Education-to-Workforce Indicator Framework

Mathematica partnered with Mirror Group and the Bill & Melinda Gates Foundation to leverage existing evidence and field expertise to establish a common set of metrics and practices for education-to-workforce (E-W) data systems to assess and address inequities along the pre-K-to-workforce continuum. The metrics identified will help systems track the key outcomes and milestones, system conditions, and adjacent system conditions that enable students and workers to achieve economic mobility and security.

The framework includes:

• Data equity principles: Principles to support ethical and safe data use across the data life cycle 

• Essential questions: Questions every E-W data system should be equipped to answer
• Indicators: Indicators that matter most along the E-W continuum for states and localities to measure 
• Disaggregates: Key student characteristics to inform data disaggregation and assess disparities 
• Evidence-based practices: Illustrative practices shown to move the needle on key outcomes

The E-W Framework is for those who use education and workforce data to diagnose inequities, make evidence-based decisions, or evaluate and monitor the impact of policies, programs, and investments designed to address those inequities. The framework can help:

• Identify and track the most consequential indicators to measure along the E-W continuum, including indicators of student outcomes and system conditions
• Promote alignment around common definitions and equity practices 
• Drive greater consistency in data collection and reporting practices
• Better support individuals least well-served by current systems
• Establish processes to use data ethically and safely, thereby promoting access to information while also protecting the privacy of individuals