Which students are frequently absent and struggling academically? How many of those students already have intervention plans? And where might additional support be needed?
Districts already have tools to monitor attendance, academic performance, and interventions. But what happens when leaders want to understand how those different pieces of information relate to one another? Answering more complex questions can require navigating multiple reports, adjusting filters, and piecing together the findings.
As districts explore how artificial intelligence (AI) can support this work, it's worth asking: What if educators could investigate these questions simply by asking their data?
What if educators could have a conversation with their data?
District reporting tools are useful for tracking established metrics, but educators' questions don't always fit neatly into a predefined report or dashboard.
Consider a superintendent reviewing attendance trends. They might want to know which schools have improved the most, which interventions those schools are using, and whether improvements vary by grade level.
With conversational AI, that could become a single, ongoing conversation with their district's data. Instead of pulling separate reports, educators could ask follow-up questions and explore findings as they go.
For district technology leaders, this presents an opportunity to reduce routine reporting requests and free up time for more complex work. For principals, intervention specialists, and classroom teachers, it means being able to explore patterns across their schools, student groups, or classes without relying on someone else to pull the data.
Putting conversational data analysis into practice
With Conversational Data, a new capability in Panorama Solara, educators can ask questions about their entire student population and get answers grounded in their district's data.
Educators can connect the dots across attendance, academics, behavior, interventions, and surveys to uncover patterns they might otherwise miss.
For example, a school leader could ask, "Which students have missed 10% or more of school days and are also struggling in math? Do they already have attendance intervention plans?"
From there, they could dig into an individual student's needs and take next steps directly in Solara, like drafting a targeted intervention plan.
Behind the scenes, Solara translates questions into SQL queries to retrieve information directly from the underlying data, helping improve the reliability of its answers. And because Conversational Data is built into Panorama, it follows the platform's existing security and privacy controls, including role-based data permissions.
Rethinking how districts use their data
As districts develop their AI strategies, there's an opportunity to look beyond content generation and individual productivity tools. Making it easier for educators to ask questions, uncover patterns, and use their existing student data to inform decisions is another practical application worth considering.
See how Panorama Solara helps educators turn questions about their student data into insights that inform action.
