Fun Ways to Get Kids to Generate, and Manipulate, Their Own Data
When students generate and graph their own data, they become more engaged in the work—and come to see math as a tool to make sense of their worlds.
Lately, the students in Michelle Russell’s high school statistics class in Alabama use the same phrase to describe how they feel about math: “sooo boring.” Teachers have always had to contend with the anxiety students feel in math class, but Russell, a veteran instructor, says the “this is dull” attitude students now bring to the subject has made her rethink her strategy. “If they think math’s boring I need to do a better job showing them it’s not,” Russell writes in a recent article for MiddleWeb.
Math teachers have too much material to cover in a school year; the demands of the curriculum limits the time they have to explore concepts deeply and provide students with the time to struggle, make mistakes, and experience the satisfaction of finding a solution. And too often, when teachers attempt to make the subject matter interesting they mix math problems with unrelated activities—like scavenger hunts. “That’s not letting students see that math is fun,” Russell writes. “The scavenger hunt is the fun part, the math is the boring part.”
One way to make the actual math engaging is to get students involved in generating the data that they’ll be using to explore statistical concepts—all the more engaging if the data tracks their own habits and behaviors.
Students can work with data like measurements of time or distance, frequency, or sums of money. But Russell says it’s always easier to get students enthusiastic about graphing and analyzing data if they’ve had a hand in creating it. “No matter how simple the activity is, students are more engaged when they are collecting and examining their own data,” Russell writes.
The “Blind Stork” Test
Sarah Carter, a high school math teacher in Oklahoma, suggests using the Blind Stork test to create a large data pool for students in a way that will have them laughing and smiling as they work.
The setup is simple: Students pair up, then one student times the other as they close their eyes and see how long they can stand on one leg, then they trade places. Using an online data storage tool, like Google Sheets, students repeat the exercise as directed and input their values in a shared Google Sheet. By the end, the students have collected a large pool of data to manipulate statistically.
Carter, for example, asks her students to find the five number summary of the data—the smallest data value, the first quartile, the median, the third quartile, and the largest data value—and solve for the interquartile range. Once they have found that range, Carter gets students to do a check to see if any of the measurements count as outliers in the data set and attempt to explain the absence or presence of those outliers—getting them to do the hard work of making sense of large data sets.
Jessica Thomas, a high school math teacher in Morgantown, West Virginia, told Edutopia she created the "Statistics Olympics" to get her freshman students engaged as they worked on various graphs, charts, and statistical computations.
On the first day of the Olympics, students in each of her two classes complete a range of challenges meant to create a pool of data. Activities include a typing test measuring how many words they can type in a minute, an online math facts quiz to see how many questions they can complete in a minute, or a simple high jump competition.
Each student completes each challenge at least three times, and at the end their data is submitted into a class pool and stored using Google Sheets. Students in each class are then placed into groups to analyze and distill meaning from the results.
For example, students calculate the mean, median, and mode of the amount of words the students typed in one minute; they then move on to more advanced concepts like the standard deviation to better understand the distribution of each classroom’s data.
In other cases, students might analyze the data to determine the type of graph that best unlocks its secrets and helps them effectively analyze both classroom’s performance in a given challenge. Thomas says students can find themselves trying out numerous graphs she’s previously covered, such as relative frequency histograms, dot plots, or box-and-whiskers plots.
In the end, Thomas said she asks each group to determine which class performed better during each particular challenge—the winners of the proverbial Olympic medals—and explain their reasoning using their data visualizations.
Lauren Hawkins, a high school instructional coach in Richardson, Texas, told Edutopia she regularly uses popular candy to get students thinking about complex statistics. One activity uses Hershey’s Kisses to teach students about the Law of Large Numbers.
To start, students toss a Hershey Kiss at least 25 times; each toss represents a trial. Each trial is then recorded on a Google Sheet indicating whether the Kiss landed on its side (1) or its bottom (0). Using the Cumulative Sum function, Hawkins said students estimate the probability, in the long run, of a Hershey Kiss landing on its side and create a line graph to visualize the likelihood. The lesson kicks off a discussion of the Law of Large Numbers—the idea that if students continue to perform the same experiment a very large number of times, the average of the results will get closer to the expected value.
With Tootsie Pops, Hawkins told Edutopia she gets students to estimate the true average amount of licks it takes to get to the center. After each student is given a Tootsie Pop and logs how many licks it takes them to get to the center, students might create and interpret a confidence interval to find a statistically reliable range of licks it actually takes to get to the lollipop’s center. In a blog post explaining the activity, Hawkins writes that the point is to emphasize that although the actual average amount of licks to the center is hard to pinpoint, by using statistical methods the students can narrow their estimates by providing a range of possible answers.
Hawkins writes that she can build on students’ understanding and interest in confidence intervals to tackle bigger questions such as: What is the average life expectancy in the United States? Or what percentage of the world is covered in water? “In statistics, it's about getting on the dart board—not the bull's eye,” Hawkins writes, adding that these activities teach students that although they may never know the true answer to a hard question, they can use graphs, charts, and functions to draw informed conclusions.
“It’s a rare glimpse into the power and insight that only mathematics can provide.”