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Using Data for Decision-making. Rob Horner, Anne Todd, Steve Newton, Bob Algozzine, Kate Algozzine. Main Ideas. Decisions are more likely to be effective and efficient when they are based on data.

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using data for decision making

Using Data for Decision-making

Rob Horner, Anne Todd, Steve Newton,

Bob Algozzine, Kate Algozzine

main ideas
Main Ideas
  • Decisions are more likely to be effective and efficient when they are based on data.
  • The quality of decision-making depends most on the first step (defining the problem to be solved)
      • Define problems with precision and clarity
main ideas1
Main Ideas
  • Data help us ask the right questions…they do not provide the answers: Use data to
    • Identify problems
    • Refine problems
    • Define the questions that lead to solutions
  • Data help place the “problem” in the context rather than in the students.
main idea
Main Idea
  • The process a team uses to problem solve is important:
    • Roles:
        • Facilitator; Recorder; Data analyst; Active member
    • Organization
        • Agenda; Old business (did we do what we said we would do); New business; Action plan for decisions.
        • What happens BEFORE a meeting
        • What happens DURING a meeting
        • What happen AFTER a meeting
main ideas2
Main Ideas
  • Build “decision systems” not “data systems”
  • Use data in “decision layers”
    • Is there a problem? (overall rate of ODR)
    • Localize the problem
        • (location, problem behavior, students, time of day)
    • Get specific
  • Don’t drown in the data
  • It’s “OK” to be doing well
  • Be efficient
using data
Using Data
  • Do we have a problem?
  • Refine the description of the problem?
      • What behavior, Who, Where, When, Why
  • Test hypotheses
      • “I think the problem on the playground is due to Eric”
      • “ We think the lunch period is too long”
      • “We believe the end of ‘block schedule” is used poorly”
  • Define how to monitor if solution is effective
slide9
Review

Status and

Identify

Problems

Team Initiated Problem Solving (TIPS) Model

Develop and

Refine

Hypotheses

Evaluate and

Revise

Action Plan

Collect

and Use

Data

Discuss and

Select

Solutions

Develop and

Implement

Action Plan

Problem Solving Foundations

identifying problems issues
Identifying problems/issues
  • What data to monitor
    • ODR per day per month
    • OSS, ISS, Attendance, Teacher report
    • Team Checklist/ SET (are we doing what we planned to do?)
  • What question to answer
    • Do we have a problem?
  • What questions to ask of Level, Trend, Peaks
    • 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?
  • If a problem is identified, then ask
    • What are the data we need to make a good decision?
using data to refine problem statement
Using Data to Refine Problem Statement
  • The statement of a problem is important for team-based problem solving.
      • Everyone must be working on the same problem with the same assumptions.
  • Problems often are framed in a “Primary” form, that creates concern, but that is not useful for problem-solving.
      • Frame primary problems based on initial review of data
      • Use more detailed review of data to build “Solvable Problem Statements.”
solvable problem statements what are the data we need for a decision
Solvable Problem Statements(What are the data we need for a decision?)
  • Solvable problem statements include information about the five core “W” questions.
    • What is problem, and how often is it happening
    • Where is it happening
    • Who is engaged in the behavior
    • When the problem is most likely
    • Why the problem is sustaining
primary versus precision statements
Primary Statements

Too many referrals

September has more suspensions than last year

Gang behavior is increasing

The cafeteria is out of control

Student disrespect is out of control

Precision Statements

There are more ODRs for aggression on the playground than last year. These are most likely to occur during first recess, with a large number of students, and the aggression is related to getting access to the new playground equipment.

Primary versus Precision Statements
primary versus precision statements1
Primary Statements

Too many referrals

September has more suspensions than last year

Gang behavior is increasing

The cafeteria is out of control

Student disrespect is out of control

Precision Statements

There are more ODRs for aggressionon the playground than last year. These are most likely to occur during first recess, with a large number of students, and the aggression is related to getting access to the new playground equipment.

Primary versus Precision Statements
precise or primary statement
Precise or Primary Statement?
  • Children are using inappropriate language with a high frequency in the presence of both adults and other children. This is creating a sense of disrespect and incivility in the school
  • James D. is hitting others in the cafeteria during lunch, and his hitting is maintained by peer attention.
precise or primary statement1
Precise or Primary Statement?
  • ODRs during December are higher than in any other month.
  • Minor disrespect and disruption are increasing over time, and are most likely during the last 15 minutes of our block periods when students are engaged in independent seat work. This pattern is most common in 7th and 8th grades, involves many students, and appears to be maintained by escape from work (but may also be maintained by peer attention… we are not sure).
precise or primary statement2
Precise or Primary Statement?
  • Three 5th grade boys are name calling and touching girls inappropriately during recess in an apparent attempt to obtain attention and possibly unsophisticated sexual expression.
  • Boys are engaging in sexual harassment
organizing data for decision making
Organizing Data for Decision-making
  • Compare data across time
  • Moving from counts to count/month
swis summary 2008 2009 majors only 3 410 schools 1 737 432 students 1 500 770 odrs
SWIS summary 2008-2009 (Majors Only)3,410 schools; 1,737,432 students; 1,500,770 ODRs

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.

start with the odr day month graph
Start with the ODR/Day/Month Graph
  • Use the information in the data to build a narrative that draws the team into problem solving.
  • Be descriptive
  • Link local data to national patterns
  • Tie the data back to local conditions/events.
slide23
Elementary School 465 students (465/ 100 = 4.6 X .34= 1.56)

Our rate of problem behavior has been above the national average for schools our size for 9 of 10 months this year. There has been a decreasing trend since Dec.

slide24
Elementary School 1000 Students (1000/100 =10 X .34= 3.4)

The rate of problem behavior has been at or below the national average schools our size for 6 of 10 months. The past 4 months have been below the national average

slide25
Middle School 765 students (765/100 = 7.6 X .85= 6.46)

The rate of problem behavior has been at or below the national average schools our size for 9 of 10 months. The past 8 months have been below the national average with a decreasing trend

using data to build precision
Using Data to Build Precision
  • Given that we know we have a problem
  • What problem behaviors
  • Where are they occurring
  • When are they occurring
  • Who is involved
  • Why do they keep happening
what questions to ask about the patterns of problem behaviors
What questions to ask about the patterns of problem behaviors?
  • Do we have one problem behavior situations or more than one?
  • Do we have many problem behaviors or just a few problem behaviors?
  • Do we have clusters of problem behaviors?
  • What school wide expectations do we need to re-teach?
data should allow asking the right question not supplying the answer
Data should allow asking the right question… not supplying the answer.
  • If many referrals in class
      • Which classes?
      • Which students?
      • When?
  • If many referrals in cafeteria
      • Which students?
      • What times? (beginning or end of lunch period?)
      • What problem behaviors?
slide33
Disrespect is our most frequent problem behavior.

We also have incidents of fighting and harassment

What are next questions?

Who, When, Why?

slide34
Our most frequent problem behavior is disrespect, followed by inappropriate language, disruption and tardy

What are next questions?

Who, When, Why?

slide35
We have many instances of disrespect, aggression/fighting. technology violations, tardy, harassment, lying, skipping, and inappropriate language
what questions to ask about referrals by location
What questions to ask about Referrals by Location
  • Where are the problems occurring?
  • Are there problems in many locations, clusters of locations, or one location?
slide37
Many problem behaviors in class

Many problem behaviors in unstructured settings (hall, playground, parking lot, bathroom)

slide38
Many problems in the cafeteria, hallway, common area, class, bathroom. Where is the ‘unknown’ location?
what questions to ask about referrals by time
What questions to ask about Referrals by Time
  • When are the problem behaviors occurring?
  • How do those times match with the daily activities?
  • How does this information match up to Referrals by Location?
slide40
Most problems are occurring between 9:45-10:45.

Other problematic times are 8-8:45 and 11:30.

what questions to ask about referrals by student
What questions to ask about Referrals by Student
  • What proportion of students has 0-1 ODR?
  • What proportion of students has 2-5 ODRs?
  • What proportion of students has 6+ ODRs?
  • Do we have systems of support that increase student success?
slide44
Student # 121 needs individualized support.

8 students are likely candidates for some type of Tier II support.

87% of our students have received 0-1 ODR

slide45
14 students are likely candidates for some type of Tier II support. Student #119 needs individualized support
slide46
We have 11 students who are likely candidates for some type of Tier II support

93% of our students have received no more than one ODR

what questions to ask about referrals by perceived motivation
What questions to ask about Referrals by Perceived Motivation
  • What is perceived as maintaining the problem behavior?
  • Are there one or more perceptions?
slide48
The problem behaviors are most likely maintained by task avoidance and peer avoidance.

We have many incidents with unknown motivation

using the tips minutes to guide problem solving
Using the TIPS Minutes to guideProblem Solving
  • Write the precision problem statement in the left hand column below
  • Define a goal and write it in the right hand column
using data to build solutions
Using Data to Build Solutions
  • Prevention: How can we avoid the problem context?
    • Who, When, Where
    • Schedule change, curriculum change, etc
  • Teaching: How can we define, teach, and monitor what we want?
    • Teach appropriate behavior
    • Use problem behavior as negative example
  • Recognition: How can we build in systematic reward for desired behavior?
  • Extinction: How can we prevent problem behavior from being rewarded?
  • Consequences: What are efficient, consistent consequences for problem behavior?
  • How will we collect and use data to evaluate (a) implementation fidelity, and (b) impact on student outcomes?
trevor test middle school

Trevor Test Middle School

565 students

Grades 6,7,8

precise problem statement hypothesis development
Precise Problem Statement &Hypothesis Development
  • Many students from all grade levels are engaging in disruption, inappropriate language and harassment in cafeteria and hallway during lunch, and the behavior is maintained by peer attention
  • A smaller number of students engage in skipping and noncompliance/defiance in classes, (mostly in rooms 13, 14 and 18), and these behaviors appear to be maintained by escape.
phoenix elementary

Phoenix Elementary

Using Data For Decision-Making

you are the behavior support team for phoenix elementary 265 students k 5
You are the Behavior Support team for Phoenix Elementary. 265 students k-5
  • Do you have a problem?
  • Where?
  • With Whom?
  • What other information might you want?
  • Given what you know, what considerations would you have for possible action?
examples
Examples
  • Phoenix Elementary
    • What is national comparison?
      • 265/100 = 2.65 2.65 X .34 = .90
    • Absolute level compared with last year, compared with teacher/staff impressions, compared with family impressions, compared with student impressions.
    • Where, what, when, who , why
    • Hypotheses?
    • Solutions
slide63
Year 2

Year 1

slide64
Year 1

Year 2

problem statement
Problem Statement
  • Do we have a problem?
  • Build a precise problem statement
precision statement hypothesis
Precision Statement/Hypothesis
  • What
  • Where
  • When
  • Who
  • Why
  • What other info needed?
  • Possible Solutions?
precision statement hypothesis1
Precision Statement/Hypothesis
  • What
  • Where
  • When
  • Who
  • Why
  • What other info needed?
  • Possible Solutions?
summary
Summary
  • Establish information systems for decision-making… not data systems for reporting.
  • Use data to identify problems
  • Use data to clarify/refine problems
  • Use knowledge of context and content to build solutions.
  • Use data to monitor impact of solutions.
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