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Data-Driven Dialogue. Phase 1: PredictBring Experiences, Possibilities,
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1. Collaborative Inquiry: Bridging Data and Results Based on the Work of
Nancy Love
&
Karen Falkenberg
NSTA National Conference on Science Education 2008
2. Data-Driven Dialogue Phase 1: Predict
Bring Experiences, Possibilities, & Expectations to the surface. Phase 2: Go Visual!
Use stoplight highlighting to emphasize patterns in data. Phase 3: Observe
Analyze Data.
What are some of the patterns, trends or surprises? Phase 4: Infer/ Question
Generate possible Explanations.
What inferences or conclusions can be made? What questions do you have?
3. Phase 1: Predict Item-Level Analysis Review the released items.
What are your predictions about how students will perform on each item?
I predict. . .
I assume. . .
I wonder. . .
I’m expecting to see. . .
What patterns do you think might develop?
Document your predictions on the prediction recording sheet.
4. Phase 2: Go Visual Explain the components of the Item Analysis Report.
Clarify criteria for different levels of work.
Use stoplight highlighting to identify areas of strength, caution, and concern.
Green=Strength
Yellow=Caution
Red=Concern
5. Phase 3: Observe Review stoplight highlighting.
Record observations.
I am struck by. . .
I observe. . .
I notice. . .
Compare predictions with actual data.
6. Phase 4: Infer/Question Examine patterns in the data.
What inferences and explanations might we draw about areas of strength or weakness?
What conclusions and questions does the data lead to?
A possible explanation. . .
An inference I am drawing. . .
A question I have now. . .
7. Principles for Effective Use of Data Pay attention to the process.
Separate data from inference.
Multiple perspective yields the richest analysis.
8. Reflecting on the Process What struck you about this process?
How might you use this process in your school/district?
What might you need to do to prepare teachers to participate in this process?