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The framework helps states connect education data across early learning through postsecondary and into workforce outcomes, using essential questions, economic mobility indicators, disaggregation methods, evidence-based practices, and data equity principles. Interviews with Colorado, the District of Columbia, and Washington highlight maturity stages, priorities, and system gaps for guiding policy decisions.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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System  \nJennifer Thomsen  \nThe following case studies explore how emerging and established Statewide Longitudinal Data Systems have used the Education-to-Workforce Indicator Framework (E-W Framework) to support their data system efforts. Developed by Mathematica in partnership with the Gates Foundation, the framework offers guidance on how states can use data to “promote equitable outcomes and economic security for all.” It identifies the data system connections that can support students moving through education systems — early learning through postsecondary — and into the workforce.  \nThe framework includes:  \n• A set of essential questions for education-to-workforce data systems to answer.  \n• Indicators associated with economic mobility and security.  \n• Disaggregates systems can use to break down data.  \n• Evidence-based practices to move the needle on key outcomes and system conditions.  \n• Data equity principles for encouraging more ethical and effective data use.  \nEducation Commission of the States interviewed state leaders in Colorado, the District of Columbia and Washington state to learn about how they have used the framework to guide their efforts in collecting and using data to support learners. They offer concrete examples and considerations for leaders in other states as they embark on this work.  \nState leaders need data to answer pressing questions, evaluate programs and identify promising approaches to inform policy decisions. Statewide longitudinal data systems (SLDSs)—systems that connect individual-level data over time and across systems including early learning, K-12, postsecondary and workforce — are an essential tool to help ensure that students have equitable opportunities for success. This is not just true throughout their P-20 experience but also as they transition into their careers and beyond. While most states have established at least some of these system linkages, the work continues.  \nEvery state and the District of Columbia has systems to collect, store and report education data. At least thirty-three have an active SLDS, and another nine are working to establish systems. The systems vary widely from state-tostate in what data they collect, how they collect it, where its housed, and how they use it to provide the information stakeholders (i.e., policymakers, schools, educators, learners, employers and the community) need to create effective pathways to education and career success. The structure and governing processes of SLDSs differ from state-to-state as well.  \nTo provide examples of states at various stages of their SLDS work, and more specifically, to highlight how they have used the E-W Framework to guide them, we interviewed leaders in two states that are developing new systems —Colorado and the District of Columbia, and one state with a long-established system — Washington. We sought to learn how they have used the framework at various stages of maturity to guide their efforts in collecting and using data to support learners. We asked them how they used the framework in building their SLDS, which of the framework’s questions they prioritized and what gaps they identified in their systems.  \nThese conversations provide concrete examples and considerations for leaders in other states as they embark on this work.  \nColorado  \nLegislation passed in 2024 requires an SLDS to link data across K-12, postsecondary and workforce systems. The system will serve as a foundation for continuous improvement in programs and data-driven policy decisions. The goal is to move the state toward a modernized, democratized SLDS, where stakeholders can view the data. The legislation came with some tight timelines, so the Governor’s Office of Information Technology, with support from outside partners, seeks to build on early successes without losing sight of the larger vision. The E-W Framework has been a time sa","cbCaisllNgpzvGpS","https://ap.wps.com/l/cbCaisllNgpzvGpS","pdf",230776,"English","# Case Summaries (Nov 2025)\n## Education-to-Workforce Indicator Framework (E-W Framework)\n## Statewide Longitudinal Data Systems (SLDS)\n## Colorado\n## District of Columbia\n## Washington","[{\"question\":\"What is the Education-to-Workforce Indicator Framework (E-W Framework) used for?\",\"answer\":\"It provides guidance on how states can use data connections across education and workforce to promote equitable outcomes and economic security.\"},{\"question\":\"How do SLDSs support equitable opportunities for students?\",\"answer\":\"They connect individual-level data over time and across systems, helping evaluate programs and identify approaches that inform policy decisions.\"},{\"question\":\"What did Colorado’s 2024 legislation require for its SLDS?\",\"answer\":\"It requires linking data across K-12, postsecondary, and workforce systems to support continuous improvement and data-driven policy decisions.\"}]","CASE SUMMARIES NOV 2025 - State Strategies for Developing and Using a Statewide Longitudinal Data System | PDF",1792050124,25]