Policymakers, college leaders and students all rely on clear, timely data for decision-making. But not all data systems are created equal.
Angela Perry, a senior advisor for postsecondary and workforce pathways at the Data Quality Campaign, answers a few questions about data availability and how states can improve their data systems.
This article comes from the current issue of the Community College Journal, CC Daily’s sister publication at the American Association of Community Colleges.
Can you sum up the overall state of data availability? With changes at the federal level — particularly with the U.S. Department of Education — are we going to see more reliance on state data?
Each state’s postsecondary and workforce data ecosystem looks different. While the U.S. Department of Education (ED) collects all K–12 data through a centralized state process, postsecondary data is generally collected directly from postsecondary institutions. As a result, although postsecondary institutions that receive federal student aid dollars must report data to ED, federal rules do not require that states collect the same comprehensive and standardized data on postsecondary education.
Additionally, states’ postsecondary governance and data systems vary widely, and workforce data accessibility in particular is often inconsistent. However, all states do collect some level of postsecondary education data and several are working to improve and connect that data to both K–12 and workforce data.
Recent cuts to contracts overseen by the Institute of Education Sciences (IES), which maintains a database of education statistics and contracts with scientists in order to compile and publicize data about schools each year, will have profound implications for decision making at all levels — whether by students and families, education leaders or policymakers.
What are the challenges we’re seeing at the postsecondary institutional level – with getting state and federal data, collecting and reporting data and using data?
Data users at all levels need meaningful access to longitudinal data in order to make informed decisions about the future. While challenges such as lack of infrastructure and capacity, insufficient data governance, siloed data, difficulty with data matching and limited accessibility have delayed progress in many states and institutions, state efforts to make use of available data do exist, and there are state and institutional policies that require the collection of expanded and improved education and workforce data. Once that data is collected, it can be used to inform decision-making and support students in a variety of ways.
One of your latest reports, “Powering Potential,” looks at state-level data systems. Can you talk about the importance of statewide longitudinal data systems?
Statewide longitudinal data systems (SLDSs) bring together individual-level data from across different sectors — early childhood, K–12, postsecondary and workforce — over time. Connecting this data enables states to view long-term outcomes from policies, student choices, and educational programs. These systems can empower data users at all levels to access and use data to support students on their journeys to and through postsecondary education and to ensure that students get a return on their investment.
Which states are doing a good job in capturing and using data? Can you give an example or two of what those states are doing?
Some states are using data in innovative ways to support postsecondary access, completion and ROI. For example, the Maryland Longitudinal Data System (MLDS) Center integrates data from the Maryland Apprenticeship and Training Program to assess the outcomes of apprenticeship completers. By examining employment and wage outcomes, this integration helps the state measure the effectiveness of apprenticeship programs in advancing participants’ careers. The insights generated inform workforce development strategies and program improvements, ensuring that apprenticeships meet labor market demands while offering high-value career pathways.
Another example is Minnesota’s Graduate Employment Outcomes tool, which is powered by its Statewide Longitudinal Education Data System (SLEDS). This resource combines data from the Minnesota Office of Higher Education and the Department of Employment and Economic Development and offers detailed insights into employment rates, wages and industry sectors for graduates, enabling program evaluation and career planning. The tool also meets Workforce Innovation and Opportunity Act (WIOA) reporting requirements, supporting compliance while enhancing the state’s ability to align education and workforce initiatives.
What are some ways states can improve their data systems?
Ensuring students have access to postsecondary education, receive the support necessary to complete their programs and experience a return on their education investment must be a high priority for states. To use data to support students navigating complex education and workforce transitions and to ensure they are successful in postsecondary education and the workforce, states must take action to:
- Codify and implement cross-agency data governance to ensure shared decision-making and inclusive representation from contributing agencies. When it comes to data, when everyone is in charge, no one is in charge. That is why it is so important for state decision-makers to demonstrate leadership in how data is collected, protected, accessed, and used through establishing cross-agency data governance.
- Identify their education and workforce priorities, and then integrate necessary data across K–12, postsecondary and the workforce within the SLDS to meet those goals. Collecting and connecting high-quality, individual-level student data across sectors enables states to view outcomes, and states must invest in robust data matching processes to connect data across sectors to accomplish their goals. Additionally, for detailed and innovative insights, states must include robust individual-level data disaggregated by factors such as race, ethnicity, income level, gender, disability status and geographic location.
- Invest in strengthening the source systems — early childhood, K–12, postsecondary and workforce — alongside investments in SLDSs to ensure data is accurate, accessible and actionable. Sustained, dedicated funding and capacity-building support are essential to ensure that SLDSs serve their intended purpose: enabling data to work for people. While federal funding is important, states must invest their own resources into making this data ecosystem a reality.
- Demonstrate the value of data sharing to contributing agencies and institutions by taking steps to simplify and improve reporting processes and providing meaningful analysis back to the data providers. These essential stakeholders are more likely to engage when they see clear benefits for the work they are responsible for undertaking.
- Develop tools that deliver the right data to the right audiences, ensuring the information is timely and useful. It is critical to identify the intended audience and clarify the intention of the tool to determine the information required to effectively make use of it — whether it be individual-level student data to support advising or high-level aggregated trends for policymakers and institutional leaders. By aligning data tools with users’ specific needs, states can maximize the value of their data systems and ensure people have the information they need to drive meaningful outcomes.
