Asking Questions OF vs FROM Data
Asking questions is a key part of working with data.
Asking questions happens to also be a key part of NGSS’s Science & Engineering Practices (SEP1), 21st century / citizenship skills, mathematical practices and ELA & literacy skills too. Hmmm…I wonder why? Maybe as it is pretty fundamental to critical thinking and being a curious human :)
But back to asking questions when working with data…sometimes we say we are asking questions of data and sometimes we say we are asking questions from data.
Let’s explore the difference.
Graph created at https://about.dataclassroom.com/ready-to-teach/progress-in-eradicating-polio
QUESTIONS OF DATA
When we ask questions of data we are often in a situation in which we are presented with a dataset or data visualization (e.g., graph, map, table) and are in essence asking something like “here are data, what does it reveal to you?”.
The way the question or prompt is worded can vary:
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From really generic, like “What do you notice?”
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To more specific to direct users towards a specific part of the relationship between the variables, like “What is the relationship between 1-year olds vaccinated and time?”
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To even more specific to direct users towards a specific takeaway message from the data, like “How have the number of 1-year olds vaccinated changed over time?”
Regardless of how the question or prompt is actually written, the general approach with asking questions of data is that you are trying to figure out what the data — be it already in a graph OR you need to make the graph — reveals. A known story is there and the user is working to find it.
Graphing interface available at https://about.dataclassroom.com/ready-to-teach/progress-in-eradicating-polio
QUESTIONS FROM DATA
Conversely, when we ask questions from data we are often in a situation in which we have a dataset or data visualization and are in essence asking something like “here are data, what can you ask, explore, find?”.
Again, the way the question or prompt is worded can vary:
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From really generic, like “What do you wonder?” or “What did you find?”
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To more specific to direct users to think about what they see in the data, like “What can you find out about time and 1-year old vaccination rates?”
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To even more specific to direct users towards certain data moves, like “How can you explore time, country, and 1-year old vaccination rates?”
But regardless of how the question or prompt is actually written, the general approach with asking questions from data is that you are actively exploring the data. There are many stories in the data and the user is making their own decisions of which to find.
SO, HOW DOES THIS APPLY TO K-12 TEACHING WITH DATA?
As we just talked about, these ways of question asking with data are different. They require different cognitive steps…meaning they help students practice different skills and thus prepare students for different future use cases with data.
For example, asking questions of data helps students develop their skills to read data visualizations and is a very common approach in K-12 data-based lessons/activities. This skill has great application in the real world when making sense of graphics in the media, our your social media feeds, on your utility statements (true story!). So that is all good and necessary.
But, the skill to read data visualizations is 1) not the only skill needed to make sense of data (see Building Blocks for Data Literacy for a K-12 scope and sequence of data skills), and 2) does not prepare you to work with and make sense of data when someone else has not already “found the answer/story” (aka what is needed in the workforce application of working with data). But, asking questions from data does build these skills. Unfortunately, far fewer K-12 data-based lessons/activities currently are framed from this perspective of question asking.
Neither are bad.
Both are good and necessary to best prepare students’ data literacy skills.
The key is to think about how to make space for both kinds of question asking in our instruction.
** To note, another implication of this relates to how we make sense of and engage with our student assessment data. Are you, the user of the data, in the driver’s seat making decisions about what questions to ask and stories to find (from data) or are you looking for what the data reveal that someone else already decided upon (of data)?
HERE ARE SOME QUESTION ASKING RESOURCES:
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Check out the July/August 2021. How Can We Use and Interact With Graphs Better? (Data Literacy 101). Science Scope 44(6): 8-14.
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Sign up to participate in the Data Literacy Series workshops to dive into helping students develop data analysis and interpretation skills
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#7 “Communicate with Data in Multiple Ways”
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Check out the Question Formulation Technique from the Right Question Institute to practice asking questions of data and from data. Visit rightquestion.org for more information and free resources.
LOOKING FOR MORE?
Interested in meeting 1:1 or 1:team to discuss question asking with data is it relates to your teaching environment, sign up for a free 30-minute video consultation time here: https://calendly.com/dataspire/coaching-session.
