Getting learning mobility right

Earlier this summer, when the Gates Foundation announced our updated education strategy, we emphasized the need for a system where all learning counts; a system in which learners can paint a comprehensive picture of their skills and experiences as they move through institutions and into the workforce. In this piece, I want to go deeper on that idea of learning mobility, including what it means and why it matters. 

First, a reality that I’m struggling against here: the way we name the problem determines where we look for the solution. In the education space, there’s always a tendency to create labels and categories: the transfer student, the adult learner, the displaced worker, the person with some college and no degree. Those categories can be useful for designing programs and doing research, but they can also make us miss something fairly obvious: those can all be the same person. 

At 17, someone may be deciding what to do after high school. At 27, that person may have developed significant new skills through work. At 34, technology may change their occupation. At 41, they may want to do something new and need training and a certification. At 48, their family may move to another state. At 56, they may decide to go in a completely different direction.  

This isn’t just my own thinking: Stanford’s Center on Longevity calls for a “New Map of Life,” one that moves beyond a front-loaded-schooling model to something with more on-ramps and off-ramps that people can take more than once, in more than one order, over longer lives. A recent Stanford Social Innovation Review piece showcased some excellent work in Wichita that underscores the same point from the employer side: the old rules and timetables simply don’t match the lives of many talented, ambitious people anymore. 

I’m encouraged by this article, but I still think there’s an opportunity to think bigger. Conversations on this topic often get constrained by how we think about the current system. When I say “learning mobility,” higher ed hears transfer, workforce development hears skills, technology hears digital credentials, data professionals hear interoperability, and employers hear skills-based hiring.  

Everyone is being reasonable: it should mean all of those things, and we all interpret new problems through the frameworks we already understand. But an existing solution category ends up defining (and limiting) the problem before it’s been defined on its own terms. It would be easier to reach for a familiar label, but learning mobility is not the next stage of transfer reform, an umbrella term for existing work, or credit mobility with more bells and whistles. 

Learning mobility is 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.

When we’re successful, every person’s learning will open more doors than it closes and compound in value over time, experienced in real economic terms.  

How will we get there?

Keeping different learner contexts and destinations in mind, we need to start asking better questions, about whether learning actually creates mobility for people:  

• Where can a person carry what they’ve learned into a new context, and where and why does its value get lost?  

• How long does it take a new institution, employer, or other destination to understand and recognize what a person already knows and can do? 

• Does what a person learned at one stage expand the number and quality of options, opportunities, and economic outcomes available to them next? 

And at the market, or system, level:  

• What would cause actors who benefit from today’s arrangement to behave differently, and what’s actually keeping them from doing so today?  

• What creates enough value for participation, and for whom is that value currently missing?  

• Where does leadership for this shift come from? Who needs to partner in new ways to drive this shift?  

• What requires public action, and where should the market lead? 

These are ultimately questions about actions.

Something I’ve learned time and time again in my career is that you can do a lot right inside an organization and still come up against a problem the organization has no authority to solve. For example: a college president could decide tomorrow to make progression dramatically easier with credit for prior learning, but realizing the full value of that decision depends on factors beyond the institution: How will that learning appear on a transcript and be understood by future institutions or employers? How will the credit interact with financial aid? And who needs to be at the table to resolve those questions? An employer can change its own hiring and training practices, but they can’t change how the labor market recognizes and values capability. 

This means individual organizational action is both necessary and insufficient, because the barriers sit outside any single actor’s boundaries. This is an infrastructure and economic capacity problem, not an organizational one. I want to be clear: when I talk about infrastructure, I’m not necessarily talking about one giant database, one government system, or one piece of technology. I’m thinking more broadly about the shared conditions that allow independent actors to do something reliably together that they cannot efficiently accomplish on their own. 

We already depend on infrastructure like this in other parts of the economy: banks compete without each inventing the conditions that let money move, and no consumer negotiates with every institution over whether a dollar is a dollar.  

Why now?

In my view, we’ve had sufficient policy authority, institutional capacity, technology, and public and private investment needed to make progress on learning mobility for decades. What’s different now? 

Well, the obvious answer is the answer: AI. AI changes the context not because it is the solution, but because it both raises the stakes and expands what may be possible.  

I am optimistic about what technology, particularly AI, may contribute. AI allows us to process information at a scale that would have been unimaginable not long ago. It can reduce transaction costs, make complicated information easier to understand, help people navigate choices, and potentially turn processes that take weeks into processes that take seconds. But, critically, it does not solve for what made this work difficult in the first place: incentives, trust, authority, institutional behavior, competing interests, and diffuse responsibility.  

Those are harder to solve for. AI won’t resolve them on its own, and there’s real risk in overstating what it can do here. Those same institutional, incentive, and trust problems will also shape whether AI helps or hurts more broadly. But it’s worth watching whether AI, in a different way, creates new openings for progress on these fronts too. Already AI is changing our economy and will inevitably change it more. No matter the scale of change, more people will be making more shifts in their education-and-career path in the future (that shift, to less linear, more winding career paths, was underway long before AI). Whether the pressure AI puts on leaders in government, the private sector, and philanthropy translates into meaningful collaboration on learning mobility is something worth paying attention to. 

I don’t want technology to become the center of this story. I want to move beyond asking “What AI can do?” and toward “What should we do differently now that AI has changed what is possible?” 

To close, I have two levels of ambition, and two levels of learning I’m focused on: 

• At the individual level, I want people to have better information when they make consequential choices. How do we build enough infrastructure that learners have the agency to make genuinely different decisions?  

• At the market level, I want us to understand where value is being created and where we are allowing it to disappear. How do we unlock enough transparency and comparability to force real competitiveness into the educational landscape?  

I look forward to exploring these questions with you. 

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In a follow-up piece I’ll go deeper into how the concept of learning mobility might be measured; how we’ll move beyond counting activity and toward quantifying impact, value, and real-life outcomes.