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

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

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Data-based Decision Making and Problem Solving in PBIS Schools

VTPBiS Leadership ForumOctober 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

– VTPBiS 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

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 Educational and Community Supports, University of Oregon, unpublished training manual.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

• 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

Launch the meeting with a data summary that helps define the problem with precision

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.

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PBIS Team Meeting Minutes and Problem-Solving Action Plan FormToday’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 Next Meeting Agenda Items1. 2. 3.

1. 2.

Information for Team, or Issue for Team to Address

Discussion/Decision/Task (if applicable) Who? By When?

Administrative/General Information and Issues

Implementation and EvaluationPrecise Problem Statement, based on review of

data(What, When, Where, Who, Why)

Solution Actions (e.g., Prevent, Teach, Prompt, Reward, Correction, Extinction,

Safety)Who? By When?

Goal, Timeline, Decision Rule, & Updates

Problem-Solving Action Plan

Our RatingYes So-So No

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?

Evaluation of Team Meeting (Mark your ratings with an “X”)

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?

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1. Do we have a problem (identify)?

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 SWIS Table/Graph

What problem behaviors are occurring?

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?

Referrals by student

Why do problem behaviors keep happening?

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?

Prevention

Teaching

Reward

Extinction

Corrective Consequence

Data Collection

Problem: The sixth graders are disruptive & use inappropriate language in the cafeteria between 11:30 AM and 12:00 PM to get peer attention.

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 presence of desired behavior

Encourage all students to work for “Friday Five”… make problem behavior less rewarding than desired behavior

Corrective Consequence: Use non-rewarding/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:

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5. Is our plan being implemented & is it working? (evaluate & revise plan)

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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?

Next Steps….

At the end of the meeting…..•Finalize next meeting date and agenda items•Evaluate how the meet went todayAfter 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.

– 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.

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 follow-up 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 VTPBiS Assessment Schedule –– Complete the BoQ, SAS & BAT (January – March,

2015)• Use each other as resources!!!

Thank you!