1. Data-Driven Dialogue Predicting, Exploring, and Explaining Data
Hygiene Elementary School
Data-Driven Dialogue Predicting, Exploring, and Explaining Data
September 6, 2012

2. Outcomes & Process What predictions do we have about our data?
What observations and trends appear from the data?
What are our top priorities from the data?
What are our root causes?

3. Why This Process?
Education Accountability Act of 2009 (S.B ) requires all schools and districts to submit Unified Improvement Plans (UIP) to CDE to be posted at
Unified Improvement Planning is a collaborative process where all staff have input into the school plan

4. Data-Driven Dialogue Steps
Outcomes & Process
Data-Driven Dialogue Steps
Step 1 – Predict (Activate & Engage)
Step 2 – Explore (Explore & Discover)
Step 3 – Explain (Organize & Integrate)
Step 4 – Take Action

5. Outcomes & Process Data Team Roles RECORDER MATERIALS MANAGER
Check with each team member before recording
MATERIALS MANAGER
Organize data & charts for viewing, recording
PROCESS CHECKER
Monitor for balanced participation
ENVRIONMENTAL ENGINEER
Organize physical arrangement for all to view

6. Step 1: Predict
The purpose: To activate interest and bring out our prior knowledge, preconceptions, and assumptions regarding the data with which we are about to work. Prediction allows dialogue participants to share the frame of reference through which they view the world and lays the foundation for collaborative inquiry.
The steps include:
Clarify the questions that can be answered by the data
Make predictions about data
Identify assumptions behind each prediction
Prediction Sentence Starters:
I predict I expect to see I anticipate . . .
Assumption Questions:
Why did I make that prediction?
What is the thinking behind my prediction?
What do I know that leads me to make that prediction?
What experiences do I have that are consistent with my prediction?
Quantify observations – describe with numeric measures or attributes

7. Step 1: Predict ~5 minutes for Predict Data Sources:
TCAP Reading, Writing and Math:
Executive Summary – % P/A each grade (overall & subgroups)
Instructional Summary – sub-contents (ex. Vocab, fiction)
Scores compared to all schools in the District and also to Colorado
Growth Percentiles – overall and for subgroups

8. Step 1:Predict Predictions Assumptions
Quantify observations – describe with numeric measures or attributes

9. Step 2: Explore
The purpose: Generate priority observations or fact statements about the data that reflect the best thinking of the group.
The steps include:
Interact with the data (highlighting, creating graphical representations, reorganizing)
Look for patterns, trends, things that pop out
Brainstorm a list of facts (observations)
Prioritize observations
Turn observations into priority performance challenges
Avoid: Statements that use the word “because” or that attempt to identify the causes of data trends.
Sentence starters:
It appears I see that It seems The data shows . . .
Quantify observations – describe with numeric measures or attributes

10. Step 2: Explore ~25 minutes for Explore Data sources (one at a time):
TCAP Reading, Writing and Math:
Executive Summary – % P/A each grade (overall & subgroups)
Instructional Summary – sub-contents (ex. Vocab, fiction)
Scores compared to all schools in the District and also to Colorado
Growth Percentiles – overall and for subgroups

11. Step 2: Explore
The purpose: Generate priority observations or fact statements about the data that reflect the best thinking of the group.
The steps include:
Interact with the data (highlighting, creating graphical representations, reorganizing)
Look for patterns, trends, things that pop out
Brainstorm a list of facts (observations)
Prioritize observations
Turn observations into priority performance challenges
Avoid: Statements that use the word “because” or that attempt to identify the causes of data trends.
Sentence starters:
It appears I see that It seems The data shows . . .
Identify no more than 2 priority needs, and write each one on a separate poster

12. Share Group Findings Share the trends you saw in your data
Share the Priority Performance Challenges
Summary of the data where there are challenges
For example:
Persistent low performance among English Language Learners in reading across all standards and grades.
For the past three years, English Language Learners have had median growth percentiles below 30 in all content areas, substantially below the minimum state expectation of 55.
Identify no more than 2 priority needs, and write each one on a separate poster

13. Step 3: Explain
The Purpose: Generate theories of causation, keeping multiple voices in the dialogue. Deepen thinking to get to the best explanations and identify additional data to use to validate the best theories.
The steps include:
Generate questions about observations
Brainstorm explanations
Categorize/classify brainstormed explanations
Narrow (based on criteria)
Prioritize
Get to root causes
Validate with other data
Guiding Questions:
What explains our observations about out data? What might have caused the patterns we see in the data?
Is this our best thinking? How can we narrow our explanations?
What additional data sources will we explore to validate our explanation?
2 posters – one for each priority need statement. Generate explanations & possible causes, categorize, and search for root cause. The “5 Whys” protocol is used to drill down and identify the true root cause.

14. The school should have control over the
Root Causes
A cause is a “root cause” if:
The problem would not have occurred if the cause had not been present
The problem will not reoccur if the cause is dissolved
Correction of the cause will not lead to the same or similar problems
The school should have control over the
root cause 

15. Root Cause Examples Non-Examples Why Non-Examples?
Student attributes (poverty level)
Parent education & involvement
Student motivation
Why Non-Examples?
Schools do not have control over these causes

16. Root Cause Examples
The school does not provide additional support/interventions for students performing at the unsatisfactory level
Lack of clear expectations for tier 1 instruction in math.
Lack of intervention tools and strategies for math.
Limited English language development.
Inconsistency in instruction in the area of language development.
Low expectations for all subgroups.
Low expectations for IEP students.

17. The “5 Whys” Protocol (Explanation)
Getting to Root Causes
The “5 Whys” Protocol (Explanation)
Proposed Cause:____________
Why? Why?
• Because… • Because….
2. Why? Why?
Why?
• Because….

18. 5 Why Example
ELL students are not engaged in learning in the core content classes.
Why?
Because…
Core curriculum is not accessible to ELL students.
ELL students’ English skills are not proficient enough to participate in discussions, ask questions, and comprehend core content.
There is inconsistent English language support for students in core content classes.
Lack of implementation of INSIDE and EDGE ELL curriculum as parallel support for ELL students in core content classes.

19. Step 3: Explain 5 minutes for explanations
15 minutes for root cause identification
Each group will chart explanations and identified root causes

20. Step 3: Explain
The Purpose: Generate theories of causation, keeping multiple voices in the dialogue. Deepen thinking to get to the best explanations and identify additional data to use to validate the best theories.
The steps include:
Generate questions about observations
Brainstorm explanations
Categorize/classify brainstormed explanations
Narrow (based on criteria)
Prioritize
Get to root causes
Validate with other data
Guiding Questions:
What explains our observations about out data? What might have caused the patterns we see in the data?
Is this our best thinking? How can we narrow our explanations?
What additional data sources will we explore to validate our explanation?

21. Share Group Work
Trends
Explanations
Root causes

22. Next Steps Refine root causes
Validate root causes (does our other data support the root cause)
Action Planning