Illuminations and Insights

At EA, we’re trying to do more than just “bridge the gap” between research and technology—we’re trying to create a new kind of organization that leverages the strengths of each field to solve the most pressing problems in public education. In our latest blog, CEO Andrew Rice and Chief of Staff Libby Pier share some of the lessons we’ve learned as we’ve worked to build a technology-enabled research organization. They discuss the cultural differences that can cause researchers and technologists to talk past each other, and highlight the commonalities across these fields that when leveraged, can help transform education into a truly information-rich, evidence-driven industry.

Two years after the release of ChatGPT, EA CEO Andrew Rice reflects on how generative AI can serve education and maintain public control. He calls for collaboration among educators, technologists, and policymakers to build publicly-owned, unified data structures and AI tools that prioritize privacy and interoperability. Andrew advocates that we can prevent data fragmentation, streamline AI tools, and protect student privacy, ensuring that the benefits of AI in remain with public institutions.

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.

The release of generative AI tools like ChatGPT has unleashed innumerable possibilities for new interfaces between computers and human experts (like teachers), where the algorithm is not just reporting information, but can instead act like a superpowered assistant. Although AI models have the potential to provide valuable insights at a low-cost to educators, challenges remain when applying these models to the education sector due to privacy concerns and data infrastructure barriers. In this blog, EA’s CEO Andrew Rice describes the importance of training AI models using specific contextual data and proposes a public-interest driven AI strategy that uses common data surfaces, prioritizes non-commercial infrastructures, and empowers educators to leverage AI tools while safeguarding privacy and avoiding commercial exploitation.

Data interoperability is poised to radically transform educational research by making work with educational data less costly but more efficient, scalable, and actionable. In our latest blog, EA’s CEO Andrew Rice highlights 10 questions that researchers could answer more meaningfully, more accurately, and more quickly when using interoperable data streams. The blog describes how interoperability is on the cusp of revolutionizing educational research by effortlessly bringing together data from different sources, allowing statistical research outputs to live in real time, and turning rigorous research into actionable, operational systems for educators.

At EA, we believe that deep integration of education research and technology has the power to create a new breed of modern, data-centric education organizations capable of achieving breakthrough student outcomes. But this integration requires the field of education research to catch up to the advances of modern technology, and the technology field to apply research-grade thinking to how we build and scale technology. In this blog, we propose that to achieve this integration, we need to replace the concept of a dataset with a data stream, and we examine this challenge from the perspective of education researchers and from technologists.