Jack Dougherty, Educational Studies
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Overview and Context
About the course
The Cities, Suburbs, and Schools seminar is an upper-level undergraduate class of between 12 to 18 students. As a prerequisite, students must have completed the introductory-level educational studies class or have come from other majors such as public policy, American Studies, or Urban Studies. About half of the class are Education Studies majors, and about half are from other departments on campus. I have taught this course about 9 times since 2002.
Key QR Assignment Description (links to section in this page)
How Quantitative Reasoning (QR) and Literacy are approached
I'm trying to shift people from consumers of data to becoming producers of data, and therefore more critical consumers as well.
While I typically use the terms "quantitative reasoning" and "quantitative literacy" interchangeably, when asked to make a distinction, I view quantitative reasoning as higher-ordered thinking compared to literacy. To me, literacy usually means comprehension, whereas reasoning means the ability to make an analytical distinction; it is a more sophisticated thought process.
The assignments we do early on in the class typically focus on reading data, which is more about literacy. But when we move on to "how to lie with charts" and "how to lie with maps," I am pushing my students further into reasoning. When students realize that anyone can easily manipulate how data is presented, and how this strongly influences the conclusions people draw, they think more critically about data.
Motivation to integrate QRIt's personal and institutional. Personally, I think data visualization is fascinating, especially when you can present the same information in different ways. And institutionally, I believe that too often it's easy for students in a liberal arts college to avoid numerical data. Sometimes students need to realize it's such a rich contribution to multiple ways of thinking.
In my academic unit at Trinity, the goal of the research project course requirement is to help students work as a group where they identify a researchable question and come up with insightful ways of answering it with persuasive primary source data. One example is the Connecticut Fair Housing Project. They asked our seminar to identify patterns in ten years of housing discrimination tester reports that they had collected--about 1,000 pages--and my students learned how to do thematic coding in a shared spreadsheet, divided the labor, and wrote interpretations of how housing discrimination had changed over time, based on real data.
In my view, a research project course requires more than being able to read prior studies or doing library-based research. We also want undergraduate experiences to focus on primary-source learning.
In the Cities, Suburbs, and Schools seminar that I typically offer each fall, I try to choose collaborative research projects that uncover relationships between schooling and housing. Sometimes we do simple quantitative projects, or sometimes qualitative or historical projects But they all have something to do with schooling, housing, and how those two entities come together and shape so much of how America works.
Pedagogic approaches used
My advice to college educators. For at least one class you teach, think of that classroom as a place where people come together to learn, rather than a place where you pontificate. When a college classroom becomes a place where students--and you--are creating knowledge, then you can begin to rethink how to maximize your time, energy, and physical layout to deepen and enrich the learning process.
I teach Cities Suburbs & Schools as a once-a-week, three-hour seminar, with drop-in hours later in the week for people to come back and get more computer help. Sometimes during the three-hour seminar, we'll have workshop time where we're working on trying to make data come alive with Google thematic mapping. I'm not lecturing for three hours--that's not a good way to have students learn.
But I do need to give presentations, or students need to give presentations, or we need to have a close reading of a text, or thinking about the project we're working on, to move the learning further along.
Knowing the course is successful
I'm looking to see whether or not students are able to demonstrate that they grasp the concepts. For the assignments on manipulating and lying with data, they have to explain it in text, as well as show how they can take one piece of data and represent it in two diametrically opposed ways. Some semesters, it works better than others.
- The first exercise, "How to lie with charts," is listed as Exercise 6 on October 16th in the 2013 syllabus.
- The second exercise, "How to lie with maps," is listed as Exercise 8 on October 23rd in the 2013 syllabus.
The premise of the assignment is you can't be a good consumer of data visualization unless you understand how visualizations could be manipulated to fool you. The way to be a critical user of this material is to learn how to lie. Once you learn how to lie, then you'll be a much more critical reader of data visualizations created by other people.
"How to lie with charts." I used to call this exercise, "How to Lie with Statistics," based on the title of a 1954 book by Darrell Huff, and several other readings address this simple concept. When the point of the exercise is not about getting the one right answer, but different ways of lying or misrepresenting the facts, my students begin to think differently. Most quickly catch on to ways of manipulating spreadsheet tools to make a line charts appear flatter or steeper, based on the scale of the axis or the position of its starting point relative to the rest of the chart.
"How to lie with maps." As for manipulating a thematic map, that is a slightly more sophisticated thinking. I have them read a four-page excerpt from Mark Monmonier's, How to Lie with Maps. It's a good explanation of how the default range settings inside mapping applications shouldn't be trusted automatically. It is so easy to change the ranges, the cut-off values, and even the color to portray the same set of data through different maps.
For the map exercise, I give them student racial data of school districts in the metropolitan Hartford area, and ask them to create two different maps with the same data using Google Fusion Tables. One map should show severe racial segregation, and the other needs to display the appearance of racial harmony. The students come up with different ways of making the same data appear different ways based upon the data ranges, the number and position of cut-off points, and the color choice as well.
Students use an online tutorial that I created to show how to make a thematic map based on any spreadsheet of data they have paired with any boundary file. And that's the magic of it. Here in Connecticut we have lots of people who have freely accessible boundary files.
The problem is, how do you go through the steps of merging the spreadsheet data with the boundary file? So that's mostly what the tutorial does. It also shows how to take the interactive merged map and display it, not just in a static PDF, but to embed it on a webpage so that it can be shared, resulting in more added value.
My Trinity colleagues and I are trying to make more opportunities available for students who wish to do more with data and spatial visualizations. We're trying to create more opportunities for students to do paid summer internships with Hartford community partners, which we're pursuing funding for right now.
I've worked with non-profit organization staff who say, "I've got an hour. Can you and your students show me how to take my data and make a map with it?" And now I say, "Yes, we can." It's often a very simple data map, but that's where we start. That's what Google Fusion Tables does.
These examples show how Trinity students work with nonprofit organizations to collect data, visualize it, and help everyone to see numbers in a new light. A lot of my students start to realize the value of their liberal arts education when they start partnering with community organizations or agencies to display what their own data tells them in ways that previously couldn't been understood when it was only in tabular or chart form.
- Keeping up-to-date with the latest technology. The tools keep changing--that's good, but it's challenging, too. I am thankful that I don't have to teach ArcGIS like I used to do for the "how to lie with maps" exercise because it required me to do much more of the behind-the-scenes prep work to make something that students could manipulate. When I taught it with ArcGIS, I had to pre-join the spreadsheet data and map boundaries before my students could start to manipulate it.
- The tools got easier to work with, such as Google Fusion Tables. Now I have an exercise that is basically, "merge spreadsheet A with map boundary file B." The web tutorial I created works because it's an online do-it-yourself guide to merge any spreadsheet with the corresponding boundary file, which is easily shared on WordPress, the web publishing tool I began using about three years ago. Nowadays, I can visually demonstrate and explain map-making steps on a web page, better than I ever could do on a printed page, and I can easily update it when the tools change. Based on user statistics for my Trinity website, the Google Fusion Tables thematic map tutorial is one of the most widely-read items I've ever written, with over 5,000 page views (and an average time of 30 minutes spent on the page) over the past year.
- Creating new materials. Some things get easier, but the burden is still on me to learn this stuff. My graduate training is in educational policy studies, not quantitative literacy or data visualization. But I personally find it interesting, so I like to know about the best tools out there that are easy-to-learn, free or inexpensive, and preferably open-access. I have great instructional technology staff, and we're always comparing notes, but I create my own instructional materials. I probably put more time into this than I should. But other people around the world also find it to be of educational value, which is great.
- Student push-back. Another issue I encounter is that some students who take the class say, "I had no idea we're supposed to use computers in this class." And some will say, "I'm a math-phobe", or, "I'm a techno-phobe." It does take more time with these students. I've been very fortunate in past semesters to have an undergraduate TA who has already had the class, got a lot out of it, and gave back by working with the next class of students. Some students get turned on by data visualization and decide to take more courses in statistics or research methods or GIS.
- Don't reinvent the wheel. Find things that people are doing elsewhere which match with your curriculum, pedagogical interests, and the academic heart of your course. Find those that match rather than detract from it, and that actually helps you. If you're teaching about stratification, find data exercises and tools that enrich our understanding more than just textual descriptions or pre-fabricated textbook pictures.
- Take advantage of informal spaces if they are available. To help students outside of class, I used to sit in my office and wait for them to come and see me. But now, with everything on my laptop and their laptops, I can help students by being accessible in different places. I'll tell them, "I'll be at the coffee bar in the library from 3:00 to 5:00 today. Drop in there if you want help." People are much more likely to come find me in a public space than they will in my office. And they're more likely to work together and help one another in more public spaces.
- Find things that help you do what you're already teaching, but in a better way. There's lots of great material out there. I need to look more at the Teaching With Data web site; there is a lot of stuff on it that I haven't seen yet, and I should be studying more of it.
- Key assignment resource: How to create thematic maps with Google Fusion Tables This step-by-step tutorial demonstrates how to use Google Fusion Tables to create thematic data maps. (Link broken- http://commons.trincoll.edu/jackdougherty/how-to/gft-thematic-maps/)
- Syllabus for the Cities, Suburbs, and Schools seminar. In the 2013 syllabus, the two exercises referred to in this profile were Exercise 6: "How to lie with charts" on October 16th and Exercise 8: "How to lie with maps" on October 23rd.