1 / 36

Data-Driven Decision Making in PBIS Schools

Learn about using data to make informed decisions and solve problems in PBIS schools. Topics include data team meetings, TIPS meeting process, data analysis, solution development, and sharing data with staff.

hesson
Download Presentation

Data-Driven Decision Making in PBIS Schools

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Data-based Decision Making and Problem Solving in PBIS Schools VTPBiS Leadership Forum October 7, 2014

  2. Agenda • Data Team Meeting • TIPS Meeting Process • Data Analyst • SWIS Updates • Solution Development • Now what? • Sharing Data with Staff • Q & A – Networking • Resources • VTPBiS Assessment Schedule • BAT

  3. Activity! With your neighbor, discuss the following: • What were your successes and challenges in using PBIS data this year? (fidelity and/or student outcome measures) • In a moment, we will ask for a sampling of responses.

  4. Welcome Data Team! Team Initiated Problem Solving (TIPS) • A structured meeting process • Formal roles (facilitator, recorder, data analyst) • Access and use of data • Use of electronic and projected meeting minutes • A process for using data to make decisions • Formal problem solving steps that a group can use to build and implement solutions. • Access to the right information at the right time in the right format

  5. Skills for Meeting Roles Newton, J. S., Todd, A. W., Algozzine, K., Horner, R. H., & Algozzine, B. (2009). The Team Initiated Problem Solving (TIPS) Training Manual. Educational and Community Supports, University of Oregon, unpublished training manual.

  6. Identify a Data Analyst • Role & Responsibilities • To create data summaries that will facilitate the team in • determining if there are problems • jump starting a problem solving discussion, and • evaluating the impact of solutions and fidelity of implementation • Prepares a brief written summary for distribution at meetings using each of the data sources needed for problem solving and decision making • Help to generate reports during the meeting as questions of the data arise

  7. Launch the meeting with a data summary that helps define the problem with precision • How? • Establish the role of a data analyst (and backup person) • Teach data analyst to develop data summary • Oakes, DIBELS, SWIS…. Etc • Start meeting with defining the problem with precision • Refine precision of problem statement through inferences and hypothesis • Have data accessible for custom report generation during the meeting

  8. POLL: To what extent does someone function as data analyst in your PBIS planning meetings? • Data has not been used in our meetings so there has been no need for a data analyst • There is no one in particular serving in this role. The Team reviews and analyzes the data together at the meetings. • One person on the team brings data to the meeting for the team to review. 4. There is a person identified in this role who prepares data for review and points out trends in advance for discussion and problem solving at meetings.

  9. PBIS Team Meeting Minutes and Problem-Solving Action Plan Form Today’s Meeting: Date, time, location: Facilitator: Minute Taker: Data Analyst: Next Meeting: Date, time, location: Facilitator: Minute Taker: Data Analyst: Team Members (bold are present today) Administrative/General Information and Issues Problem-Solving Action Plan Evaluation of Team Meeting (Mark your ratings with an “X”)

  10. 1. Do we have a problem (identify)? Look for gaps and trends in your data • How do our data compare with last year? • How do our data compare with national/regional norms? • How do our data compare with our preferred/expected status?

  11. Types of data to consider

  12. Data Analyst found the following trends…… Disruption in the cafeteria Middle of the day

  13. 2. What is the precise nature of our problem(define, clarify, confirm/disconfirm inferences)? 

  14. Go to SWIS!www.pbisapps.org

  15. What?

  16. When?

  17. Where?

  18. Who?

  19. Our Precise Problem Statement…. The sixth graders are disruptive & use inappropriate language in the cafeteria between 11:30 AM and 12:00 PM. We need to take it one step further……Why is this happening?

  20. 3. Why does the problem exist, & what can we do about it? (hypothesis & solution) • Problem Statement: The sixth graders are disruptive & use inappropriate language in the cafeteria between 11:30 AM and 12:00 PM • Hypothesis: We believe they are trying to get attention from their peers.

  21. Why?

  22. 4. What are the actual elements of our plan? Problem: The sixth graders are disruptive & use inappropriate language in the cafeteria between 11:30 AM and 12:00 PM to get peer attention.

  23. Solution development for disruption in cafeteria

  24. ….including logistics:

  25. 5. Is our plan being implemented & is it working? (evaluate & revise plan) • Ask the following: • What will ‘it’ look like when you say it is not a problem? • How often will you conduct a status review? • How you will know that the solutions had a positive effect on student achievement, social competence, and/or safety? • How often will you monitor student progress? • What will the data tell you when the problem is solved?

  26. Next Steps…. At the end of the meeting….. • Finalize next meeting date and agenda items • Evaluate how the meet went today After the meeting…… • Distribute Meeting Minutes and Problem- Solving Form to team members within 24 hours

  27. Now what? Share data and plan with your staff!

  28. Lake Morey Middle School –Aug. 1 through Oct. 6, 2014 Problem: The sixth graders are disruptive & use inappropriate language in the cafeteria between 11:30 AM and 12:00 PM to get peer attention.

  29. Our Plan…….. Prevention: • Maintain current lunch schedule, but shift classes to balance numbers. • 6th graders will now eat with the 7th graders, not 8th graders Teaching: • All students should be reminded of the cafeteria expectations before leaving the classroom. Please use the Teaching Matrix • 6th Grade Teachers and Para Educators - • Set aside time at the beginning of lunch to role model one of the expectations until all have been covered this week.

  30. Acknowledge students for following the expectations: • We’d like to establish “Friday Five” – an Extra 5 min of lunch on Friday for five good days. Extinction: • Be diligent about acknowledging positive behaviors in the cafeteria by handing out our BEST Bucks. Our goal is to make appropriate behaviors much more desirable

  31. Corrective Consequence: • We plan to increase and have more active supervision (ie. Walking around during lunch, talking with students, etc….). • Continued early consequence, if neccessary (Minor -ODRs) Data Collection: • We will continue to record ODRs and will follow-up in a week to see if problem behaviors decreased.

  32. Questions???

  33. Guiding Questions Think about this question again….. What were your successes and challenges in using PBIS data this year? (fidelity and/or student outcome measures) What more do you need to know about in order to make positive change?

  34. Resources and Next Steps! • Attend Universal Data Day Training: • November 6 at the Hampton Inn, Colchester • November 7 at the Franklin Center, Rutland • Participate in Targeted Data Day in April • April 2 at the Hampton Inn, Colchester • April 3 at the Franklin Center, Rutland • Review VTPBiS Assessment Schedule – • Complete the BoQ, SAS & BAT (January – March, 2015) • Use each other as resources!!!

  35. Thank you!

More Related