On researching activity tracking to support learning: a retrospective
| Published date | 14 January 2019 |
| Pages | 133-154 |
| Date | 14 January 2019 |
| DOI | https://doi.org/10.1108/ILS-06-2018-0048 |
| Author | Victor R. Lee |
| Subject Matter | Library & information science,Librarianship/library management,Library & information services |
On researching activity tracking
to support learning:
a retrospective
Victor R. Lee
Utah State University, Logan, Utah, USA
Abstract
Purpose –This paper aims to discussresearch and design of learning activities involvingactivity tracking
and wearableactivity tracking technology.
Design/methodology/approach –Three studies are summarizedas part of a program of research that
sought to design new learning activities for classroom settings. The first used data from a qualitative
interview study of adult athletes who self-track. The second used video excerpts from a designed learning
activity with a group of fifth grade elementary students. The third study draws largely on quantitative
assessmentdata from an activity tracking unit enactment in a rural sixth grade class.
Findings –Activity trackingappears to provide opportunities for establishingbenchmarks and calibration
opportunitiesrelated to intensity of physical activities. Those featuresof activity tracking can be leveraged to
develop learning activitieswhere elementary students discover featuresof data and how data are affected by
different distributions. Students can show significant improvement related to statistical reasoning in
classroominstructional units that centralize the use of self-trackeddata.
Originality/value –As activity tracking is becoming a more ubiquitous practice with increased
pervasiveness and familiarity with mobile and wearable technologies, this paper demonstrates a topical
intersection between theinformation and learning sciences, illustrates how self-tracking can be recruited for
instructionalsettings, and it discusses concerns that have emergedin the past several years as the technology
related toactivity tracking begins to be used for educationalpurposes.
Keywords Quantified self, Activity tracking, Elementary statistics, Personal informatics,
Self-tracking, Wearables
Paper type Research paper
Introduction
It has become more common to see individuals of certain means sporting wearable devices
that assist in their personal tracking of their physical activity. Often, these devices take
the form of wristbands or smartwatches that track, at a minimum, the number of steps
taken throughout the day and the calories expended. More expensive models will
includefeaturessuchasheartratemonitoring, sleep detection, amount of time spent
sitting versus standing, number of floors equivalent climbed, minutes spent exercising,
Members of the research team who contributed substantially to the work described here include Joel
Drake, Ryan Cain, Jeffrey Thayne, Mary Briggs, Kylie Williamson, Michelle Berry, Ralph Trumble,
Brad Buccambuso, Jon Thomas, Ani Aghababyan and Scott Smith. The author thanks Rebecca
Reynolds and anonymous reviewers for feedback on earlier drafts. The author is grateful to teachers,
students and participants in the various studies described. The work presented in this article was
supported by a grant from the National Science Foundation under Grant No. DRL-1054280. The
opinions expressed herein are those of the author and do not necessarily reflect those of the National
Science Foundation.
Activity
tracking
133
Received13 June 2018
Revised26 October 2018
26November 2018
Accepted29 November 2018
Informationand Learning Sciences
Vol.120 No. 1/2, 2019
pp. 133-154
© Emerald Publishing Limited
2398-5348
DOI 10.1108/ILS-06-2018-0048
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2398-5348.htm
specific workouts completed and locations traversed by way of GPS technology. The
primary market for these technologies has been adults with disposable income who
were seeking to pursue active lifestyles and maintain a level of ongoing fitness and
health in pursuit of wellness.
Several years ago, just prior to activity tracking wearables becoming commonplace,
my research group had begun a program of educational inquiry and design that
examined the potential of these technologies to be sources of data that youth could collect
and examine to support learning with and about data (Lee and Dumont, 2010). The
underlying assumption had been that youth would be more knowledgeable about the
data because they had produced it and had direct firsthand understanding (Hug and
McNeill, 2008) of the activities that were represented by the data. Our first target
population to help us examine those assumptions had been high school-age youth who
used chest-worn heart rate monitors (built by Garmin) that communicated with
wristwatches to log beats per minute based on electrical conductivity. At the time, the
data transfer process was more onerous than what is required today, with today’s
technology typically involving a Bluetooth data transfer to a smartphone that happens
regularly in the background of other activities. Back when that work began, obtaining
records of electrical impulses from one’s torso to infer heart rate was already cutting edge
for a commercial wearable technology. To enable pilot students to examine the data, a
specialized synching cradle that connected to a desktop or laptop computer had to be
used. The computer that received the data needed specialized proprietary software for
the data to be stored and viewed in any meaningful form. Now, those data are stored in
the cloud. The data are viewed in custom apps with encouraging messages and prompts
to be more active and earn badges for meeting goals that are configured into each device.
Everyday conversation around activity tracking has shifted from “what is that thing
around your wrist?”to “have you met your step goal today?”and “do you like that model
better than the rival activity tracking technology?”.
Regardless, my research team had different considerations in mind when beginning
work with activitytracking technologies. Rather than focus on whetherpeople were meeting
fitness goals and whether the technology was effective at promoting wellness, we were
curious about the questions that youth would pose if given access to such technology and
how data about one’s own activity could facilitate ways of thinking that were valued in
mathematics and science. Indeed, we found through our earliest forays that students who
were obtaining data from chest-worn heart-rate wearables began to interrogate the data
based on what they alreadyknew about themselves and physical activity. At the time, these
technologies were used predominantly by athletes and fitness enthusiasts as personal
training tools. In our original case study that represented our first published work on the
topic (Lee and DuMont, 2010),we documented how a pair of teen girls who were asked to
determine what activity was making them work harder, according to heart rate data,
showed evidence of new learning about how to examine data. The pair that we studied
had collected data from some common outdoor play activities (i.e. throwing a Frisbee
and playing the basketball game “HORSE”) and started their investigation by focusing
on maximum values obtained in a single minute. Whoever had the highest single value
was seen as having done harder work. However, they shifted to looking at where there
were greater density of data points. Basically, they transitioned to considering more
aggregate properties of the distribution of data points instead of making judgments
based on a specific data point. What enabled this shift was personal views of who was
more or less athletic and how simply looking at maximum values conflicted with their
views of themselves. Also, their recall of the specific activities contributed, with
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