1. Data Literacy for All Schools SLDS Grant Goal 2
Analyzing Perception Data
ESUPDO
January 22, 2015

2. Purpose
Understand and integrate the Data Literacies into training for districts and schools
Know where to find resources on perception data for AdvancEd, Frameworks, Data Guidebook, and Bernhardt
Leave with protocols to analyze perceptual data that can be used with districts, schools, and ESUs

3. Tiered Training Delivery
Goal 2 SLDS Grant
Provide 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 ✔

4. Data Cadre
Create data use and literacy capacity and culture in Nebraska school districts
Collaborative effort between NDE and ESUCC
9 professional developers from ESUs
5 NDE Representatives
Expanded to include representatives from NDE departments and post-secondary

5. Statewide Data Cadre ESUs/ESUCC Higher Ed NDE 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
Streamline the trainings around data use to one unified message
Curriculum being delivered to districts will also be utilized for internal training at NDE so that a common process and language is spoken

6. Data Literacies
Data Literacies

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

8. 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

9. Literacy 1 Concepts Data Comprehension
a. Continuous Improvement Process
b. District/School Profile
e. Data Tools and Skills

10. Data Literacies Definitions

11. Text Protocol

12. Text Rendering Directions
Divide into groups of 4 with others outside your ESU.
One of the 4 literacies will be assigned to each group.
Take a few moments to review the document and mark the sentence, the phrase, and the word that you think is particularly important for our work.
Choose a scribe for each group to track the phrases and words that are shared.

13. Steps
First Round: Each person shares a sentence from the document that he/she thinks/feels is particularly significant.
Second Round: Each person shares a phrase that he/she thinks/feels is particularly significant. The scribe records each phrase.
Third Round: Each person shares the word that he/she thinks/feels is particularly significant. The scribe records each word.

14. Discussion
Discuss what you’ve heard and what it says about the Data Literacies document.
How might you present this document and use it with districts and schools?

15. Data Use Curriculum Nebraska Data Literacies
Freedom to utilize existing protocols or materials

16. AdvancEd Standard 5 Using Results for Continuous Improvement
The school implements a comprehensive assessment system that generates a range of data about student learning and school effectiveness and uses the results to guide continuous improvement. *

17. AdvancEd Surveys Required within one year of accreditation visit
Setup in ASSIST
Parents, Students, and Staff
Use ASSIST to generate the Survey Scoring Summary for each AdvancED survey
Complete Stakeholders Feedback Diagnostic in ASSIST
Answer 2 Rubric questions
Questionnaire Administration
Stakeholder Feedback and Analysis

18. AdvancEdSurvey Reports in ASSIST
pp give examples of how to generalize survey results
AdvancEd™ Guide to Administering Surveys and Generalizing Survey Results
*Will display survey results by standard and indicator as well as by question.
AdvancEd™ Guide to Administering Surveys and Generalizing Survey Results

19. AdvancEd Survey Diagnostic Questions Answered in Stakeholder Feedback Diagnostic
Areas of Notable Achievement
Which area(s) indicate the overall highest level of satisfaction or approval?
Which area(s) show a trend toward increasing stakeholder satisfaction or approval?
Which of the above reported findings are consistent with findings from other stakeholder feedback sources?

20. AdvancEd Survey Diagnostic Questions Answered in Stakeholder Feedback Diagnostic
Areas in Need of Improvement
Which area(s) indicate the overall lowest level of satisfaction or approval?
Which area(s) show a trend toward decreasing stakeholder satisfaction or approval?
What are the implications for these stakeholder perceptions?
Which of the above reported findings are consistent with findings from other stakeholder feedback sources?

21. Sharing: How do you support schools?
In your group, briefly identify the ways in which you support schools in completing and analyzing the results of the perceptual surveys and completing the required AdvancEd questions.

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

23. 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?

24. Continuous Improvement Framework
Page 14
Data Literacy 1
What do the data
show?

25. Page 17

26. Perceptual Data Surveys Facilitated by NDE
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 and then the district contact receives links to the surveys
Schools and ESU staff developer will receive the perceptual survey data results
The data belongs to the districts/schools *

27. Perceptual Data Request Form Return to ESU Staff Developer

28. Perceptual Data
Ability to administer surveys will be available in future years as well
NDE’s capacity to manage the perceptual data surveys is developing

29. Displaying Perceptual Data Results Line Graph
Page 248

30. Why Line Graphs?
Tables can be confusing. Which items are most important, highest, or lowest?
Page 246

31. Why Line Graphs?
Bar Graphs – How to compare? How many are needed?
Page 247

32. Why Line Graphs?
A very effective tool for presenting all item responses in relation to each other
Seeing the relationship of items to each other allows us to leverage what we are doing well and what it might take for us to do better.
The disaggregation can quickly show if there are subgroups with specific issues.
The line graph is a very effective tool for presenting all item responses in relation to each other so that those interpreting the graph have a clear idea of the relationship of the low items to each other, and the high items to each other, and how the lows and the highs are related.

33. Perceptual Data Results The power of graphs comes from their ability to convey data directly to the viewer.
High School Students
by Grade
Total Respondents (N=94)
10th Grade (N=11)
7th Grade (N=20)
11th Grade (N=20)
9th Grade (N=16)
8th Grade (N=17)
12th Grade (N=9)

34. Perceptual Data Results
Student Survey Results
Results for each school
4 pages of line graphs – Elementary
Total Survey Respondents, Gender, Ethnicity, Grade
12 pages of line graphs – High School
Above areas + Plans after graduation & Club Affliation
# of comment pages dependent on input

35. Perceptual Data Results
Staff Survey Results
Results for each school – 7 pages each
Total Respondents
By Job Title
By Years of Experience
# of comment pages dependent on input

36. Perceptual Data Results
Parent Survey Results
Results by School – 6 to 11 pages
Total Respondents
Children’s Grade Level
Person Completing Survey
Number of Children in Household
Number of Children in School
Graduate of Same High School Y-N (HS only)
# of comment pages dependent on input

37. Perceptual Data Results Open Ended Questions

38. Analyzing Open-Ended Question Results
Page 243

39. Analyzing Open-Ended Question Results

40. Important Understand the big picture shown by the survey results.
Consider the relationship of the items to each other.
Avoid tackling only negative items.
Determine solutions that can effectively work across the items

41. Data Sharing Protocols Strengths, Challenges, Implications

42. 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.

43. 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.

44. OTHER DATA
List other perception 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.

45. Data Sharing Protocols Analysis of Questionnaire Data

46. Overall Activity Directions
Divide into groups and within the group distribute pages of the handout
Analyze assigned perception data
Combine strengths, weaknesses, implications, additional data on chart paper
As a full group, complete the Analysis of Questionnaire Data Worksheet

47. 1. Divide into groups and within the group distribute pages of the handout
Divide into groups of 3-4
Work with others from your ESU if possible
Each group will receive pp
Divide the pages in the handout and assign
pp Student Perception Data
pp Staff Perception Data
pp Parent Perception Data

48. 2. Analyze assigned perception data
Use the strengths, challenges, implications, additional data handout
Quickly review the definitions of strengths, challenges, implications, and additional data *

49. 3. Combine strengths, weaknesses, implications, additional data , on chart paper

50. 4. Complete Analysis of Questionnaire Data Worksheet
As a full group, complete the worksheet

51. Analysis of Activity What worked? What didn’t work?
What would you change?

52. Other Protocols for Analyzing Data
Bernhardt 3rd edition Appendix C5 pp
Committee review meetings
Fish bowl
Gallery walk
Small groups with protocol
Data party
Review as a part of overall data profile

53. 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?
Reinforce the steps in the process to analyzing data and the next steps.

54. Brad Geise Wednesday, May 6, 2015
Professional Development Training by
Brad Geise
of Education for the Future - The Victoria Bernhardt Group
at ESUPDO
Wednesday, May 6, 2015
Topics: Data Analysis for CIP and
Analyzing Program Data
Save the Date

55. Perceptual Data Resources
/SLDS_Grant/ESUPDO_PerceptualData. html

56. *

57. Survey http://goo.gl/0uGkvI