Data-based Decision Making: Basics

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Data-based Decision

Making: Basics

OSEP Center on Positive Behavioral

Interventions & Supports

February 2006 www.PBIS.org www.SWIS.org

C/3

George.sugai@uconn.edu

4 PBS

Elements

Supporting Social Competence &

Academic Achievement

OUTCOMES

Supporting

Staff Behavior

Supporting

Decision

Making

PRACTICES

Supporting

Student Behavior

3 Elements of Data-based

Decision Making

1.

High quality data from clear definitions, processes, & implementation (e.g., sw behavior support)

2.

Efficient data storage & manipulation system (e.g., SWIS)

3.

Process for data-based decision making

& action planning process (e.g., team)

Assumptions

• Continuum of school-wide system of positive behavior support in place

• “Good” data available

• Team-based leadership

• In-building expertise

• School-level decision making needed

Start with Questions &

Outcomes!

• Use data to verify/justify/prioritize

• Describe in measurable terms

• Specify realistic & achievable criterion for success

School-wide PBS Systems Implementation Logic

LEADERSHIP TEAM

Establish measurable outcome

Build Data

System

Collect, analyze, & prioritize data

Monitor implementation & progress

Select evidence-based practice

Ensure efficient, accurate, & durable implementation

Implement

SCHOOL-WIDE

Kinds of Data

• Office discipline reports

• Behavioral incidents

• Attendance

• Suspension/Detention

• Observations

• Self-assessments

• Surveys, focus groups

• Etc.

Office Discipline Referral

Caution

• Reflects 3 factors

– Student

– Staff member

– Office

• Reflects overt rule violations

• Underestimations

General Approach: “Big 5”

• # referrals per day per month

• # referrals by student

• # referrals by location

• #/kinds of problem behaviors

• # problem behaviors by time of day

Office Referrals per Day per Month

Last year

2

1.5

1

0.5

0

Sept Oct Nov Dec Jan Feb Mar Apr May Jun

School Months

Office Referrals per Day per Month

Last year

20

15

10

5

0

Sept Oct Nov Dec Jan Feb Mar Apr May Jun

School Months

Days: 175 Referrals: 471 Avg: 2.69

M/m

Days: 175 Referrals: 86 Avg: 0.49

M

M/M

Is action needed?

Office Referrals per Day per Month

This Year Is action needed?

20

15

10

5

0

Sept Oct Nov Dec Jan Feb Mar Apr May Jun

School Months

Office Referrals per Day per Month

This Year

20

Is action needed?

15

10

5

0

Sept Oct Nov Dec Jan Feb Mar Apr May

School Months

Office Referrals per Day per Month

This year (Middle)

20

Is action needed?

15

10

5

0

Sept Oct Nov Dec Jan Feb Mar Apr May Jun

School Months

Office Referrals per Day per Month

Last Year and This Year

20

Is action needed?

15

10

5

0

Sept Oct Nov Dec Jan Feb Mar Apr May Jun

School Months

Office Referrals per Day per Month

Last Year and This Year

20 Is action needed?

15

10

5

0

Sept Oct Nov Dec Jan Feb Mar Apr May Jun

School Months

Office Referrals per Day per Month

Last Year and This Year

20

Is action needed?

15

10

5

0

Sept Oct Nov Dec Jan Feb Mar Apr May Jun

School Months

Office Referrals per Day per Month

Last Year and This Year

20

Is action needed?

15

10

5

0

Sept Oct Nov Dec Jan Feb Mar Apr May Jun

School Months

What?

50

Referrals per Prob Behavior

40

30

20

10

0

Lang A chol A rson B omb Combs Defian Disrupt Dress A gg/fgt Theft Harass P rop D S kip Tardy Tobac V and W eap

Types of Problem Behavior

What?

50

Referrals per Prob Behavior

40

30

20

10

0

Lang A chol A rson B omb Combs Defian Disrupt Dress A gg/fgt Theft Harass P rop D S kip Tardy Tobac V and W eap

Types of Problem Behavior

15

What?

Referrals per Prob Behavior

10

5

0

Lang A chol A rson B omb Combs Defian Disrupt Dress A gg/fgt Theft Harass P rop D S kip Tardy Tobac V and Weap

Types of Problem Behavior

Where?

Referrals by Location

50

40

30

20

10

0

Bath R Bus A Bus Caf Clas s Comm Gym Hall

School Locations

Libr Play G Spec Other

Where?

Referrals by Location

50

40

30

20

10

0

Bath R Bus A Bus Caf Clas s Comm Gym Hall

School Locations

Libr Play G Spec Other

20

Who?

Students per Number of Referrals

10

0

Students

Who?

Students per Number of Referrals

20

10

0

Students

When?

Referrals by Time of Day

30

25

20

15

10

5

0

7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 1:00 1:30 2:00 2:30 3:00 3:30

Time of Day

When?

Referrals by Time of Day

30

25

20

15

10

5

0

7:00 7:30 8:00 8:30 9:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 1:00 1:30 2:00 2:30 3:00 3:30

Time of Day

“Real” Data

• “A. E. Newman” Elementary School

– ~450 K-5 students

– ~40% free/reduced lunch

– Suburban

# Behavior Incidents/Day/Month

# BI by Problem Behavior Type

# Major BI/Day/Month

# BI by Location

# BI by Time of Day

# BI by Staff Member

# Major BI by Staff Member

SW v. Individual

• Examine impact of individual student behavioral incidents on school-wide behavior incidents

# Major BI by Student w/ >1

# BI by Student w/ >3

1-2

3-5

>5

SW v. Individual

Majors + Minors Majors Only

# % # %

89

27

20%

6%

44

10

10%

2%

30 7% 4 1%

What about

CLEO

?

• 12 BI Dec. 2000 – Jun. 2001

• 19 BI Sep. 2001 – Dec. 2001

Suspensions/Expulsions Per Year

2000-01 2001-02

In School Suspensions

Events Days Events Days

0

Out of School Suspensions 1

0

1

2

3

2

2.5

Expulsions 0 0 0 0

CLEO: # BI/Day/Month

CLEO: # BI by Type

CLEO: # BI by Location

Guidelines: To greatest extent possible….

• Use available data

• Make data collection easy (<1% of staff time)

• Develop relevant questions

• Display data in efficient ways

• Develop regular & frequent schedule/routine for data review & decision making

• Utilize multiple data types & sources

• Establish clarity about office v. staff managed behavior

• Invest in local expertise

Conclude

• Data are good …but only as good as systems in place for

– PBS

– Collecting & summarizing

– Analyzing

– Decision making, action planning, & sustained implementation

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