Using Data for Continuous School Improvement 2014 Fall CIP Workshops

4 Types of Data Type: Perceptions How do we do business? Type: Student Learning How are our students doing? Type: School Processes What are our processes? Type: Demographic Who are we? Reference to Day 1 – Activity identifying types of data available in schools/districts.

Goal 2 SLDS Grant Provide a statewide system of professional development training for data analysis that reaches every district. Tiered Training Delivery ✔ Statewide Data Cadre ✔ ESUs and NDE Staff ✔ School District Leadership School District Staff

Statewide Data Cadre NDE ESUs/ESUCC Higher Ed Rhonda Jindra – ESU 1 Mike Danahy – ESU 2 Marilou Jasnoch – ESU 3 Annette Weise – ESU 5 Lenny VerMaas – ESU 6 Denise O’Brien – ESU 10 Melissa Engel – ESU 16 Jeff McQuistan – ESU 17 NDE Data, Research, Evaluation Russ Masco Matt Heusman Rachael LaBounty Kathy Vetter Assessment John Moon Federal Programs Beth Zillig Special Education Teresa Coontz Curriculum Cory Epler Tricia Parker-Siemers Accreditation and School Improvement Don Loseke Sue Anderson Higher Ed Dick Meyer – UNK

Nebraska Data Literacies What do the data show? Data Comprehension Why might this be? Interpretation Did our response produce results? Evaluation How should we respond? Data Use Developed by the Data Cadre Standards document to support the standardization of expected outcomes 4-question framework

Data Literacies Format 1. a. i. Concept Indicators Literacy

Data Literacies http://www.education.ne.gov/DataServices/SLDS_Grant/Data_Literacies.pdf

Data Use Curriculum Nebraska Data Literacies

AGENDA WHY data analysis/continuous school improvement? WHAT process/data do we need to engage for school improvement? HOW do we involve all staff in the process of school improvement? Tools and resources…

Data Analysis for Continuous School Improvement Bernhardt, V.L. (2013) Data Analysis for Continuous School Improvement (Third Edition) New York, NY: Routledge

BACKGROUND Education for the Future – Non-Profit Initiative Victoria L. Bernhardt, Exec Director California State University, Chico Our Mission Funded by contracts. 17 Books, Conferences, Institutes, Workshop. Manage long-term implementation contracts. Monthly online meeting series.

Data Analysis for Continuous School Improvement, Third Edition, ……is about inspiring schools and districts to commit to a continuous school improvement framework that will result in improving teaching for every teacher, and improving learning for every student, in one year, through the comprehensive use of data. It is about providing a new definition of improvement, away from compliance, toward a commitment to excellence. P. 5

HOW MUCH TIME DOES IT TAKE? It will take one school year for a school staff to do all the work described in this book. If parts of the work are already done, a staff might still want to spread out the work throughout the year. P. 10

WHY Data Analysis/Continuous and School Improvement? Before

What would it take to ensure student learning at every grade level, in every subject area, and with every student group? In your team, answer and discuss this question. Make a list.

WHAT IS THE HARDEST PART FROM YOUR PERSPECTIVE? Beliefs that all children can learn. Schools honestly reviewing their data. One vision. One plan to implement the vision. Curriculum, instructional strategies, and assessments clear and aligned to standards. Staff collaboration and use of data related to standards implementation. Staff professional development to work differently. Rethinking current structures to avoid add-ons. Dick? Kate or Denise Table discussion Share out

THINGS WE KNOW ABOUT DATA USE For data to be used to impact classroom instruction, there must be structures in place, to— implement a shared schoolwide vision. help staff review data and discuss improving processes. have regular, honest collaborations that cause learning. Kate or Denise

Mission Vision Continuous Improvement Cycle

VISION defines the desired or intended future state of an organization or enterprise in terms of its fundamental objectives relative to key, core areas (curriculum, inst, assess, environ).

Curriculum— What we teach. Instruction— How we teach the curriculum. VISION Curriculum— What we teach. Instruction— How we teach the curriculum. Assessment— How we assess learning. Environment— How each person treats every other person.

MISSION succinctly defines the fundamental purpose of an organization or an enterprise, describing why they exist.

FOCUSED ACTS OF IMPROVEMENT The vision of the school which is created from what we expect students to know and be able to do, values and beliefs of the staff, and the purpose and mission of the school, must be at the center of everything that the school does. When the vision is shared and clear, everything that is planned is planned to implement the vision. Everything implemented in the school must be about the vision. Everything is evaluated in terms of how it will get the school to its vision, and everything is improved to better implement the vision. This will lead to Focused Acts of Improvement.

Data Analysis for Continuous School Improvement Is About What You Are Evaluating Yourself Against

“In times of change, learners inherit the earth, while the learned find themselves beautifully equipped to deal with a world that no longer exists.” - Eric Hoffer

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Page 14 Data Literacy 1 What do the data show? Where are we now? How did we get to where we are? Where do we want to be? How are we going to get to where we want to be? Is what we are doing making a difference? Data Literacy 1 What do the data show? Data Literacy 2 Why might that be? Data Literacy 3 How should we respond? Data Literacy 4 Did our response produce results? Page 14 Data Literacy 2 Why might that be?

Data Literacy 1 What do the data show?

Data Literacy 2 Why might that be?

Data Literacy 2 Why might that be?

Data Literacy 3 How should we respond?

Data Literacy 4 Did our response produce results?

IMPORTANT NOTES Continuous School Improvement describes the work that schools do, linking the essential elements Continuous School Improvement is a process of evidence, engagement, and artifacts

A PROCESS OF EVIDENCE, ENGAGEMENT, AND ARTIFACTS Data to inform and drive a logical progression of next steps. Engagement: Bringing staff together to inform improvement through the use of data, moving from personality driven to systemic and systematic. Artifacts: The documentation of your improvement efforts.

RANDOM ACTS OF IMPROVEMENT Data analysis is only one piece of the puzzle in continuous school improvement. Without one critical piece of information, a target, our results might resemble “Random Acts of Improvement.”

Page 14 Data Literacy 1 What do the data show? Where are we now? How did we get to where we are? Where do we want to be? How are we going to get to where we want to be? Is what we are doing making a difference? Data Literacy 1 What do the data show? Data Literacy 2 Why might that be? Data Literacy 3 How should we respond? Data Literacy 4 Did our response produce results? Page 14 Data Literacy 2 Why might that be?

FOCUSED ACTS OF IMPROVEMENT The vision of the school which is created from what we expect students to know and be able to do, values and beliefs of the staff, and the purpose and mission of the school, must be at the center of everything that the school does. When the vision is shared and clear, everything that is planned is planned to implement the vision. Everything implemented in the school must be about the vision. Everything is evaluated in terms of how it will get the school to its vision, and everything is improved to better implement the vision. This will lead to Focused Acts of Improvement.

COMPLIANCE VERSUS COMMITMENT Page 4 Bernhardt, V.L. (2013). Data Analysis for Continuous School Improvement. Third Edition. New York, NY: Routledge. Page 4. Reproducible.

Evidence

Data Literacy 1 What do the data show?

“Study the past if you would like to define the future.” - Confucius

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DEMOGRAPHICS ARE IMPORTANT DATA Describe the context of the school and school district. Help us understand all other numbers. Are used for disaggregating other types of data. Describe our system and leadership.

Attendance (Absences) Expulsions Suspensions DEMOGRAPHICS Enrollment Gender Ethnicity / Race Attendance (Absences) Expulsions Suspensions Note: Tell audience to bring yoga clothes tomorrow!

DEMOGRAPHICS (Continued) Language Proficiency Indicators of Poverty Special Needs/Exceptionality IEP (Yes/No) Drop-Out/Graduation Rates Program Enrollment Note: Tell audience to bring yoga clothes tomorrow!

WHAT STUDENT DEMOGRAPHIC DATA ELEMENTS CHANGE WHEN LEADERSHIP CHANGES? Enrollment Gender Ethnicity/Race Attendance (Absences) Expulsions Suspensions Language Proficiency Indicators of Poverty Special Needs/ Exceptionality IEP (Yes/No) Drop-Out / Graduation Rates Program Enrollment

School and Teaching Assignment Qualifications STAFF DEMOGRAPHICS School and Teaching Assignment Qualifications Years of Teaching/At this School Gender, Ethnicity Additional Professional Development Note: Tell audience to bring yoga clothes tomorrow!

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PERCEPTIONS ARE IMPORTANT DATA Help us understand what students, staff, and parents are perceiving about the learning environment. We cannot act different from what we value, believe, perceive. Note: Tell audience to bring yoga clothes tomorrow!

Student, Staff, Parent, Alumni Questionnaires Observations PERCEPTIONS INCLUDE Student, Staff, Parent, Alumni Questionnaires Observations Focus Groups Note: Tell audience to bring yoga clothes tomorrow!

PERCEPTIONS What do you suppose students say is the #1 “thing” that has to be in place in order for them to learn? Note: Tell audience to bring yoga clothes tomorrow!

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STUDENT LEARNING ARE IMPORTANT DATA Know what students are learning. Understand what we are teaching. Determine which students need extra help.

STUDENT LEARNING DATA INCLUDE Diagnostic Assessments (Universal Screeners) Classroom Assessments Formative Assessments (Progress Monitoring) Summative Assessments (High Stakes Tests, End of Course) Defined: Pages 54-57

STUDENT LEARNING ARE IMPORTANT DATA What happens when learning organizations react solely to the measures used for compliance and accountability?

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SCHOOL PROCESSES Schools are perfectly designed to get the results they are getting now. If schools want different results, they must measure and then change their processes to create the results they really want.

SCHOOL PROCESSES Processes include… Actions, changes, functions that bring about a desired result Curriculum, instructional strategies, assessment, programs, interventions … The way we work.

SCHOOL PROCESSES ARE IMPORTANT DATA Tell us about the way we work. Tell us how we get the results we are getting. Help us know if we have instructional coherence.

SCHOOL PROCESSES DEFINITIONS INSTRUCTIONAL: The techniques and strategies that teachers use in the learning environment. ORGANIZATIONAL: Those structures the school puts in place to implement the vision.

SCHOOL PROCESSES DEFINITIONS ADMINISTRATIVE: Elements about schooling that we count, such as class sizes. CONTINUOUS SCHOOL IMPROVEMENT: The structures and elements that help schools continuously improve their systems. PROGRAMS: Programs are planned series of activities and processes, with specific goals.

Data Profile Demographic Data ENGAGEMENT Appendix F Page 265-296 Data Profile Demographic Data

Data Literacy 1 What do the data show?

STUDY QUESTIONS Demographic Data Strengths Challenges Implications for the continuous school improvement plan. STUDY QUESTIONS — DEMOGRAPHIC DATA Page 348 Other data . . .

DEFINITIONS STRENGTHS: Something positive that can be seen in the data. Often leverage for improving a challenge. CHALLENGES: Data that imply something might need attention, a potential undesirable result, or something out of a school’s control. 81

DEFINITIONS IMPLICATIONS FOR THE SCHOOL IMPROVEMENT PLAN are placeholders until all the data are analyzed. Implications are thoughts to not forget to address in the school improvement plan. Implications most often result from CHALLENGES. 82

OTHER DEMOGRAPHICS List other demographic data you would like to have in your data profile. Make sure your data profile describes your uniqueness and provides the information you need to monitor your system.

LETS SEE WHAT IT LOOKS LIKE Pages 265-334

DEMOGRAPHIC DATA PP 265-296 Individually review the data to identify strengths, challenges, implications for planning, and further data needed. Write your findings on the Demographic Data handout.

WHAT ARE THE BENEFITS OF THIS APPROACH? ANALYZING THE DATA Answer Questions— Strengths, Challenges, Implications, Other Demographic Data. Independently Merge to Whole Group Write combined findings on Poster Paper WHAT ARE THE BENEFITS OF THIS APPROACH?

CASE STUDY Demographic Data DEMOGRAPHIC DATA PP 265-296 CASE STUDY Demographic Data 5 Divisions Enrollment: Pages 265-273 Mobility: P. 273, Attendance: P. 274, ELL: P. 275, & FRL: P. 276 Special Education: P. 277-284 Retention: PP. 276-277, Pre-Referral Team: PP. 285-286, Staff: Pages 294-296 Behavior: Pages 287-293

NEXT STEPS Work with your ESU Staff Developer to Engage with your district/school data Analyze demographic, perceptual, student learning, and school process data Understand the common and systemic implications of strengths and challenges from all four data types Solve challenges using data

DATA INVENTORIES - APPENDIX B Pages 205-217

Aggregating Implications for Planning Across All Areas of Data Next Steps…. Aggregating Implications for Planning Across All Areas of Data

After analyzing all four types of data MERGE STRENGTHS, CHALLENGES, AND IMPLICATIONS FOR THE SCHOOL IMPROVEMENT PLAN After analyzing all four types of data Review implications across data. Look for commonalities. Create an aggregated list of implications for the school improvement plan.

AGGREGATING IMPLICATIONS Intersections Presentation and interpretation/en gagement as a function of analysis. Page 17

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FACILITATION GUIDE Pages 343-353

“Education is learning what you didn’t even know you didn’t know.” - Daniel J. Boorstin

Pages 105-108 CONTRIBUTING CAUSES: Underlying cause or causes of positive or negative results.

PROBLEM SOLVING CYCLE EXAMPLE Page 106-108 PROBLEM SOLVING CYCLE EXAMPLE

Not enough students are proficient in Mathematics. IDENTIFY THE PROBLEM Not enough students are proficient in Mathematics.

THE PROBLEM-SOLVING CYCLE Example Hunches/Hypotheses Page 106

THE PROBLEM-SOLVING CYCLE Example Hunches/Hypotheses Page 106

THE PROBLEM-SOLVING CYCLE What questions do you need to answer to know more about the problem and what data do you need to gather?

THE PROBLEM-SOLVING CYCLE Example Questions/Data Needed Page 107

THE PROBLEM-SOLVING CYCLE 1. Identify a problem/ undesirable result. 2. List 20 reasons this problem exists (from the perspective of your staff).

THE PROBLEM-SOLVING CYCLE 3. Determine what questions you need to answer with data. 4. What data do you need to gather to answer the questions?

Please record on chart paper. THE PROBLEM-SOLVING CYCLE Please record on chart paper. P. 357 P. 358

PROBLEM SOLVING CYCLE Time savings. Evidence: Automatically end up at the 4 circles. Focus on the process(es) at the root. Engagement: Makes big problems manageable. Time savings. Key in making the move from personality driven to systemic and systematic.

FACILITATION GUIDE Pages 354-358

Page 14 Data Literacy 1 What do the data show? Where are we now? How did we get to where we are? Where do we want to be? How are we going to get to where we want to be? Is what we are doing making a difference? Data Literacy 1 What do the data show? Data Literacy 2 Why might that be? Data Literacy 3 How should we respond? Data Literacy 4 Did our response produce results? Page 14 Data Literacy 2 Why might that be?

Data Literacy 1 What do the data show?

Perceptual and Demographic Resources available through NDE

Perceptual Data Surveys are available for students, parent, staff, for districts/schools that will work with their ESU staff developer to learn how to analyze the perceptual data Districts/schools complete a (revised) form Schools receive links to the surveys Schools and ESU staff developer will receive the perceptual survey data The data belongs to the districts/schools

Perceptual Data Request Form Return to ESU Staff Developer

Perceptual Data Ability to administer surveys will be available in future years as well NDEs capacity to manage the perceptual data surveys is developing

Data Profile - Reports in DRS Profile similar to Bernhardt Appendix F

Continuous Improvement

Data Profile Enrollment example

Data Profile-Enrollment by Ethnicity

Data Profile Ethnicity Not SPED/ SPED Example

Evaluation & Next Steps with your ESU Staff Developer https://www.surveymonkey.com/s/dataliteracy Please complete one survey per district together as a district team

Resources PPT http://www.education.ne.gov/DataServices/SLDS_Grant/Data_Cadre.html