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Good Afternoon! Thank you for joining us After you sit and get comfortable, please work with a partner and complete the Crossword Puzzle “MiBLSi Data Tools”

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Good Afternoon!. Thank you for joining us After you sit and get comfortable, please work with a partner and complete the Crossword Puzzle “MiBLSi Data Tools”. Analyze, Use and Report Behavior Data Fluently. Susan Bogart and Christine Russell [email protected] - PowerPoint PPT Presentation

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Page 1: Good Afternoon!

Good Afternoon!

• Thank you for joining us• After you sit and get

comfortable, please work with a partner and complete the

Crossword Puzzle“MiBLSi Data Tools”

Page 2: Good Afternoon!

Susan Bogart and Christine [email protected]@wmich.edu

Page 3: Good Afternoon!

Our Experience with MiBLSi Data Tools

• We can predict problem behavior so we can prevent problem behavior

• Team based decision making• Making the smallest change for a big

impact

Page 4: Good Afternoon!

Data

• Office discipline reports• Behavioral incidents• Attendance• Suspensions/Detentions• Observations/Tracking Forms• Self-assessments• Surveys, focus groups

Page 5: Good Afternoon!

ONLY 3 PBS Data Tools required by MiBLSi

• EBS Self Assessment Survey

• EBS Team Implementation Checklist

• SWIS

PBS Tools

Page 6: Good Afternoon!

• Big 5 reports– Only required to keep data on

“major” behaviors– Generate and review at monthly

team meetings and @ data review – See “Guidelines for Data-Based

Decision Making”

swis.org

Page 7: Good Afternoon!

• Year End Report

– # ODR’s per day per 100 students– Compare to national average– For a school with 300 students Elementary schools: 1 major daily Middle schools: 3 majors daily

swis.org

Page 8: Good Afternoon!
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EBS Self-Assessment Survey

• free, all staff, anonymous, every spring, password is 6 numbers for all to use, web based

See “Data Based Decision Making Flowchart”

pbssurveys.org

Page 10: Good Afternoon!

EBS Self-Assessment Survey

Page 11: Good Afternoon!

EBS Team Implementation Checklist

• free, 4 times a year, leadership team discusses questions, consensus, one person input, same 6 number password

• if your team says “I” to 80% or more of the questions then correlation to reduced ODR’s

pbssurveys.org

Page 12: Good Afternoon!

EBS Team Implementation Checklist

Page 13: Good Afternoon!

0.813

0.59

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Not Met Criteria Met Criteria

OD

R p

er

100 S

tudents

per

day

Meeting 80% criteria on Team Checklist

Save approximately 7 school days/year!

n = 31n = 22

Page 14: Good Afternoon!

PBS Surveys Homepage

www.pbssurveys.org

MiBLSi Websitewww.cenmi.org/miblsi

Page 15: Good Afternoon!

DIBELS, SWIS & MoreOH MY!

• DIBELS• SWIS• SET• EBS• PBIS• SW-PBS• Moodle• ODR

• Sugai• Horner• Todd• Sprick• CHAMPS• Sopris West• TIC• BofQ

• TAP• FBA• BIP• FACTS

Page 16: Good Afternoon!

Coaching: Patterns & PrioritiesSchool Z Y X W V U T S R Q P O

# of ODRs (major)

12 13 x 177 x 67 71 64 81 100 331 166

Average Major ODR per day per 100 students

.02 .07 x .22 x X .10 .16 .18 .40 .47 .11

Average all ODR per day

.80 .75 x 11.7

x 1.4 n/a 1 .83 6.3 4 1.5

Grade priority

K 3 x 4 x x 3 K 3 3 n/a 6

Time priority

12:00 to 12:4

5

End of

day

x 12:30to

1:15

x 12:00 11:30 to

1:00

11:45 to

12:15

12:15 to

12:45

12:00 to

1:00

12:00 to1:00

2:30

Location priority

Class

Bus x Class

x Class Play-groun

d

Class Class Class Class

Bus

Major Problem Behavior priority

PhysAgg

Ha-rass-men

t

x Agg/Figh

t

x Agg/fight

Agg/fight

Agg/fight

Dis-respec

t

Agg/fight

Disre-

spect

Disrupt

Pattern

Page 17: Good Afternoon!

Coaching: Patterns & PrioritiesTeam Time

Using the Lighthouse District Graph please reflect on these questions:

1) Does this data guide you as a coach regarding priorities and patterns?

- What data will you follow-up?

2) What do you see that concerns you the most and what actions will you take?

Page 18: Good Afternoon!

Group Data

Focus is on:– What you can predict

– What you can prevent

– What patterns you see in your data

Page 19: Good Afternoon!
Page 20: Good Afternoon!

Strategic Data

Page 21: Good Afternoon!
Page 22: Good Afternoon!
Page 23: Good Afternoon!

Intensive Student Data

• Focus is on:

– Brining together accurate information to assist in completing a Functional Behavioral Assessment

– Once FBA is completed, can be used to write an effective behavior plan

– Data should also be helpful in evaluating whether the plan is working

Page 24: Good Afternoon!

Intensive Student Data

• SWIS Individual Student Report• Additional data collection• Any data collected by school/teachers

Don’t Forget!!• Schoolwide and Group Analysis• Reading/Academic Data

Page 25: Good Afternoon!

Individual Student Data

• A common “Complaint”– “It’s too difficult to fill out a referral form for the

kids that have persistent/reoccurring problem behaviors”

– What to do?• Modify the referral form!• Keep critical information included• See examples

Page 26: Good Afternoon!
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Intensive Student Data

Tracking Form0_occurrences = 1 occurrence = 2 or more =

Tuesday

8:00

8:10

8:20

8:30

8:40

Tuesday

1st Hour

2nd Hour

3rd Hour

4th Hour

5th Hour

Page 30: Good Afternoon!

Intensive Student DataWhat Questions do we ask as we look at the

data?• Antecedent and Setting Event Questions:

– Does the problem behavior occur • at a certain time of day?• in a certain classroom/with a certain teacher?• in structured vs nonstructured settings?• with certain peers?

• Behavior Questions:– Is the problem behavior consistent/similar each time?– Are these major or minor issues?

• Consequence Questions:– Is the student trying to gain something or avoid something?– Does the Administrative Decision play into the motivation for the

problem behavior? (i.e. wants to obtain adult attention and has a conference with the teacher each time the behavior occurs)

Page 31: Good Afternoon!

Intensive Student DataTeam Time

• Look at the data provided regarding three Intensive students in relationship to the schoolwide and group data provided.

1. Should the student’s problem behavior be problem-solved at the individual or group level?

2. What patterns/thoughts do you have regarding next steps in problem solving based on the questions you asked while looking at the individual student data?

Page 32: Good Afternoon!

• MiBLSi measurement tools are graphic

• Data collection easy (<1% of staff time)

• We can utilize multiple data types & sources

• Data is relevant, timely, efficient and practical

• Helps us “refine a problem statement to a level of precision that allow functional solutions” Dr. George Sugai

Page 33: Good Afternoon!

Systems (How things are done)

Data (How decisions are made)

Practices (How staff interact with students)

Lucile Eber, Ed.D.Illinois PBIS

Page 34: Good Afternoon!

SYST

EMS

PRACTICES

Information

SupportingStaff Behavior

SupportingDecisionMaking

SupportingStudent Behavior

OUTCOMES

Social Competence, Academic Achievement, and Safety

Page 35: Good Afternoon!

pbis.org

Page 36: Good Afternoon!

School nameMinutesHoursDays

Average # of minutes

Enter info below Time Regained

567

Student

Average # of minutes student is out of class due to referral

136 102

Average # of minutes administrator needs to process referral

20

15

COST/BENEFIT ANALYSIS WORKSHEET

Number of referrals for this year 159

K - 2 Elementary 350+ students

Number of referrals for last year

17 13

Administrator8160 6120

K - 2 Elementary 350+ students

11340

3180

81608505

2385

6120

0

2000

4000

6000

8000

10000

12000

Last

Yea

r

Thi

s Y

ear

Tim

eR

egai

ned

Student Minutes Admin Minutes

K - 2 Elementary 350+ students

189

53

142

40

0

50

100

150

200

Last

Yea

r

Thi

sY

ear

Student Hours Admin Hours

K - 2 Elementary 350+ students

24

7

18

5

05

10152025

Last

Yea

r

Thi

sY

ear

Student Days Admin Days

Page 37: Good Afternoon!

pbismaryland.org