school count the course. In this example, learning might happen, get recognized, and yet the value may diminish along the way when a student has to fight to get credits accepted or retake courses. That’s the kind of friction learning mobility needs to address.
And by optionality, I mean whether learning creates more and better choices for what they can do next.
AN EXAMPLE:
“A state can measure outcomes within its own education system and labor market, but…does what a person learns continue to create value and options wherever they go?”
An example: One state changed how it funds community colleges, moving away from enrollment alone and tying more funding to outcomes such as earning credentials of value and college credits in high school. That drives conversation about whether education is actually opening doors to high-wage, high-demand jobs. In other words, delivering optionality. But it also shows the limits of state-level action. A state can measure outcomes within its own education system and labor market, but it has a much harder time understanding what happens when people move across state lines. And it still leaves unanswered the broader optionality question: does what a person learns continue to create value and options wherever they go?
We have to stop compromising on what we’re measuring. Without data that reflects the full reality of learners’ lived experiences, we’ll get stuck solving for individual pieces of the much bigger puzzle.
And the stakes learners are facing are only mounting. The work ahead requires us to see much more clearly where learners are encountering barriers, understand what those experiences are telling us, and be willing to act on what we learn. I look forward to working with you to get there.
