Improving Youth Apprenticeship Data Quality: Challenges and Opportunities

The report, developed by the Partnership to Advance Youth Apprenticeship's (PAYA) Data Quality workgroup, addresses the most urgent youth apprenticeship data quality challenges and describes the roles that different stakeholders can play in improving the quality and use of data.

Share

Improving Youth Apprenticeship Data Quality: Challenges and Opportunities

One of the biggest challenges that states and local intermediaries face in setting up and scaling high-quality youth apprenticeships is gathering relevant, accurate and actionable data. High-quality data is an essential ingredient for a strong youth apprenticeship program because it equips state and local leaders to evaluate impact, monitor equity, identify best practices, and make the case for youth apprenticeships to employers and learners.

This report summarizes the discussions of the Partnership to Advance Youth Apprenticeship’s (PAYA) Data Quality Workgroup. The workgroup was convened by Advance CTE and New America in 2020 to discuss challenges and opportunities for using data to improve quality and equity in youth apprenticeship. The report addresses the most urgent youth apprenticeship data quality challenges and describes the roles that state leaders, local intermediaries, and education and employer partners can play in improving the quality and use of data. It also identifies high-impact strategies for using youth apprenticeship data to advance quality and equity and provides next steps for the field.

Submit a resource or resource edit to the Learning that Works Resource Center