State education agencies (SEAs) have always had a difficult job. While their primary purpose has traditionally been to set policy and regulations, ensure compliance, acquire and distribute funding, and monitor performance, they are now at a crucial crossroads. The outdated patchwork infrastructure that has previously been used to accomplish their direct role is no longer an affordable option due to the rapid innovation of technology.
So, what next?
While the world of technology quickly evolves, SEAs that cling to legacy systems stand still. As a technologist who has worked in the education industry alongside SEA leaders to build and manage state longitudinal data systems (SLDS), I have never believed more strongly in the need for data system modernization.
Let’s discuss the current state of technology and data infrastructure in K–12 education from the perspective of an SEA investigating the potential value of a modern, cloud-based SLDS and how this step is foundational to unlocking the power of AI and predictive analytics.
How Antiquated Data Systems Hold Back Progress in K–12 Schools
The legacy systems many SEAs have in place use old technology, old programming languages, and on-premises infrastructure, often cobbled together over the course of 20-plus years. Data resides in silos with limited interoperability, resulting in slow response times and cumbersome, manual processes for analyzing data and generating useful reports.
Technology that’s slow, inefficient, and error-prone cannot meet the demands of today’s data-driven world, particularly in the public sector. In the K–12 sector specifically, data collection, reporting, and analysis are not happening at the pace or scale required to make meaningful decisions.
Educators, administrators, and policymakers are hungry for actionable insights, and the SEA often already has massive amounts of meaningful data that could be leveraged. However, a massive gap exists between the collection of data and the delivery of digestible, real-time insights downstream. This lag limits the ability of SEAs to indirectly support districts and schools in proactively implementing near-real-time student interventions, allocate resources, and optimize performance.
Cloud-Native SLDS: Scalable, Flexible, Fast
A cloud-based approach is critical to modernizing a state’s longitudinal data system. We’ve already seen this happen with some forward-leaning states like Indiana, Nebraska, Texas, and Georgia. There’s no question anymore that cloud-native data systems are scalable, flexible, affordable, and secure, allowing SEAs to move away from on-premises legacy systems that have become fiscally irresponsible to maintain “the way we’ve always done it,” as some might say.
Instead of being limited by the compute power, storage capacity, and network speed of on-premises infrastructure, moving to the cloud makes it possible for SEAs to collect, store, analyze, and, most importantly, provide vast amounts of data at unprecedented speeds, all while maintaining the highest levels of data security and privacy.
Instead of taking months to collect and analyze assessment data, cloud-based SLDS can generate reports in near-real-time, since compute and storage resources can automatically scale to meet current demand. And the SEA will only pay for what compute/storage/networking they actually use (operating expenditures) as opposed to the recycling of servers, routers, and data centers they pay for today (capital expenditures).
The flexibility of the cloud allows for seamless integration of various structured and unstructured data streams. This data integration can create a holistic view of aggregate student performance data using early childhood through post-secondary education insights. This would enable districts and schools to shift to proactively generating actionable insights that drive positive outcomes for educators, students, and families.
AI and Predictive Analytics: The K–12 Game-Changer
Imagine a world where data can be used to proactively predict and prevent challenges before they happen. This is the promise of integrating AI and predictive analytics into modern SLDS and serving these insights back to the state’s constituents. By using historical data to identify patterns and predict future trends, schools and districts can gain access to actionable insights that empower informed decision-making at every level.
Predictive learning models can use AI to help districts anticipate staffing needs based on enrollment trends, optimize funding and resource allocation for high-needs areas, and even predict long-term outcomes like graduation rates and college readiness. All of this is achievable, but only with the right infrastructure: modernized, cloud-based systems designed to handle autoscale-capable data analytics.
Empowering Educators and Administrators: Data with Purpose
More than simply collecting high volumes of data, modernizing state SLDS would empower the SEA to deliver the right data to the right people at the right time. Investments in cloud-based, AI-driven systems will provide schools and districts with near-real-time dashboards, performance metrics, and predictive insights that empower them to make data-driven decisions.
Resultant’s education team knows a thing or two about secure data interoperability. In fact, we received the 2023 Innovation of the Year Award from Ed-Fi Alliance for our work on the development, implementation, and configuration of the Indiana Department of Education’s Graduates Prepared to Succeed (GPS) dashboard. The GPS dashboard uses longitudinal data from multiple agencies and provides insights that inform decision-making.
Think about the impact of an SEA providing a district superintendent with a near-real-time dashboard that shows early warning indicators for students at risk of dropping out, as well as personalized intervention strategies. Imagine empowering a school principal with near-real-time teacher performance data and predictive models that can identify areas where professional development is most needed. These tools have the potential to transform how we address issues like chronic absenteeism, learning loss, and achievement gaps.
The possibilities are endless when meaningful, actionable data and easy-to-understand insights are delivered directly to those who need it most: teachers, administrators, and policymakers on the front lines of education. The role an SEA can have in making this happen is exciting.
Investing in Positive Change and Progress
SLDS modernization is not a luxury. It’s now a necessity that requires investment. The world around us is changing, and education must change with it.
States must prioritize funding for cloud infrastructure, AI capabilities, and predictive analytics as core components of their education strategy. Advocacy for training and professional development is needed to help school staff and administrators fully understand and leverage the power of these tools.
The goal is not just to build modern systems, but to foster a culture of data-driven decision-making at every level of education.
Building the Future of Education, Today
The modernization of SLDS is not just a technical upgrade. It’s an opportunity to revolutionize the way we approach education in the K–12 sector. By embracing cloud-based infrastructure, AI, and predictive analytics, we can move from reactive to proactive decision-making, empower educators with real-time data, and drive meaningful change that transforms student outcomes and paves the way for a brighter future. The time to act is now.
Let’s commit to building data systems that work for educators and students alike. Today’s investment will pay dividends in the form of more equitable, effective, and impactful education for generations to come. Please reach out to Resultant for a FREE Gap Analysis and discuss the benefits of moving to modern, cloud-based SLDS.
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