Deliberating Data (Student Guide) - Digital Promise

Deliberating Data (Student Guide)

How might we find meaningful information in data?


Prepare: Learn about the ideas in the project

There is data almost everywhere we look, but with so much data out there, how do we know what data will help us learn what we want to know? This project is all about asking questions that help make meaning out of data.

First, a quick introduction to two categories of data: quantitative data and qualitative data. Data that is quantitative can be expressed by numbers through a measurement, a count, or a numerical estimation. Qualitative data, on the other hand, is expressed through characteristics and qualities. It is not easily expressed through numbers.

For example, let’s say that you would like to gather information about your peers’ tastes in sports. If you want to know how many of your classmates play a sport, you will likely end up with a number count, or quantitative data. If you want to know what kinds of sports your peers like to play, you will likely end up with a list of their preferences, or qualitative data.


Practice: Try as many activities as you would like to build your skills

  • With a partner, brainstorm more questions that will help you learn about your peers’ tastes in sports. Which questions could lead you to quantitative data? Which questions could lead you to qualitative data?
  • Explore data on the number of international tourist arrivals by country. With a partner, write down your observations about the information. Use the See / Think / Wonder routine to discuss:
    • What do you see?
    • What do you think?
    • What do you wonder?

Produce: Dig in to the project and make it your own!

Return to the data on the number of international tourist arrivals by country. You could also use any other data available to you.

Build off the discussion from the See / Think / Wonder routine by discussing the following with a partner or group:

  • What questions could be answered by this data?
  • What questions might be difficult to answer from this data?
  • Where do you think you could find answers to the questions that this data set couldn’t answer?
  • What questions do you have about how the data was collected?
  • What questions do you have about how the data is organized and presented?
  • Do you think there may be any bias in the the way the data was collected? Who was included/excluded from the data? Why?

Create a presentation to share highlights from your discussion with your class.


Produced by Digital Promise Global, with thanks to the Open Educational Resources listed throughout this guide. Distributed to Learning Studios schools as part of HP, Inc. and Microsoft’s Reinvent the Classroom.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. You may share this project or modified versions of it under this same license.

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