Susan Barrett sbarrett@pbismaryland.org

 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

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

 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.

 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

 Think about each of the scenarios

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Administrators
Teachers
Staff
Students
Parents
School Climate
Interventions
Support Services needed
Academic Achievement

Solution
From
Problem
To
Problem
Problem
Solving
Information
Solution

 Decision making
 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

 Primary statements are vague and leave us with more questions than answers
 Precise statements include information about 5 “Wh” questions:
 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?

 Primary statement:

“There is too much fighting at our school”
 Precise statement
 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. “

 Primary statement:

“ODRs during December were higher than any month”
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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 7 th and 8 th grades, involve many students, and appears to be maintained by work avoidance/escape.
Attention may also be a function of the behaviorwe’re not sure.

 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.

 The “Big 5”
 Average referrals per day per month
 Location
 Problem behavior
 Student
 Time

 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?
 Next steps

How will we know if it’s working?
 Where will we review the data?

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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?
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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?

 Absolute level (depending on size of school)
 Middle, High Schools (> 1 per day per 100)
 Elementary Schools (> 1 per day per 250)
 Trends
 Peaks before breaks?
 Gradual increasing trend across year?
 Compare levels to last year
 Improvement?

 Referrals by problem behavior ?
 What problem behaviors are most common?
 Referrals by location ?
 Are there specific problem locations?
 Referrals by student ?
 Are there many students receiving referrals or only a small number of students with many referrals?
 Referrals by time of day ?
 Are there specific times when problems occur?

 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)

 Our data tells us that we should be giving 5 positives to each corrective response
 How is that measured?
 Number of coupons versus number of referrals.

Quarter
One
Two
K 1 2 3 4 5
306 289 278 236 110 193
678 526 423 278 147 191
Total
1412
2243
Overall 984 815 701 514 257 384 3655

6.0
5.0
4.0
3.0
2.0
1.0
0.0
S ep te m be r
O ct ob er
N ove m be r
D ece m be r
Ja nu ar y
F eb ru ar y
M ar ch
A pr il
M ay
Ju ne
T ot al

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%
80-90%
1-5%
5-10% 5-10%
80-90%
6+ referrals
2-5 referrals
0-1 referral

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%
10-15%
80-90%
07%
%
03%
90%
Students with 2 or more referrals
Students with 1 referral
Students with 0 referrals

Theory Actual data
Intensive, Individual Interventions

Individual Students

Assessment-based

Intense, durable procedures
Targeted Group Interventions

Some Students (at-risk)

High Efficiency

Rapid Response
1-5%
10-15%
3%
4%
Students with 2 or more referrals
Students with 1 referral
Students with
0 referrals
Universal Interventions

All Settings

All Students,

Preventive, proactive
80-90%
93%

Cost Benefit Analysis
Minutes
Student
6300
Hours
Days
105
13
Staff
14175
236
30
Number of referrals Q1 and
Q2 2005-2006
548
Number of referrals Q1 and
Q2 2006-2007
233
Average # of minutes student is out of class due to referral
Average # of minutes administrator needs to
20
45
30000
25000
20000
15000
10000
5000
0
10960
24660
La st
Ye ar
4660
10485
Th is Y ea r
Student Minutes Admin Minutes
6300
Tim e Re ga ine d
14175

COST/BENEFIT ANALYSIS WORKSHEET
Enter info below
School name Robert
Moton
Elementary
School
Number of referrals
November 2005
Number of referrals
April 2006
132
61
3000
2500
2000
1500
1000
500
0
2640
660
6
Average # of minutes student is out of class due to referral
Average # minutes staff need to process referral
22
5
6
5
4
3
2
1
0
1220
305
1
3
1420
1
355

 Is our attendance rate improving?
 Is our achievement data improving?
 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?

 Is there a problem on
 Bus
 Cafeteria
 Hallways
 If you have been implementing for many years, are you still seeing the same results?
 Are older students still motivated by the same incentives?

 Comparing academic and behavior data
State-Wide
Assessment:
Basic
Classroom
Performance:
Below grade level
1-5% 1-5%
Discipline:
6+ referrals
Borderline Approaching grade level
5-10% 5-10%
2-5 referrals
Proficient or
Advanced
On or above grade level
80-90% 80-90% 0-1 referral

 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?

 Excel data template
 Cost-Benefit Analysis Worksheet

Staff have questions regarding effective discipline strategies
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?
Discipline Data is collected to answer questions
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?

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?

 www.pbis.org
 www.swis.org
 www.pbssurveys.org
 www.pbismaryland.org
“Without data, you’re just another person with an opinion”- Unknown