Databased Decision Making and Problem Solving in PBIS
Data-based Decision Making and Problem Solving in PBIS Schools VTPBi. S Leadership Forum October 7, 2014
Agenda • Data Team Meeting – – TIPS Meeting Process Data Analyst SWIS Updates Solution Development • Now what? – Sharing Data with Staff • Q & A – Networking • Resources – VTPBi. S Assessment Schedule – BAT
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.
Welcome Data Team! Team Initiated Problem Solving (TIPS) 1. A structured meeting process – Formal roles (facilitator, recorder, data analyst) – Access and use of data – Use of electronic and projected meeting minutes 2. 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
Skills for Meeting Roles Facilitator Note Taker Data Analyst • Ask questions • Implements group norms • Keeps people on track (back on track) • Uses computer • Word processer • Save files • Edit files • Listens to a discussion and paraphrase critical information • Is fluent with meeting minute form • Likes data • Navigates through application • Discriminates what to ask when creating custom reports • Creates a story from data summary • For new problems • Status on old • problems 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 Educational and Community Supports, University of Oregon, unpublished training manual.
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 – –
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
POLL: To what extent does someone function as data analyst in your PBIS planning meetings? 1. Data has not been used in our meetings so there has been no need for a data analyst 2. There is no one in particular serving in this role. The Team reviews and analyzes the data together at the meetings. 3. 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) Today’s Agenda Items 1. 2. 3. Next Meeting Agenda Items 1. 2. Administrative/General Information and Issues Information for Team, or Issue for Team to Address Discussion/Decision/Task (if applicable) Who? By When? Problem-Solving Action Plan Precise Problem Statement, based on review of data (What, When, Where, Who, Why) Solution Actions (e. g. , Prevent, Teach, Prompt, Reward, Correction, Extinction, Safety) Who? Implementation and Evaluation Goal, Timeline, By When? Decision Rule, & Updates Evaluation of Team Meeting (Mark your ratings with an “X”) 1. Was today’s meeting a good use of our time? 2. In general, did we do a good job of tracking whether we’re completing the tasks we agreed on at previous meetings? 3. In general, have we done a good job of actually completing the tasks we agreed on at previous meetings? 4. In general, are the completed tasks having the desired effects on student behavior? Our Rating Yes So-So No
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
Data Analyst found the following trends…… Disruption in the cafeteria Middle of the day
2. What is the precise nature of our problem (define, clarify, confirm/disconfirm inferences)? Question What problem behaviors are occurring? SWIS Table/Graph Referrals by problem behavior When are problem behaviors occurring? Referrals by time Where are problem behaviors occurring? Referrals by location Who is engaging in problem behaviors? Why do problem behaviors keep happening? Referrals by student Referrals by motivation
Go to SWIS! www. pbisapps. org
What?
When?
Where?
Who?
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?
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.
Why?
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. Prevention Teaching Reward Extinction Corrective Consequence Data Collection
Solution development for disruption in cafeteria Prevention: Remove/alter “trigger” for problem behavior Maintain current lunch schedule, but shift classes to balance numbers. Teaching: Define, instruct & model expected behavior Teach behavioral expectations in cafeteria Reward: Expected/alternative behavior when it occurs; prompt as necessary Establish “Friday Five”: Extra 5 min of lunch on Friday for five good days. Extinction: Increase acknowledgement of Encourage all students to work for presence of desired behavior “Friday Five”… make problem behavior less rewarding than desired behavior Corrective Consequence: Use nonrewarding/non-reinforcing responses when problem behavior occurs Active supervision and continued early consequence (ODR) Data Collection: Indicate how you know when you have a solution Maintain ODR record and supervisor weekly report
…. 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
Now what? Share data and plan with your staff!
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.
Our Plan……. . Prevention: • Maintain current lunch schedule, but shift classes to balance numbers. – 6 th graders will now eat with the 7 th graders, not 8 th graders Teaching: • All students should be reminded of the cafeteria expectations before leaving the classroom. Please use the Teaching Matrix • 6 th 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.
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
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 followup in a week to see if problem behaviors decreased.
Questions? ? ?
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?
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 VTPBi. S Assessment Schedule – – Complete the Bo. Q, SAS & BAT (January – March, 2015) • Use each other as resources!!!
THANK YOU!
- Slides: 36