harnessing the power of data: effecting improvement in schools please answer our survey at

Harnessing the Power of Data: Effecting Improvement in Schools

Please answer our survey at

www.zellerandassociates.com/IL-TCE.

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Harnessing the Power of Data: Effecting Improvement in Schools

Dr. Leslie R. WilsonGerry Zeller

February 2008

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Agenda

1. Introductions

2. Protocols

3. Survey Report

4. Illustrative Story

5. The Process

6. Tools

7. Work

8. More Tools

9. Reflection and Evaluation

Protocols for this Academy

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Survey Results

Why are you here? Your School Improvement Involvement Your Expertise

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Know and be able to do

School Improvement = Problem Solving Problem Solving = Process District, School, and Classroom Levels

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Story

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Area of Concern

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Targeted Concern

There were approximately 15 students out of total student population of 1,000 that were dropping out of school when they reached their 16th birthday.

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Generate Hypotheses: Answer the “Why?”

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Hypotheses Generated

Young men leave school. Low income students do not value education. Students who get discipline referrals want out. The lower the GPA, the more likely one is to walk. Parents didn’t finish high school, children won’t. Single parent families and similar find it difficult to

shepherd students through school. These students come to us with poor test scores. These students earn too few credits. These students are frequently tardy or leave early.

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Determine and Collect Needed Data

Gender

SES

Discipline Referrals

GPA

Parental Background

Family Makeup

Entry Test Scores

Credits

Attendance

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Analyze Data

Gender No

SES: No

Discipline Referrals: Yes

GPA: No

Parental Background: No

Family Makeup: No

Entry Test Scores: No

Credits: Yes

Attendance: Yes

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Develop Solution Criteria

1. Diploma/GED (Rigor)

2. On Campus Program (Relationships)

3. Quick Successes (Relevance)

4. Non-traditional School Day (Relevance)

5. In-depth Knowledge of/Caring for Students (Relationships)

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Investigate Solutions

Brainstorm: What ideas do we have? SBR: What does research suggest? Best Practice: What are other schools

doing?

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Select Best Match to Criteria: Late School

Diploma/GED On Campus Program Quick Successes Non-traditional School Day In-depth Knowledge

of/Caring for Students

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Implement Solution

Human Resources• A Multiple Certified Person• U of MO HS Extension Material/Facility Resources• Classroom/Computer Lab Policies/Procedures• Ineligible for Interscholastics• Application and Interview

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Communicate Solution

Constituencies• Formally• Informally

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Monitor Progress

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Monitor Progress

Method• Attendance• Credits• Behavioral Contracts Frequency Responsibility

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(Re)Define Problem

Generate Hypotheses

Collect Needed Data

Analyze Data

Investigate Solutions

Implement Solution

Share with Constituencies

Monitor Progress

School Improvement/Problem Solving Cycle

Develop Solution Criteria

Determine Needed Data

What's Perfect?

Data Confirms Perfection?

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Holcomb, Edie L.

Bernhardt, Victoria

What Does Your DIP/SIP Model Look Like?

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IIRC Access e-Plan Review District Data

State Report Card Special Education Profile Multiple Measures PISA TIMMS

What's Perfect?

District Improvement

School Improvement

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State Report Card

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Special Educ. Profile

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IIRC Review School Data Top Comparables

CPS School Profile Bernhardt’s Perception Surveys Local School Data

Summative Assessment Data Behavioral Trend Data

What's Perfect?

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Interactive Illinois Report Card: School

Performance Over Time By Grade Level By Subject Area By Cohort

Comparison To Others Scatter Plots Compare Tool

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CPS Profile

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High School “Perfect” Resources

College Board http://www.collegeboard.com/splash

ACT http://www.act.org/

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Do We Have the Whole Picture?

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Generate Hypotheses

Brainstorm (Bias and Consensus) Eighth graders cannot do Math. Eighth grade teachers cannot teach Math. We do not use the appropriate eighth

grade textbook. The test is too hard.

Correlations Steven D. Levitt and Stephen J. Dubner Reading and Writing

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Determine Needed Data

Sources of Data Holcomb, Edie L.: Workbook, p. 5

Bernhardt, Victoria L. Data Analysis for Continuous School Improvement. Larchmont, NY: Eye on Education, 2004.

---. Using data to improve student learning in school districts. Larchmont, NY: Eye on Education, 2006.

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On-line Survey Tools

Survey Monkey

http://www.surveymonkey.com/ Zoomerang

http://info.zoomerang.com/ Profiler Pro

http://www.profilerpro.com/

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Bernhardt Perception SurveysSocial – Emotional Measures

When I am at school, I feel:

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Discipline Referral Tracking System (SIS/PBIS)

Student Infraction Reporter Location Day/Date Time Disposition Etc.

Analyze Data

The Five “W’s”

1. Who’s Learning, Who’s Not?

2. Why?

3. What’s Being Learned, What’s Not?

4. Why?

5. What Are You Going To Do About It?

See, Say, So

What do you SEE in the data? What do you want to SAY about the

data? And SO what’s next?

Dr. Jay Linksman

3 Whats

What? So what? Now what?

Rick Prestley

Your Questions

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The Five “Gets”

1. Get Data

2. Get Them Electronic

3. Get Them Disaggregated

4. Get Them Graphical

5. Get Talking (Bias and Consensus)

Get It Graphical: 1869

Get It Graphical: 2009

http://www.wordle.net/

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SI/PS Tools

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Analysis Tools

Spreadsheets such as MS Excel Databases such as MS Access Inspiration’s InspireData Key Curriculum Press’ Fathom Data Warehouse

See Workbook

Investigate Solutions

S.M.A.R.T. Goals

Specific Measurable Attainable Realistic Timely

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Six Types of Involvement1. Parenting2. Communicating3. Volunteering4. Learning at Home5. Decision Making6. Collaborating with the Community

A Team A Plan

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Bloomington H S Goals

1. Improve test scores for all

2. 80% in all populations in core classes

3. Proportionate representation in all classes and levels

4. 90% of all earn 1 year’s credit in 1 year

As presented June 2008 at the High School Coalition Conference

Classroom Improvement

What's Perfect?

IIRC: Individual Student Data Instructional Lenses

Marzano Bloom IES Practice Guide: Seven Recommendations for

Improving Student Learning Cawelti

Survey of Enacted Curriculum Formative Assessment Data Discipline Referral Tracking System (SIS/PBIS)

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Analyze Data

Interactive Illinois Report Card Individual Student Data

Sorts Individual Comparisons Versus School, District, State By Standard Sets Versus Classmates Disaggregations

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Cawelti’s Research

Cawelti, Gordon. Handbook of Research on Improving Student Achievement (3rd Ed.). Arlington, VA: Educational Research Service, 2004.

Meta-analysis by Subject Area

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SEC: Curriculum, Instruction, and Professional Development

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(Re)Define Problem

Generate Hypotheses

Collect Needed Data

Analyze Data

Investigate Solutions

Implement Solution

Share with Constituencies

Monitor Progress

School Improvement/Problem Solving Cycle

Develop Solution Criteria

Determine Needed Data

What's Perfect?

Data Confirms Perfection?

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In Summary

School Improvement = Problem Solving Problem Solving = Process District, School, and Classroom Levels

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Reflection

Reflect Share Use

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Thank-you

Dr. Leslie R. WilsonWilson Educational Consulting, Inc.drlrwilson@aol.com312.335.9526

Mr. Gerry ZellerZeller and Associates

gzeller@zellerandassociates.com847.828.4606

Zeller and Associates