Building Infrastructure for Non-Degree Credentials

Title: A Global Review of Non-degree Credential Quality Frameworks: Matching Aspirations to Available Data

Authors: Kyle Albert and Thomas Weko

Source: George Washington University (GWU) Program on Skills, Credentials & Workforce Policy (PSCWP)

With the continued increase of alternative, non-degree credentials, education and professional stakeholders have developed quality frameworks meant to guide these credentials.

The authors of a new report from PSCWP examine and evaluate criteria and data used in current credential quality frameworks. The brief highlights the growing need for institutions to consider and build out data sources for these non-degree frameworks. Whereas foundations, nonprofits, and policy organizations shape frameworks in the United States, government ministries do so outside of the U.S. The U.S. does not recognize non-degree credentials in the Higher Education Act, meaning that such credentials are not required to be reported to the Integrated Postsecondary Education Data System and other government databases.

A 2024 GWU/UPCEA survey showed that for non-degree, credit-based credentials, quality standards and procedures are primarily established at the institutional level and are modified forms of standards for degree programs. For non-degree, non-credit credentials, however, there is a “far greater decentralization of responsibility” (p.15). Standards for these programs are often established at the faculty or departmental level, and only about 10 percent of respondents reported that their institution could link learner data from these programs to external data systems.

Given the variation among commonly used datasets as well as processes within institutions, private actors hold substantial power in refining quality frameworks. The authors suggest the following ways to improve data standardization when it comes to quality frameworks:

• Use consistent language: Using consistent language across non-degree credentials can support organizations not only in how they describe and distinguish between programs but also in how they measure outcomes.
• Make data accessible: Membership and research-based organizations can empower the field to be more transparent and develop legal and technical guidelines for data sharing beyond the confines of the organization.

To see the full report, click here.

—Kara Seidel