Data management professionals recommend integrating siloed data to create a comprehensive dataset that brings enhanced value.
Every state collects data for children and students pre-kindergarten through postsecondary and beyond, including employment. This data is a valuable resource to inform policy and practice, and by integrating or pulling together various data sources, it can support a cohesive, seamless education system that performs better.
Over the past ten years, education data systems have undergone a significant transformation. They have made progress in moving from independent silos of aggregate data around a specific program or sector to repositories of longitudinal, linked, child, student, and staff-level record data with connections across programs agencies and sectors.
Every state has developed statewide longitudinal data systems (SLDSs) to support data-informed decision making through early childhood, K12, and postsecondary systems. Yet in many states across programs, agencies, and sectors, pockets of isolated data remain and the full potential of data integration has not been realized.
In fact, a survey conducted in 2015 indicated that less than 20% of states had the special education data needed to satisfy required federal reporting integrated with their SLDS.
Data integration paints the big picture.
Data integration combines data from different sources into valuable information. When applied across early learning, K12 and post-secondary data systems, this means ensuring the data from various sectors and their program areas can be seamlessly combined to provide a cohesive picture.
For the past decade, many states have been building, managing, and enhancing longitudinal data systems that contain student level data connected over time. In the best situations, these systems include data not just about the student’s demographics and academic progress, but also about programs in which the child or student has participated, such as special education, career and technical education (CTE), English language learner programs, migrant education, after school tutoring, and others.
A data system that integrates data across programs and sectors provides a rich source of information for program administrators, school leaders, researchers, and policymakers to understand what works and how to invest resources.
Information matters.
Students, parents, educators, program managers, school administrators, community leaders, legislators, and stakeholders all need information in order to make effective decisions regarding education.
Three examples:
1. Program managers need information on the outcomes of students in programs like reading interventions to determine fidelity of implementation.
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- For example, it would be valuable for reading program managers in elementary and middle schools to know about the high school remedial course taking patterns of students who participated in their reading programs.
2. Students need information to decide what post-secondary institution to attend, what classes to take, and what programs to enroll in.
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- For example, it would be valuable for a student wanting to major in computer science to know the types of companies that graduates from different institutions find their first jobs with.
3. Integration of special education data into an SLDS can allow special education program staff to analyze the progress of students with disabilities as compared to the total student population.
- They would also be able to identify schools and districts whose special education students have high achievement levels (enabling identification and dissemination of best practices), and more easily extract data for required federal reporting.
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Moving from data silos to an integrated data system is not without costs, but the payoff can be substantial – not only in dollars and human resources, but in the increased value and usability of the data.
Integrated data systems provide many benefits to data providers and data users.
They save money and resources:
- Reduces staff burden for programs and schools through elimination of duplicate data entry
- Reduces staff burden for the state by minimizing efforts toward reconciling inconsistent data
- Reduces system costs by eliminating the need to maintain and reconcile redundant and inconsistent data and processes
- The same data, such as student program participation, will never match when collected by two different systems. Save time and energy by integrating the data to reduce redundancies and eliminate effort to reconcile different systems.
They make data more valuable:
- Increases the quality of data collected, reported, and used
- Integrated data has a higher value and is more likely to be used. Data that is used is higher quality data. Follow data management best practices and integrate your data to increase its use.
- Provides the ability to cross-validate data and minimizes the risk of inconsistent reporting
- Reduces security risks by minimizing the number of systems for storage and data access
They make data more usable:
- Allows the program area to provide context and meaning to research and evaluation efforts
- Provides program areas with evidence to evaluate and demonstrate the effectiveness of the program
- Improves communication, collaboration, and relationships between programs, agencies and sectors
- Integrating data across agencies in different sectors is an excellent way to build relationships and collaboration. For example, collaboration between a state education agency and institution of higher education on high school feedback reports could lead to relationships and work in other areas, like teacher preparation.
What are some next steps?
As described here, data integration leads to informed decision making. Check out some of our other blog posts that explore topics in data education, such as data standards and interoperability.
Have any questions? Contact us any time.
