Let's Talk Titles!
By: Kristin Hunter-Thomson
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What titles should students be putting on their graphs, charts, etc.?
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What makes a “good” title?
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Why can’t they remember to put on/look at the title?
I often get questions like this from teachers/educators frustrated around their students’/learners’ practices when it comes to titles for their data visualizations*. The answers depend on what we are showing in our data visualizations, but for a quick foreshadowing rarely (if ever) is the answer to repeat the names of the axes that are already labeled with a “vs.” in between.
So let’s take some time to unpack “the title” to explore why we use them, how do titles differ depending on what we are using them for, and how we can support students in including/reading the titles.
Why do we use titles?
There are two main ways that we often use titles with data visualizations:
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To get familiar with what data are there in the visualization.
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To communicate/show something specific from the data.
Ok, but what does that mean for what kinds of titles my students/learners should be using? Let’s explore this further.
How do titles differ depending on their use
1. TO GET FAMILIAR WITH WHAT DATA ARE THERE IN THE VISUALIZATION
When we are getting familiar with what data are there in the visualization it is important to know some context about things like: what variables are included (especially if they are not labeled on the axes), where and/or when the data were collected, how were the data collected, etc. This metadata — data about the data — helps give you a sense of what you are looking at. It helps the wheels start to turn in our heads about what kinds of questions we could ask/try to answer from the data. It orients us to what is and is not there in the data to help us set our expectations as we dive into exploring the data.
In essence, this is the information that we need to start to make sense of the data. These are the kinds of titles that we, and our students/learners, should be using when:
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we (teachers/educators AND students/learners) are presenting a data table of data collected in an investigation,
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we (teachers/educators AND students/learners) are iteratively making quick graphs as we are exploring our data (think Exploratory Data Analysis),
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we (teachers/educators) are giving our students/learners a graph and asking them to draw conclusions/make a claim from the data (and we do not want to direct them towards a specific conclusion/claim).
Here on the left is an example of a line graph from The New York Times that is set up for you to interactively make quick graphs to explore the data, and thus the title is all about getting familiar with what data are in the visualization. Notice the y-axis is not labeled, but much of the information that you need to make enough sense of the data to start playing around and making graphs is included in the title.
“Do insects prefer local or foreign foods?” Data Nugget worksheet, available at http://datanuggets.org/2014/01/do-insects-prefer-local-or-foreign-foods/.
And here on the right is an example of a data table from the “Do insects prefer local or foreign foods?” Data Nugget worksheet for students to use the data to answer questions and make a graph, and thus the title is all about getting familiar with what data are in the visualization. Notice the title adds information (what numbers are included in the cells “Average Proportion Leaf Area Eaten by Herbivores”) as the table is oriented in a wide format rather than a tall/tidy format, and thus this information is critical to know when trying to plot the data and answer the worksheet questions from the data.
2. TO COMMUNICATE/SHOW SOMETHING SPECIFIC FROM THE DATA
When we are communicating/showing something specific from the data it is important to lead with the conclusion to make it as easy as possible for the reader to get and remember your takeaway. Many journalist, politician, or communication specialist will tell you that to best communicate your message you should start with the takeaway, aka what you want someone to care about. We have already taken the time to make sense of the data and we are presenting it in an explanatory format…therefore we stake our claim in the title, aka state what is going on in the data. In the field of data visualizations, this is often accomplished by a short title of the claim and then a longer subtitle to provide the context for the claim.
In essence, when it comes to communicating with data spell it out really clearly for the reader in your title. These are the kinds of titles that we, and our students/learners, should be using when:
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we (teachers/educators AND students/learners) are sharing our claim/conclusion from the data (think Explanatory Data Analysis),
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we (teachers/educators AND students/learners) are presenting a final version of a graph/chart/plot from our work towards the end of a project (e.g., Science Fair),
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we (teachers/educators) are giving our students/learners a graph and asking them to evaluate the conclusions/claims made by others from the data (and we do want to direct them towards a specific conclusion/claim).
Here on the left is an example of a line graph from The New York Times that is set up for you to interactively adjust the graph to see the authors conclusion that “strikeouts are on the rise” in baseball. Thus this title is all about communicating/showing something specific from the data. Notice the y-axis is again not labeled, but the information that you need to make sense of the data to see how the number of strikeouts per game per team are increasing is included in the title, subtitle, and legend.
http://www.storytellingwithdata.com/blog/2014/04/exploratory-vs-explanatory-analysis
And here on the right is an example of a horizontal bar chart from Cole Nussbaumer Knaflic (2014) for readers to see quickly what the two two issues were communicated from a survey. Thus the title is all about communicating/showing something specific from the data. Notice the title and subtitle give you information about what the survey was asking, and the colors between the graph and title align to direct your idea to see the takeaway message. While not for a lesson plan exactly, the same principles can apply to our teaching with data.
How we can support students in including/reading the titles?
Beyond teaching our students these skills, we also need to assess their abilities and provide them feedback to help them along their path towards mastery of this and other data skills. Check out our Example Graphing Rubric document (if you like it, Make a Copy or Download and use it for your purposes with attribution).
The document outlines suggested aspects to include in a rubric for a graphing exercise, in terms of categories and expectations of students execution of each category successfully. Depending on what you are asking the students to do themselves, versus providing for them, the actual rubric you will use will vary.
All of the expectations (aka rows) are applicable for students in grades 3-12. However, the expectations italicized below will vary across grade levels. For example, the number of graph types that students can choose from in Grade 6 is less than in Grade 10.
*Here “data visualization” means any way that you visually represent and organize data (e.g., graph, chart, table, map, plot)
