Keeping Students on Track to Postsecondary Success: Learnings from the Pathways to Adult Success (PAS) Initiative

Background/Context Over the past decade early warning systems which use predictive indicators to identify students in need of additional supports to stay on track to high school graduation have spread from a few schools to most states. There is now a growing interest in extending the utility of early warning systems from high school graduation to post-secondary readiness. Purpose/Objective/Research Question/Focus of Study Report on initial findings and insights from a three year effort to build a learning community of early adopters of early warning systems for high school graduation to figure out how they can be extended to keep students on track to post-secondary success. Intervention/Program/Practice A key outcome of the learning community which included 150 representatives of K-12 local and state school systems, as well as non-profits and institutions of higher education was the development a framework for keeping students on track to post-secondary success, called Pathways to Adult Success which has four main components (1) how to use Early Warning Systems to support postsecondary success, (2) how to provide better postsecondary navigation and guidance supports to all students, (3) how to develop cross-sector collaborations, and (4) how to improve data use and data systems. Research Design Participant-observation supported by interviews and surveys Conclusions/Recommendations The PAS learning community assembled a multi-part framework of recommendations and guideposts to help states, schools, and districts increase and improve pathways to adult success for all youth. This framework extends the early warning approach to support bridges to postsecondary outcomes, while acknowledging the need to improve and expand navigation and guidance supports for all students, and to increase cross-sector collaborations to improve and expand existing pathways. Finally, it stresses the power of and need for data, data systems, and data use to drive all elements of the Framework. The remaining challenge will be creating the conditions which enable its widespread implementation.