This is Part 2 of a multi-part post. Read Part 1 here. In short, some colleges are purchasing technology based on smartphones to track student movements.
At the end of Part 1 on student surveillance, I wonder how this tricky issue will play out as schools and students find common ground.
In this post, I focus on another side of the conversation, which is how disruptive cellphones have been to the classroom learning environment. Technology Review has an article touching upon this recently, and I’ve also heard off and on from colleagues complaining about these trends.
The philosophy professor who wrote the article enticed 12 students to give up their phones for nine days. (The fact that they had to be bribed with extra credit to do so is itself revealing.) One of the students wrote: “One of the worst and most common things people do nowadays is pull out their cell phone and use it while in a face-to-face conversation. This action is very rude and unacceptable, but yet again, I find myself guilty of this sometimes because it is the norm.”
This behavior is also spreading to the classrooms. The professor estimates that 70 percent of the students in his classes at any time are using their phones. How does the professor feel when students start texting each other in the middle of a lecture? Are the students expressing confusion or worse, boredom? Has s/he misspoken, or said something unintentionally funny? One of the main advantages of in-class learning is the continuous feedback through body language and facial expressions – this is lost when students are preoccupied with, or snickering about, something unrelated to the class.
One drastic solution is to ban the phones. Are there less extreme measures?
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In the same way that “smart” phones and devices reveal locations, with the appropriate software, they can also reveal whether students are using their phones during class, how frequently they are doing it, and what apps they are running. The first version of tracking software might inform the professor "Student D came to class late by 2 minutes” but the next version will say “Student D spent 16 minutes in your class today playing League of Legends”.
The debate around where to place the limits should be based on what these technologies can do, not just what actions are built into current versions of the software.
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For data analysts reading this, realize that even if the data say someone was present in the auditorium, you don’t know that for a fact. You only know that the “smart” phone was there -- the person who owns the phone might not have been.
“Smart” phones are already disrupting lectures. But watch out for the day when totes of smartphones show up in lecture halls!
P.S. As a statistician, I can’t help but point out the iffy science behind this Technology Review article. The professor created an extra-credit assignment because he surmised that cellphone usage depressed his students’ learning ability. He then “paid” volunteers to conduct this exercise. The paid volunteers reported that being without the phones made them more productive, confirming the expected effect. This methodology is like an airline sending you a customer satisfaction survey after paying you for volunteering to vacate your seat on their overbooked flight, and then offering frequent-flyer “status” as a reward for filling out the survey.
Since I’m sympathetic to Professor Srigley’s conclusion, my skepticism didn’t come as fast or as strongly as when I disagree with the finding. This is a type of confirmation bias that data scientists have to guard against.
P.S. [1/23/2020] Part 3 is now up. In this new post, I deal with the other use case of student surveillance data - predicting student behavior.
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