What do Katy Perry, LeBron James, the terrorist group known as ISIS, Pope Francis, and the students in my introductory course on business statistics have in common? All are Twitter users.
Katy Perry has over 67 million followers, while my statistics students are barely out of single digits. Yet their goal is the same: to share their interests and establish their "brand" in 140-character bites.
Much like a museum that carefully chooses its exhibits and preserves its collections, Twitter users also have a curating role, choosing what to share and establishing a presence through their tweets and followers. Many Twitter users also take on educational missions, producing news, reporting on research, and attempting to influence the conversations of the day through their arguments and supporting evidence. With that latter goal in mind, in 2013 I began requiring my students in introductory statistics to engage with the Twittersphere.
The teaching of introductory statistics is often not pretty. My own journey started more than 25 years ago, when a "real world" example of statistics in action might consist of pulling black and white marbles out of urns, with little thought to the relevance or appeal of the exercise. More recently, there has been a push to make introductory statistics classes more relevant, with textbooks that contain more realistic, yet highly stylized examples of how statistics are used in the business world. But even with fresher material, I found that when I asked students to apply those concepts outside the course, many could not. While they were often getting the math part, they weren’t getting the statistics part.
It finally dawned on me that since statistics is at heart a contextual science, and since my students had zero business experience, I was doubling their intellectual load. I was trying to teach 18- and 19-year-olds about business and statistics at the same time. I needed to do something different, and that’s where Twitter entered the scene.
I was inspired by Hans Rosling, a Swedish academic who is a statistics and Twitter superstar, to take advantage of social media. Rosling (@HansRosling) is a global-health expert with 222,000 Twitter followers. Organizers of the TED Talks have said that "In Hans Rosling’s hands, data sings." Indeed, data can be beautiful, and Twitter can bring its beauty to light in a way that speaks to my students’ social-media DNA.
My interest in Twitter was also piqued when a colleague showed me how Twitter allowed easy access to credible sources of news and information. After establishing an account (@ferristician), I was initially intimidated, but I soon learned that while half of my students already had Twitter accounts, very few were familiar with what I’ll call its knowledge-generation side. I actually found this both surprising and reassuring, as it created a "we’re all in this together" atmosphere.
I require my students to open a new Twitter account for the course so their focus can be professional. They must find and follow 10 new organizations a week (until they have 50) that use statistics prominently in their Twitter feeds. Examples include The Wall Street Journal, Pew Research Center, The Economist, the science journal Nature, and FiveThirtyEight, a blog founded by the statistician Nate Silver. All of these have highly active Twitter accounts and frequently link to content that uses statistics as evidence, such as news articles or research studies.
Students must post seven statistical tweets a week. Every week I assign different topics to study and tweet about. By the end of the semester, students have produced an account with more than 50 statistical entities and around 100 statistical tweets. Some recent student tweets, for example, have linked to research on the mental health of college students and the costs and benefits of drinking alcohol. Several students have gotten job and internship offers based on their Twitter activities.
Since we are a Jesuit university with a social-justice mission, I assign one or two tweets a week focused on some statistical aspect of poverty, such as poverty and violence. (One student tweeted statistics from the radio program Marketplace on the economic costs of violence in Chicago.)
Students must also retweet two of my tweets each week so they know what issues I am covering in my feed. Finally, they must come up with two or three tweets of their own by choosing statistical topics of interest, such as upset probabilities in the NCAA basketball tournaments.
If students are required to produce something tangible, they will take an assignment more seriously. So I require a weekly written assignment, worth 15 percent of a student’s grade. Every Tuesday students must choose one of their weekly tweets and do the following: (1) Write two sentences summarizing the article they chose to tweet about; (2) Write another two sentences evaluating the credibility of the article and its sources; and (3) Come up with two questions about the article.
I start class by breaking students into groups of three to discuss their write-ups. I then take 10 or 15 minutes to randomly call on students to report their findings, and I ask follow-up questions. Random calling is the enforcement mechanism: It is extremely rare to have a student not complete the assignment.
Throughout the course, I model critical-thinking skills, while providing a rich tapestry of statistical facts and evidence about the world. My students leave the course with a more nuanced and fuller understanding of the context in which statistics are used, having practiced evidence-based thinking. From a pedagogical point of view, this is a form of flipping the classroom.
Here are a few of my students’ comments regarding the Twitter assignment: "I liked that the Twitter assignments made us look at real issues happening in the world now and look at them through a statistical lens."
"I appreciated the course’s focus on challenging/being critical of statistics." "I think the Twitter assignment was cool b/c we got to use a social media website."
Using Twitter in the classroom gives students a direct connection to an unlimited number of interesting statistical applications that could never be replicated in a textbook. We professors need to take advantage of these resources that we could have only dreamed of 25 years ago.