The Problem with Averages
When a school reports 75% proficiency, it sounds successful. But if White students are 90% proficient while Black students are 50% proficient, that average masks a 40-point gap. Equity analysis requires looking beyond the aggregate.
Lincoln Middle School celebrated their reading proficiency: 72%, above state average. But when new leadership disaggregated the data, celebration turned to concern. White students: 85% proficient. Hispanic students: 58%. Students with disabilities: 31%. The school wasn't succeeding for all students—just some.
Why Disaggregation Matters
Reveals Hidden Disparities
Aggregate data can show success while subgroups struggle. Disaggregation exposes gaps that require attention—problems invisible in overall averages.
Focuses Improvement Efforts
Knowing which students struggle enables targeted response. Generic improvement efforts may not reach students who need them most; disaggregated analysis directs resources where they're needed.
Ensures Accountability
Federal and state accountability systems require subgroup performance reporting. Schools must demonstrate progress for all students, not just overall averages.
Advances Equity
Equity requires seeing inequity. Disaggregation makes disparities visible, creating urgency and enabling action.
Key Disaggregation Categories
Demographic
- • Race/ethnicity
- • Gender
- • Income status
- • English learner status
- • Special education status
Academic
- • Grade level
- • Prior achievement level
- • Course enrollment
- • Program participation
- • Mobility status
All AcumenEd Features
Explore our complete suite of data analytics tools designed for Michigan charter schools.
Disaggregation in Practice
Academic Achievement
Break down proficiency rates, growth scores, and assessment results by subgroup. Compare gaps over time. Are disparities widening or narrowing?
Attendance
Examine chronic absenteeism by subgroup. Are certain populations missing more school? What patterns emerge?
Discipline
Analyze suspension rates by race, gender, and disability status. Disproportionate discipline is a common equity concern revealed by disaggregation.
Access and Opportunity
Examine enrollment in advanced courses, gifted programs, and extracurriculars by subgroup. Are opportunities distributed equitably?
Moving from Data to Action
Set Subgroup Goals
Don't just track overall improvement—set specific goals for closing gaps. Hold the organization accountable for subgroup progress.
Target Interventions
Design interventions specifically for struggling subgroups. Generic approaches may not address root causes of disparities.
Examine Root Causes
Disparities have causes. Are they curricular? Instructional? Related to access? Understanding causes enables effective response.
Monitor Progress
Track subgroup performance over time. Are gaps closing? Are interventions working? Continuous monitoring enables course correction.
Resources & Guides
Access implementation guides, best practices, and training materials for your team.
Lincoln Middle School used disaggregated data to drive change. They implemented targeted literacy intervention for underperforming subgroups, examined instructional practices for bias, and set explicit gap-closing goals. Three years later, gaps had narrowed significantly. Disaggregation revealed the problem; action addressed it.
Key Takeaways
- Aggregate data hides disparities—disaggregation reveals inequities that averages obscure.
- Key categories include race, income, EL status, special education, gender, and grade level.
- Disaggregate achievement, attendance, discipline, and access data.
- Move from data to action: set subgroup goals, target interventions, examine root causes.
Dr. Emily Rodriguez
Director of Student Support Services
Expert in student intervention strategies with a focus on early warning systems and MTSS implementation.
