Seven sample reports demonstrating how student-perspective data analysis transforms raw numbers into actionable insight. Built with synthetic data from the DataInEd District Factory.
Track rate-of-change in student metrics to catch declining patterns 8–12 weeks before crisis. Demonstrates why a dropping 3.2 GPA matters more than a stable 2.5.
Connect external economic data — income, employment, internet access — to student reality. Understand why a student struggles before deciding how to help.
How teacher-level patterns — grading distributions, referral rates, course assignments — predict student outcomes. A diagnostic lens, not an evaluation tool.
A 92.4% average hides a bimodal reality. Breaks down how aggregate metrics mask the students who need help most — including the extracurricular connection.
The same data, reframed for a school board audience. Demonstrates how framing, cost analysis, and equity dimensions turn insight into budget decisions.
Violin plot visualizations showing one student's position within every class and cohort they belong to. Grade distributions, period-level absences, and GPA percentile across demographic, activity, and context cohorts — all on one page.
A live intervention snapshot: baseline vs. current metrics, weekly progress tracker, team notes with context, and actionable next steps. Shows what a data-informed support plan looks like when it centers the student's reality.
Track trajectory changes over time. Catch the drift before it becomes a crisis.
External context that explains what the numbers alone cannot.
Teacher-level patterns that predict student outcomes.
Present data in formats that move decision-makers to act.
The full curriculum teaches you to create analyses like these using Python, real-world methodology, and your district's own data — always with the student's perspective at the center.
Explore the Curriculum →