Illuminations and Insights

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.

Data generated by students and teachers are often locked up in siloed data systems across school districts, with hundreds of disparate systems within a given district. Despite substantial investments from government and philanthropic organizations into figuring out how to unlock these data, we still haven't seen the progress needed to drive widespread change in the market. In this blog, Chief of Partner Strategy Jami O’Toole addresses this paradox and outlines key strategies to accelerate solutions for these data interoperability challenges.

We had the opportunity to sit down and talk with EA Board President Dr. Richard Bowman about the challenges impacting education and data spaces, what excites him the most about being affiliated with EA, and how he thinks the field is going to change in the future.

At Education Analytics (EA), we enjoy collaborating with our staff and partner organizations to write blogs that discuss the current challenges and successes in education and data spaces and work at EA. In this blog, we reflect on this past year, highlight our five most popular blogs of 2023, and look forward to what 2024 holds for EA.

At Education Analytics, we’ve seen firsthand the advantages given to the education field when we can connect data systems, like attendance, assessment, lunch programs, and more together through Ed-Fi. Whether you are just starting your exploration of how Ed-Fi can benefit your work, or you’re established in the process, here are five Ed-Fi vocabulary terms to know and share: Interoperability, Education Agency, Source System, Student Information System, and Data Warehouse.

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.