As a school administrator, you know that behavior data tells a story about your campus. But are you reading that story effectively? Monthly behavior data reviews are one of the most powerful tools principals have for shaping campus culture, supporting struggling students, and empowering teachers. This guide walks you through exactly how to make these reviews productive and actionable.
The Leadership Imperative
Schools that conduct regular data reviews see 23% fewer discipline referrals over time. The key is consistency and follow-through, not perfection. Your attention to data signals to your entire staff that behavior support is a priority.
Why Monthly Data Reviews Matter for Campus Culture
Monthly behavior data reviews do more than track incidents. They fundamentally shift how your campus approaches student behavior from reactive to proactive.
+ With Regular Data Reviews
- Patterns identified before they become crises
- Teachers feel supported with struggling students
- Resources allocated based on actual need
- Interventions adjusted based on effectiveness
- Staff develops shared understanding of priorities
- Students receive timely, targeted support
- Without Regular Data Reviews
- Problems escalate before anyone notices trends
- Teachers feel isolated with challenging students
- Resources spread thin without strategic focus
- Same ineffective interventions repeated
- Inconsistent expectations across classrooms
- Students fall through the cracks
What Data to Pull Before the Meeting
Walking into a data review unprepared wastes everyone's time. Here is the essential data you should gather before each monthly meeting:
Identify your highest-need students. Look for:
- Total incident count per student
- Trend direction (increasing, decreasing, stable)
- Types of behaviors for each student
- Current intervention status (BIP in place? Tier level?)
Hot spots reveal environmental factors. Track:
- Cafeteria, hallways, bathrooms, playground
- Specific classrooms (without naming teachers publicly)
- Transition areas and unstructured spaces
- Before school, after school, during passing periods
Timing patterns reveal scheduling and fatigue issues:
- Morning arrival vs. end of day
- Before lunch vs. after lunch
- During specific class periods
- Patterns by day of week (Monday spikes? Friday fatigue?)
Category analysis shapes professional development:
- Physical aggression, verbal disruption, defiance
- Attendance/tardy patterns
- Technology violations
- Comparison to previous month and same month last year
Pro Tip: Create a Data Dashboard
If possible, set up a simple dashboard that auto-updates with these metrics. Whether in a spreadsheet, your SIS, or a tool like Classroom Pulse, having data ready at a glance saves hours of monthly prep time.
Key Questions to Ask During the Review
Great data reviews are driven by great questions. Use these to structure your discussion:
The Essential Question Framework
What changed from last month?
Look for significant increases or decreases. Any change of 20% or more warrants investigation.
Who needs more support right now?
Identify 2-3 students who would benefit from additional intervention or a team review.
What is working that we should celebrate or expand?
Data should highlight successes, not just problems. A classroom with declining incidents deserves recognition.
Are our current interventions producing results?
If a student has been on a BIP for 6 weeks with no improvement, it is time to revisit the plan.
What environmental changes could reduce incidents?
If the cafeteria is a hot spot, consider supervision changes, seating arrangements, or schedule adjustments.
Red Flags That Signal a Need for More Support
Not all data points are created equal. Train yourself to spot these warning signs that require immediate attention:
A student goes from 2 incidents per month to 10. This signals a major change in the student's life or environment that needs investigation.
Action: Same-day teacher conference, possible parent contact
Multiple students having incidents in the same location or with the same adult. This may indicate an environmental or supervision issue.
Action: Conduct a walkthrough, observe the setting, interview staff
A student with 30 minor incidents is often more concerning than one with 3 major incidents. Chronic patterns erode learning for everyone.
Action: Tier 2 intervention review, consider FBA referral
A student whose behaviors are becoming more intense or dangerous over time. Verbal disruption becoming physical aggression is a critical warning.
Action: Urgent team meeting, safety plan review, possible crisis support
A student on multiple interventions with no improvement after 6-8 weeks. The plan is not working, and staff may be burning out.
Action: Full team review, consider outside consultation
One teacher with significantly more or fewer referrals than peers teaching similar populations. Both extremes warrant a supportive conversation.
Action: Private coaching conversation, not punitive review
Translating Data into Action Items
Data without action is just information. Every review should produce 2-3 specific, achievable action items.
| Vague (Avoid) | Actionable (Better) |
|---|---|
| "We need to work on cafeteria behavior" | "Ms. Johnson will implement assigned seating in cafeteria starting Monday; Mr. Smith will add roving supervision during first lunch" |
| "Marcus needs more support" | "Schedule FBA meeting for Marcus by Friday; Ms. Davis will begin daily check-in starting tomorrow" |
| "We should do more positive reinforcement" | "Launch campus-wide positive referral system next Monday; target 5:1 positive to negative ratio by end of month" |
| "3rd grade is struggling" | "Schedule grade-level PLC focused on classroom management strategies for Thursday; principal will conduct supportive walkthroughs in all 3rd grade rooms this week" |
The Action Item Formula
Every action item should answer: WHO will do WHAT by WHEN. If it does not have all three components, it is not actionable.
Sample Monthly Review Meeting Agenda
Use this 45-minute agenda template to keep your reviews focused and productive:
45-Minute Monthly Behavior Data Review
Review Last Month's Action Items
What did we commit to? What got done? What is still pending?
Big Picture Data Overview
Total incidents, comparison to last month, comparison to same time last year. Major trends.
Deep Dive: Students of Concern
Review top 5-10 students by incident count. Current interventions, trends, team recommendations.
Location and Time Analysis
Hot spots, timing patterns, environmental factors. Discuss supervision and structural changes.
Celebrations and Bright Spots
Students showing improvement, classrooms with positive trends, successful interventions.
Action Items and Assignments
Identify 2-3 specific actions with owners and deadlines. Document and share.
Supporting Teachers with Challenging Students
Data reviews often reveal teachers who need support. Here is how to approach these conversations productively:
"I noticed you have had some challenging situations with Marcus. Tell me what you are seeing." Listen before offering solutions.
"Would it help if I covered your class so you could observe Ms. Davis's approach?" or "Let me arrange for the behavior specialist to co-teach with you."
"Let's check in again in two weeks to see how the new strategy is working." Teachers need to know you are invested in their success.
Critical Mindset Shift
A teacher with many behavior incidents is not automatically a "bad teacher." They may have the most challenging student load, be new to the profession, or be dealing with systemic issues beyond their control. Use data to support, not punish.
Building a Culture of Data-Informed Decision Making
True culture change happens when data-driven thinking becomes automatic across your campus. Here is how to build that culture:
Make Data Visible
Share anonymized, aggregate data with staff regularly. "This month we had 15% fewer cafeteria incidents than last month." Transparency builds buy-in.
Celebrate Data-Driven Wins
When an intervention works, tell the story with data. "We implemented check-in/check-out with Jayden in October. His incidents dropped from 12 to 3 by December."
Train Teachers to Use Their Own Data
Give teachers access to their classroom data and show them how to interpret it. Empowered teachers make better daily decisions.
Model Data Use in Your Own Decisions
"Based on our data, I am adding supervision to the east hallway during passing period." Show staff that you practice what you preach.
Be Consistent
Monthly reviews should happen every month, without fail. Inconsistent attention to data tells staff it is not really a priority.
The Long-Term Impact
Schools that commit to monthly data reviews typically see these outcomes over the course of a school year:
By End of Year 1
- 15-25% reduction in total behavior incidents
- Faster identification of students needing Tier 2/3 support
- Improved teacher morale and sense of support
- More consistent behavior expectations across campus
By End of Year 2
- 30-40% reduction in serious incidents
- Data-driven culture embedded in school practice
- Reduced time spent in reactive crisis management
- Improved student outcomes and school climate surveys
Your Next Step
Do not wait for the perfect system. Start where you are:
This week: Pull your campus behavior data for the past month. Look for one pattern you had not noticed before.
This month: Schedule your first formal data review meeting with your behavior team or leadership team.
This semester: Commit to monthly reviews and track your progress over time.
Remember: Progress, Not Perfection
The goal is not to have a perfect meeting or perfect data. The goal is to pay consistent attention to what is happening on your campus and respond thoughtfully. Every school has behavior challenges. The difference is whether leaders engage with them systematically or react to them randomly.
References
Ruble, L. A., McGrew, J. H., Wong, W. H., & Missall, K. N. (2018). Special education teachers' perceptions and intentions toward data collection. Journal of Early Intervention, 40(2), 177–191. https://doi.org/10.1177/1053815118771391
Kearns, D. M., Feinberg, N. J., & Anderson, L. J. (2021). Implementation of data-based decision-making: Linking research from the special series to practice. Journal of Learning Disabilities, 54(5), 365–372. https://doi.org/10.1177/00222194211032403
U.S. Department of Education, Privacy Technical Assistance Center. (2015). Data governance checklist. https://studentprivacy.ed.gov/resources/data-governance-checklist
U.S. Department of Education. (2021). FERPA general guidance for parents and eligible students. https://studentprivacy.ed.gov/
Simonsen, B., Fairbanks, S., Briesch, A., Myers, D., & Sugai, G. (2008). Evidence-based practices in classroom management: Considerations for research to practice. Education and Treatment of Children, 31(3), 351–380. https://doi.org/10.1353/etc.0.0007
Stormont, M., Reinke, W. M., Newcomer, L., Marchese, D., & Lewis, C. (2015). Coaching teachers’ use of social behavior interventions to improve children’s outcomes: A review of the literature. Journal of Positive Behavior Interventions, 17(2), 69–82. https://doi.org/10.1177/1098300714550657
Carr, E. G., Dunlap, G., Horner, R. H., Koegel, R. L., Turnbull, A. P., Sailor, W., Anderson, J. L., Albin, R. W., Koegel, L. K., & Fox, L. (2002). Positive behavior support: Evolution of an applied science. Journal of Positive Behavior Interventions, 4(1), 4–16. https://doi.org/10.1177/109830070200400102
Sugai, G., & Horner, R. H. (2020). Sustaining and scaling positive behavioral interventions and supports: Implementation drivers, outcomes, and considerations. Exceptional Children, 86(2), 120–136. https://doi.org/10.1177/0014402919855331
Billingsley, B. S., & Bettini, E. (2019). Special education teacher attrition and retention: A review of the literature. Review of Educational Research, 89(5), 697–744. https://doi.org/10.3102/0034654319862495
Brunsting, N. C., Bettini, E., Rock, M. L., Royer, D. J., Common, E. A., Lane, K. A., Xie, F., Chen, A., & Zeng, F. (2022). Burnout of special educators serving students with emotional-behavioral disorders: A longitudinal study. Remedial and Special Education, 43(3), 160–171. https://doi.org/10.1177/07419325211030562
Kranak, M. P., Andzik, N. R., Jones, C., & Hall, H. (2023). A systematic review of supervision research related to Board Certified Behavior Analysts. Behavior Analysis in Practice, 16(4), 1006–1021. https://doi.org/10.1007/s40617-023-00805-0
Springer, A., Marchese, N. V., & Dixon, M. R. (2024). An analysis of variables contributing to Board Certified Behavior Analyst turnover. Behavior Analysis in Practice. https://pubmed.ncbi.nlm.nih.gov/41523810/
Take Action
Put what you've learned into practice with these resources.
Key Takeaways
- Monthly data reviews transform reactive discipline into proactive campus culture building
- Pull data by student, location, time of day, and behavior type before each review meeting
- Red flags like sudden spikes, clustering patterns, or chronic low-level disruption require immediate attention
- Effective reviews result in 2-3 specific action items with owners and deadlines
- Building a data-informed culture starts with consistent, transparent review processes
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About the Author
The Classroom Pulse Team consists of former Special Education Teachers and BCBAs who are passionate about leveraging technology to reduce teacher burnout and improve student outcomes.
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