Data Collaborative for a Skills-based Economy (Data Collab) - Education Design Lab


The Data Collaborative for a Skills-based Economy (Data Collab) is a data hub that connects and aggregates data across a range of data sources to uncover how new education-to-work models can support economic mobility for new majority learners. The data collaboration infrastructure enables the Education Design Lab which manages the initiative and its partners to ask and answer deeper questions about equitable learner outcomes in non-credit programs.

Originally formed to support the Community College Growth Engine Fund, the Education Design Lab (the Lab) has designed and deployed the new data collaborative with a growing set of innovative higher education institutions that are rolling out, at scale, data infrastructure for evaluating “what works” in the world of micro-credentials, alternative pathways, skills assessments, and other short-term, non-credit programs.

The Data Collab partners (see below) established the data infrastructure and the technical, governance, and legal frameworks to support data collaboration across education institutions, government agencies, community-based organizations, and others.

The Data Collab lives at the intersection of design and data. Its work has shown that (1) education providers, policymakers, learners, and employers are eager for insights on the impact and return on investment (ROI) of short-term or non-credit programs; and (2) learners need better data on what programs are available and what their investment of time, money, and energy will yield for their own economic mobility.

Examples of the Data Collab’s accomplishments include:

  • Built an infrastructure for gathering data, monitoring progress, and researching the impact of innovative alternative, short-term credentials and pathways.
  • Created and executed data sharing templates with colleges and national partners.
  • Developed data guides with submission templates identifying key data elements including (L)earner Enrollment + Progression, (L)earner demographics, and Programs (Competencies, Courses, Credentials, Pathways).
  • Performed a gap analysis of missing individual (l)earner demographic data and developed protocols for gathering this information in innovative ways.
  • Established the data architecture, data privacy, data protection, data security, and data governance to ensure compliance and elevation of individual rights to data privacy.
  • Established collaborative partnerships with national organizations to maximize data standards and minimize duplicative data efforts.
  • Established a multi-pronged model for incorporating wage and employment outcome data elements.

Six developing areas of work are focused on more fully leveraging data to evaluate learner impact and generate new insights on non-credit programs:

  • Data Dashboard Products for Insights
  • Standardization of Non-credit Credential Data
  • Test and Support Integration of K-12 Data
  • Data Capacity-Building Support
  • Employment and Wage Data Integrations
  • Inclusion of Industry Certification and Non-Credit Credential Data


The Lab, Brighthive (technical administrator), National Student Clearinghouse (Postsecondary Data Partnership submission), an external project research group (evaluator), and Credential Engine (data schema and mapping) established the data infrastructure as well as the technical, governance, and legal frameworks to support data collaboration across education institutions, government agencies, community-based organizations, and others.

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