What should we first ask our students to do with data? (Process for Teaching with Data, Phase 1)

What should we first ask our students to do with data?

When first presented with a visualization, either one that you create or that is created by someone else, it is important to pause and just look at it before you start trying make sense of it. You can do this by asking yourself:

  • What do I notice?
  • What do I wonder about when looking at this?

 These questions assist you in essence to find the visualization’s introduction, as if you were meeting a new person.

 So how can we guide students to become “acquainted” with a graph that is new to them?

  • Show the visualization to students, either by projecting it for all to see, having it printed on a worksheet, or having them open it on their computers/tablets.
  • Ask students these two questions and have them first think about it for themselves. They can write down their thoughts in an in-print or online science journal or just think for themselves.
  • Have them share out loud their ideas:
    • As a think-pair-share exercise where they turn to their neighbor to discuss what they were thinking.
    • As a small group share out where they each share their thoughts in turn without interruptions or feedback (like a microlab setup) and then discuss with one another everyone’s ideas.
    • As a full group discussion about it.

The key is to have your students pause for a moment and engage with the visualization. There are no correct or wrong answers at this point. The emphasis should be on getting them to think for themselves about what they see and what questions that leads them to think about. This helps activate students brains for making sense of the data and connects to their prior knowledge of the subject matter and/or type of visualization.

Once students have done this initial work of articulating what they notice and what they wonder, they are ready to move on to getting ready to interpret the visualization!

See “Strategies for Teaching with Data, Part 2” for effective strategies for starting students off in interpreting data.

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