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Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin PBIS Network (CFDA #84.027) acknowledges the support of the Wisconsin Department of Public Instruction in the development of this PowerPoint and for the continued support of this federally-funded grant program. There are no copyright restrictions on this document; however, please credit the Wisconsin DPI and support of federal funds when copying all or part of this material

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Page 1: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Data Driven Decision Making Across All Content Areas

WI PBIS NetworkSummer Leadership Conference

Rachel SaladisLynn Johnson

The Wisconsin RtI Center/Wisconsin PBIS Network (CFDA #84.027) acknowledges the support of the Wisconsin Department of Public Instruction in the development of this PowerPoint and for the continued support of this federally-funded grant program. There are no copyright restrictions on this document; however, please credit the Wisconsin DPI and support of federal funds when copying all or part of this material

Page 2: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Agenda

• Introduce RtI Center data tools• Analyze data • Write precision statements

Page 3: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Who is here today?

Classroom Teachers: General Special EducationAdministratorsInternal CoachesAcademic Support

School CounselorsExternal CoachesSchool PsychologistsParentsOther

Page 4: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Wisconsin RtI Center

Our mission is to support schools through the phases and sustainability of their RtI system implementation.

The core reason that the Wisconsin RtI Center exists is to develop, coordinate and provide high-quality professional development and technical assistance…as well as to gather, analyze and disseminate RtI implementation data to enhance the support of schools’ implementation.

Page 5: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Principles for RtI in Wisconsin1. RtI is for ALL children and ALL educators.

2. RtI must support and provide value to effective practices.

3. Success for RtI lies within the classroom through collaboration.

4. RtI applies to both academics and behavior.

5. RtI supports and provides value to the use of multiple assessments to inform instructional practices.

6. RtI is something you do and not necessarily something you buy.

7. RtI emerges from and supports research and evidence based practice.

Page 6: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Defining Your Multi-Level System of Support

What do we want all students to know and learn?

What common instructional programs & practices will we use? Are we using them with integrity?

How will we know if they’ve learned it?

Are additional supports being provided with integrity?What will we do if they have not or already learned it?

How will we know if additional supports are effective?

Adapted from: Rick DuFour of Solution Tree

Page 7: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Defining Your Multi-Level System of Support

What do we want all students to know and learn?

What common instructional programs & practices will we use? Are we using them with integrity?

How will we know if they’ve learned it?

Are additional supports being provided with integrity?What will we do if they have not or already learned it?

How will we know if additional supports are effective?

Adapted from: Rick DuFour of Solution Tree

Page 8: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Intensive Level / Tier 31-5%

Selected Level / Tier 25-15%

Universal / Tier 180-90%

Page 9: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

RtI in Action>> Implementation Tools>> Automated Tracking Tools

Collaboration: Universal

Month of September #Students

# of Students Meeting Screening Benchmark in Reading 259

# of Students Scoring Below Benchmark on Reading Screening 103

# of Students Scoring Significantly Below on Reading Screening 38

# of Students Receiving Tier 1/Universal Reading Intervention this Month 280

# of Students Receiving Tier 1/Universal and Tier 2/Selected Reading Interventions this Month

85

# of Students Receiving Tier 1/Universal / Tier 2/Selected and Tier 3/Intensive Reading Interventions this Month

35

Instructions: Fill in cells that are shaded blue. Note: For months with no new Reading/Math screening results, just carry results over from previous screening.

Page 10: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

www.wisconsinpbisnetwork.org

Page 11: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Graph Sample

Page 12: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

• ALL students should have access to solid Tier 1/universal level instruction.

• What percent of ALL students are successful in Tier 1/universal? How data is disaggregated?

• Does data indicate that your system is healthy?

• Does data indicate a population is being underserved?

Analyzing Process for Tier 1/Universal

Page 13: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Using data to identify concernsWhat data to monitor

• Attendance, grades, behavior referrals• Screening/achievement data

What question to answerWhat priority areas do we need to celebrate and address?

What questions to ask of Level, Trend, PeaksHow does our data compare with last year?How does our data compare with national/regional norms?How does our data compare with our preferred/expected status?

If a problem is identified, then askWhat additional data do we need to make an informed decision?

Page 14: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Precision Problem Statements

• What is the problem?• Where/when is the problem evident?• Who is involved?• Why is the problem sustaining?

Page 15: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Behavioral Precision Problem Statement

• In the month of November, only 60 % of our population responded to our Tier 1 behavioral instruction ( received 0-1 ODR). Most reported behaviors are occurring on the playground, during the lunch break, across all grade levels. There are large group of playground supervisors that may not have been part of the universal Kick Off on the playground. Additionally, the snow on the ground means that there are some additional playground rules that need to be taught universally.

Page 16: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Fall Universal Reading Screener400 Sixth Grade Students

% / # students

% of Students Meeting Reading Benchmark

65%/259

Target Goal: 80%

% of Students Below Reading Benchmark

25%/103

Target Goal:15 %

% of Students Significantly Below Reading Benchmark

10%/38

Target Goal: 5%

Precision statement: Data from the 2013 fall 6th grade reading screener indicates that 65% of the sixth grade students are meeting the fall reading benchmark, 25% of the sixth grade students are below the fall reading benchmark and 10% of the 6th grade students are significantly below the fall reading benchmark. The student outcome data is below the expected goal of at least 80% of sixth grade students meeting the benchmark by a difference of 15%.

6th grade teachers are inconsistent in what they provide at the core. The new district reading curriculum is in classrooms, but teachers have not had the opportunity to receive PD on this curriculum.

Academic Precision Problem Statement

65%

25%

10 %

Page 17: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Precision statement: Data from the 2013 fall 6th grade reading screener indicates that 65% of the sixth grade students are meeting the fall reading benchmark, 25% of the sixth grade students are below the fall reading benchmark and 10% of the 6th grade students are significantly below the fall reading benchmark. The student outcome data is below the expected goal of at least 80% of sixth grade students meeting the benchmark by a difference of 15%.

6th grade teachers are inconsistent in what they provide at the core. The new district reading curriculum is in classrooms, but teachers have not had the opportunity to receive PD on this curriculum.

Page 18: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Defining Your Multi-Level System of Support

What do we want all students to know and learn?

What common instructional programs & practices will we use? Are we using them with integrity?

How will we know if they’ve learned it?

Are additional supports being provided with integrity?What will we do if they have not or already learned it?

How will we know if additional supports are effective?

Adapted from: Rick DuFour of Solution Tree

Page 19: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Tier 2/3 Automated Tracking Tool

Page 20: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

www.wisconsinrticenter.org(Right Side) Click: Implementing RtI

(Left Side): Under RtI in Action Click: Implementation Tools

Under the Heading: Automated Tracking Tools Click: Academic Selected and Intensive (Tier 2/3) Intervention Tracking Tool

Page 21: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Academic Selected and Intensive (Tier 2/3) Intervention Tracking Tool: Graph Sample

% of students responding to the intervention

Page 22: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Analyzing Tier 2/Selected & Tier 3/ Intensive Levels of Support

• What % of students participated in tier 2/selected levels of support? Tier 3/intensive?

• What % of students responded to those interventions?

• Are at least 70-80% of students involved in intervention responding? – No -Address system of intervention– Yes – what do you do for those students who are

not responding• What are the most common areas of need?

Page 23: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

We want to go from this…

“CICO is not working.”

Precision Statement: 50% of students involved in CICO are not making progress. Most of these students are in 8th grade. 8th grade teachers consistently write negative comments on the DPR.

…to this

• Are our data rules identifying the correct students?

• Is our full staff oriented in the CICO intervention and using it appropriately?

• Is our location easily accessible, and our greeter always positive?

• Are there patterns in the data? Grade level, day of the week, time of day?

• Are subgroups of students over-represented?

Page 24: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

We want to go from this…

“Some of our interventions do not seem to be effective .”

Based on the Academic Selected and Intensive Tracking Tool, data indicates 47% of students receiving Comprehension interventions at the Selected level and 58% at the Intensive level are not responding and at the current rate will not be expected to meet end of year grade-level expectations. 33% of students receiving a Selected Vocabulary intervention are not responding and at the current rate will not be expected to meet end of the year grade-level expectations.

We have not finalized our formal intervention time so there is an inconsistent time frame for interventions. Students seem to be confused about when to come, as do teachers. Attendance has been sporadic at best. We have not set up a consistent fidelity check process for our interventions. The progress monitoring data collection process is not consistent among teachers.

…to this

.

• Is the intervention being provided with fidelity?

• Are the students attending consistently? Why not?

• Is the intervention a good match for student need?

• Are any sub-groups in the population over represented?

Page 25: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Your Turn

• Access data tools• Answer questions from case study• Write precision statement

Page 26: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin
Page 27: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Outcome

• Introduce RtI Center data tools• Analyze data • Write precision statements

Page 28: Data Driven Decision Making Across All Content Areas WI PBIS Network Summer Leadership Conference Rachel Saladis Lynn Johnson The Wisconsin RtI Center/Wisconsin

Lynn Johnson

[email protected]

Thank You!

RachelSaladis

[email protected]