About the Framework
The Education-to-Workforce Indicator Framework (E-W Framework) is designed to help systems collect and use data that advance educational and economic opportunity for all. The framework offers guidance for using data to inform action through the following components:
What Does the Framework Include?
- Data equity principles. Seven principles for centering equity throughout the data life cycle to encourage more ethical and effective data use, plus guidance on how to apply them.
- Essential questions. Twenty questions essential for E-W data systems to answer about how students are progressing from early education through career—and using the answers to guide action.
- Indicators. Ninety-nine student outcomes and milestones and related system conditions associated with economic mobility and security, plus guidance on how to measure them.
- Disaggregates. Twenty-five characteristics that E-W systems should use to break down data, plus guidance on how to collect them.
- Evidence-based practices. Twenty-six examples of practices shown to move the needle on key outcomes and system conditions, plus guidance on how to select them.
What Is the Framework’s North Star?
The North Star, or big goal, for the E-W Framework is to advance equity and help people achieve economic mobility and security. We’ll know we’ve achieved this when:
- Structural barriers based on race, ethnicity, gender, sexual orientation, zip code, class, disability, and other factors are dismantled such that a person’s background and identities no longer predict their outcomes in life.
- People have the income and assets needed to achieve and maintain their economic independence.
- People possess power and autonomy over their lives.
- People feel the respect, dignity, and sense of belonging that come from contributing to one’s community.
Why This Framework?
Working together to share data across sectors helps education and workforce organizations achieve a greater impact. But disconnected or incomplete data systems make it hard to understand how students progress from early education through their career and the conditions most critical to their success. The E-W Framework offers comprehensive guidance on how to measure and act on the data that matter most to help every student succeed. The E-W Framework:
- Can help users assess data systems, identify opportunities and gaps, and make plans to support equity and economic security for all
- Highlights practical examples of how to measure and create conditions that help all people thrive
- Summarizes evidence about how to use data ethically and effectively
- Recommends indicators for measuring what matters most as students transition along their journey from early education through their career
- Consolidates and builds on leading frameworks and evidence to encourage alignment along the E-W continuum
Who Can Use the Framework?
The E-W Framework is designed for a broad group of people who use education and workforce data to diagnose inequities, make evidence-based decisions, and monitor the impact of policies and programs to address those inequities.
How Was the Framework Developed?
Mathematica developed the framework in partnership with the Bill & Melinda Gates Foundation, Mirror Group, and an external advisory board of 15 E-W data experts and leaders, including state and district policymakers, researchers, and policy advocates.
External advisory board members
David Montes de Oca
The framework’s development was grounded in the following set of core values and design principles.
We followed a similar approach to develop each component. First, we reviewed and synthesized existing frameworks, reports, and research, and then we shared findings with the two advisory groups to gather their feedback and refine the content. During the early development phase, we also led input sessions with staff and partners from five collective impact organizations across the country to learn how the framework could support their work. This process led to the recommendations that appear in the report.
Collective impact organizations consulted
Gonzalez, Naihobe, Elizabeth Alberty, Stacey Brockman, Tutrang Nguyen, Matthew Johnson, Sheldon Bond, Krista O’Connell, Adrianna Corriveau, Megan Shoji, Megan Streeter, Jennifer Engle, Chelsea Goodly, Adrian N. Neely, Mary Aleta White, Mindelyn Anderson, Channing Matthews, Leana Mason, and Sheryl Felecia Mean. “Education-to-Workforce indicator framework: Using data to promote equity and economic security for all." Seattle: Mathematica, August 2022. Available at https://educationtoworkforce.org/sites/default/files/2023-04/E-W-Indicator-Framework_Final.pdf