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Data Driven Dialogue
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
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.
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.
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 ….
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.
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?
• 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.
• “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.
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
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 ….
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 ….

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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 ….