Data-Driven
Decision Making
Echoes of Learning
How Data Hears What Schools Can't See
Many schools collect massive amounts of data: student attendance, grades, engagement, behavioral reports, test scores, and more. However, they rarely have the capacity to analyze this data effectively to drive improvements in teaching, resource allocation, or interventions.
We provide a low-cost consulting service that audits how your data is currently collected, stored, and used (or neglected) and delivers actionable insights to help improve student outcomes without requiring new tools or expensive investments.
1
Gather Information About Existing Data
Meet with administrators, teachers, and IT staff to understand:
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What types of data you collect
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Where it’s stored (student information systems, spreadsheets, learning platforms)
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How often it’s reviewed and by whom
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How it’s currently being used to make decisions
2
Evaluate Key Data Sources - We look at aggregate data, not individual data, ensuring privacy and protection of individuals.
We create a checklist to review common data areas:
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Attendance Data: Are patterns in absenteeism being tracked and flagged for interventions?
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Assessment Data: Are teachers using formative and summative assessments to adjust instruction?
- Behavior/Discipline Logs: Are discipline issues correlated with academic struggles or absenteeism?
- Engagement Metrics: Is data from online platforms (e.g., LMS, Google Classroom) being reviewed?
- Grades and Progress: Are grading patterns reviewed to identify at-risk students or struggling cohorts?
- Intervention Data: Are intervention outcomes tracked and evaluated for effectiveness?
3
Analyze for Gaps and Opportunities
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Look for data silos: Are different departments (e.g., special ed, general ed, counselors) using separate systems that don’t communicate?
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Identify underutilized data: Is valuable data (e.g., engagement metrics) being collected but not analyzed effectively?
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Highlight missed opportunities: Could early warning signs of student disengagement be caught earlier using attendance or behavior patterns?
4
Deliver Custom Report and Recommendations
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Summary of Findings: Key gaps in data usage, bottlenecks, or missed opportunities.
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Quick Wins: Simple, no-cost recommendations (e.g., set up weekly grade reviews or early warning alerts).
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Example: “Use attendance data to identify students with 3+ absences in a month and flag them for intervention.”
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Long-Term Recommendations: Process improvements or changes that could have a long-term impact (e.g., setting up teacher dashboards or integrating data across departments).