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Using Data for Continuous
School Improvement
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Goal 2 SLDS GrantProvide a statewide system of professional development training for data analysis that
reaches every district.Tiered Training Delivery
✔
School District Staff
School District Leadership
ESUs and NDE Staff ✔
Statewide Data Cadre ✔
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Statewide Data Cadre• ESUs/ESUCC
– 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
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Nebraska Data Literacies
What do the data show?
DataComprehension
Why might this be?
DataInterpretation
Did our responseproduce results?
Evaluation
How should we respond?
Data Use
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Data Literacies Format
1.
a.
i.
Concept
Indicators
Literacy
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Data Literacieshttp://www.education.ne.gov/DataServices/SLDS_Grant/
Data_Literacies.pdf
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Nebraska Data Literacies and Their Relationship to the
Continuous School Improvement Process
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Nebraska Data Literacies
What do the data show?
DataComprehension
Why might this be?
DataInterpretation
Did our response produce results?
Evaluation
How should we respond?
Data Use
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Data Use Curriculum
Nebraska Data
Literacies
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Bernhardt, V.L. (2013)
Data Analysis for Continuous
School Improvement
(Third Edition)
New York, NY: Routledge
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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 1What do the data show?
Data Literacy 2Why might that be?
Data Literacy 3How should we respond?
Data Literacy 4Did our response produce results?
Data Literacy 2Why might that be?
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FOCUSED ACTS OF IMPROVEMENT
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Data Analysis for Continuous
School Improvement Is About
What You Are Evaluating Yourself
Against
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Data Literacy 1What do the data show?
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Data Literacy 2Why might that be?
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Data Literacy 2Why might that be?
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Data Literacy 3How should we respond?
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Data Literacy 4Did our response produce results?
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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
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A PROCESS OF EVIDENCE, ENGAGEMENT, AND ARTIFACTS
Evidence:
• 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.
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RANDOM ACTS OF IMPROVEMENT
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FOCUSED ACTS OF IMPROVEMENT
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Four Types of Data
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Data Literacy 1What do the data show?
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Demographic Data
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Describe the context of the schooland school district.
Help us understand all other numbers.
Are used for disaggregatingother types of data.
Describe our system and leadership.
DEMOGRAPHICS AREIMPORTANT DATA
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Enrollment
Gender
Ethnicity / Race
Attendance (Absences)
Expulsions
Suspensions
DEMOGRAPHICS
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Language Proficiency
Indicators of Poverty
Special Needs/Exceptionality
IEP (Yes/No)
Drop-Out/Graduation Rates
Program Enrollment
DEMOGRAPHICS (Continued)
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School and Teaching Assignment
Qualifications
Years of Teaching/At this School
Gender, Ethnicity
Additional Professional
Development
STAFF DEMOGRAPHICS
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NDE Data Profile – Reports in DRS
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Data ProfileEnrollment example
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Data Profile-Enrollment by Ethnicity
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Data ProfileEthnicity Not SPED/ SPED Example
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Perceptual Data
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Help us understand whatstudents, staff, and parents are perceiving about the learning environment.
We cannot act differently from what we value, believe, perceive.
PERCEPTIONS AREIMPORTANT DATA
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Student, Staff, Parent,Alumni Questionnaires
Observations
Focus Groups
PERCEPTIONS INCLUDE
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PERCEPTIONS
What do you suppose students
say is the #1 “thing” that has to
be in place in order for them to
learn?
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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
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Perceptual Data Request FormReturn to ESU Staff Developer
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Perceptual Data
• Ability to administer surveys will be available in future years as well
• NDEs capacity to manage the perceptual data surveys is developing
• The data belongs to the districts/schools
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Student Learning Data
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Know what students are learning.
Understand what we are teaching.
Determine which studentsneed extra help.
STUDENT LEARNING AREIMPORTANT DATA
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STUDENT LEARNINGDATA INCLUDE
Diagnostic Assessments(Universal Screeners)
Classroom Assessments
Formative Assessments(Progress Monitoring)
Summative Assessments(High Stakes Tests, End of Course)
Defined:
Pages54-57
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School Process Data
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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
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SCHOOL PROCESSES
Processes include…
Actions, changes, functions that bring about a desired result
Curriculum, instructional strategies, assessment, programs, interventions…
The way we work.
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Tell us about the waywe work.
Tell us how we get theresults we are getting.
Help us know if we have instructional coherence.
SCHOOL PROCESSES AREIMPORTANT DATA
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SCHOOL PROCESSES DEFINITIONS
INSTRUCTIONAL: The techniques and strategies that teachers use in the learning environment.
ORGANIZATIONAL: Thosestructures the school puts in placeto implement the vision.
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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.
SCHOOL PROCESSES DEFINITIONS
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DATA INVENTORIES - APPENDIX B
Pages 265-334
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Review implications across data. Look for commonalities.
Create an aggregated list ofimplications for the schoolimprovement plan.
MERGE STRENGTHS, CHALLENGES,AND IMPLICATIONS FOR THE SCHOOL
IMPROVEMENT PLAN
After analyzing all four types of data
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AGGREGATING IMPLICATIONS
• Intersections
• Presentation
and
interpretation/en
gagement as a
function of
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NDE Continuous School Improvement
2014-2015 Workshops
• Sept. 25-26– North Platte • October 6-7 – Kearney• October 23-24 – Norfolk• October 27-28 - Omaha
• Each school will receive a copy of Data Analysis for Continuous School Improvement
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Fall CIP Workshops Agenda
Why Data Analysis? - What would it take to ensure student learning at
every grade level, in every subject area, and with every student group?
- Strengths/Challenges/Implications protocol using Demographic Profile Data
- Analyze District Data with DRS Reports