Strategic Data Project Convening 2026

Session Description: Districts often struggle to build trust with community stakeholders that their input has been captured, accurately represented, and equitably reflected in decision making. Atlanta Public Schools will share how it explored the use of artificial intelligence to support large scale community feedback, including data sources, validation strategies, and efficiency gains. Participants interested in engagement, data, and equity are invited to join a closing discussion on persistent challenges, including how to better surface and amplify voices that have been historically underrepresented.

Intended Audience: Districts, charters or other local education agencies; State education agencies; Higher Education

Session Description: Education data systems are abundant yet fragmented, unstable, and difficult to reuse for
strategic decision-making. This session offers two solutions to address these challenges. First, we present a FAIR-aligned framework and practical tools for mapping, stabilizing and reusing education data from a cross-state study of 3,822 public K-12 datasets. Then we present findings from an empirical study of AI-produced mappings across higher education data sources to show which AI models provide the best balance between performance and cost. Together the session provides an interoperable way to work with K-12 datasets and a means to scale the mapping of education data.

Intended Audience: Districts, charters or other local education agencies; Managers of data or technology teams; Senior leaders (including cabinet-level leaders and executive directors)