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IES Grant

Title: Leveraging Washington State's Longitudinal Data System to Understand School-to-Work Pathways
Center: NCER Year: 2024
Principal Investigator: Unterman, Rebecca Awardee: MDRC
Program: Using Longitudinal Data to Support State Education Policymaking      [Program Details]
Award Period: 3 years (07/01/2024 – 06/30/2027)  Award Amount: $999,584
Type: Exploration Award Number: R305S240017

Co-Principal Investigator(s): Selby, John; Tessler, Betsy; Deane, Kathryn

Partner Institution: Washington Student Achievement Council (WSAC)

Purpose: Although the state of Washington has invested in policies to address inequities in educational opportunities for its learners, deep inequities persist in postsecondary degree attainment and earnings. Differences in the pathways young people take from high school to postsecondary education and work may be one mechanism causing these differences in outcomes. Much attention has been paid to traditional school-to-work routes, e.g., going straight to a 4-year degree program after graduating high school, but less is known about the relative effectiveness of other types of "non-traditional" pathways such as dual enrollment, career and technical education, and occupation skills training programs.

To identify important patterns in postsecondary education and employment in this new landscape, researchers from MDRC and representatives from the Washington Student Achievement Council (WSAC), the state agency overseeing higher education in Washington, are studying students' school-to-work pathways and their academic achievement and labor market implications using social sequence analysis, an approach to identifying and understanding student trajectories.

Project Activities: Working with the Education Research & Data Center's (ERDC) Preschool-to-Grade 20-to-Workforce (P20W) State Longitudinal Data System (SLDS), the project team will answer questions for state policymakers and practitioners about students' educational trajectories and labor market participation, with a specific focus on the key learner subgroups of interest to state policymakers: Black students, Hispanic students, Indigenous students, male students, students from low-income families, and students from rural areas. The research team will address the following research questions:

  • What are the range and variety of trajectories young adults take as they seek to transition from school to work?
  • Are there clusters of trajectories (i.e., pathways) that lead to better postsecondary education and labor market outcomes, including postsecondary degree attainment, higher earnings, and more stable employment?
  • How does the use of school to work pathways differ for our key learner subgroups?
  • Do the economic returns of the identified pathways vary for our key learner subgroups?
  • What are the pivot points at which policy could be most effective in influencing outcomes?

Products: The project team will produce an infographic on the identified student pathways, publications in a peer-reviewed journal focused on the subgroups of interest, a practitioners' brief, and a data science toolkit with open-source code. To publicize this work, the team will pursue several different dissemination strategies such as sharing the results of the study with the Washington state legislature and governor's office, as well as with all other state agencies that focus on education, disseminating findings through email announcements, direct mailings, and freely available publications on MDRC and WSAC's websites.

Structured Abstract

Setting: The project will take place in the state of Washington, using data from the state's high schools, postsecondary institutions, and labor markets.

Sample: The sample include all students who graduated from Washington state public high school, starting with the cohort who graduated in 2011 through cohort 2019. Each yearly cohort typically includes about 40,000 graduates. Of those students, approximately 33 percent received Free or Reduced-Price Lunch. In 2019 about 54 percent of graduates are White, 24 percent are Hispanic or Latino, 10 percent are Asian, six percent are two or more races , four percent are Black, one percent are American Indian or Alaska Native, and one percent are Native Hawaiian/Pacific Islander. The longitudinal data will follow students up to 12 years since high school graduation.

Project Focus: Key Issue, Program, or Policy: Stark gaps in postsecondary enrollment exist for Black, Hispanic, and Indigenous students, male students, students from low-income families, and rural students. Researchers and policymakers predominately rely on indicators such as access, enrollment, and graduation rates to assess issues of equity and efficacy of postsecondary education programs. However, less attention is paid to the issue of student trajectories. The project team will examine how different clusters of pathways (as factors) are associated with earnings or employment. In addition, the team will explore variation by learner subgroups within the identified pathways.

Research Design and Methods: The project team will combine social sequence analysis and cluster analysis to allow rich summaries of individuals' experiences. By applying sequence analysis to the SLDS, they will observe and categorize the range of possible trajectories young adults follow though postsecondary education and employment. The team will use cluster analysis to identify groups of individuals who have broadly similar trajectories. Predictive models will then identify which baseline characteristics are most associated with each group. The team will also conduct implementation research with key informants from identified pathways of interest.

Comparison Conditions: The project team will compare subgroups of students based on the aforementioned demographic characteristics and based on the level of benefit of a pathway (e.g., comparing demographically similar students who took different paths that led to more or less long-term benefit).

Key Measures: The key postsecondary education outcomes include postsecondary enrollment and postsecondary degree attainment. The key labor market outcomes include wages and employment status. The researchers will explore these outcomes for each of the main learner subgroups: Black, Hispanic, and Indigenous students; male students; students from low-income families; and students from rural areas.

Data Analytic Strategy: This study will link person-level records of education outcomes with employment data and will track individuals' pathways beginning after high school graduation through postsecondary studies and employment. This data coverage ensures robust longitudinal research, and the inclusion of wage data allows the project to associate labor market outcomes with postsecondary trajectories. The project team will use social sequence analysis to map individuals' educational and employment states (e.g., enrolled in a degree/nondegree program or employed) at specific points in time and produce dissimilarity measures. They will also apply cluster analysis to identify groups with broadly similar trajectories and predictive modeling to highlight baseline characteristics linked to each cluster, supporting equity gap identification and exploration of associations between pathways and career outcomes.

State Decision Making: The findings of this project will be used by state policymakers, legislators, and education leaders to ensure that decisions regarding postsecondary education and workforce training program options are informed by reliable evidence and are fundamentally data driven. The results are also relevant to financial aid directors and career services coordinators to provide effective programs and communicate with students and their families about opportunities they may not be aware of.

Related IES Projects: A Collaborative Use of a State Longitudinal Data System: A Study of the Washington College Grant Program (R305S230019), SLDS Grants to Washington State – Washington State Longitudinal Data System Project (R372A090024), Washington State Plan for a PK-20 Statewide Longitudinal Education Data System (R384A100016), Washington State P20W Research and Data Exploration (R372A150019), Washington State P20W Studies in Educational Equity (R372A200022)