![]() Looking for an Icebreaker for your first social science class? I've used a certain icebreaker exercise in my economics classes for years, and it never ceases to amaze me. I first go over the basics of how field studies and investigative science work: how scientists will propose hypotheses, gather data, identify correlations, and then attempt to explain causal relationships. I then ask the students (alone or in groups, depending on the class size) to develop a hypothesis that they might be able to examine by just studying the students in our class. Each student (or group) must then interview each and every student in the class in order to collect the two variables that they wish to examine. Do their classmates have any siblings? How tall are they? Do they wear corrective lenses? Do they wear a watch? How many languages do they speak? The possibilities are endless. The students plot the data they collect on a graph, and then present both their hypothesis and their findings to the class. The study / icebreaker portion of this exercise can take place in a single 80-minute class, and the presentations can generally be completed in the next class. Google Spreadsheets Serve Up Excellent Scatter Graphs in Three Easy Steps Google spreadsheets provide a particularly quick and easy way to illustrate a correlation between variables. If you have access to Google Apps in your school, then a Google spreadsheet can plot the data points and illustrate correlations in three easy steps: Art Lightstone ![]() ii) Highlight just the two columns of data (without any names), and then click on the "Chart Wizard" button. You will see a variety of chart options, but click on "more" chart options to find the scatter graph option. (You must select the "scatter" graph option to plot correlations between variables.) ![]() i) Set up three adjacent columns: the first column being for the names of the students interviewed (so the interviewer can track who she has and hasn't interviewed), and the next two columns being for the two variables that are being analyzed. ![]() iii) Click on the "Customize" tab and then scroll down to exercise the options of setting your chart title, naming your X and Y axes, and even generating a line of best fit. (The line of best fit is a particularly handy feature of Google spreadsheets that Google had previously been criticized for not including. As you can see, Google Apps are constantly evolving.) These mini-studies are a great way for students to meet and learn about each other while also exploring the tools of investigative science. Every class will inevitably find themselves exploring issues of correlation, causality, sample bias, split effects, and even post-hoc fallacies. Try this the next time you're looking for a way to break the ice in your social science course, and let me know how it goes. Please note: While computers help, you don't need computers to do this exercise. I did this exercise for years before my school became a laptop school. You can download a PDF below that will facilitate a pen and paper version of this exercise. Over the years, I've seen my students make so many amazing discoveries right before my eyes. For example, did you know that people who wear watches tend to enjoy greater academic success in school? How about this one: Did you know that blue-eyed people tend to wear corrective lenses less than brown-eyed people? Finally, would you believe that people who speak two languages tend to do better in school than people who speak one - or even three - languages? These are just a few of the incredible findings that my students have unearthed during this exercise. While these are just correlations, not causations, they are still pretty amazing discoveries. ![]()
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The New Learner Lab
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