Advanced Data Based Decision Making

1. Advanced Data Based Decision Making Kimberly Ingram, Ph.D. Professional Development Coordinator Oregon Dept. of Education February 2008 Southern Oregon PBS Network Conference

2. Agenda • Part 1 • Look at your SET data – Is your Correction Feature at 80% • If Yes, the next few slide will be very meaningful • In No, the next few slides will be meaningful and we need to discuss ways to enhance that Feature – “corrections Packet” • Examine Data Decision Rules for • School-wide Interventions • Targeted Group Interventions • Individualized Interventions • Practice Data-based Decision-Making • Additional Data for further prevention efforts • Ethnicity reports • Special education • Part 2 – Prepare for First Day of School

3. CONTINUUM OF SCHOOL-WIDE POSITIVE BEHAVIOR SUPPORT Tertiary Prevention: FBABSP for Students with High-Risk Behavior ~5% ~15% 2-5 ODR Primary Prevention/Universal Interventions: School/Classroom- Wide Systems for All Students, Staff, & Settings Secondary Prevention: Specialized Group Systems for Students with At-Risk Behavior ~80% of Students 0-1 Referrals

4. School-wide Positive Behavior Support Supporting Decision Making Supporting Staff Behavior INFORMATION SYSTEMS PRACTICES Supporting Student Behavior

5. Improving Decision-Making Solution Problem From Problem Solving Solution Problem To Information

7. Using Data for On-Going Problem Solving • Start with the decisions not the data • Use data in “decision layers” (Gilbert, 1978) • Is there a problem? (overall rate of ODR) • Localize the problem • (location, problem behavior, students, time of day) • Get specific • Use data to guide asking of “the right questions” • Don’t drown in the data • It’s “OK” to be doing well • Be efficient

8. Using Discipline Data for Decision Making

9. Use Referral data to Inform Intervention • In order to maximize school resources, it is important to know where the majority of behavior problems are occurring • Prevention measures, such as: • Re-teaching expectations • increasing supervision and monitoring • increased use of acknowledgments, or • environmental restructuring • are often the best interventions for misbehavior especially when referrals are not successfully addressing the problem

10. Using Discipline Data • There are many different data systems for tracking, organizing, and presenting discipline data: • You can either make your current system work for you, or • SWIS (School Wide Information System) is one of the best systems for flexibility in manipulating data and ease of presenting data to maximize the use of your data • eSIS has some similar graphing abilities (Big 5, and a few others). It is not as flexible as SWIS, however, it can still offer excellent data for decision-making

11. Key features of data systems that work. • The data are accurate and valid • The data are very easy to collect (1% of staff time) • Data are presented in picture (graph) format • Data are current (no more than 48 hours old) • Data are used for decision-making • The data must be available when decisions need to be made (weekly?) • Difference between data needs at a school building versus data needs for a district • The people who collect the data must see the information used for decision-making.

12. Using Data for Decision Making

13. PBS Teams use data for • School-wide, universal, interventions • Targeted group, secondary, interventions • Individual, tertiary, interventions

14. School-wide Positive Behavior Support Systems Classroom Setting Systems Nonclassroom Setting Systems Individual Student Systems School-wide Systems

15. SW v. Individual

16. Suspensions/Expulsions Per Year 2000-01 2001-02 Events Days Events Days In School Suspensions 0 0 2 2 Out of School Suspensions 1 1 3 2.5 Expulsions 0 0 0 0 What about CLEO? • 12 By Dec. 2000 – Jun. 2001 • 19 By Sep. 2001 – Dec. 2001

17. CLEO: # By/Day/Month

18. CLEO: # By by Type

19. CLEO: # BI by Location

20. Elementary: > 1 ODR per day per month per 300 students (majors only) Middle: > 1 ODR per day per month per 100 students (majors only) >40% of students received 1+ ODR >2.5 ODR/student Modify universal interventions (proactive school-wide discipline) to improve overall discipline system Teach, precorrect, & positively reinforce expected behavior 1. School-wide systems if…

21. SWIS summary 06-07 (Majors Only)1974 schools; 1,025,422 students; 948,874 ODRs

22. SWISTM summary 05-06 (Majors Only)1668 schools, 838,184 students

23. Interpreting Office Referral Data:Is there a problem? • Absolute level (depending on size of school) • Middle, High Schools (> 1 per day per 100) • Elementary Schools (> 1 per day per 300) • Trends • Peaks before breaks? • Gradual increasing trend across year? • Compare levels to last year • Improvement?

24. Elementary School with 250 students

25. Average Referrals per Day per MonthMiddle School of 600 students

26. Middle School with 500 students

27. Middle school with 500 students

29. Middle School with 500 students

30. Is there a problem? Middle school with 500 students (Dec)

31. Is there a problem? Middle School with 500 students

32. Is there a problem? Middle School with 500 students (Dec 04-05)

33. Is there a problem? Middle School with 500 students (Feb 3, 04-05)

34. >60% of referrals come from classroom >50% of ODR come from <10% of classrooms Several teachers not writing referrals at all Enhance universal &/or targeted classroom management practices Examine academic engagement & success Teach, precorrect for, & positively reinforce expected classroom behavior & routines 2. Classroom system if…

35. >35% of referrals come from non-classroom settings >15% of students referred from non-classroom settings Enhance universal behavior management practices teach, precorrect for, & positively reinforce expected behavior & routines increase active supervision (move, scan, interact) 3. Non-classroom systems if…

36. Referrals by Location

38. Middle School

39. Elementary School

40. Referrals by Time

41. >10-15 students receive >5 ODR Provide functional assessment-based, but group-based targeted interventions Standardize & increase daily monitoring, opportunities & frequency of positive reinforcement 4. Targeted group interventions if….

42. <10 students with >10 ODR <10 students continue rate of referrals after receiving targeted group support Provide highly individualized functional-assessment-based behavior support planning 5. Individualized action team system if...

43. Referrals by Student

44. Student Referral Report

45. School Example A middle school getting ready to implement targeted group interventions. They had been implementing school-wide interventions for one school year.

46. Some Questions ABC Middle School had re: student needs • How many students in the middle of the triangle? • How many need at the top of the triangle? • How many students in the targeted group have 2, 3, 4, 5, thru 25 referrals? • What types of behaviors are targeted group students and tip of triangle students engaging in? • What percent of students in targeted and tip are Sped? • What percent of students in targeted and tip met AYP the previous year?

47. ABC Middle School • 541 students • 1314 total number of referrals for SY 04-05 • Pre and Post Set completed • Team attended 4 PBS trainings throughout year and implemented along the way • Team leader attended district leadership meeting consistently throughout year

49. Triangle Data • 0-1 referral: 381 (65% of students) • 2-5 referrals: 124 (21% of students) • 6+ referrals: 82 (14% of students)

50. Break down of all referrals (1314) by behaviors • Disrespect: 354 • Disruption: 310 • Tardy: 274 • Inappropriate Language: 80 • Fighting/Aggression: 73 • Skip: 56 • Harassment: 37 • Theft: 28 • Other: 82 • Miscellaneous (drugs, lying, prop. damage, weapons, vandalism): 20