Using Data to Explain and Solve

Today you will learn how to use data and models to explain what is happening and to suggest a way to fix a problem.

Imagine the grass on your school playground in Texas. Near the swings, the grass is gone and the ground is bare dirt. Near the fence, the grass is thick and green. You wonder why. To find out, you collect data, which is information you gather by observing, counting, or measuring. For two weeks, you count how many students play in each spot. You count 40 students near the swings each day and only 3 near the fence.

Now you can write an explanation, which is a statement that tells why something happens and uses evidence to back it up. Your explanation might be: the grass died near the swings because many feet pressed down and broke the plants every day. Notice that your explanation is not just a guess. It points to your counting data as proof.

You can also use a model, which is a drawing, diagram, or small version of something that helps you show an idea. You could draw a map of the playground and shade the bare spots dark brown and the green spots light green. Your map shows, at a glance, that the worn spots match the busy spots. That makes your explanation easier for others to understand.

Next comes the solution. Since heavy foot traffic hurts the grass, you might propose adding mulch or rubber chips under the swings. Or you could suggest a rope fence that closes one area for a month so the grass can grow back. A good solution always connects to your data. If your data showed the bare spot was caused by a leaking pipe, mulch would not help at all.

Try it: If your data showed plants died only in the shady corner of a garden, what explanation and solution would you suggest?