Think of all the different ways that learning happens, both formally and informally. For example: A soldier who gains technical skills in the military. A student who takes classes at a community college before transferring to a four-year institution. A working parent who participates in online trainings to work toward a promotion. A pre-apprentice who learns a new trade on-the-job. Each person is building real, demonstrable skills. Yet all of them may face the same frustrating reality when they try to move forward: the courses they’ve completed may not transfer, the skills aren’t recognized, or the digital badge can’t be compared against the next step in learning or employment needs. Rather than building on the learning they’ve already completed, people often have to start over.
The Transfer Gap Is a Data Issue
Two related but distinct problems stand in the way of learning mobility. One problem lies in getting appropriate credit for prior learning, regardless of where the learning happened. People like veterans or adult learners bring skills they earned outside a traditional classroom, but institutions lack a consistent way to evaluate and recognize what they already know. –
Another issue is course equivalency. When a learner transfers from one college to another, institutions can have trouble determining whether a course taken at one school covers the same ground as a course offered at another. It’s not an indicator that the learning didn’t happen, but rather that the information describing the course isn’t structured in a way that allows comparison and transferability.
In both situations, what’s missing is a way to carry meaningful information about learning from one context to another. Doing that requires structured, open, linked, interoperable, and durable (SOLID) data describing what a course or credential actually teaches, what skills and competencies it builds, and how it connects to someone’s education or career journey.
For decades, organizations like the American Council on Education have worked to ensure learners earn academic credit for non-traditional learning through its credit recommendation system. But to fully solve this challenge, we need a shared data infrastructure that makes all learning information and data structured, open, and comparable across institutions and systems — enabling much faster transfer decisions, and making the skills learners have worked to build visible within the learn-to-work systems.
The Same Problem Shows Up on the Employer Side
The data gap that plagues learning mobility is the same one that stalls skills-based hiring. Employers want to hire based on a candidate’s verified skills and abilities. But evaluating whether a credential or prior course of learning demonstrates a specific competency is nearly impossible without proper descriptive data. When a certification accurately describes the skills it assesses, a training program’s data connects clearly to occupational requirements, and when a transcript contains both course and competency outcomes, then an employer has what they need to make a confident, skills-based decision.
Any learning data that is SOLID can clearly link to competencies and occupational standards. An employer can look at a credential and see exactly what skills it validates and how those skills map to the role they’re hiring for, and AI-powered career navigation tools can recommend a pathway that builds toward a specific job based on verified, connected data.
The infrastructure that makes learning portable for learners is the same infrastructure that makes hiring smarter for employers. It’s the same data problem, seen from two sides of the same coin.
What It Looks Like When It Works
California gives us a window into what’s possible. Through the California MAP Initiative, Credential Engine is helping build a statewide credential registry specifically designed to expand credit for prior learning for working adults, apprentices, and veterans across the community college system. Several colleges — including Chaffey College, De Anza College, and Foothill College — have published all their credentials, courses, and competencies in structured, open formats, creating transparent, comparable data infrastructure that enables fast, consistent, and fair transfer decisions. If a learner’s prior coursework is described in a format every institution can read, it can be built upon. Connecting that same data to competency frameworks and occupational standards ensures it’s useful to employers too.
The Ask Is Simple
When every institution, credentialing body, and training provider publishes their courses, credentials, and competencies in SOLID formats, every system downstream — career navigation, AI-powered tools, workforce development boards, employer hiring systems — will work better because the data can travel. Right now, learning that isn’t visible doesn’t count. Getting the data right is how we make sure it does.
Get started publishing your credentials and skills information by creating an account. Or, contact us at info@credentialengine.org to learn how you can support learners, workers, and employers by making your data open and transparent.