Your SlideShare is downloading. ×
Data Driven Dialogue
Data Driven Dialogue
Data Driven Dialogue
Data Driven Dialogue
Data Driven Dialogue
Data Driven Dialogue
Data Driven Dialogue
Data Driven Dialogue
Data Driven Dialogue
Data Driven Dialogue
Data Driven Dialogue
Data Driven Dialogue
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Data Driven Dialogue

1,055

Published on

Published in: Education, Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
1,055
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
0
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Data Driven Dialogue
  • 2. Data Driven Dialogue• This protocol leads a team to begin by thinking of questions about student achievement.• National School Reform Faculty – Data Driven Dialogue• Article from ASCD, “Answering Questions That Count” December 2008/January 2009, pages 18-24.• Links to documents are on my web site
  • 3. Getting Started• All participants have equal voice.• This will assist groups in making shared meaning of data.• Helps to replace hunches and feelings with data- based facts.• Examines patterns and trends of performance indicators.• Generate “root-cause” discussions that move from identifying symptoms to possible causes of student performance.
  • 4. Overview• Phase I—Predictions – Surfacing perspectives, beliefs, assumptions, predictions, possibilities, questions and expectations.• Phase II—Observations – Analyzing the data for patterns, trends, surprises, and new questions that jump out.• Phase III—Inferences – Generating hypotheses, inferring, explaining and drawing conclusions. Defining new actions, interactions, and implementation plan.
  • 5. Before You See the Data• Activate prior knowledge, surface assumptions, and make predictions to create a readiness to examine and discus the data.• Hear and honor all assumptions.• I assume ….• I predict ….• I wonder ….• My questions/expectations are influenced by …• Some possibilities for learning that this data may present ….
  • 6. Consider• “When important questions drove the dialogue about school effectiveness, school staff quickly learned how to identify and use different types of data to answer those questions. (Lachat& Smith, 2004)• Organizing data around essential questions about student performance is a powerful strategy for building data literacy.
  • 7. Possible Essential Questions• How do student outcomes differ by demographics, programs, and schools?• To what extent have specific programs, interventions, and services improved outcomes?• What is the longitudinal progress of a specific cohort of students?• What are the characteristics of students who achieve proficiency and of those who do not?• Where are we making the most progress in closing achievement gaps?• How do absence and mobility affect assessment results?
  • 8. • How do student grades correlate with state assessment results and other measures?• What percent of the students improved, stayed the same or declined from last years achievement?• Are students making sufficient grade-to-grade progress?• How many of the lower performing students in grade 4 are still lower performing students in grade 5.• What is the variation in students’ scores within each course or grade.
  • 9. • “Asking questions such as these enables administrators and teachers to focus on what is most important, identify the data they need to address their question, and use the questions as a lens for data analysis and interpretation.” P 18• Limit the number of questions to no more than five or six crucial questions that get at the heart of what they need to know.
  • 10. What is Needed?• Time to look at data, analyze data and ask more questions.• Time to look at the data rather than time spent creating the graphs and charts.• Teachers need opportunity and support to plan and implement improvement strategies and then collect data to see if the strategies work.• Opportunity to ask questions and then find data to answer the question.• Data that is sufficiently disaggregated – By broad categories, male, female, economic status, programs – Combinations of categories ie female and low SES
  • 11. Phase II—Just the Facts• The terms; because, therefore, it seems, and however may not be used.• Use these sentence starters• I observe that ….• Some patterns/trends that I notice ….• I can count ….• I am surprised that I see ….
  • 12. Phase III—Inferences• I believe that the data suggest …. Because …• Additional data that would help me verify/confirm my explanations is …..• I think the following are appropriate solutions/responses that address the needs implied by the data ….• Additional data that would help guide implementation of the solutions/responses and determine if they are working ….

×