Strategic Data Project Convening 2026

Session Description: The promise of a data warehouse is realized when schools trust and rely on it to support students in real-time. Learn how continuous improvement and collaboration with educators led to a system used daily in schools across the district. Attendees will examine high impact reports, see how innovative data are transforming practice, and leave with strategies to increase adoption and improve reporting immediately in their own contexts. Ideal for data, school, and district teams.

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

Session Description:

Education leaders often need to turn complex data into clear, usable tools for planning and decision-making. In this hands-on session, participants will use a teacher workforce planning example to learn how R Shiny apps are structured and how interactive features are built. The session will introduce the roles of global.R, ui.R, and server.R, then guide participants through simple edits that change the app layout, connect outputs to server logic, and add user controls that update what the app displays.

Participants will leave with a fully functional Shiny app template based on the Teacher Workforce Planning Tool being used at the Delaware Department of Education, available through GitHub: https://github.com/MatthewFaiello/twpt_shiny_app_toy

Intended Audience:
This session is designed for SEA, LEA, charter, and education nonprofit staff who work with data or decision-support tools, including analysts, program managers, data and technology leaders, and senior leaders who want a practical introduction to interactive data applications.

This session assumes participants have an understanding of R syntax and basic data manipulation and visualization skills.

Session Description: This session explores how emerging speech and sensing technologies and teacher-feedback tools can enhance school-readiness measurement by capturing naturalistic indicators of language, engagement, and self-regulation. Speakers will examine links between these multimodal data sources and traditional readiness assessments, highlight responsible integration within multilingual and culturally diverse classrooms, and share models for open, researcher-accessible data infrastructures. Participants will gain actionable insights for incorporating these innovations into early childhood and P20W data systems to support equitable, evidence-based decision-making.

Intended Audience: State education agencies; Philanthropies and Foundations; Managers of data or technology teams

Session Description: Education leaders often default to "additive bias," layering initiatives until systems become cluttered and ineffective. This interactive session reorients leaders toward achieving coherence through strategic subtraction. Drawing on Leidy Klotz’s research, participants will audit their agencies for "zombie programs" and redundant processes using a practical "Proving and Improving" laboratory. Attendees will leave with a roadmap to reduce initiative fatigue, reallocate resources, and create space for high-impact practices to flourish.

Intended Audience: Districts, charters or other local education agencies; State education agencies; Philanthropies and Foundations; Data analysts or independent researchers; Managers of data or technology teams; Senior leaders (including cabinet-level leaders and executive directors); Nonprofit organizations; Service providers

Session Description: Accessing and analyzing education finance data requires significant data wrangling expertise, creating barriers for researchers, advocates, and policymakers. In this hands-on workshop, participants will use edfinr – a free, open-source R package – to load clean school finance datasets, analyze funding patterns, and adjust for inflation, leaving with working code for their own contexts. Basic R experience recommended.

Intended Audience: Data analysts or independent researchers; Nonprofit organizations; State education agencies

Session Description: In the age of Generative AI, student data is no longer just a record of achievement; it’s the key source for training and refining frontier models. As districts determine what AI tools to use, procurement is the intersection where safety meets connectivity. Participants will get hands-on experience with our AI Data Use and Protection Toolkit and walk away with a standardized framework for vetting AI vendors through the S.A.F.E. benchmarks and Project Unicorn’s interoperability standards.

Intended Audience: Districts, charters or other local education agencies; State education agencies; Senior leaders (including cabinet-level leaders and executive directors)

Session Description: Education research often fails to influence decisions because findings are communicated in ways that are accurate but not actionable. In this interactive workshop, participants will learn and practice evidence-based strategies for writing clear, concrete, and decision-ready insights that communicate what works and why, using real examples from education research. This session is designed for analysts, researchers, and education leaders who want their evidence to be understood, trusted, and used in practice.

Intended Audience: Data analysts or independent researchers; Service providers; Districts, charters or other local education agencies

Full Session: This session is at or near capacity. Please be sure to fill in every seat where possible.