Showing Skills Mastery in Real-Time
Imagine an electrician who becomes proficient in safety and installation procedures for industrial equipment months before completing their formal hours. Or an IT professional earning a coveted certification at night while holding down a full-time day job.
These learners are developing valuable skills in real-time. But under our current educational and technological infrastructure, they can’t demonstrate these accomplishments until they finish their program—their skills are tied to a certificate. If they could show them earlier, they could be getting a step ahead in their job search or positioning themselves for a promotion.
This delay throttles career progress in a work environment that increasingly focuses on demonstrated skills over credentials. For the most part, current institutional and employer systems associate skills with degrees or other credentials, entirely overlooking the continuous stream of learning happening every day.
Unicon is currently collaborating with the Competency-Based Education Network (C-BEN) and Axim Collaborative, the stewards of Open edX, to build infrastructure specifically designed to make skills data portable and usable across ecosystems. This will bridge the gap between learning and work, enabling learners to demonstrate their capabilities in real time, both for their own benefit and the benefit of employers.
Learning Doesn’t Happen in Milestones
Traditional academic systems evolved around rigid, event-based milestones: completing a course, earning a certificate, or receiving a degree. These made sense when education followed a linear, predictable path from enrollment to graduation.
But the contemporary learning journey is dynamic, lifelong, and sometimes even stop-and-start. Students drop out of school and return later, earn credentials from different providers, and work toward degrees or certifications while holding down a full-time job.
When the underlying infrastructure relies entirely on a diploma or certificate to validate their achievements, the data is trapped and invisible to employers until those credentials are earned—and even then, it may be difficult to show proof of capability with specific skills.
“Skills data is powerful. But if that data doesn't move downstream, it's really just held captive inside of the learning environment.” — Kate Valenti, CEO of Unicon
In a skills-based learning ecosystem, this data is generated consistently when students complete a competency, pass a rigorous assessment, or successfully perform a verified workplace task.
The Economic Effects of Education Bottlenecks
The delay caused by an outdated technology infrastructure affects the entire ecosystem.
Learners are prevented from showcasing the practical abilities they can execute right now. A student may have mastered 80% of the core competencies required for a job, but they can’t provide an employer with a verifiable record to show eligibility.
Employers cannot always wait for long graduation cycles to access talent. They need real-time visibility into verified capabilities to fill immediate gaps. When institutions lack the ability to surface these skills independently, employers miss out on an entire pool of qualified or soon-to-be qualified candidates.
Higher education institutions can’t show students’ ongoing progress and skill development, delaying their ability to show the impact of their programs until students have advanced several years into their careers.
Enabling Skills Data to Move in Real-Time
To change this equation, the educational ecosystem must shift from tracking milestones to a technology layer focused on skill mastery. This framework would use an intelligent, LLM-powered hub to orchestrate the movement of skills data in three primary steps:
An event, such as a skill mastered or a credential earned, serves as a trigger.
AI transforms, adds context to, and maps the data for compatibility with interoperable standards such as Open Badges 3.0, the Comprehensive Learner Record (CLR), or CASE.
Once standardized, this skills data flows directly into downstream systems: digital wallets, advising tools, and employer human resources information systems (HRIS).
“We’re moving data that is being created inside of the learning environment, but we're moving it more readily as the learner is proceeding through curriculum, and not just waiting until there's a final credential at the end.” — Kate Valenti, CEO of Unicon
When a learner no longer has to wait for a diploma, they can leverage their skills as they are verified. Employers can identify individuals with the capabilities they need, enabling them to fill workforce gaps faster.
Building skills-first infrastructure requires more than simply making data portable. Data must flow seamlessly between learning, credentialing, and employment systems so that digital credentials can be recognized and used across the ecosystem. This requires open standards as well as common definitions of skills to ensure that a competency means the same thing to all stakeholders. Just as important, skills data needs to carry supporting evidence—such as the rubric, assessment, or artifact demonstrating mastery—so that its meaning and context aren’t lost as it moves between systems.
But interoperability is also a matter of trust. Employers need confidence that the skills represented by a credential are accurate, meaningful, and backed by credible evidence. AI can help organizations map skills, identify relationships, and manage large volumes of data, but validation cannot be outsourced entirely to technology. Faculty, instructors, employers, and other industry experts must remain the ultimate authority, establishing governance and validating skills data.
From Credentials to Continuous Progress
Degrees and certificates will always be important credentials for gaining employment. However, graduation should not be the first and only time a learner’s capabilities become visible to the professional world.
As higher education, workforce development, and talent acquisition shift toward a skills-based framework, the question changes from “When did you graduate?” to “What skills can you demonstrate today?” Supporting this transition requires building the infrastructure necessary to let trusted skills data move continuously across the entire learning and employment life cycle.
