This Action Guide describes the phases and steps that stakeholders can take to develop and sustain trusted LER ecosystems. It is based on Credential Engine’s widely and successfully used State Roadmap and Action Guide for Transparency

We encourage you to use this Action Guide and provide feedback. We also encourage you to make a copy to remix and reuse for your LER purposes.

State stakeholders, including policy makers, state agencies, employers, community-based organizations, and education providers, are searching for ways to help learners and workers find the most efficient and equitable pathways to secure the right skills and credentials that lead to good jobs and careers. Credential and skill transparency helps state stakeholders address a major source of labor market friction: unequal access to information about quality education and career opportunities for learners and workers, as well as information gaps in employer processes that often produce poor matches between available positions and candidates. With improved access to information, individuals have increased agency to find, understand, and compare opportunities to advance along their learning and career pathways, and employers can make more precise selections based on skills and competencies rather than degrees alone. Verifiable Learning and Employment Records (LERs) are emerging as a powerful tool for accessing, linking, and verifying this information as part of broader state, regional, national, and global investments in information systems, data transparency, digital literacy, and learner/worker sovereignty. LERs issued to individuals representing all types of credentials, skills, and experience can improve labor markets and access to opportunities for all stakeholders. 

Currently, there are over 1,000,000 unique credentials offered in the U.S. With so many credentials to choose from, people get lost and lose out on opportunities. Learners and workers too often don’t know which credentials and skills lead to desired outcomes. With limited information on skills, employers are unable to understand what skills workers actually bring to a job and tend to over-rely on degrees to select candidates. Educators are increasingly under pressure to ensure that their programs help students succeed in the workplace, which can be challenging when they don’t have easy access to information from employers about the skills needed. This complexity is compounded by the fact that credentials are issued to individuals without transparent information about what skills those credentials represent. Data transparency is an essential foundation for interoperable, meaningful, human- and machine-actionable LERs.

State leaders are in a unique position to require that LERs include transparent, interoperable information about credentials, skills, and experience and make these digital records foundational in their education and workforce strategies. Not only do states have responsibility for education and workforce training, but they have also invested in data systems for labor market improvements. State leaders can build a culture that encourages state government, employers, and education and training providers to work in a coordinated and aligned fashion to improve data transparency in learning and career systems, including LERs issued to individuals.  

New LER technologies enable credential, employment, and skill data to be aggregated, analyzed, and made actionable for career success. LERs empower people with control over records of their own achievements, offering transformative opportunities to connect learning with careers and to improve the impacts of investments in education and workforce development. 

The big picture goal is to ensure that policy and state actions create ecosystems where LERs are widely accessible, understood, and trusted, inclusive of all aspects of an individual’s education, training, military, experiential learning, and work achievements, and securely shareable to connect people with opportunities. This Action Guide provides steps to get there, to enable more efficient career navigation and provide more equitable access to actionable information through LERs.

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Fact Sheets

How to Align Digital Credentials with Meaningful CTDL Data

Examples of digital credentials that are designed to include alignments to the Registry are Open Badges, W3C Verifiable Credentials, and Velocity Network credentials. Use these simple steps to enrich digital credentials by linking to CTDL data in the Registry.

Fact Sheets

Learning Economy Foundation and Credential Engine Joint Services Scaling LER Ecosystems with Linked Open Data and LearnCard

Learning Economy Foundation (LEF) and Credential Engine (CE) are excited to announce a partnership and joint services offering to empower learners and accelerate the adoption of open tools and protocols that enable individual agency and organizational insights. Together, LEF and CE bring a complementary package of technologies and best practices to states, post-secondary institutions, employers, and any organization looking to make ecosystem-level impact at scale.

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