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Designing for Advanced Amateurs:
Beyond Badges and Couch-to-5K
Pawel Wo´
zniak
t2i Interaction Lab
Chalmers University of
Technology
Gothenburg, Sweden
[email protected]
Kristina Knaving
Department of Applied IT
University of Gothenburg
Gothenburg, Sweden
[email protected]
Abstract
In this position paper we postulate a shift in designing for
sports and physical exertion. Most past efforts in
Human-Computer Interaction (HCI) have concentrated on
how to persuade users to engage in physical activity in
order to change their lifestyle. We are engaged in
ethnographic work with runners and those attending
fitness classes. Based on our results, we posit that there is
a user group that has been neglected — those committed
to a training routine (advanced amateurs) are lacking
technology support. We describe how we envision a shift
from persuasion to reflection in designing for sports and
provide directions for the development of future systems.
We suggest that future design should concentrate on the
less-than-ideal aspects of running and rich qualitative
accounts of the running experience. This can be achieved
by stimulating reflection and sense making through new
ways of visualising running data and facilitating creating
narratives.
Author Keywords
Running, exertion, sports, race, competition
Copyright is held by the author/owners). CHI ’15, April 18th - April 23rd,
Seoul, South Korea. Workshop on ’Beyond Personal Informatics: Designing
for Experiences of Data’.
ACM Classification Keywords
H.5.m [Information interfaces and presentation (e.g.,
HCI)]: Miscellaneous.
Introduction
A growing interest in health has led to many efforts
centered on helping people with very little intrinsic
motivation for sports to start fitness activities. Since
running is low-cost and readily available for most people,
it has been one of the more popular entry sports with
dozens of commercial applications built to convince
people to start a running routine e.g through gamification
[6] or peer pressure [1]. In contrast, our research focuses
on how technology support for runners can move from
persuading to engage in physical activity to helping the
users who are already active reflect and make sense of
their regular sports efforts. Our idea is influenced by a
general trend in HCI of moving away from
theory-motivated persuasive interventions towards building
infrastructures for reflection [2].
Those who practice running regularly have a variety of
needs that require them to monitor and understand their
progress. We believe that providing advanced amateurs
with the means to reflect on their routines will not only
help internalise motivation (our past research shows that
this is crucial motivation goal), but also lead to an overall
improved quality of life. This is especially relevant when
one considers the different geographical locations
inhabited by runners and how the yearly cycles affect their
training. Furthermore, one cannot forget about race
experiences and how perceptions of feeling healthy are
altered by organised events.
Advanced Amateur Runners
When we studied runners these past two years, we have
focused on advanced amateur runners 1 , i.e. individuals
1 Many of the motivations mentioned in this paper are based on
our extensive ethnographic research of running communities. The
results of this work are now in submission.
engaged in a regular training routine with an intention of
participating in organised races. These running enthusiasts
are often perceived by others as very motivated — they
train relatively often and it a factor in how they plan their
lives. They also participate in longer races and always
strive to finish the race in the best time possible. This
perception may be why most technology designed for
these runners is focused on delivering numbers as-is, i.e.
geopositioning and pulse data with fairly basic graphs.
When interviewing advanced amateur runners on
motivation, it is clear that they are helped by intrinsic
motivations (e.g. ”I like running”), but also that extrinsic
motivation (e.g. ”I want to beat my personal best” or ”I
want to stay healthy”) are important tools that support
their everyday training routines. We also used the Sports
Motivation Scale [7] questionnaire, and the results
support this finding as well. Many of the interviewed
runners also mention the need to set a goal for training as
a main motivator for signing up to events. While
members of this group often report that they have to run
to feel good, they also note that it is sometimes very
tough to run and that they have lapsed in their training,
sometimes for years. Matching personal expectations is
hard and individuals are often unsatisfied if they do not
comply with their training goals. This, in turn, affects not
only the runner, but also their social environment. We
wonder how technology can alleviate this and we believe
that more sense making with running data can be of help.
The runners we interviewed found it difficult to find time
in their often very busy lives to go out running. While the
image of race preparation promoted by current running
phone app companies and sports stores is that of an
ideally dressed runner taking a mid-day run, our work
revealed that a more relevant image would be that of a
tired father squeezing in a 10pm interval training session
in the rain after the kids had gone to bed, or scarfing
down a quick sandwich in order to run during the lunch
hour. Running data is not complete without the context,
and this context is also one of the building blocks of
creating a personal running narrative.
An often cited reason for dissatisfaction is the weather
changes throughout the year, especially in countries with
moderate climate. Data has shown that many runners
skip running during the winter months, either making do
with gym sessions or mostly skipping physical workouts
altogether. Supporting advanced amateur running also
means supporting the training-event cycles throughout the
year, where planned training culminates in a race event,
both with very different needs and expectations from
technology. Our experience is that current technology
rarely take different goals and environments into account.
Figure 1: Example of the current
state of the art for running
applications. Simple maps and
elevation plots are not enough to
stimulate reflection and enable
runners to understand more
about their training routines.
Another reason is the fairly high number of sports related
injuries among amateur runners [9]. This was evident in
our supporter interviews, where a third of randomly
contacted supporters at a race informed us that they
wanted to run the race, but were injured, and by
interviewed runners talking about how they regretted past
injuries. Injured runners often talked about how they
planned to start running again, and stressed both the
importance of not over-extending as well as the fear that
the need to go out running would make them restart their
training too early. Unlike elite runners, who rely on
trainers and medical specialists, the runners we
interviewed rarely found that they were helped in their
decision to decide on the best time to start running by
health services. Since they are mainly guided by their own
knowledge, it is imperative that they have good decision
support to counteract their ambitions. By supporting
reflection and sensemaking, we hope that runners can
learn more about the patterns that lead to injury.
Gamifying fitness classes
Another advanced amateur group we are currently
investigating is those attending regular fitness classes
aimed at overall body development. We are engaged with
coaches and users participating in a programme where
participants complete a number of challenges to complete
quests similar to role-playing games. The coaches have
decided that the game is only accessible to those with
training experience, a minimum period of two months of
continuous attendance is required. The game is
paper-based — an overview board is available at the
training facilities and participants have their own paper
player cards. Figure 2 shows the current version of the
system.
Figure 2: The current version of the fitness class game with
user markers depicting the progress of each user.
This setting is quite different than working with runners.
The challenge for data collection and, consequently,
technology support for the activities is enhancing group
dynamics and promoting healthy competition. We are
now in a process of determining what the qualities of a
groups support system should be. Before the programme
began, we administered the Sports Motivation Scale
questionnaire to all participants and whenever a new user
joins the programme, they are required to complete the
form. The impact of the system will be measured by using
the questionnaire once again after six months. We are
now conducting regular semi-structured interviews with
the participants to monitor their progress and the impact
of the game on their training experience.
Initial interview data indicated that while the users have
different motivations to attend the classes (e.g. weight
loss, support of other sports, the company of others) they
all stress group support as the most important factors
that keeps them attending the exhausting training
routines. When asked about the toughest moments of the
training session, they often report thinking of the praise
and support of their training friends. We have also
observed that placing and moving the markers in the
game became an important group activity and users
reported the event as a source of motivation. Figure 3
shows the initial marker placement event. A question that
remains is how digital systems can be built to support
these types of interactions. Reflecting the human values
involved in group activities while still presenting the data
for analysis in training support technology remains a
challenge for interaction design.
Figure 3: Users gathered around the overview board for fitness
class progress. On this particular occasion, most users are
placing their markers for the first time and thus their starting
fitness level is determined.
Making Sense of Sports Data
The key to our proposed approach is an attempt to use all
of the data we can possibly gather about running and
create interfaces that will enable runners to understand
more about their training. Speed, pace, route length and
heart rate measurements are now easily accessible. Soon,
more sensors, such as advanced gait and foot strike clips
will be available. With an abundance of data produced by
every run and even more input generated by training
plans, we need to build tools that enable runners to
immerse themselves in the data and see the story of their
running among the data points. We propose using a
data-aware design approach [4] where runners are not only
enabled to curate how their running data is collected, but
also to analyse and process it for a variety of purposes.
Moving away from the map-and-elevation-plot model (see
Figure 1 for an example) we know see in most running
software can potentially be beneficial. For example, if we
can couple workout data with knowledge from physiology
and medicine, we will be able to design systems that
foster reflection and, hopefully, lead to a reduction in
injury rates.
Figure 4: Some pictures of a
cross country race taken with the
Narrative Clip.
We also see a need for building more sports memories. In
our studies, we often found that runners find it find hard
to recall details of past running events. Most importantly,
it is quite hard to recall and analyse what happened on
race day due to the heightened emotions and intensified
exertion. Recall of training sessions, while not intense, is
often hampered by their routine nature — most of our
respondents, for example, mainly ran in the same limited
area because of time constraints. Systems that facilitate
recall (such as the SenseCam [3]) are known in HCI and
we believe we should seek to apply them in a running
context. Enhanced memories of running achievements and
the hardships that one had to endure can lead to more
satisfaction and motivation. Or, maybe, a memory of a
past success can suggest a well-deserved day off? An
important question is which data that should be gathered
and how it should be presented in order to trigger runner’s
memories [8]. In a preliminary effort, we used the
NarrativeClip2 mounted on a running belt to gather visual
material from a cross country race. Figure 4 presents some
of the pictures taken. The material allowed telling a richer
story of the race as well as supporting recall of particular
events. It also enabled those not participating to become
more engaged and ask relevant questions. Furthermore,
we are also taking snapshots of the fitness class game.
The role of HCI
We ask ourselves how HCI can help advanced advanced
amateurs make sense of data. As interaction designers, we
2 getnarrative.com
have a robust apparatus of visual interface design and
interactive information visualization at hand. We know
how to build effective, usable and fun interfaces given that
we have a profound understanding of the users and the
design constrained [5]. In the case of sports technology,
we need more understanding before we are able to design
the next big thing. Not only do we need more
ethnographic studies of running, but we also need to
engage in other disciplines that have a tradition of
studying sports. We will need more knowledge from the
domains of sports physiology and sports psychology to
design better systems. Understanding the social aspects
of running seem to be particularly challenging as one
needs to understand the complicated processes of how
runner groups are formed and maintained as well as how
runners interact with friends and family. We do not need
to redo all the ethnographic work that has already been
done, but we rather need focus on studying the role
technology plays in the lives of runners.
Conclusions
In this paper we presented our vision of future sports
support technology which stimulates reflection and story
telling by creative use of the extensive sensing capabilities
available for runners. We shared some of the insights from
our studies of runners and races to look for directions for
future development. We believe that innovative
visualisation can help runners reflect about their training
process, understand more about their bodies and enjoy
the sport more. We illustrated how a game-based is now
used to organise fitness classes and motivate users to
improve their physical skills. We also think that there is
an emerging need for technology that supports and
triggers runner memories as the unique mental state of
participating in a race often makes it hard to recall events.
Life logging technology can be used to cater to those
needs. We also highlighted how HCI needs to enter a
dialogue with other disciplines concerned with running to
acquire a better understanding of the design constraints
involved.
[4]
We believe that the increased availability of sensor and
camera data present a huge opportunity for enabling
people to recall, reflect and learn from their activities, and
that we have to create solutions that facilitate this
process in the future. While we focus on advanced
amateur runners, it is likely that increasing storytelling
support with the gathered data can translate well to other
usage scenarios e.g. helping patients see the progress of
their physiotherapy sessions or aiding users who monitor
their food intake for health reasons. As there are many
opportunities in this area, we hope that future design can
be inspired by our analysis.
[5]
[6]
[7]
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