1. Using Data for Decision Making School-wide Information System Teri Lewis-Palmer, Anne Todd, Rob Horner, George Sugai, & Shanna Hagan-Burke

2. Assumptions zSchool has team focused on school-wide behavior support. zTeam has an action plan zTeam meets regularly (weekly, every two weeks) zTeam has access to information about student behavior

3. Why Collect Discipline Information? zDecision making zProfessional Accountability zDecisions made with data (information) are more likely to (a) be implemented, and (b) be effective

4. Key features of data systems that work zThe data are accurate zThe data are very easy to collect (1% of staff time) zData are used for decision-making yThe data must be available when decisions need to be made (weekly?) yDifference between data needs at a school building versus data needs for a district yThe people who collect the data must see the information used for decision-making.

5. What data to collect for decision-making? zUSE WHAT YOU HAVE yOffice Discipline Referrals/Detentions xMeasure of overall environment. Referrals are affected by (a) student behavior, (b) staff behavior, (c) administrative context xAn under-estimate of what is really happening xOffice Referrals per Day per Month yAttendance ySuspensions/Expulsions yVandalism

6. Office Discipline Referral Processes/Form zCoherent system in place to collect office discipline referral data yFaculty and staff agree on categories yFaculty and staff agree on process yOffice Discipline Referral Form include needed information xName, date, time xStaff xProblem Behavior xLocation

9. When Should Data be Collected? zContinuously zData collection should be an embedded part of the school cycle not something “extra” zData should be summarized prior to meetings of decision-makers (e.g. weekly) zData will be inaccurate and irrelevant unless the people who collect and summarize it see the data used for decision-making.

10. Using Office Discipline Referrals for Team Planning School-Wide Systems Non Classroom Setting Systems Classroom Systems Individual Student Support Systems

12. Sugai, Sprague, Horner & Walker, in press z11 elementary schools, 9 middle schools zFor the 9 Middle Schools yNumber of students: Mean = 635 (204-1194) yOffice Dis Referrals: Mean = 1535 (136-3520) yReferrals per student: Mean = 2.4 yReferrals per school day : Mean = 8.6 y% students with at least 10 referrals = 5.4% y% of referrals from top 5% of students = 40%

13. Focus on School-Wide System if: zMore than 35% of students receive 1 or more referral zAverage referrals per student is greater than 2.5

14. Focus on Non-Classroom Systems if zMore than 35% of referrals come from non- classroom settings zMore than 15% of students who receive a referral are referred from non-classroom settings.

15. Focus on Classroom Systems if zMore than 50% of referrals are from classroom settings. zMore than 40% of referrals come from less than 10% of the classrooms.

16. Focus on Individual Student Systems zTargeted Group Interventions yIf 10 or more students have 10+ referrals xExample (check-in, check-out BEP) zTargeted Individual Interventions yFewer than 10 students xIntense, individualized support xWrap Around xPersonal Futures Planning xFunctional Assessment

17. Using Data for On-Going Problem Solving zStart with the decisions not the data zUse data in “decision layers” yIs there a problem? yWhat “system(s)” are problematic yWhat individuals (individual units) are problematic? zDon’t drown in the data zIt’s “OK” to be doing well zBe efficient

18. The Decisions/Decision Questions zInitial Self-Assessment yWhere to focus “investment” energy/time zOn-Going Assessment/Planning yIs the action plan working? Should we change? xDecision: Maintain, Modify, Terminate yWhat is the problem? Where should we focus? xDecision: Allocation of time, money, skills yDo we understand the problem? yWhat is the smallest effort that will produce the biggest effect?

19. Interpreting Office Referral Data: Is there a problem? zAbsolute level (depending on size of school) yMiddle Schools (>6) yElementary Schools (>1.5) zTrends yPeaks before breaks? yGradual increasing trend across year? zCompare levels to last year yImprovement?

26. Is There a Problem? #1 Maintain - Modify - Terminate

27. Is There a Problem? #2 Maintain - Modify - Terminate

28. Is There a Problem? #3 Maintain - Modify - Terminate

29. Is There a Problem? #4 Maintain - Modify - Terminate

30. What systems are problematic? zReferrals by problem behavior? yWhat problem behaviors are most common? zReferrals by location? yAre there specific problem locations? zReferrals by student? yAre there many students receiving referrals or only a small number of students with many referrals? zReferrals by time of day? yAre there specific times when problems occur?

31. Referrals by Problem Behavior

33. Referrals per Student

35. Referrals by Time of Day

37. Combining Information zIs there a problem? yWhat data did you use? zWhat systems are problematic? zWhere do you need to focus? yThe next level of information needed zWhat information is NOT needed?

38. What Individuals/Specific Units are problematic? Detailed Data Sources zIndividual student data zDirect observation zFaculty/Staff report

39. Designing Solutions zIf many students are making the same mistake it typically is the system that needs to change not the students. zTeach, monitor and reward before relying on punishment.