spring data review workday school leadership teams

Spring Data Review WorkdaySchool Leadership Teams

May 20 & 21, 2014

AcknowledgementsThe material for this training day was developed by Ingham ISD:• Theron Blakeslee, John Endahl, Melanie Kahler, Matt Phillips, Jeanne

Tomlinson, Kelly Trout, Nate Stevenson Laura Colligan and Mary Jo Wegenke

Content based on the work of…• MiBLSi project•George Batsch, University of South Florida•Robert Balfanz, Everyone Graduates Center and

Johns Hopkins University•Roland Good and Rob Horner, University of Oregon•George Sugai, University of Connecticut•Joe Torgesen, Florida Center for Reading Research•Dawn Miller, Shawnee Mission School District, Kansas

Learning Targets

Participants will be able to: • Analyze process data and outcome data to identify

academic and/or behavior areas in need of improvement

• Make connections between process and outcome data and its impact on student achievement

• Identify an academic and/or behavioral priority based upon the data analysis and use the Continuous Improvement Process to address the priority

Where to access materials for today:1. POMPOMS!The documents we are using today are on flash drives attached to ISD pompoms.

2. MTSS Implementers Website

http://mtss-implementers.wiki.inghamisd.org Building Data Review page

OR

Materials you will need today• Data Review Workbook(MTSS Wiki & hardcopy)• Problem Solving Guide (MTSS Wiki & hardcopy)• Worked Example Problem Solving Guide (MTSS Wiki & hardcopy)• Log-in Information: Illuminate, BAA, pbisapps.org, and SWIS• Process Data: PETR/SWEPT, PET-M, BSA, BoQ, SAS

Cute as they are, please don’t take them home!

Agenda

9:00-9:05 Welcome

9:05-9:30 Review modifications to Data Toolkit and Problem Solving GuideIlluminateData Analysis

9:30-11:45 Team Time to work through the School Improvement Continuous Improvement Cycle

11:45-12:00 District Check-in: Celebrations and Areas to Grow

12:00-1:00 Lunch

1:00-3:15 Continue Team Time

3:15-3:30 District Check-in: Celebrations and Areas to GrowSession Evaluation

Data Review Workday Working Agreements

Participants Work through the Continuous Improvement Process using current data to identify school-wide and grade level needs and create an action plan to address area(s) of concern.

Administrator Assist staff to make instructional decisions based on data Assist with resource allocation so action items can be

implemented

Ingham ISD Provide tools to assist with data analysis Provide guided facilitation for problem solving using the

Continuous Improvement Cycle

Role of The School Leadership Team• Acts on school-wide data (Process Data and Student

Outcomes) on a regular basis

• Sends content area specific information to the appropriate staff to address during content area/grade level meetings

• Provides all stakeholders with an overview of the data and areas for celebration and areas targeted for growth. This includes teachers, support staff, volunteers and parents.

• Utilizes work groups to address relevant needs

• Following through on action plans and updating progress along the way

• Sends school-wide information to district level staff

New and Improved Materials

• Page 4 in the Data Toolkit• Trend Data Columns on the School-wide Literacy and

Mathematics Overview Forms• Vocabulary in the Problem Solving Guide aligned with

School Improvement Process• Spring to Fall Transition Action Plan

Evaluating Previous Plan New

Page 4 in Data Tool Kit

Schoolwide Overview- Reading

Schoolwide Overview-Mathematics

Problem Solving Guide

Data-based Problem Solving

Connection to School Improvement

Scheduling of Action Items

First Few Days of School

Schoolwide Overview- Academics

Where to find the academic data! Record information on the Illuminate note taking form.

Data Analysis…Something to think about

What …

Assumptions do we bring to this discussion?

Important points seem to pop out?

Patterns, categories, or trends are emerging?

Seems to be surprising or unexpected?

Additional data sources do we need to explore?

Inferences, explanations, or conclusions might we draw?

Solutions might we explore as a result of our conclusions?

got data? Now What?, Solution Tree Press, 2012

5 Reasons Why Problem Exists

• got data? Now What?, Solution Tree Press, 2012

Criteria for Pursuing Worthy Problems

• An issue recurs with frequency, year after year.• An issue is pervasive across multiple grade

levels, student groups or school settings.• An issue consumes high levels of energy, time

and resources.• Even after an improvement bump, performance

plateaus and subsequent data flatline.

• got data? Now What?, Solution Tree Press, 2012

Remember…

• The Building Leadership Team…• Does not have to solve every problem• Needs to study building data to determine

school-wide and grade-level priorities• Will identify the appropriate individual(s) who

will address these needs (e.g., which grade-level teams need to address the identified needs)

Team Time• Review/update previous action plan. Page 4 in Data Toolkit

• Use the School-wide overview sheets for problem(s) Identification

• Prioritize “Problems” • Identify a problem; complete Continuous Improvement Process process and create an action plan.

• Move on to second (and third) problem, if able

• Identify building Glows and Grows

You do!

Interpreting BSA Data

Schoolwide Overview- Behavior

Process Data - Behavior

Benchmarks of Quality (BoQ)

• Completed annually by school leadership teams

• Tier 1 SWPBIS implementation fidelity check

• 53 benchmarks across 10 critical elements of implementation.

• Identifies areas of strength and need; informs problem analysis and action planning.

• 70% Implementation Goal

Self-Assessment Survey (SAS)

• Completed annually by building staff • Fidelity check of PBIS implementation

across (a) school wide, (b) non-classroom, (c) classroom, and (d) individual students

• Seven key elements of the Implementation Subsystems

• Informs of areas of strength and need, including communication between leadership team and staff

• 70% Implementation Goal

pbisapps.org

Process Data - Behavior

Schoolwide Overview- Behavior

Outcome Data - Behavior

Outcome Data - Behavior

Early Warning Signs

Early Warning Signs (EWS)• Routinely available data; available early in the school year• Better predictor than background characteristics• Cut points selected to balance yield and accuracy.• Helps target interventions• Informs of patterns and trends

Early Warning Signs (EWS)

ATTENDANCE: Missing more than 10% of instructional time

BEHAVIOR: Suspensions (ISS or OSS); Minor or Major ODRs

• ISS or OSS: 6 hours of academic instruction lost per day• ODR: 20 minutes of academic instruction lost for student per referral

COURSE PERFORMANCE: Course failures, grade point average; credit accrual

• Combinations of academic indicators can reduce graduation likelihood to 55%

EWS Outcome Data - Building Level

ATTENDANCE: > 90% missing more than 10% of instructional time

• State of Ohio retrospective analysis of top/bottom 10% academic outcomes

• Balances yield vs. accuracy

BEHAVIOR: > 80% with 0 Suspensions (ISS or OSS)• “High Quality Instruction” research• MTSS Targeted Intervention

COURSE PERFORMANCE: ACT-Explore Data• Course Failures (MTSS Model of 80% corrected for accuracy to 85-90%)• Credit Accrual is building-specific • Combinations of academic indicators can reduce graduation likelihood to 55%

Schoolwide Overview – BehaviorWorked Example

Process Data SnapshotsACADEMICS & BEHAVIOR

PET-M SNAPSHOTS

BSA: BUILDING SELF-ASSESSMENT

Scale: Not Started (N) — In Progress (I) —

Achieved (A) — Maintaining (M) —

What Does BSA

Data Tell you?

Process Data SnapshotsBEHAVIOR

Benchmarks of Quality (BoQ)

• Tier 1 SWPBIS implementation fidelity check

• 53 benchmarks across 10 critical elements:

• Identifies areas of strength and need to inform action plans

• Completed annually by school leadership teams

Self-Assessment Survey (SAS)

• Completed annually by building staff • Fidelity check of PBIS implementation

across (a) schoolwide, (b) non-classroom, (c) classroom, and (d) individual students

• Seven key elements of the Implementation Subsystems

• Informs of areas of strength and need, including communication

Process Data SnapshotsBEHAVIOR

Benchmarks of Quality (BoQ)

• Tier 1 SWPBIS implementation fidelity check

• 53 benchmarks across 10 critical elements:

• Identifies areas of strength and need to inform action plans

• Completed annually by school leadership teams

Self-Assessment Survey (SAS)

• Completed annually by building staff • Fidelity check of PBIS implementation

across (a) schoolwide, (b) non-classroom, (c) classroom, and (d) individual students

• Seven key elements of the Implementation Subsystems

• Informs of areas of strength and need, including communication

Process Data Snapshots: PBIS Benchmarks of Quality (BoQ)

Process Data Snapshots: PBIS Self-Assessment Survey (SAS)

While summary data from the SAS provides a general sense of a building’s PBIS systems, more focused analysis can inform a team of the most vital and influential next steps.

Low Implementation

Status

HighStaff

Priority

PBIS Subsystem

TargetedImplementation

Supports

Process Data Snapshots: PBIS Self-Assessment Survey (SAS)

Problem Solving Guide: Step 1

Determine your (first) problem to be addressed today based one what you’ve derived from:• Previous SIP• Outcome Data• Process Data and

Process Data Snapshots

Problem Solving Guide: Step 2

Complete a Problem Analysis: Hypothesize what may be contributing to the problem

Again, your data and the Snapshots can inform this discussion.

Problem Solving Guide: Worked Example

Problem Solving Guide: Worked Example

Problem Solving Guide: Worked Example

Problem Solving Guide: Worked Example

Problem Solving Guide

Data-based Problem Solving

Problem Solving Guide

Please take a moment to complete the Evaluation Survey:

https://www.surveymonkey.com/s/elementarydays

THANK YOU!