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-by Timothy Grivois-Shah, Ed.D., Director of Professional Learning and Community Engagement


Schools implementing Positive Behavior Interventions and Supports (PBIS) believe that students’ social, emotional, and academic achievement depends upon building a values-based school culture, explicitly teaching social and emotional skills, and by affirming—out loud—the positive contributions that each student makes to the school community. Most PBIS schools accomplish this by creating a values / skills matrix, developing a system to teach social and emotional skills early and often, and by designing a developmentally appropriate way to recognize students when they make school values visible through their actions.

Using data to support decision making upgrades your Positive Behavior Intervention and Supports systems and practices.
Using data to support decision making upgrades your Positive Behavior Intervention and Supports systems and practices.

Schools that spend the least amount of time managing student discipline are schools where:

  • All staff share a common set of values and expectations.
  • Teachers have taught all students how to live these values throughout the school.
  • Students are recognized for making school values visible through their actions.

Learning the practices that support student success and building systems to ensure that staff can implement these practices successfully is usually how most of the teams that I work with spend implementing their first year of PBIS. Once these practices and systems are in place, the next step is for PBIS teams become fluent in using data to support decisions.

Schools that collect student discipline information digitally have a powerful tool for identifying precisely what problem the PBIS team should solve, what measurable goals to set, what solutions are likely to align with the problem. One powerful protocol to move your PBIS from problem to solution in an hour or less is to:

  • Use data that your school likely already collects to define a precision problem. 
  • Design solutions that match the problem that needs to be solved.

From time to time, people who work in schools get a sense that something seems to be a little off. For example, teachers might wonder if the noise in the hallways is louder than normal. However,  designing solutions for hallway noise is hard to do without knowing

  • Who is making the noise?
  • What is the exact kind of noise?
  • When is the noise happening?
  • Where is the noise the worst? Is it just one hallway, or several?
  • Why do we think students are making so much noise?

Most computer systems that log student discipline incidents can likely provide exact answers to each of these questions. When PBIS teams have the right data available to them, a general problems of hallway noise becomes a precise problem that the team can more easily solve:

  • Who: Third, fourth, and fifth grade students.
  • What: Slamming lockers.
  • When: Right before lunch.
  • Where: Hallways by their classrooms.
  • Why: Students are in a hurry to get to lunch sooner.

Here is an example of a general problem statement and a precise problem statement:

General: There’s too much noise in the hallway.

Precise: Third, fourth, and fifth grade students are slamming their lockers next to their classrooms right before lunch because they are in a hurry to get to lunch sooner.

While general problem statements indicate that there might be an issue to address, precision statements use data to clarify issues in ways that suggest solutions. Because the team knows exactly who is making noise, what kind of noise students are making, and where the noise is happening, and why students are being noise, the team can think through solutions that are more likely to be effective. For this school, finding ways to speed up the lunch line, reassuring students that they’ll have plenty of time to eat and play, and reteaching students how to close locker doors softly will likely be more effective than just telling kids to be quieter in the halls.

Systems, Data, and Practices Support Outcomes--PBIS
Data is an essential part of supporting positive outcomes for all students.

Positive Behavior Interventions and Supports begins with learning practices that support students behavior and developing systems to support staff in implementing effective practices throughout the school. Then, the school’s PBIS team shifts its focus from building the structure of PBIS to using data to do PBIS. By using data to define precise problems, teams can implement the solutions for their site that are most likely to prevent unexpected behaviors from occurring. 

Although many schools implementing PBIS begin with a similar set of systems and practices, using data is what makes PBIS work in each school’s individual context. Rather than relying on one strategy to solve every problem, teams can use data that already exists  to uncover nuances in each situation that are critical to designing effective solutions. Precision is the first step towards effective PBIS.

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