1. Advanced Uses of SWIS Data and SWIS Facilitation Skills presented by Susan Barrett Anne Todd, Nadia Sampson, and Celeste Rossetto Dickey, University of Oregon Steve Romano, Marla Dewhirst, Susan Barrett, Jerry Bloom, Kelly Davis, Rachel Freeman, and Rob Horner SWIS Facilitator Trainers Seth May, Megan Amedo, & Mary Green, University of Oregon June 2007 www.swis.org

2. Goals Review for teaching teams to use the Big 5 reports Recommend use of SWIS individual student data to jump start an FBA for a student Review of roles and responsibilities Update new features within SWIS Definitions, extra information SWIS integration with district packages SAMI VISA License Agreement Review and summarize Ethnicity Reports Getting connected

3. SWIS TM Facilitation is an Eight Step Process 1. Complete Readiness Tasks. 2. Submit License Agreement and School Information Form. 3. Setting Up for Swift at SWIS™ Training. 4. Conduct Swift at SWIS™ Training. 5. Provide Follow Up Support. 6. Maintenance. 7. Annual SWIS™ Facilitator Boosters. 8. SWIS™ License Renewal Process.

4. Your challenges should you decide to except them…… Use your resources to make their job easier Use your skills to teach others your skills You want to work yourself out of ‘the job’ so that you can move on to the next school/ district/region/state Teach others to keep it going in your absence Teach others to keep it going in each others absences

8. SYSTEMS PRACTICES DATA Supporting Staff Behavior Supporting Decision- Making Supporting Student Behavior SW Positive Behavior Support OUTCOMES Social Competence, Academic Achievement, and Safety

9. Improving Decision-Making Problem Solution From To Problem Problem- solving Information Solution

10. Problem-solving Steps 1. Define the problem(s) – Analyze the data 2. Define the outcomes and data sources for measuring the outcomes 3. Consider 2-3 options that might work 4. Evaluate each option: – Is it safe? – Is it doable? – Will it work? 5. Choose an option to try 6. Determine the timeframe to evaluate effectiveness 7. Evaluate effectiveness by using the data – Is it worth continuing? – Try a different option? – Re-define the problem?

11. Key Features of Effective Data Systems Data are accurate Data are very easy to collect Data are used for decision-making Different decisions require different data sources at different times Don’t collect it unless you are going to use it Data are available when decisions need to be made Data collectors must see the information used for decision-making… make it valuable for them to collect

12. SWIS TM summary 05-06 (Majors Only) 1668 schools, 838,184 students Grade Range Number of Schools Number of Students Mean ODRs per 100 per school day K-61010439,932 Mean = 435.37 (sd=.50) 6-9312205,129 Mean = 657 1.01 (sd=1.06) 9-12104102,325 Mean = 983 1.16 (sd=1.37) K-(8-12)23990,198 Mean = 377 1.09 (sd=1.56)

13. Standard Deviation for non- statisticians Normal distribution: Bell curve most of examples in set of data are close to the average, with a few examples tend to be from one extreme to the other Standard Deviation: a statistic that tells you how tightly all the various examples are clustered around the mean in a set of data. When the examples are pretty tightly bunched together and the bell- shaped curve is steep, the standard deviation is small. When the examples are spread apart and the bell curve is relatively flat, that tells you that you have a relatively large standard deviation. One standard deviation away from the mean in either direction on the horizontal axis accounts for somewhere around 68 percent of the people in this group.

14. Standard deviation is a measure of variation in a distribution of data Red represents one standard deviation from the mean (about 68% of data set Red & green represent two standard deviations from the mean (about 95% of data set) Red, green & blue represent three standard deviations from the mean (about 99% of data set)

15. Interpreting Office Referral Data: Is there a problem? Absolute level (depending on size of school) SWIS data summaries per 100 students Trends Peaks before breaks? Gradually increasing trend across year? Compare levels to last year Improvement?

16. Teach Teams a ‘Using Data Routine’ Teach a routine Examine data during the first 10-15 min of each meeting Teach the basic questions to ask: How many ODRs? (Do we have a problem?) What types of problem behaviors are most common? Where, When, Who? Use problem solving strategy Define problem Identify 2-3 solutions Talk about which solutions will work, are doable, fair Determine the solution to try  What is the smallest change we could make that would improve student behavior? Determine next steps How will we know if our efforts have been successful? Who do we need to share the data with and when?

17. The BIG 5 How often where what when who How often ? Where ? When ? Who ? What ?

18. What is summary for: 1.High school of 850 students?2. High School of 1825 students? 3. Elem. school of 625 students?4. Middle School of 625 students?

19. What is summary for: 1.High school of 850 students?2. High School of 1825 students? 3. Elem. school of 625 students?4. Middle School of 625 students?

20. Trevor Test Middle School 565 students Grades 6,7,8

21. Cafeteria Class Commons Hall 12:00 Lang. Defiance Disrespect Harrass Skip

22. Summarize the big 5 Is there a problem? If no, what will we do to sustain our efforts? If yes, is problem definable or do we need more information? More information? What is needed? Definable problem? What is the problem? Next steps How will we know if it is working? When will we review the data?

23. Langley Elementary School 478 Students K-5

26. What do you do when? A problem is being discussed at a meeting without looking at data/information… Data is being reviewed and the problem being defined doesn’t have team members confidence in data or the problem being defined Data is being reviewed, the team continues to look for things that need fixing… you notice that their rates are way below the national SWIS average

27. Data Entry WhoWhatWhen Ginger/ Doug Office Referrals End of each day Ginger/ Doug Integrity Report and Accuracy Checks 4 th tues of each month Report Generation WhoWhatWhen SW PBS Student Services Team Administration/ Counseling BIG 5 Individual student report Custom report of all students referrals Defined as needed 2 nd tues/month Thursday afternoons As needed Data Entry and Reporting Schedule

28. Teach Teams a ‘Using Data Routine’ Teach a routine Examine data during the first 10-15 min of each meeting Teach the basic questions to ask: How many ODRs? (Do we have a problem?) What types of problem behaviors are most common? Where, When, Who? Use problem solving strategy Define problem Identify 2-3 solutions Talk about which solutions will work, are doable, fair Determine the solution to try  What is the smallest change we could make that would improve student behavior? Determine next steps How will we know if our efforts have been successful? Who do we need to share the data with and when?

29. Tailoring SWIS to Individual School Needs: “Extra Info” and “Comments” Elaborate an Existing Problem Behavior Category E.g. Harassment (sexual, racial, religious) E.g. Weapon (gun, knife, other) Defining a ‘track’, small learning community, or homeroom When selecting Extra Info categories remember core features of all Categories Operationally defined Can see it and hear it Mutually Exclusive No overlap between definitions Exhaustive Everything is included

30. Categories for Harassment separate form and content Which set(s) of categories are acceptable? A Sexual Racial Religious Other B Sexual Verbal Physical Gender C Verbal only Physical only Verbal and Physical D With weapon With Gang With intent to harm

31. Categories for Weapons separate form and content Which set(s) of categories are acceptable? A Gun Knife Club Hand gun Gang B Gun Knife Club C Bomb Physical Threat Intimidation D Hand gun Rifle Short knife (< 3 in) Long knife (> 3 in) Other

32. Report Options To record Build new categories Add new categories to ODR form Train faculty and staff to enter data Train faculty to use the reports for decision making Train data entry person Custom Reports Advanced Options Activate “Show” extra info Run Custom Report

34. 45 students (7.6%) and 117 referrals589 total enrollment 8 students 6+ referrals 1.3% 37 students 2-5 6.2%

35. 38 students (6.4%) and 146 referrals total enrollment = 589 8 students 6+ 1.3% 30 students 2-5 5%

36. Using SWIS for Individual Student Intervention Design Assumption The design of behavior support is most efficient and effective when based on basic functional behavioral assessment information [who, what, where, when, why] Who engaged in problem behavior What problem behavior(s) were performed Where (what conditions/situation) are associated with problem behavior Why do problem behaviors occur (e.g. what is the maintaining function?)

37. Individual Student Referrals by student report (Who) Individual Student Report (What, Where, When, Why) Use these data to build preliminary hypothesis statement(s). Use the data to identify additional information needed from FBA Interviews. Context/Setting  Problem Behavior  Maintaining SR+

38. Use SWIS Data To Define Preliminary Hypothesis Statements/ Other Info Needed Mark Banks (2003-2004)  Grade 7 Compare the challenges Mark presented last year with the challenges he presents this year. What is the current hypothesis statement? What other information would you want? Setting Context Problem Behavior Maintaining Reinforcer

39. Individual Student information Mark Banks  Grade 8 Allie Pierce (2003-2004) [May 1, 2003]  Grade 7 Willie Loman (2003-2004)  Grade 6 Identify ONE Hypothesis Statement Identify additional information you would want

40. Mark Banks Time Location Motivation Average per day per month Problem Behavior

41. Mark Banks (04-05) SettingBehavior Maintaining Reinforcer Commons AreaAggression Harassment Obtain Attention Tardy Escape Task 9:45 am Math

42. Allie Pierce Average per day per month Problem Behavior LocationMotivation Time

43. Allie Pierce (03-04) ( If you were to conduct an observation, when would you observe Allie?) Setting Behavior Maintaining Reinf 8:30Class 10:45 class Skipping class Avoid Work

44. Willie Loman Average per day per monthProblem Behavior Location Motivation Time this year

45. Willie Loman (May, 03-04) Setting Behavior Maintaining Reinf Bus ZoneInappropriate language To get peer attention

46. Use Hypothesis Statements Verify Hypotheses FACTS Interviews Direct Observation Formal Functional Analysis Combine with Wrap Plan/Person Centered Plan Design Support Prevent access to problem context/conditions Teach new, replacement skills Place problem behavior on extinction Exaggerate rewards for appropriate behavior Improve consequences for problem behavior Establish safety systems Establish system for on-going data collection

47. Roles & Responsibilities SWIS™ Management Team = SM SWIS™ Facilitator = SF SWIS™ User = SU _____Provide ongoing assistance to SWIS™ Facilitators _____Provide ongoing assistance to schools using SWIS™ _____Complete and submit a License Agreement and School Information Form _____Complete the SWIS™ Readiness Checklist _____Respond to questions from school personnel using SWIS™ _____Collaborate with a SWIS™ Facilitator to adopt SWIS™ _____Send passwords over email _____Provide training on how to use data for decision-making _____Enter data into a SWIS™ account _____Sign the License Agreement _____Attend team meetings and offer coaching for using the data for decision-making _____Log in and preview school account monthly to check for data entry accuracy

48. Roles & Responsibilities cont. SWIS™ Management Team = SM SWIS™ Facilitator = SF SWIS™ User = SU _____Maintain password confidentiality _____Make changes to school SWIS™ accounts _____Check and update billing information _____Update Facilitator contact information _____Use the SWIS™ User’s Manual for problem-solving _____Contact SWIS™ Management Team with questions about SWIS _____Change a school’s Facilitator _____Pay for SWIS™ account _____Check www.swis.org for updateswww.swis.org _____Set up SWIS™ accounts in a timely manner _____Sign the School Information Form _____Use a referral form and referral procedure that are compatible with SWIS™ _____Problem-solve SWIS™ bugs

49. What potential problems do you anticipate and what can you do to prevent them from occurring? What steps will you take so that this transition happens smoothly for the school? You are taking over some schools from another SWIS™ Facilitator who has retired or moved to a different position:

50. Someone at the school contacts you and wants to know how they can delete a referral. They are not listed as a SWIS™ user and they are not on the SWIS™ team. Before telling them how to do it: What concerns might you have? How will you help the team define the problem and come up with solutions?

51. You are working with a school that is K-8. They have asked you to help them meet readiness requirements. Some questions have arisen about how many SWIS™ accounts the school might need. They have one administrator, two school-wide teams (one for K-5 and one for 6- 8), they are housed in one building. They report data to the NCES as one school: How will you help the school determine how many SWIS™ accounts they may need for decision-making?

52. You are doing your monthly data accuracy check in one of the school accounts that you facilitator and notice that the school far exceeds the number of referrals per 100 students that is average for the school type and size: Is there a problem? If so, how will you help the team define the problem and find possible solutions? If there isn’t a problem, why?

53. Supporting SWIS Schools Readiness Work with team at the school Licensing License Agreement and School Information Form Data sharing Annual updates (SIF & passwords) Teaching, coaching, & on-going support Data entry Using the data for decision making Updating accounts annually

54. SAMI SWIS Account Management Interface SAMI allows Facilitators to make changes to their SWIS™ schools ONLINE without sending in a School Information Change Form. http://sami.swis.org http://samibeta.swis.org School Management School Summary Integrity report Report status Billing Summary Facilitator information updates

55. District Integration Update ASIST a software application that builds a bridge from eSIS discipline data to SWIS accounts. Data entry into eSis On a 24 hour schedule, ASIST will transfer eSIS data to SWIS. S-Dex A software application that builds a bridge from SWIS to district databases Data entry into SWIS Beta testing with ten school districts in Oregon School Interoperability Framework (SIF) Spring 2007 Download and upload from district databases Anticipated to be used nationwide to link software applications

56. New Features Definitions updated CICO VISA

57. New Problem Behavior Categories Problem behaviors Minors Dress Code Tardy Information and other Electronic Technology Violations Majors Inappropriate displays of affection Information and other electronic technology violations Gang Affiliation Display (next SWIS update)  Student uses gesture, dress, and/or speech to display affiliation with a gang.

58. Schools within schools What decisions need to be made for whole school? What decisions need to be made for small schools within large school? What reports are needed for: ‘Parent’ school? School within school?

59. Check In Check Out CICO data collection and reporting application Must have a SWIS account Development and deployment timeline Spring ’07: development and beta testing Fall ’07: further testing November ’07: determine next steps for deployment

65. Credit Card Payment SWIS can now be paid for with a Charge Card Currently, transaction over the phone Future: Online Visa payment Thank you to Jody & Megan for making this happen!

66. Ethnicity Reports Rationale The power of information The risks and ethics of dis-proportionality Format Multiple reports are needed for decision- making

67. Ethnicity Reports Key Questions What proportion of enrolled students in school are from each ethnicity? What proportion of referrals are contributed from students in each ethnicity? What proportion of students with at least one referral are from each ethnicity? What proportion of students within each ethnicity have received at least one office discipline referral?

68. Figure 1: (a) % of students enrolled, (b) % of ODRs by ethnicity Figure 2: Proportion of all students with referrals by student ethnicity. Figure 3: Proportion of students within ethnicity who have at least one ODR. Ethnicity Report Analysis #1

69. Ethnicity Analysis #2

70. Ethnicity Analysis #3

71. Resources www.pbis.org www.swis.org www.pbssurveys.org www.pbismaryland.org