Putting SLDS to Work: A New SDP Tool to Link Education and Workforce Data

“These datasets are powerful tools. They can help states better understand the critical junctures where students need more support and how those junctures relate to their later outcomes in life.” - Dr. Rachel Worsham, senior research analyst at the Center for Education Policy Research at Harvard University 

How do we understand students’ movement from K-12, to and through college, and into the workforce? Do we know where students need support along the way? If the purpose of education is to prepare students for their future, policymakers need to have the answers to these questions at their fingertips.  

These questions, and more, drive the federal Statewide Longitudinal Data Systems (SLDS) Grant Program, which has funded efforts in all 50 states and the District of Columbia to link data across agencies and build new data systems that can track inputs and outcomes in four domains: early learning, K–12, postsecondary education, and workforce participation. A recent review found that 42 states have started to build a SLDS so far, and 33 states are actively using their systems. 

With these data, analysts can track student progress from early learning to the workforce, linking earlier academic experiences with future outcomes. But building those analyses from scratch in every state could take years. 

Enter the Strategic Data Project’s Education to Workforce Pathways Diagnostic Toolkit, a plug-and-play data analysis and visualization tool built to help educators trace K–12 students’ journeys through postsecondary studies and the workforce. This rich, open-source suite of guidance and analytic code can be used in any state to answer questions like: How many students earn a post-secondary credential within 10 years of high school graduation? Which students enroll but don’t get a degree? Which students go on to earn a living wage as adults? 

“These analyses can provide insights into where states and schools should invest resources,” said Dr. Rachel Worsham, a senior research analyst at the Center for Education Policy Research at Harvard University, which houses the Strategic Data Project. Dr. Worsham spearheaded the tool’s development. “For example, if we see that certain students are less likely to have earned college credentials by 10 years out of high school, we can assess whether these gaps in attainment rates are more driven by students not entering college or entering college but stopping out before they graduate. This will help states discern whether to focus scarce resources on college enrollment campaigns, stop out efforts, or both.”  

Investigating Outcomes for Students and States 

The SDP Diagnostic is informed by the Education-to-Workforce (E-W) Indicator Framework, which articulates the questions states can use to measure student success as well as key indicators and disaggregates used to answer these questions. 

With its readymade Stata code and accompanying technical guidance, the SDP Diagnostic builds on the E-W framework to help analysts in states with SLDS to answer key questions about education and workforce outcomes.  

The new diagnostic has four areas of focus and specific guidance and code to answer pressing questions in these domains, such as: 

• Patterns in Educational Attainment: How many students earn postsecondary credentials within 10 years of high school graduation? Are some students more likely than others to earn postsecondary credentials? 

• K12 to College Enrollment: How many students enroll in college within one year of high school graduation? Which students are more likely to enroll in college right away? 

• College Completion and Stop Out: Which state high school graduates stop out of college? Which students are more likely to stop out than others? 

• Earning a Living Wage: How much more do college graduates earn than workers with a high school diploma? Which students are more likely to earn higher wages? 

The Diagnostic also includes examples of data visualizations that are easy for nontechnical audiences to understand.

Synthetic Data, but Rooted in Real Life 

While the sample analyses provided in the toolkit use synthetic data, the toolkit was developed using actual data from two state partners, in collaboration with SDP Fellows. 

After creating actual analyses for partner states, SDP then created “skeleton code” that any analyst can use with their own data, said Worsham. This ensures that the Diagnostic is realistic and responsive to state agencies’ data structures and needs. The detailed narrative guide that accompanies the technical tools is designed to instruct and inspire, with how-to steps on data structure and presentation, as well as prompts for follow-up questions and further analyses. 

It's all in service to SDP’s broader mission: “to provide resources that expedite analyses and answer critical questions,” said Worsham. 

“Analytic staff are often focused on meeting requirements to report data to the federal and state government, which takes a lot of time and energy,” she said. “This helps to supplement their capacity and make the barrier to answering these types of questions a little bit lower.” 

------- 

The tools and analyses were prepared and supported by Atticus Bolyard, Sue Dynarski, Jon Fullerton, Miriam Greenberg, Julia Lubner, Aleksei Opacic, Eric Taylor, and Rachel Worsham (listed alphabetically).   

The authors would also like to thank Elise Swanson, Lisa Sanbonmatsu, Mimi Tan, Alyssa Reinhart, Julia Bloom-Welton, Jayashree Krishnan, Jackie Lundberg, Bonnie Nelson, Dani Fumi, Katie Weaver-Randall, as well as our state partners for their feedback and guidance throughout the development of the tool. 

The SDP Pathways Diagnostic was prepared with support from the Bill and Melinda Gates Foundation. 

Access the full tool on SDP’s website.

This abridged blog was originally posted on the Strategic Data Project website.