1. Using Data for Continuous School Improvement
2014 Fall CIP Workshops

2. 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.

4. 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

5. 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

6. 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

7. Data Literacies Format1. a. i.
Concept
Indicators
Literacy

8. Data Literacies

9. Data Use Curriculum
Nebraska
Data
Literacies

11. 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…

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

13. 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.

14. 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

15. 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

17. WHY Data Analysis/Continuous and School Improvement?
Before

18. 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.

20. 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

21. 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

23. Mission
Vision
Continuous Improvement Cycle

24. 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).

25. 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.

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

27. 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.

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

30. “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

31. Page 14

32. 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?

33. Data Literacy 1
What do the data show?

34. Data Literacy 2
Why might that be?

35. Data Literacy 2
Why might that be?

36. Data Literacy 3
How should we respond?

37. Data Literacy 4
Did our response produce results?

38. 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

39. 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.

41. 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.”

42. 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?

43. 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.

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

46. Evidence

48. Data Literacy 1
What do the data show?

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

50. Page 17

51. Page 17

52. 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.

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

54. 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!

55. 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

56. 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!

57. Page 17

58. 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!

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

60. 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!

61. Page 17

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

63. 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

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

66. Page 17

67. 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.

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

69. 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.

70. 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.

71. 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.

73. Data Profile Demographic Data
ENGAGEMENT
Appendix F Page
Data Profile
Demographic Data

74. Data Literacy 1
What do the data show?

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

78. 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

79. 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

80. 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.

82. LETS SEE WHAT IT LOOKS LIKE
Pages

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

84. 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?

85. CASE STUDY Demographic Data
DEMOGRAPHIC DATA PP
CASE STUDY Demographic Data
5 Divisions
Enrollment: Pages
Mobility: P. 273, Attendance: P. 274, ELL: P. 275, & FRL: P. 276
Special Education: P
Retention: PP , Pre-Referral Team: PP , Staff: Pages
Behavior: Pages

87. 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

88. DATA INVENTORIES - APPENDIX B
Pages

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

90. 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.

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

92. Page 343

93. FACILITATION GUIDE
Pages

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

96. Pages
CONTRIBUTING CAUSES: Underlying cause or causes of positive or negative results.

97. PROBLEM SOLVING CYCLE EXAMPLE
Page
PROBLEM SOLVING CYCLE EXAMPLE

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

99. THE PROBLEM-SOLVING CYCLE Example Hunches/Hypotheses
Page 106

100. THE PROBLEM-SOLVING CYCLE Example Hunches/Hypotheses
Page 106

101. 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?

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

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

104. 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?

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

106. 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.

107. FACILITATION GUIDE
Pages

108. 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?

109. Data Literacy 1
What do the data show?

111. Perceptual and Demographic
Resources available
through NDE

112. 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

113. Perceptual Data Request Form Return to ESU Staff Developer

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

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

116. Continuous Improvement

118. Data Profile Enrollment example

119. Data Profile-Enrollment by Ethnicity

120. Data Profile Ethnicity Not SPED/ SPED Example

121. Evaluation & Next Steps with your ESU Staff Developer
Please complete one survey per district together as a district team

122. Resources
PPT