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Data + Questions/Problems [Data in the Practices Series]

data in practices data moves & topics

Data in the Practices, Data Moves & Topics 

By: Kristin Hunter-Thomson

 

Source: https://pixy.org/692963/ 

Asking questions…

Defining problems…

Making sense of problems…

There are many ways that we discuss the critical thinking work that goes into working through something across our different disciplines. While the exact products or steps we are taking vary, the thinking required is similarly grounded in what are we trying to do and what should we do next.

How does data fit in here?

Questions and problems interface with data in numerous ways. While we certainly ask many questions and solve problems that do not involve data, when we are working with data asking questions and making sense of problems are important aspects of the work.

In fact, the practice of asking questions and making sense of problems can come at the start, during, and at the end of process of working with data. Therefore, rather than thinking about this practice as existing in any one step of a sequence I find it helpful to think about this through the lens of two overarching ways that data typically comes into play in our work with this practice.

1. Clarifying what is at hand: for example we…

  • Ask clarifying questions to better understand the problem or investigation at hand to determine what data would be needed to make an informed design to solve a problem or to investigate the phenomenon/system,

  • Look critically at the data and ask questions to gain a better understanding of what is there and what is not there within the data,

  • Look critically at our data visualized to ask questions about things like:

    • is this the best way to represent the data given the data and our question/problem at hand,

    • what visual features are apparent in the data,

    • what those visual patterns could mean,

    • what mechanisms or situations could be driving the different features in the data, etc.

  • Ask questions to understand others’ claims or design solution from the data,

2. Identifying a next step: for example we…

  • Figure out what kind of data to look for to help us explore or investigate the phenomenon/system or problem we are trying to solve,

  • Identify questions from the data we already have to pursue a deeper understanding of what is going on within the data,

  • Ask internal questions of ourselves about what a good next step would be to solve the problem or investigate the phenomenon/system,

  • Explore how others troubleshooted an issue or hiccup when solving a similar problem or conducting a similar investigation to ask what we could adapt or try ourselves,

  • Identify follow-up questions to pursue next to solve the next problem or pursue a deeper understanding of the phenomenon/system, etc.

Being aware that working with data is more than just “Analyzing and Interpreting Data” or “Measurement and Data” is important for students to build their overall data literacy skills. One way to build that awareness is to explicitly make the connections to data within each of our practices. Therefore, I propose that a key component of helping students build their skill set in this practice — asking questions and making sense of problems — should be acknowledgment of and support for helping students practice these skills with data, as well as with abstract numbers and prose.

Engaging in this practice involves both internal decision making and communication, as well as external communication. Additionally, we can engage with this practice with our work with data both formally and informally. Regardless of when, how, or what we are doing with the data and this practice let’s help our students build on and enhance their skills of this practice by being more explicit about what we are doing with data, and how this practice relates to data.

What could this look like?

We can get at asking questions and making sense of problems from many different angles, and in fact the more we vary our students entry points into this practice the bigger their muscles will become in using the practice. Here are some examples, certainly not an exhaustive list, of what this could look like (for more examples see Hunter-Thomson & Shauffler (2020), updates coming January 2021):

  • Formulate questions in a given context:

    • Phrase wonderings in the form of questions. (Grades K-2)

    • Describe features of phenomena that are measurable and pose questions about them. (Grades 3-5)

    • Critique and refine questions to focus an investigation. (Grade 6)

    • Formalize something that is unknown into a question that can be investigated with data. (Grades 7-8)

    • Ask questions to draw inferences or make generalizations about populations or phenomena. (Grade 9)

    • Simplify a problem into logical steps; reframe, represent, or describe problems using abstractions. (Grades 10-12)

  • Connect data, questions, and predictions:

    • Describe expectations based on prior knowledge (e.g., what will you see, what do you think will happen). (Grades K-2)

    • Anticipate what the data may show about a question before looking at the data. (Grades 3-5)

    • Understand that the data you have determines what questions you can ask. (Grade 6)

    • Pursue questions to investigate with the available resources. (Grades 7-8)

    • Evaluate a question to determine if it is testable and relevant to the phenomenon or problem. (Grade 9)

    • From a question, frame a null hypothesis that can be feasibly tested with an investigation. (Grades 10-12)

  • Generate follow-up questions and discussion:

    • With teacher assistance, raise new questions when looking at outcomes or thinking about the original question. (Grades K-2)

    • Identify new questions after reviewing results and answering the original question. 9Grades 3-5)

    • Identify new questions based on unexpected results and/or to clarify the results. (Grade 6)

    • Ask questions about provided arguments and/or interpretations of data. (Grades 7-8)

    • Identify related sub-questions to answer with data that can help answer an overarching question. (Grade 9)

    • Pose new questions raised by data or findings for further investigation to better understand phenomenon or problem. (Grades 10-12)

What are your thoughts or resources?

What are you doing to help learners better understand how we use data when asking questions and making sense of problems? What resources have your found helpful? What are teaching strategies that help your students hone these skills and practices?

Reach out and let us know! We will add it to this list so that it can become a community generated resource.

Resources for more information:

Data-related resources for this practice:

Resources related to the practice:

Standards-related resources for this practice:

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