Making education data accessible

Zelma, a GPT‑4 powered research assistant, is making education data accessible to parents, teachers, school administrators, and policymakers across the United States.

The problem they’re solving? While standardized tests are issued to every student in grades 3–8 in the U.S., data about how students perform remains largely untapped and underutilized, scattered across different sources and formats. Test data offers powerful insights into how well students are learning in English language arts (ELA) and math, across district and demographic group levels. But crucial insights that could shape the future of education are effectively beyond the reach of most parents, journalists, educators, and policymakers.

Recognizing this gap, Dr. Emily Oster, a Brown economist and author, set out to change the narrative. “Zelma makes it possible for parents and policymakers alike to use plain language to get instant, tailored educational insights on what matters most to them,” Dr. Oster explained. How did Zelma accomplish this? Dr. Oster’s team of student researchers at Brown University spent a year gathering the data and meticulously cleaning it into one uniform format. Zelma then worked with Novy⁠(opens in a new window) to bring the data to life using OpenAI’s API.

Novy leveraged function calling⁠(opens in a new window) to tell GPT‑4 which visuals and fields to choose from in displaying the data. For Zelma’s "Ask a Question" view, they fine-tuned⁠(opens in a new window) a model to create a data-aware type-ahead that suggests questions with available data. And they embedded⁠ and stored known-good example graphs in a vector database to improve accuracy on difficult edge cases.