2  Getting Started with CODAP

CODAP has been designed to be easy to use. See if you agree.

… or you can work in the live illustration below.

You should see a box that gives you a choice called Open Document or Browse Examples. Choose that.

Then, under Example Documents, pick Getting Started with CODAP, then click Open. You should see a box that looks like this:

The “Getting Started” box

Alternatively, you can try to do these tasks in the live illustration below, although space will be cramped:

It should be pretty self-explanatory. Try to do the five tasks, and if you need to see how, the Show me links will play tiny videos of how it’s done.

When you’re done, all five boxes will be checked. More importantly, you will have made a graph or two.

2.1 Commentary (aka TL;DR)1

We will include sections like this from time to time. Here is some meta-commentary, that is, commentary about this commentary:

  • You can learn a lot in this book even if you skip these sections. But doing things—actually interacting with the data—is more important than reading.
  • Teachers: we will have suggestions for how to present this material and why we think it’s important.
  • Students: this may tell you what the teacher cares about in case you want to focus on something.

Enough meta. Onward!

Overview

The file has data about things like LifeSpan, Speed, and Diet for 27 species of mammal. Doing the activity, you make graphs of these attributes. This dataset is problematic in a number of ways, and does not smell like data science. Nevertheless, it’s a good place to start.

What we’re calling attributes you could just as well call variables or even column headings. Sometimes I will use variable when my audience is likely to understand what I mean, and when attribute might make them pause longer than I want. Why “attributes?” See this section from a later chapter.

When you first make a graph, the points appear randomly (but they still represent the data; try clicking on one and see what happens in the table). To organize the points, that is, to make a meaningful graph, do what we always tell students to do when making graphs by hand: label your axis, that is, drag a label—the name of an attribute—from the column heading to an axis of the graph.

The “Starting CODAP” Lesson

You could conceivably assign this for homework so that students “hit the ground running.” But it also works well simply to give them the link in class and let them do the task together.

  • Encourage talking to others.
  • Walk around and make sure everybody is eventually making graphs; at the end everyone should have bivariate graphs—different attributes on the two axes. These could be scatter plots or parallel dot plots.
  • If students are having trouble, have other students help them before you do.

The underlying point is that students do not need you to explain things. They can figure out a lot by themselves, and in collaboration with other students.

They should be secure in making graphs in just a few minutes. Stop them from spending too much time with this data set, and maybe lead the class in a discussion. Some possible issues:

  • Did anybody get lots of colored points in your graph? How did you do that? (“Plop” an attribute into the middle of a graph)
  • The graph of Speed and the graph of Diet are qualitatively different. How? Why?
  • What happens when you click on a point in a graph? (The same case gets selected in the table—and in any other graphs)
  • What happens when you hover over a point in a graph?
  • What does one row of the table represent? (Importantly: a species, not the common response, an animal.)
  • How do you change the size of the points in a graph? (It’s in the “paintbrush” palette. But maybe don’t tell them; Let somebody discover it and tell the class.)
  • Why are there no birds in this dataset?

These discussions have multiple purposes. They help students listen to each other and feel part of a community. And they also let you highlight software features that students will need to know about. Ideally, students highlight these features to each other, so it’s not always your voice.

This is important because students will go in different directions. If we wrote instructions for everything students might need, we would forever be teaching features and never get to exploring; furthermore, many students would be bored. So we delay learning about some features until students need them or discover them by accident. The best transmission is often viral: Zak sees that Annabelle has a graph with colored points, so he asks her how she got them. Then, in the discussion, she gets to tell the class and we can step in with the cool enhancement: here, in the paintbrush palette, is where you can change the colors. Everybody will remember.

  1. Teachers and other oldsters, just in case this is new: TL;DR means “Too Long; Didn’t Read.”↩︎