Students should recognize that some types of charts are more appropriate than others, depending on the nature of the data or the message the author is trying to convey. Teaching Tip Reading Strategies: Students can read individually, in partners, or as a whole class. The guide is not particularly long, but you’ll want all students to have had a chance to look through those pages before the discussion. Let students know ahead of time that you’ll be discussing the reading and ask them to pick one or two key points as they are going through. Make a table of good v. bad visualization characteristics Prompts: Following the principles of good data visualization, which one would we say is better? What makes the good one good and the bad one bad? As students respond, steer the discussion toward generating general characteristics of good and bad visualizations. Make a simple chart that everyone can see. Something like this… Good Bad simple easy to read a basic graph that makes a simple point …etc… complicated confusing colors too much text …etc… Wrap-up (15 mins) Data Visualization 101 discussion Remarks We’re going to be making some of our own visualizations of data very soon. To help us do that, we’re going to look at some helpful tips for effectively communicating with data visualization. Distribute: Data Visualization 101: How to design charts and graphs - Link . Students should read the first 4 pages of this document. Discuss: What are the key take-aways from this guide? Some key ideas that should come up: Choosing the right way to visualize data is essential to communicating your ideas. There are stories in data; visualization helps you tell them. Before understanding visualizations, you must understand the types of data that can be visualized and their relationships to each other. Certain chart types are right for certain situations, depending on the data. Remarks The Data Visualization 101 guide is a resource for you (students). The rest of the guide goes into some specifics of different chart types. You should keep this guide at your side as you review visualizations data, and when you develop your own in the future. Further Discussion Points: What else did we learn about data visualization today? What are the benefits of visualizing data? Can we characterize common mistakes in visualizations to which we gave low ratings? Can we characterize common strengths in effective visualizations? Not all visualizations were charts; what other types are there? As you embark on making your own visualization, what do you want to keep in mind so that you can avoid rookie mistakes? Assessment Assessment Posibilities
Assessment Idea: show students a visualization and have them analyze it, using the table of characteristics of good/bad visualizations to justify their opinion.