Translating Data: Using Student Performance Data to Inform Policy and Improve Outcomes

By Linda Baglia, Jeff Stanley -

Over the past two decades, states have built data systems to capture and store vital information that can be used to measure student performance. Most states have K-12 and postsecondary data repositories that hold statewide longitudinal data on enrollment, demographics, assessments, retention and completion. Increasingly, states have invested in comprehensive online data dashboards in an attempt to increase transparency on how students are progressing through the educational system and into the workforce.

What’s less clear is how effective these dashboards, and the data systems that drive them, are for actual decision making. Are the systems answering the questions posed by policymakers, and if not, where are the gaps? Are the dashboards easy to find and understand and do they provide the necessary information to follow students through school to the workforce? And the biggest question — are policymakers using the information to make informed policy decisions, and if not, why?

Data collected by states is used for a variety of purposes, including to inform policymaking and improve consumer choice. However, it’s primarily used to hold schools and institutions accountable for providing high quality and equitable education. Collectively, local, state and federal policymakers have a high stake in understanding the return on investment of public dollars invested annually in education, from early learning through college, and into workforce development efforts. The goal of collecting, connecting and translating student data is to ensure our public investment is serving its intended purpose — to provide quality education to our residents in a way that ensures their future success and prosperity.

35 states have postsecondary data systems that also connect to K-12 and to workforce/labor [1]

27 states have student data in some sort of online dashboard or report that is easy to find and accessible to multiple stakeholders [2]

And what gets measured matters. When states collect equity-focused demographic data like race, ethnicity, gender and income levels, they can quickly identify gaps and develop targeted solutions to address inequities. States that collect data on student enrollment and progression can see where in the pipeline students are most likely to falter or drop out, making it easier for institutions to provide extra support when it is most needed.

Comprehensive and connected data allows us to identify the gaps, understand where and why they occur, provide feedback loops between sectors, and translate that information into actionable, promising practices that improve student outcomes. Postsecondary data on enrollment and retention can provide important insights to K-12 about college readiness levels. Workforce employment data can provide feedback to postsecondary about which credentials and skills are in high demand. And critically, the transparency and accessibility of this data allow for better stakeholder advocacy. For example, data-driven advocacy laid the groundwork for remedial education reform and guided pathways development – two movements that are beginning to yield improved outcomes for students.

32 states disaggregate their postsecondary data by race or ethnicity [3]

Though most states collect a variety of enrollment and progression data elements, only 13 states have established feedback loops with the K12 and workforce sectors to share these data [4]

So how can states establish effective data systems and translate hundreds (maybe thousands) of data points into useful information for decision making by policymakers?

HCM’s research and work with states reveals some promising practices for consideration:

  • Identify the audience (in this case state policymakers) and create metrics to answer their key questions and track progress of key state priorities and needed outcomes.
  • Ensure that the state’s longitudinal data system contains data to populate those metrics and if not, establish a long-term vision, goals and action plan to get there.
  • If not already in place, establish linkages (through cross-sector agreements or a consolidated data system) to follow students from early learning through the workforce and ensure coverage of a significant proportion of the state’s student population.
  • Create robust governance and security plans that protect the privacy and integrity of student data.
  • Prioritize adequate funding to ensure sustainability and future improvement of the data system.
  • Conduct regular audits and annual updates to ensure validity and reliability of the data.
  • Provide regularly updated, public dashboards that are simple to follow and answer the key policymaker questions on an easily accessible and navigable website, including availability in multiple languages.
  • Create and make publicly available simple instructions or storyboards on how to use and interpret the information.

Ultimately, states need to articulate what they are trying to accomplish, identify which data they can use to help them make their case and report out clearly in an easy to understand format. As data-driven decision making becomes standard, the efficiency of state data systems will only increase in value to policymakers. Efficient systems that provide the most useful data across multiple sectors hold the potential to help states meet attainment goals, narrow achievement gaps and solve difficult problems.

[1] Strong Foundations, State Higher Education Executive Officers (SHEEO), 2018

[2] Original research conducted by HCM Strategists

[3[ Original research conducted by HCM Strategists

[4] Original research conducted by HCM Strategists

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