Data Crunchers’ Delight
Use of online forms can enrich students’ inquiry and analysis and assist in peer assessments.
By Chris Rogers
I am co-teaching a course on experimentation methods. During one class, our junior mechanical engineers correlated a person’s height both to wingspan (fingertip to fingertip) and to birth month as a way to learn about means, standard deviations, linear fits, and even kurtosis. As one might expect, the correlation of the first two is quite good, whereas it is a little known fact that the month in which you were born does not determine your height. They predicted the skewness, found the R-squared value, and generally started the discussion around correlation and causation.
What impressed me was the speed with which we could get a personally relevant data set for the students to investigate. In the first few minutes of class, the students whipped out their phones and filled in a Google form. They then downloaded the resulting Google Sheet as a CSV file, pulled it into LabVIEW, and embarked on their analysis. In five minutes we were analyzing data. The larger the class, the better the data set. I was excited to see how quickly they started questioning the accuracy of self-reported data, looking for physical causes of correlations, and wondering about why the distribution of birth months was more bimodal than flat—was that a result of less than 50 students in the class or something else?
Online forms, such as the Google form, can be used in many ways in the engineering classroom. My colleagues use Qualtrics, Survey Monkey, Google, or other tools to get at student thinking and gauge class knowledge. How is the class progressing? What do they understand? What do they predict will happen? Is the class moving too fast? Real-time surveys like Mentimeter or Socrative allow students to vote or give an opinion on the spot for the entire class to see, allowing the teacher to get instant feedback on a question or idea. Forms that allow attachments can also promote the idea of data sharing. Instead of every team duplicating the same data set, the class as a whole develops a shared data set for analysis. One team might measure the heat loss in an aluminum fin, for instance, while other teams measure the loss in different materials. The forms act as a rudimentary data sharing scaffold, ensuring that everyone documents his or her experimental setup and standardizing the data storage format. It allows the students to think of a design of experiments (DOE) that includes the entire class rather than just a single team, providing substantially more data to analyze and compare. Again, a larger class (or multiple sections) only improves the DOE and the diversity of data sets.
Where I use forms the most, though, is in peer-to-peer assessments. Students can grade one another’s presentation, project, or journal paper, and as the instructor, I can define the rubric (or the rubric can be developed as a class). These grades can vary from a single rating (8 = good, 9 = excellent, 10 = I called my parents I was so impressed) to written assessments. Rather than grading 40 papers from students, the forms allow me to emulate the peer-review system in our journals. Students read and review three articles each, learning not only the review process but also how to critique both their own and others’ work. Students appreciate the ability to leave the typical confines of the traditional classroom (one expert who knows all) and more closely follow the assessment methods of the world outside college (where there is no one expert). When trying to assess students’ creativity, in particular, I find that the crowd-sourced assessment is always better than mine.
Forms help the instructor understand student thinking. They also catalyze critiques and allow students to share data. These are all vitally important parts of the engineering process. For these tools to be really meaningful, though, students need to be working on an authentic problem—one that does not have the right answer in the back of a book. Moreover, I have found solving authentic problems makes teaching more fun and the students always seem to appreciate it (based on the student reviews). And who knows? Maybe someday we will find that unexpected correlation, show it is causal, and then the class will get really exciting.
Chris Rogers is a professor of mechanical engineering at Tufts University.