Illuminations and Insights

At EA, we strive to build standard data infrastructure that democratizes data access, so educators can gain insights and improve student outcomes. In the age of AI, we are expanding that goal to cover not just data infrastructure, but “AI infrastructure” as well. That means building a system for AI-friendly context and deploying tools that utilize LLMs to answer prompts, so educators or agency staff who otherwise don’t have the time or technical expertise can access the data insights they need. We have built Stadium AI to test the hypothesis that a natural language interface on top of a well-structured education data warehouse could let more people, not just analysts, ask questions about their data and get answers they can trust. We started with testing a beta version of Stadium AI with real analyst users at the South Carolina Department of Education (SCDE) to see how they would use it, and if that could inform how a broader audience may use the tool. What we didn't expect? What users would ask when given the tool. In this blog, Technical Lead Manager Rob Little and Senior Product Manager Molly Stewart share what we've learned throughout the process of building Stadium AI.

CEO Andrew Rice explores the growing role of AI-powered tutors and learning agents—and the powerful, deeply personal data they are beginning to capture. These systems don’t just track performance; they build a longitudinal model of how a student thinks, learns, and engages. Right now, much of that “learning context” lives on corporate servers. In the blog, Andrew proposes a different path: a custodian model, where student learning data is held in trust by institutions, but owned by students and their families—portable, auditable, and protected.

In this blog, CEO Andrew Rice reflects on the new vision document from the Institute of Education Sciences (IES), Reimagining the Institute of Education Sciences. In the blog, Andrew shares how strongly the vision resonates with the work EA's been building toward for years—especially the call to move education data from a static snapshot to a continuous stream. Real modernization requires shared, durable software. It requires governance, engineering capacity, and cross-state collaboration through models like state consortia. It requires equipping researchers with data engineering skills alongside statistical expertise. Andrew reflects on what it will actually take to make the IES vision a reality—and why this moment matters.

K-12 has lived through many “next big things” in edtech. Some have delivered real value, especially in large-scale data collection and adaptive learning. But across states and districts, student outcome progress and gaps remain stubborn, and leaders are rightly skeptical that a new wave of AI tools alone will change that. This is not simply a failure of technology. It reflects a basic fact: no algorithm can solve challenges rooted in resource inequities or social conditions. What AI can do is help educators, policymakers, and researchers reason more clearly with the information they already have. That only works if the data are accurate, standardized, and connected, and if the people closest to students remain in charge of how those data are used. In this blog, Vice President of Data Science Dan Jarratt discusses how, in order to ensure that AI systems that are effective, auditable, and equitable for students, we must start with something more basic: open, interoperable, standardized data infrastructure that public agencies can govern and sustain.

The conversation about AI in education has been dominated by the power and potential of AI to further galvanize ed tech usage and impact in classrooms. It’s time for that conversation to expand to focus on the opportunity—and the need—for staff at Local Education Agencies (LEAs) and State Education Agencies (SEAs) to embrace AI literacy. In this blog, we highlight three focus areas with action steps that agencies can take to build up their AI literacy to ensure they are well positioned to navigate and embrace AI usage within their agency.

From March 3 - 7, several Education Analytics’ staff had the opportunity to attend and present at SXSW EDU in Austin, TX. CEO Andrew Rice and EA Board President Richard Bowman (Chief Information and Strategy Officer at Albuquerque Public Schools) presented the session, “Data Interoperability & AI: Veggies Before Dessert.” Also in attendance at SXSW EDU was Development Strategist Ben Dederich, Director of Brand & Communications Marlena Holden, and Chief of Staff Libby Pier. In this blog, the group reflects on their time at SXSW EDU and highlights their key takeaways from the conference.