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6/20/17 1 50 Shades of Green: Continuous Quality Improvement for Tier I with SWIS Kelsey Morris University of Missouri Leverage Your Learning What to you know? What do you want to learn? What did you learn? What will you do with your learning? Tier I: Universal Systems OSEP, 2008 Equitable Outcomes Systems for Staff Practices for Students Data for Decisions How is your organization making decisions at Tier I? 0 2 4 6 8 10 12 Aug Sept Oct Nov Dec Jan Feb Mar Apr May Jun 0-1 2-5 6+ Cumulative Mean ODRs Per Month for 325+ Elementary Schools 08-09 McIntosh, K., Frank, J. L., & Spaulding, S. A. (2010). Establishing research-based trajectories of office discipline referrals for individual students. School Psychology Review, 39(3), 380. Cumulative Mean ODRs

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6/20/17

1

50 Shadesof Green:Continuous Quality Improvement for Tier I with SWIS

Kelsey MorrisUniversity of Missouri

Leverage Your Learning

What to you know?

What do you want to learn?

What did you

learn?

What will you do

with your learning?

Tier I:Universal Systems

OSEP, 2008

Equitable Outcomes

Systemsfor Staff

Practicesfor Students

Datafor Decisions

How is your organization making decisions

at Tier I?

0

2

4

6

8

10

12

Aug Sept Oct Nov Dec Jan Feb Mar Apr May Jun

0-1 2-5 6+

Cumulative Mean ODRs Per Month for 325+ Elementary Schools 08-09

McIntosh, K., Frank, J. L., & Spaulding, S. A. (2010). Establishing research-based trajectories of office discipline referrals for individual students. School Psychology Review, 39(3), 380.

Cum

ulativ

e M

ean

ODR

s

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2

0

2

4

6

8

10

12

Aug Sept Oct Nov Dec Jan Feb Mar Apr May Jun

0-1 2-5 6+

Potential Trajectories with Early Identification

McIntosh, K., Frank, J. L., & Spaulding, S. A. (2010). Establishing research-based trajectories of office discipline referrals for individual students. School Psychology Review, 39(3), 380.

Cum

ulativ

e M

ean

ODR

s

Performance Gap

Valued Outcomes

Current Reality

Current Reality

Valued Outcomes

Gilbert, T.F. (1978). Human competence: Engineering worthy performance. New York: McGraw-Hill.

Causal Analysis

InformationResources Resources

Incentives Incentives Incentives Incentives

Current Reality

Valued Outcomes

• What are the expectations? What is the system? What data do we have?

• What materials/tools do we have? Is there time allocated? What are our processes?

• How are we encouraging good work?

Gilbert, T.F. (1978). Human competence: Engineering worthy performance. New York: McGraw-Hill.

Causal Analysis

InformationResources Resources

Incentives Incentives Incentives Incentives

Individual Motives

Personal Capacities

Knowledge & Skills

Current Reality

Valued Outcomes

Is there a desire (motive) to work

and excel?

Is there an ability (capacity) to

learn and do?

Is there the requisite knowledge and skill

base?Gilbert, T.F. (1978). Human competence: Engineering worthy performance. New York: McGraw-Hill.

Where does your organization spend most

of its time and effort?

Causal Analysis

Information

Current Reality

Valued Outcomes

Cycle of Continuous Quality

Improvement

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Continuous Quality Improvement

EvaluateIdentify problems with precision

Establish goal(s)

Develop solutionsImplement plan with integrity and fidelity

Monitor outcomes and compare to goals

Reassess and revise solutions as needed

Problem Solving with Precision

Primary

Precise

Who?What?

When?Where?

Why?How often?

Problem Solving with Precision

• Primary• Too many referrals• Gang behavior is

increasing.• The cafeteria is out of

control.• Students are way too

disrespectful.

• Precise• There are more

referrals for disruption in the hallway during the morning than last month. These involve a large number of students across grade levels, and it seems to be related to getting access to peer attention.

Problem Solving with Precision

• Precise• There are more

referrals for disruption in the hallway during the morning than last month. These involve a large number of students across grade levels, and it seems to be related to getting access to peer attention.

Who?What?When?Where?Why?How often?

What is the value in problem solving with precision?

How are problems solved in your organization?

Keep Your Finger on the Pulse

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Checking the Vital Signs

May, S., Ard, W., Todd, A., Horner, R., Glasgow, A., Sugai, G., & Sprague, J. (2017) School-wide Information System 5.8.0 b10. University of Oregon, Eugene, Oregon.

How often are we issuing referrals?

May, S., Ard, W., Todd, A., Horner, R., Glasgow, A., Sugai, G., & Sprague, J. (2017) School-wide Information System 5.8.0 b10. University of Oregon, Eugene, Oregon.

Where are we issuing referrals?

May, S., Ard, W., Todd, A., Horner, R., Glasgow, A., Sugai, G., & Sprague, J. (2017) School-wide Information System 5.8.0 b10. University of Oregon, Eugene, Oregon.

What behaviors are we referring?

May, S., Ard, W., Todd, A., Horner, R., Glasgow, A., Sugai, G., & Sprague, J. (2017) School-wide Information System 5.8.0 b10. University of Oregon, Eugene, Oregon.

When are we issuing referrals?

26

34

17

May, S., Ard, W., Todd, A., Horner, R., Glasgow, A., Sugai, G., & Sprague, J. (2017) School-wide Information System 5.8.0 b10. University of Oregon, Eugene, Oregon.

When are we issuing referrals?

May, S., Ard, W., Todd, A., Horner, R., Glasgow, A., Sugai, G., & Sprague, J. (2017) School-wide Information System 5.8.0 b10. University of Oregon, Eugene, Oregon.

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Who is receiving referrals?

May, S., Ard, W., Todd, A., Horner, R., Glasgow, A., Sugai, G., & Sprague, J. (2017) School-wide Information System 5.8.0 b10. University of Oregon, Eugene, Oregon.

Who is receiving referrals?

May, S., Ard, W., Todd, A., Horner, R., Glasgow, A., Sugai, G., & Sprague, J. (2017) School-wide Information System 5.8.0 b10. University of Oregon, Eugene, Oregon.

Checking the Vital Signs

May, S., Ard, W., Todd, A., Horner, R., Glasgow, A., Sugai, G., & Sprague, J. (2017) School-wide Information System 5.8.0 b10. University of Oregon, Eugene, Oregon.

Are referral rates equitable?

May, S., Ard, W., Todd, A., Horner, R., Glasgow, A., Sugai, G., & Sprague, J. (2017) School-wide Information System 5.8.0 b10. University of Oregon, Eugene, Oregon.

Are racial/ethnic groups referred at the same rate?

Out of all the referrals issued, do subgroups receive referrals

proportionate to their size in the population?

Are referral rates equitable?

May, S., Ard, W., Todd, A., Horner, R., Glasgow, A., Sugai, G., & Sprague, J. (2017) School-wide Information System 5.8.0 b10. University of Oregon, Eugene, Oregon.

Of the students with referrals, do subgroups receive referrals

proportionate to their size in the population?

How much more/less likely is a subgroup to receive referrals in

comparison to others?

Drill Down for Deeper Analysis

What problem behaviors were

referred between

10:30a and 1:30p in March?

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Drill Down for Deeper Analysis

Where were referrals issued

between 10:30a and

1:30p in March?

Drill Down for Deeper Analysis

Were referral rates

equitable for the hallway between

10:30a and 1:30p in March?

Drill Down for Deeper Analysis

Why do we perceive students

engaged in referral

behaviors in the hallway between

10:30a and 1:30p in March?

What data can your organization access to

problem solve with precision?

Meeting Foundations

System for detailed meeting minutes

Formal roles with substitutes:• Facilitator• Data Analyst• Minutes Manager

Expectations for before, during, and after the meeting

Accessible/Usable data

Live display of minutes and data

Procedure for monitoring meeting fidelity

System for detailed meeting minutes

Todd, A. W., Newton, J. S., Algozzine, K., Horner, R. H., Algozzine, B., Cusumano, D. L., & Preston, A. I. (2013). The Team Initiated Problem Solving (TIPS II) Training Manual. Eugene, OR: University of Oregon, Educational and Community Supports.

Solution Components

What are the Action Steps?

Who is Responsible? By When? How will Fidelity

be Measured? Notes/Updates

Prevention

Teaching

Recognition

Extinction

Corrective Consequences

What data?Who is responsible for gathering the

data?

When/How often will data be gathered?

Where will data be shared?

Who will see the data?

Data Collection

Precise Problem Statement: Goal:

Solution Development

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Sustainability

• Enablers• Administrative support• Staff buy-in• Fidelity• Data

• Barriers• Resources• Turn-over• Staff buy-in• Fidelity

McIntosh, K., Predy, L. K., Upreti, G., Hume, A. E., Turri, M. G., & Mathews, S. (2014). Perceptions of contextual features related to implementation and sustainability of school-wide positive behaviour support. Journal of Positive Behavior Interventions, 16, 29-41.

McIntosh, K., Mercer, S. H., Hume, A. E., Frank, J. L., Turri, M. G., & Mathews, S. (2013). Factors related to sustained implementation of School-wide Positive Behavior Support. Exceptional Children, 79, 293-311.

Schools benefit from PBIS teams with efficient systems and regular use of data.

Data Storytelling

Enga

ge

Data

Data

Data

Narrative Narrative

Narrative

Visuals

Visuals

Visuals

Dykes, B. (2016, March 31). Data Storytelling: The Essential Data Science Skill Everyone Needs. Retrieved from https://www.forbes.com/sites/brentdykes/2016/03/31/data-storytelling-the-essential-data-science-skill-everyone-needs/#11ed323a52ad

How is your organization making decisions

at Tier I?

Leverage Your Learning

What to you know?

What do you want to learn?

What did you

learn?

What will you do

with your learning?

50 Shadesof Green:Continuous Quality Improvement for Tier I with SWIS

Kelsey MorrisUniversity of Missouri

Data Integration

https://pbisapps.wistia.com/medias/92yddhh6ql