Transcript Returning Team Training July 17, 2008 AGENDA  Introductions and Celebrations  Team Check-up  Creative ways to use data: A toolkit for schools  Check-in Check-out:

Returning Team
Training
July 17, 2008
AGENDA
 Introductions and Celebrations
 Team Check-up
 Creative ways to use data: A toolkit for
schools
 Check-in Check-out: Behavior Education
Program
 Action Planning
Introductions
&
Celebrations
Goals
 Define the use of data driven decision to
reach full implementation of school-wide
PBS

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Team Implementation Checklist (TIC)
School-wide Evaluation Tool (SET)
 Assess implementation level
 Determine need for strategies to assist
students in the “Yellow Zone”
Assumptions
 School teams will be successful if:
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They start with sufficient resources and commitment
They focus on the smallest changes that will result
in the biggest difference
They have a clear action plan
They use on-going self-assessment to determine if
they are achieving their plan
They have access to an external coach who is
supportive, knowledgeable and persistent.
Team Implementation Checklist
 Self-assessment tool for monitoring
implementation of School-wide PBS
 Start-Up Elements
Establish Commitment
 Establish and Maintain Team
 Self-assessment
 Establish school-wide expectations
 Establish consequences for behavioral
errors
 Recognize appropriate behavior
 Establish information system
 Establish capacity for function-based support

Team Implementation Checklist
Checklist #1: Start-Up Activity
Complete & submit Monthly.
Status: Achieved, In Progress, Not Started
Date:
(MM/DD/YY)
Establish Commitment
1. Administrator’s support & active involvement.
Status:
2. Faculty/Staff support (One of top 3 goals, 80% of faculty
document support, 3 year timeline).
Status:
Establish & Maintain Team
3. Team established (representative).
Status:
4. Team has regular meeting schedule, Positive operating
procedures.
Status:
5. Audit is completed for efficient integration of team with other
teams/initiatives addressing behavior support.
Status:
Self-Assessment
6. Team/faculty completes PBS self-assessment survey.
Status:
7. Team summarizes existing school discipline data.
Status:
8. Strengths, areas of immediate focus & action plan are
identified.
Status:
Use of the Team Checklist
 Who completes the Team Checklist?
 The
school-team (individually or together)
 When is Team Checklist completed?
 At
least quarterly, best if done monthly
 Who looks at the data?
 Team
 Coach
 Coordinator
 Action Planning
TIC (continued)
TIC (continued)
What does the SET measure?
Measures the level of implementation of
SWPBS
(not intended to measure everything!)
 The Critical Features
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Expectations Defined
Expectations Taught
System for Encouraging Expected Behaviors
System for Discouraging Problem Behaviors
Monitoring and Decision Making
PBS Team Management
District Level Support
Why use it?
The results help PBS teams:
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Assess the features of PBS in place
Determine annual goals for school-wide
positive behavior support
evaluate on-going efforts toward school-wide
behavior support
design and revise procedures as needed
compare efforts toward school-wide effective
behavior support from year to year
Data Review Worksheet
 Review office referrals
 Review TIC results
 Review SET results
 Complete Action Planning Form
Creative ways to use data:
A toolkit for schools
Susan Barrett
[email protected]
Objectives
 Review why and how to use discipline data
 Provide examples of how CCPS schools use various
forms of data to monitor the effectiveness of PBIS
 Highlight and demonstrate templates utilized to share
information with staff and PBS teams
 Determine what barriers to learning we have
 Complete an activity to help plan for data-based
decision making
Data
IS NOT:
 A scary or “four letter”
word
 Should not intimidate us
 Just numbers
IS:
 Powerful when used to
discuss discipline
 Empowering when used
by school teams
 Reviewed frequently to
determine areas of
strength and weakness
Scenarios
 You work at an elementary school with 400 students.
Upon reviewing data at the end of the year you find
that your school had 20 suspensions.
 You work at a high school with 1000 students. You
have a total of 100 days of suspension during the
school year.
Scenarios
 You work in a middle school of 650 students.
Last school year there were 100 referrals.
 You work at an elementary school of 450
students. Last year there were 800 referrals
What impact does it have?
 Think about each of the scenarios
Impact
 Administrators
 Teachers
 Staff
 Students
 Parents
 School Climate
 Interventions
 Support Services needed
 Academic Achievement
Improving Decision-Making
From
Solution
Problem
Problem
To
Problem
Solving
Information
Solution
Why Collect Discipline Data?
 Decision making
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What decisions do you make?
What data do you need to make these decisions?
 Professional Accountability
 Decisions made with data (information) are more
likely to be (a) implemented, and (b) effective
From primary to precise
 Primary statements are vague and leave us with
more questions than answers
 Precise statements include information about 5 “Wh”
questions:
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What is the problem and how often is it happening?
Where is it happening
Who is engaging in the behavior?
When is the problem most likely to occur?
Why is the problem sustaining?
From primary to precise:
An example
 Primary statement:
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“There is too much
fighting at our school”
 Precise statement
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There were 30 more ODRs for
aggression on the playground than
last year, and these are most likely
to occur from 12:00-12:30 during
fifth grade’s recess because there
is a large number of students, and
the aggression is related to getting
access to the new playground
equipment. “
From primary to precise:
An example
 Primary statement:

“ODRs during December
were higher than any
month”
 Precise statement:
 Minor disrespect and disruption are
increasing and are most likely to occur
during the last 15-minutes of our classes
when students are engaged in
independent seat work. This pattern is
most common in 7th and 8th grades, involve
many students, and appears to be
maintained by work avoidance/escape.
Attention may also be a function of the
behavior- we’re not sure.
Effective Data Systems
 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.
Data Collection
 The “Big 5”
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Average referrals per
day per month
Location
Problem behavior
Student
Time
Summarize the “Big 5”
 Is there a problem?
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If no, what will we do to sustain our efforts?
If yes, is problem definable or do we need more
information?
 Next steps
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How will we know if it’s working?
Where will we review the data?
Steps to Problem-Solving
 Define the problem(s)
Analyze the data
Define the outcomes and data sources for measuring the outcomes
Consider 2-3 options that might work
Evaluate each option
 Is it safe?
 Is it doable?
 Will it work?
 Which option will give us the smallest change for the biggest
outcome?
Choose an option to try
Determine the timeframe to evaluate effectiveness
Evaluate effectiveness by using the data
 Is it worth continuing?
 Try a different option?
 Re-define the problem?
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Interpreting Office Referral Data:
Is there a problem?
 Absolute level (depending on size of school)
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Middle, High Schools (> 1 per day per 100)
Elementary Schools (> 1 per day per 250)
 Trends
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Peaks before breaks?
Gradual increasing trend across year?
 Compare levels to last year
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Improvement?
What systems are problematic?
 Referrals by problem behavior?
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What problem behaviors are most common?
 Referrals by location?
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Are there specific problem locations?
 Referrals by student?
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Are there many students receiving referrals or only a
small number of students with many referrals?
 Referrals by time of day?
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Are there specific times when problems occur?
Designing Solutions
 If many students are making the same mistake it typically
is the system that needs to change not the students.
 Teach, monitor and reward before relying on punishment.
 An example (hallways)
5:1 Ratio of tickets to referrals
 Our data tells us that we should be giving 5
positives to each corrective response
 How is that measured?
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Number of coupons versus number of referrals.
Number of RRR Tickets
Quarter
K
1
2
3
4
5
Total
One
306
289
278
236
110
193
1412
Two
678
526
423
278
147
191
2243
Overall
984
815
701
514
257
384
3655
ry
y
r
r
l
ne
ay
il
To
ta
Ju
M
Ap
r
ar
ch
ua
M
Fe
br
nu
ar
em
be
Ja
De
c
em
be
No
v
r
be
r
mb
e
to
te
Oc
Se
p
Ratio of Tickets: Referrals
6.0
5.0
4.0
3.0
2.0
1.0
0.0
Triangle of Student Referrals
Intensive, Individual Interventions
Individual Students
Assessment-based
High Intensity
Targeted Group Interventions
Some Students (at-risk)
High Efficiency
Rapid Response
Universal Interventions
All Students
Preventive, proactive
1-5%
1-5%
5-10% 5-10%
80-90%
80-90%
6+ referrals
2-5 referrals
0-1 referral
Triangle of Student Referrals:
August/September 2005
Intensive, Individual Interventions
Individual Students
Assessment-based
Intense, durable procedures
Targeted Group Interventions
Some Students (at-risk)
High Efficiency
Rapid Response
Universal Interventions
All Settings
All Students,
Preventive, proactive
1-5%
07%
%
03%
Students with 2 or
more referrals
Students with 1
referral
10-15%
90%
80-90%
Students with 0
referrals
Triangle of Student Referrals:
April 2006
Theory
Actual data
Intensive, Individual Interventions
Individual Students
Assessment-based
Intense, durable procedures
1-5%
4%
Students with 1
referral
Targeted Group Interventions
Some Students (at-risk)
High Efficiency
Rapid Response
Universal Interventions
All Settings
All Students,
Preventive, proactive
Students with 2 or
more referrals
3%
10-15%
93%
80-90%
Students with
0 referrals
Cost Benefit Analysis
Student
Minutes 6300
Hours
105
Days
13
Number of
referrals Q1 and
Q2 2005-2006
548
Staff
14175
236
30
30000
24660
25000
Number of
referrals Q1 and
Q2 2006-2007
233
20000
14175
15000
10960
20
10485
10000
6300
4660
5000
d
ne
eg
ai
e
R
Th
is
Y
Y
ea
ea
r
r
0
45
La
st
Average # of
minutes
administrator
needs to
Ti
m
Average # of
minutes student
is out of class
due to referral
Student Minutes
Admin Minutes
Cost-Benefit Analysis
COST/BENEFIT ANALYSIS WORKSHEET
3000
Enter info below
2640
2500
2000
School name
Robert
Moton
Elementary
School
1000
1420
1220
1500
660
355
305
500
6
Average # of
minutes student is
out of class due to
referral
Average #
of
Average # of
minutes staff need
to process referral
Time
Regained
This Year
61
6
5
22
4
3
3
2
1
1
1
5
0
This
Year
Number of referrals
April 2006
132
Last
Year
Number of referrals
November 2005
Last Year
0
Other data to consider
 Is our attendance rate improving?
 Is our achievement data improving?
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How many students are on the honor roll?
Are state tests scores improving?
What is our graduation rate?
How many students are taking AP courses?
What else does the data tell you?
 Is there a problem on
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Bus
Cafeteria
Hallways
 If you have been implementing for many years, are
you still seeing the same results?
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Are older students still motivated by the same
incentives?
Next Steps
 Comparing academic and behavior data
State-Wide
Assessment:
Basic
Borderline
Proficient
or
Advanced
Classroom
Performance:
Below
grade level
Approaching
grade level
On or
above
grade level
Discipline:
1-5%
1-5%
5-10% 5-10%
80-90%
80-90%
6+ referrals
2-5 referrals
0-1 referral
What is the academic/behavior
connection in your school?
 What information do you need to answer this
question?
 What types of data do you currently use?
 How often? Is it working?
 What would make it better?
 What are your goals when you leave to return to
your building?
Templates
 Excel data template
 Cost-Benefit Analysis Worksheet
Discipline Data:
Essential Questions
Staff have questions
regarding effective
discipline strategies
Discipline Data is
collected to answer
questions
How do you collect data?
What data do you use?
What do we do with the data?
When do you know you have a problem?
How often do you look at your data?
How often is discipline data shared with
staff?
What information do you already have?
Attendance, suspension, office referrals,
achievement scores, tardies,
timeout/support room referrals
What are the critical discipline issues in your
building?
Who, What, How Often, When, Where?
Discipline Data:
Essential Questions
Design intervention
to target concern
How do you know what invention is
needed?
How many students contribute to your
referrals?
Are referrals coming from one grade,
classroom, or area?
Measure success
What do we measure?
How do we measure "it"?
How often do we measure "it"?
How do we know when we have success?
How do we know when we need to make
changes?
Who do we share it with?
How do we share it?
Resources
 www.pbis.org
 www.swis.org
 www.pbssurveys.org
 www.pbismaryland.org
“Without data, you’re just another person
with an opinion”- Unknown