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 Data + instructional strategies

Below are a list of various instructional strategies that work well when teaching with data. We have tried to articulate how to facilitate them in ways to promote your students understanding of data. We look forward to hearing how they go. Drop us a note to share what did and did not work with your learners!

Curious about examples of how these strategies line up with data?

Check out great data literacy Instructional Strategies for the Earth Science Classroom resources put together by colleagues at My NASA Data of these and other strategies linked with cool NASA data visualizations. As a note, these can be applied in non-ESS classrooms as well.

Curious about other strategies that come from other disciplines, but that can be leveraged to help students when working with data?

Check out the “What are some strategies we can use to draw conclusions better?” video and/or slidedeck.

CLAIM, EVIDENCE, REASONING, REBUTTAL: (MCNEILL & KRAJCIK 2012)

To emphasize making a claim from the data, but also supporting it with evidence, reasoning logically about it, and considering/critiquing alternative explanations. This provides students with a framework to follow that mimics how scientists/professionals present the results from their data/analysis.

Provide students with a visual or data, and ask:

  1. What conclusion can you draw from these data based on the original question?

  2. What aspects of your data -- observations, measurements, results, outputs, etc. -- support this claim?

  3. Why do those aspects of your data support your claim?

  4. What other claims could you make from these data? What evidence and reasoning do you have that this alternative is not the best claim?

CLAIM, SUPPORT, QUESTION: (RICHHART, CHURCH, & MORRISON 2011)

To identify and probe claims for their validity and supporting evidence. This helps students move away from “agree or disagree” and into a place of thoughtful scrutiny of claims to better develop their ability to make and receive claims.

Ask students to:

  1. Make a claim about the topic/issue/idea/visual being explored.

  2. Identify support for your claim. What things do you see, feel, or know that lend evidence to you claim?

  3. Raise a question related to your claim. What make make you doubt the claim? What seems left hanging? What isn’t fully explained? What further ideas or issues does your claim raise?

CONNECT, EXTEND, CHALLENGE: (RICHHART, CHURCH, & MORRISON 2011)

To help students connect different pieces of information together and elicit any questions that students still have. This helps students explore their thinking about something new based on their experiences with the new information.

Consider what you have seen/learned about, and ask them:

  1. How are the ideas and information presented connected to what you already knew?

  2. What new ideas did you get that extended or broadened your thinking in new directions?

  3. What challenges or questions have come up in your mind from the ideas and information presented?

DATA PUZZLES: (KASTENS & TURRIN 2010)

To provide students the “ah-ha” moments when they see a concept represented in real-world data. This uses clear-cut, ambiguous cases in real-world data to help students see the connections between concepts and data.

Provide students a static data visual that clearly demonstrates a pattern, and ask them to:

  1. Describe what you see in the data visualization.

  2. Connect what you see in the data to the larger concept.

HEADLINES:  (RICHHART, CHURCH, & MORRISON 2011)

To encourage students to reflect and synthesize as they identify the key takeaways / core of the situation. This reminds students to pull back out to the big picture from the details.

Provide students with a visual OR ask them to think about a big idea/important theme you are discussing, ask them to write a headline (or figure legend) for the topic/visual that summarizes and captures a key aspect that you feel is significant and important.

HYPOTHESIS ARRAY: (KASTENS, KRUMHANSL, & BAKER 2015)

To focus interpretation of data around potential hypotheses to provide them with an initial starting point to make sense of the data. This provides students with a place to start when thinking about what hypotheses to make from the data and how data supports or refutes a hypothesis.

Provide students with written descriptions of sketches of several working hypotheses, then are asked to:

  1. Explore real-world data on the topic.

  2. Collect evidence in support of one of the hypotheses.

  3. Explain why the evidence supports one hypothesis and refutes the other hypotheses.

I2 (IDENTIFY / INTERPRET): (BSCS 2012)

To identify what you see and then interpret what it means. This helps students break down the information in a visual into smaller parts to make sense of first.

Provide the students with a visual, and ask them to:

  1. Identify what you see in the graph with “What I see is…” comments.

  2. Interpret each thing that you have seen with “What it means is…” comments.

  3. Write a caption for the graph, starting with a topic sentence of the overall pattern in the graph, followed by your connected “What I see” and “What it means” comments into a paragraph.

I USED TO THINK…., NOW I THINK…: (RICHHART, CHURCH, & MORRISON 2011)

To help students reflect on their thinking about a topic/visual and explore how and why their thinking has changed over time. This supports students developing their metacognitive skills as they are processing and making sense of information.

Ask students to reflect on their current understanding of a topic/visual, and then to complete these sentences:

  1. I used to think…

  2. Now I think…

NOTICE/SEE, THINK, WONDER: (RICHHART, CHURCH, & MORRISON 2011)

To emphasize the importance of observation as the first step in thinking through and interpreting something. Good starting point in to a topic because the “wonder” section elicits questions to pursue in the future.

Provide students with a visual and ask: 

  1. What do you see/notice?

  2. What do you think is going on?

  3. What does it make you wonder?

PREDICT, OBSERVE, EXPLAIN: (HAYSOM & BOWEN 2010)

To predict what data pattern will look like under certain circumstances and then to compare their prediction to actual data and explain the similarities and differences. This helps students explore larger datasets, connect their prior knowledge to the data pattern at hand, and/or start to have a starting point to know what to look for within the data based off of their prediction.

Present students with a topic area, and then:

  1. Ask them to make a prediction about what the data will show under certain conditions.

  2. Show them real-world data from a range of conditions.

  3. Ask them to look for evidence in the data that supports or refutes their predictions.

  4. Ask them to explain why they think that is the case.

THE EXPLANATION GAME: (RICHHART, CHURCH, & MORRISON 2011)

To emphasize the importance of looking closely and building explanations and interpretations. Helps learners build causal explanations or connected understandings for what they see, what it means, why, and what else could be going on.

Provide students with a visual and ask them to: 

  1. Name It - Name a feature or aspect of the visual that you notice.

  2. Explain It - What could it be? Why might it be there? What does it mean?

  3. Give Reasons - What makes you say that? Or why do you think it happened that way?

  4. Generate Alternatives - What else could it be? And what makes you say that?

THINK, PUZZLE, EXPLORE: (RICHHART, CHURCH, & MORRISON 2011)

To help students connect their prior knowledge and to encourage their curiosity. This is similar to the Know-What to know-Learned (KWL) common strategy but is more process and inquiry driven than fact driven which fosters students developing critical thinking skills.

Provide students with a topic, concept, phenomena and ask:

  1. What do you think you know about this topic/concept/phenomena?

  2. What questions/puzzles do you have about this topic/concept/phenomena?

  3. How might you explore your questions/puzzles around this topic/concept/phenomena?

ZOOM IN: (RICHHART, CHURCH, & MORRISON 2011)

To develop a hypothesis/interpretation from part of a visual and to revisit the hypothesis/interpretation when provided more information. Helps students build up their understanding of the meaning of a visual in a fun”detective” way.

Repeats between two phases with a visual: 

  1. Looking closely at one small part, ask students: What do you see or notice? What is your hypothesis or interpretation of what this might be based on what you are seeing?

  2. Reveal more of the visual, ask students: What new things do you see or notice? How does this change your hypothesis/interpretation? Has the new information answered any of your wonders of changed your previous ideas? What new things are you wondering about?