Strategic Data Project Convening 2026

Session Description: Large public data systems are often built for accountability, then later expected to support urgent, human-centered decisions they were never designed for. This session examines what it actually takes to repurpose administrative data responsibly, using work from the California Community Colleges in response to the 2025 Los Angeles wildfires as a case study. Participants will explore why meaningful analytic insights often emerge after moments of crisis, and how putting processes in place ahead of time can make data more actionable, ethical, and useful when systems are under stress.

Intended Audience: Districts, charters or other local education agencies; State education agencies; Institutions of higher education; Data analysts or independent researchers; Senior leaders (including cabinet-level leaders and executive directors)

Session Description: What happens when Early Childhood Educators drive research and data analysis about the sector? This session explores a Participatory Action Research (PAR) and Policy model developed for Black and Latine women in ECE. Based on the report "Participatory Action Research and Policy Change" we will explore model design, impact on worker agency, and strategies for successful implementation. System and policy leaders will gain insights into how to implement PAR to improve listening, empathy, and trust.

Intended Audience: Senior leaders (including cabinet-level leaders and executive directors); Philanthropies and Foundations; Nonprofit organizations

Session Description: Many districts struggle to ensure that their investments in educational programs improve student outcomes and are implemented with integrity. Participants will explore one district’s successful Outcomes Based Contracting approach—which produced a 0.39 SD effect in middle school math—and gain practical tools including contract templates, a framework for evaluating evidence, and strategies for building data partnerships that drive continuous improvement. Data leaders are especially encouraged to attend to strengthen evidence-based resource allocation practices.

Intended Audience: Districts, charters or other local education agencies; State education agencies; Managers of data or technology teams

Session Description: SEA staff across the country face shared challenges in data reporting, assessment, and accountability but often lack opportunities to connect with peers in similar roles. This networking session will bring SEA professionals together for structured small-group discussions to share experiences, compare approaches, and learn from one another. SEA staff working in reporting, assessment, accountability, research, or related roles are encouraged to attend.

Intended Audience: State education agencies; Data analysts or independent researchers; Managers of data or technology teams

Session Description: Knowing whether educational improvement efforts are yielding improved student outcomes often depends on information outside state longitudinal systems. From Logs to Learning shows how a data standard for tutoring creates shared definitions that enable transparency, comparability, faster feedback loops, and high-quality continuous improvement. We will share an open tutoring data standard and toolkit, then present a case study with Florida Tutoring Advantage, Littera, and Accelerate demonstrating earlier-cycle monitoring, cross-district benchmarking, and implementation refinement.

Intended Audience: State education agencies; Districts, charters or other local education agencies; Service providers