// all modules

The Curriculum

Six completed modules and five in development. Each module is self-contained — start anywhere, or work through them in order for the full progression from raw data to equity-aware early intervention.

🏫

Practitioner Track

For classroom teachers, counselors, and school leaders. Focuses on concepts, interpretations, and decisions — no coding required.

Concept-first · No code required

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Technical Track

For data analysts, district staff, and technically-minded administrators. Full Python walkthroughs with pandas, matplotlib, and real dataset exercises.

Python · pandas · matplotlib

Available Now

6 Modules Live

Introducing the Synthetic School Dataset

Tour all 11 tables, understand the relational schema, and load your first dataset in Python. Learn what raw school data looks like before any analysis touches it.

pandasdata explorationschemaFERPA

Delta Analysis 101: Seeing Change Over Time

What is a delta, and why does direction of change matter more than current value? Build your first rolling attendance trend and find students whose trajectory is shifting.

delta analysisrolling averagesattendance trends

Equity & Context

The False Positive Problem: When "At-Risk" Is Wrong

25 students are flagged as chronically absent. Join the cultural holiday calendar and discover which ones shouldn't be on that list at all — and what that means for your interventions.

equitycultural contexttable joinsfalse positives

Reading Hunger in Attendance Data

Students who show up only at lunch — and only at the end of the month. Learn to surface food insecurity signals hidden inside standard attendance records, and handle that knowledge responsibly.

food insecuritypattern detectionSNAP signalsethics

Academic Trends

GPA Trend Analysis: Catching the Slide

Build assignment-level GPA trends instead of waiting for report cards. Pinpoint the exact week a student's trajectory shifted — not the month it became a problem.

grade trendsassignment-level dataearly warningvisualization

Outcomes & Measurement

Measuring Whether Interventions Actually Worked

You intervened. Did it work? Use before/after delta analysis to measure real outcomes — and learn to separate genuine improvement from seasonal variance or regression to the mean.

outcome measurementbefore/after analysisintervention effectiveness

In Development

5 Modules Planned

07

Coming Soon · Attendance & Access

Transportation Barriers & Weather Pattern Analysis

2,768 records where getting to school was the barrier. Identify which absences correlate with distance and weather — before labeling them truancy.

08

Coming Soon · Behavior Data

Behavior Trends: Escalation Before the Incident

7,600+ behavior incidents. Build a delta view and identify students whose pattern is changing before they hit a disciplinary threshold.

09

Planned · Engagement Metrics

LMS Data as a Leading Indicator

Login frequency, time-on-task, and discussion activity — do engagement signals predict grade declines before they happen?

10

Planned · Early Warning Systems

Multi-Metric Risk Scoring Without Black Boxes

Combine attendance, GPA, behavior, and engagement into an interpretable score you can explain to a parent or school board.

11

Planned · Live Data Architecture

Building a Live Data Pipeline with AWS

Move from static CSVs to daily-updating tables with a lightweight AWS architecture that feeds new attendance, grades, and incidents automatically.