This section identifies and describes six core elements of a high-quality career readiness data ecosystem, highlighting recommended actions state leaders can take to improve the quality and effective use of career readiness data across education levels. The core elements include sub-elements, which further describe the dimensions of effective policy and practice within each element. Each core element and sub-element is informed by research and input from an expert workgroup.
1. Data is collected consistently and accurately
- Data is reliable and collected consistently around the state, across different career pathway programs and across institutions.
- Processes and protocols are in place to validate career readiness data.
- Stakeholders are aware of what the data represents, how it will be used and its limitations.
Read our case study on Texas' approach to automated learner identification systems and statewide Programs of Study.
2. Processes and protocols are in place to ensure effective data governance
- Roles and responsibilities for collecting, validating and reporting data are clearly laid out in statute and/or policy.
- Decisions related to the collection and use of career readiness data are coordinated across agencies and responsive to stakeholder needs.
- State agencies are sufficiently staffed and funded, and structures are in place to withstand personnel and political transitions.
- Measures are in place to protect the privacy of learner records.
Read our case study on Maryland's approach to building a longitudinal data system center.
3. Data systems, policies and practices are fully aligned across agencies and learner levels
- Learner-level records are reliably linked across agencies and among states, as appropriate.
- The collection and reporting of career readiness data are coordinated and, to the extent possible, aligned across programs, agencies and learner levels.
- State agencies use common indicators and business rules for measuring career readiness and align their goals and performance targets.
Read our case study on New Jersey's approach to their state education to earnings data system.
4. Information is relevant, timely and disaggregated
- All information is contextualized to provide a clear understanding of the career readiness system.
- Reports and dashboards are differentiated by user depending on their need and understanding of the data.
- Information is made available in a timely manner.
- Data is disaggregated by population, institution and career pathway and available to relevant users.
Ready our case study on North Dakota's approach to building data dashboard.
5. Practitioners and the public are equipped to understand and leverage data
- Public reports are accessible and easy to understand.
- Professional development and technical assistance are provided to practitioners to build data literacy and help them leverage the data.
- A statewide career readiness communications strategy is in place that leverages career readiness indicators to tell a story of impact.
Read our case study on Kentucky's approach to their data partnership between the Kentucky Center for Statistics and Department of Education.
6. Information is used effectively to promote quality and equity in career pathways
- Career pathway approval and renewal processes are data driven.
- State- and local-level decisionmakers regularly reflect and act upon data to inform policy and improve equity, access and quality.
- State and local leaders regularly identify and respond to opportunity gaps by race/ethnicity, gender and special population status to ensure equitable access to and success in career pathways.
- Local practitioners have access to real-time data that they use to target interventions.
Ready our case study on Ohio's Perkins V Equity Labs.
