Wearable Tech Weaves Its Way Into Learning

Wearable Tech Weaves Its Way Into Learning

Eye-trackers that detect when your mind is wandering. Clothes that let you “feel” what it’s like to be in someone else’s body. Sensors that connect your heart rate to how engaged you are in class. These are the kinds of wearable technologies that could soon impact how we learn.

That was the takeaway from a recent gathering of researchers studying how personal data might improve learners’ self-awareness and performance. At the first ever aWEAR conference on the use of wearable technologies in education, held this week at Stanford University, experts shared how self-tracking tools like Fitbits and motion sensors might give humans insight about the way they learn.

While it’s become a habit for people to count their steps or log their hours of sleep, similar “quantified self” practices in education are in early stages of development.

Ralph Mercer, a researcher at The Open University in the UK, sums up what education experts imagine as they experiment with wearable tech in K-12 and college settings: “Is it possible to self-track our learning journey? Can we figure out what made one learning day better than another one? Can we make that data visible in a meaningful and academic way?”

To understand how self-monitoring devices might impact education, first we need a definition of these technologies. According to Rich Voithofer, associate professor of educational technology at Ohio State University, wearables are an “intimate two-way interface between ourselves and the world.” Unlike a computer or cellphone that we choose to interact with, wearables collect information about us automatically, and they might give unsolicited prompts to take action. Think of a Fitbit that softly nudges you to get up from your desk and take a few steps every so often.

As the cost of wearable technologies continues to decline, researchers have more opportunities than ever to study the relationships between human physiology and learning. Is there a correlation, for instance, between heart rate or skin temperature and engagement in class?

“We’re trying to get at mental states that can be somewhat inferred through the body,” says Catherine Spann, a researcher at the University of Texas at Arlington’s LINK Research Lab. She and her colleagues outfitted students with Empatica’s E4 wristbands that measure heart rate variability and electrodermal activity—a measurement that indicates emotional responses. The idea is to better understand how “emotions that are felt in the body” impact learning.

At SUNY Oswego, assistant psychology professor Roger S. Taylor has been tracking students’ heart rates to see how they relate to emotions throughout their days in class. Every three hours from 9 a.m. to 11 p.m., a text message prompts students to enter their heart rates and answer questions to put those numbers in context, including “what are you feeling” and “are you in a small or large class?” By mapping students’ emotional states over time, Taylor hopes to get a better understanding of the relationship between learning and feelings.

Researchers are even studying how posture might relate to learners’ ability to retain information. By planting Microsoft’s Kinect motion sensors in classrooms, Chadi Kari and colleagues at the University of the Pacific are tracking 48 skeletal positions of students. “Can we correlate sitting posture and the attention of students?” Kari asks. “Are some activities better at reinvigorating students?”

Another way to bring wearable tech into the classroom is to empower students with their own data. Drawing on Peter Drucker’s “if you can’t measure it, you can’t improve it” theory, educators are thinking about how wearable technologies might spur introspection among students. If a learner can see physical signs of her learning in real time, could she make adjustments similar to how a Fitbit owner might choose to take a few extra steps?

In some cases, researchers posit that students will learn better when they’re analyzing their own data—as opposed to hypothetical numbers from a textbook. Victor Lee, associate professor of instructional technology and learning sciences at Utah State University, studied elementary school students who—outfitted with personal health trackers—analyzed their heart rates and step counts after they walked uphill and downhill. Those students performed better in statistical reasoning than peers who analyzed numbers from textbook prompts.

As with any emerging technology, ethical questions abound for the use of wearables in education. Who has access to learners’ data, and for what purpose?

“Ethics often falls behind the technology,” says Voithofer of Ohio State. Personal data becomes more abstract when it’s combined with other datasets or reused for multiple purposes, he adds. Say a device collects and anonymizes data about a student’s emotional patterns. Later on that information might be combined with information about her test scores and could be reassociated with her. Some students might object to colleges making judgments about their academic performance from indirect measurements of their emotional states.

Before researchers, educators and companies implement wearable technologies in learning environments, Voithofer warns them to carefully consider how data is gathered and used. “We need to develop our ideas of information transparency as we integrate wearables into education,” he says. “Transparency is central to ethical accountability.”

It’s worth a reminder, too, that not everything that counts can be measured. An over-reliance on data can lead researchers to make false assumptions about how students learn.

“Students come into the classroom with many thoughts and feelings, and social, family and financial issues,” says Spann, from UT Arlington’s LINK Lab. “They are a whole person, and it’s quite important to keep that in mind.”

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