Enhancing Education Data Systems: A Guide for State Education Agencies

There’s money on the table for state education agencies to do more with their data. Education data systems enable state education agencies to respond effectively to unforeseen events like the COVID-19 pandemic, for example. These systems, collectively known as statewide longitudinal data systems (SLDS), have helped states uncover new questions about their data, address inequities, assist individuals through special programs, and mitigate learning losses.

With the availability of grant opportunities to modernize SLDS, state education agencies have a unique chance to strengthen their data infrastructure and improve their ability to inform policy decisions. But how best to use these funds? We’ve worked with a lot of states to do just that and have developed some suggestions.

1. Understand the priorities.

The grant opportunity outlines four key priorities for the development and use of SLDS:

  • Infrastructure and interoperability
  • College and career
  • School Finance
  • State policy questions

It is essential to thoroughly comprehend each priority and evaluate which aligns best with your state’s specific needs and goals. Resultant leverages its subject matter expertise to evaluate a set of proven accelerators. These accelerators have assisted state leaders in determining which use cases would effectively address their most urgent priorities and gain significant support from stakeholders. A growing trend with the expansion of work-based learning initiatives and career pathway programs by the Biden Administration many states are looking for ways to invest dollars to improve the collaboration and data sharing between schools, colleges, workforce development agencies, and employers.

2. Assess existing infrastructure.

Before embarking on any SLDS modernization project, conduct a comprehensive assessment of your current data infrastructure. Identify strengths and weaknesses, evaluate data quality, storage capacity, security measures, and interoperability capabilities.

Understanding the existing infrastructure will help you identify the necessary upgrades and determine the best use of grant funds. Resultant’s strategic data assessment has helped numerous state agencies identify areas of opportunity and map out which to address in the short and long term.

3. Engage stakeholders.

Effective data systems require input and collaboration from various stakeholders. Engage with educators, administrators, researchers, policymakers, and community representatives to understand their data needs and challenges. Seek their insights on the potential improvements that can enhance the value of the SLDS system.

By involving stakeholders in the planning and implementation process, you can ensure that the modernization efforts address their requirements and priorities.

4. Prioritize interoperability.

Interoperability is a critical aspect of modernizing SLDS systems. When you enhance data interoperability to facilitate seamless data exchange between various education entities, such as K-12 schools, the state education agency (SEA), colleges, and career training institutions, you enable comprehensive tracking of student progress, inform college and career readiness initiatives, and ensure a holistic view of educational outcomes.

Through work with several of our clients, Resultant has expanded the utility of interoperable platforms beyond the exchange between various education entities to include the exchange of information between the SEA and other state agencies. For example, increasingly, states desire to share data between the SEA and the agency responsible for workforce development and post-secondary attainment to address the school-to-workforce pipeline.

Resultant has expertise in including data related to career pathways, workforce outcomes, and post-secondary education transitions. One example is the Indiana Graduates Prepared to Succeed platform created by Resultant in partnership with the Indiana Department of Education. This integration has enabled educators, policymakers, and employers to make data-informed decisions to improve career readiness, align education programs with workforce needs, and support the continuous improvement of education services and outcomes.

5. Enhance data security and privacy.

Increased reliance on technology and data makes robust data security and privacy measures critically important.

While the latest technologies have prioritized security, states would be wise to devote funds towards operationalizing their governance structures. Resultant works with agencies to develop and implement a robust privacy and data governance framework to ensure compliance with relevant regulations and protect the privacy rights of students and individuals.

This framework establishes clear guidelines for data collection, storage, access, sharing, and retention while promoting transparency and accountability in data management practices. Our consultants work shoulder-to-shoulder with state representatives to model and facilitate how various teams should work within the governance framework.

6. Make data accessible.

Historically, investments in SLDS accessibility have prioritized research and policy-making audiences. What about the students themselves? These systems could be positioned to increase student agency through interactive and user-friendly student success dashboards that provide real-time access to comprehensive data on individual students, including academic performance, attendance, behavior, and socio-economic factors.

Any SLDS-related dashboards should enable educators, administrators, and parents to monitor student progress, identify areas for improvement, and make data-driven decisions to support student success.

7. Increase capacity.

Artificial intelligence (AI) has become the topic du jour. Most SLDS platforms today have been designed to examine what happened in the past. To mature in this area, SEAs should prioritize activities that move the state toward using these systems to predict what might happen in the future to optimize outcomes. This type of prescriptive analytics should include inter-agency data communities.

Allocate grant funds towards building data analytics capacity within SEAs and educational institutions. Provide training programs, resources, and technical assistance to educators, administrators, and data professionals to enhance their data literacy, analytical skills, and knowledge of best practices in data-driven decision-making.

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