1. Pointe Coupee Parish July 23, 2015 Monica Ballay mballay@lsu.edumballay@lsu.edu Analyzing School Discipline Data

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6. Archived Webinars This webinar is being recorded and will be available for viewing at www.laspdg.org under Data Based Decisions | Webinars | 2015-2016www.laspdg.org

7. People First Language Kathie Snow. (n.d.) A few words about People First Language. Disability is Natural. Retrieved August 1, 2012 from http://www.disabilityisnatural.com/images/PDF/pfl-sh09.pdf “People First Language puts the person before the disability and describes what a person has, not who a person is.”

8. Goal: Provide step-by-step process to analyze school level discipline data Objectives: Gain knowledge on the process to analyze school level discipline data Gain skills on the process to analyze school level discipline data

9. Build positive relationships 3-5 Expectations Positively stated rules aligned w/expectations Model, teach, practice Reinforce appropriate behaviors Minor vs. Major Behaviors; Develop array of consequences & interventions Evaluate; data-based decisions 1 2 3 4 5 6 7 Behavior System of Supports

10. The data output is only as good as the data input Data should lead you to more questions Do not look at 1 data source; use multiple sources What doesn’t get measured and monitored is less likely to be implemented Discipline Referral Data Considerations

11. System (School) Issue (Ex: Too few teachers during recess duty and they are huddled up and not supervising) vs Student Issue (Ex: The sixth grade students are defiant) Question whether it is a…..

12. Primary vs. Precision Statements Primary Statements – Too many referrals – September has more suspensions than last year – Violence is increasing – The cafeteria is out of control – Student disrespect is worse Precision Statements – There are more ODRs for aggression (what?) on the playground than (where?) last year. These are most likely to occur during first recess (when?), with a large number of students (who?), and the aggression is related to getting access to the new playground equipment (why?)

13. Step 1: Identify and Analyze the Problem Step 2: Develop the Plan Step 3: Implement the Plan Step 4: Evaluate the Plan What do we do about it? What’s the problem and why is it happening? System vs. Student How do we do it? Is it working? Problem-Solving Process

14. Last Year’s Discipline Data School & District DATA: – What are the top 3 behavior incidents? – What are the top 3 infractions? – Staff members with the most referrals? – Highest month? – Highest time of day? – Highest location after classroom? – Students with the highest number of referrals?

15. This Year’s Discipline Data 1 st Quarter Know your School & District DATA: – What are the top 3 behavior incidents? – What are the top 3 infractions? – Staff members with the most referrals? – Highest time of day? – Highest location after classroom? – Students with the highest number of referrals?

16. Analyzing Discipline Data: Who? School Implementation Team Who is on the TEAM? (Representative of staff) When & how often TEAM meet? Specific roles for each TEAM member? What data analyzed? How is analyzed data used to make changes, decisions? How is data share with stakeholders?

17. Data Leads to More Questions… This is 2014-2015 Data: School is a K-12 School What questions do you have? What could you do proactively in 2015-2016 school year? What would be your priority?

18. Who are these 11 SWD? Questions: What are some observations? Gender: Of the 11 SWD, 10 were males (90.9%) and 1 was female (9.1%) Grade Levels: 8 (72.7%) - Elementary Grades (K-5 th ) 3 (27.3%) - Middle School Grades (6-8 th ) None at High School Grades Questions: What else would you like to know? Exceptionality Race How does data compare to school demographics?

19. Behavioral Infractions Questions: What are the top 2 infractions? 1 st is Willful Disobedience (73) & 2 nd is Tardy (12) What % of top infractions compared to total? Will Disobedience 72/132 = 55% How could you address Willful Disobedience as a school???????

20. Analyzing School Discipline Data : A. Overall Referrals per day per month B. What problem behaviors are most common? – ODR per Problem Behavior/Incident C. Where are problem behaviors most likely? – ODR per Location D. When are problem behaviors most likely? – ODR per time of day E. Who is engaged in problem behavior? – ODR per student F. Why are problem behaviors sustaining? – Brainstorm as a team

21. Data Activity

22. Overall Referrals Per Month Avoid simple counts (ex: Oct-26 ODR, Dec-14 ODR) Always use per day per month Look at previous years data to determine trends

23. A. Overall Referrals per Day per Month 2014-2015 School Year Activity A Month#Avg per dayThoughts, Concerns, Action Steps September33316 February24215 March22910

24. B. What problem behaviors are most common? (ODR per problem behavior/incident)

25. Activity B What? (Incident)#%Thoughts, Concerns, Action Steps Tardy50228 Willful Disobedience20813 Cell Phone17716

26. C. Where are problem behaviors most likely? (ODR per location)

27. Activity C Where? (Location)# % Thoughts, Concerns, Action Steps Campus70736 Class58633 Detention Room1157

28. D. When are problem behaviors most likely? (ODR per time of day)

29. D. When? (ODR per time of day) Activity D When? (Time)#%Thoughts, Concerns, Action Steps 2 PM41020 8 AM20712 1 PM20512

30. E. Who is engaged in problem behavior? (ODR per student) Is it the same students contributing to most of the referrals? Specific grade? Do they share similar teachers? What interventions are needed (green, yellow, red)? Have the students truly been taught what is expected? Is it mainly one teacher referring?

31. E. Who is engaged in problem behavior? (ODR per student)

32. Behavior Infractions? Action? (Infraction)#%Thoughts, Concerns, Action Steps Detention65837 OSS45723 Conference25118

33. Why are problem behaviors sustaining?

34. Data Reminders: Should look at it during every monthly meeting to tailor booster lessons and to make data-based decisions What is the school doing for those students who aren’t displaying these problem behaviors? How often is discipline data shared with faculty? Through what method (in service, email, etc.) Big 5 Data for ODR’s – Location, time of day, ODR per day/per month, problem behavior, student – Can also look by teacher, by disciplinary action, etc.

35. Building Capacity When you leave today, what will you do with this information? How will you share it with others in your district? When will you share it? (Timeline)

36. The contents of this PowerPoint presentation were developed under a grant from the US Department of Education, #H323A110003. However those contents do not necessarily represent the policy of the US Department of Education, and you should not assume endorsement by the Federal Government. www.laspdg.org Monica Ballay mballay@lsu.edumballay@lsu.edu

37. Webinar Wednesday Series (go to www.laspdg.org homepage calendar for information; all webinars begin at 10 AM)www.laspdg.org October 14- Culturally Responsive Practices | Effective Behavior Interventions for Challenging Students | Daniel NoackLesage October 21- Inclusive Practices- | Co-Teaching Observations & Coaching | Dr. Richard Villa October 28 - Family Engagement | Partner with Families with Low Income for High Student Achievement | Dr. Joyce Epstein

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