420
P. J. Wolff, III
living lab research as it happens. It was a response to the complexity of the living
lab ecosystem—and the need for organizational tools that connect people, ideas, and
processes—that led to the creation of tools which seek to organize the concurrent
processes and timelines and to document progress through time (see the section
“Transaction Tools”).
A second question that emerged was, How can the stories of living lab research be
documented and shared more easily? Although new research was often documented
carefully on websites, or in recently published articles, the retrieval of older work
was more challenging. As a result, details of the front-line stories of research and the
place in which it occurred may only be available in the minds of those who did the
work, or who remember it as a bystander. In response to these challenges, a concept
was conceived as a means to collect and share the stories of living lab research (see
the section “The Learning Adventure Card Concept”).
A third question in response to the observed collection and retrieval challenges
was, how can the findings of campus-based research be scaled to be accessible
for wider audiences (including novices, experts, and a growing cadre of “digital
natives
1 ”)? The solution that emerged was an idea for a dynamic digital tool that
allows large amounts of structured and unstructured data to be collected, stored, and
retrieved via an interactive, app-like interface (see the section “A Vision for a Digital
Storytelling Machine”).
4 Transaction Tools
Scholars have described the messy, unpredictable nature of campus-based research
as “in-the-wild” experimentation and have examined the influence of context on the
user experience (Ballon and Schuurman 2015). A similar variety of processes were
observed in the 62 living labs that were examined for this study, but three were
the most prevalent: a research process (research questions, literature review, design
methodology, and data collection/analysis), an ideation process (intake/define, collaborate, digest, prototype, connect/reconnect, and test/outcomes), and a filtering
process utilized as a means to make strategic decisions about the prioritization of
new work (scales of impact, alignment with institutional goals, capacity for formal or
informal learning, risk assessment, etc.). So, in an effort to collect these simultaneous
processes in one device and as an aid to the application of new knowledge, I imagined
the Process Wheels, which are meant to support deep learning and high-level skill
development such as analysis, synthesis, and creative problem solving required for
active participants in living lab research (see Fig. 1).
The Process Wheels were inspired by the analogy of an artist’s color wheel—a
device that collects large amounts of complex information related to color physics and
1 “Digital natives” are those born after 1980, who have grown up with video games, instant messaging, and smartphones and who prefer to learn from hyperlinked, random access, digital sources and
with the assistance of online cameras, simulations, games, wikis, and blogs that they help create
(Kelly et al. 2009).
P. J. Wolff, III
living lab research as it happens. It was a response to the complexity of the living
lab ecosystem—and the need for organizational tools that connect people, ideas, and
processes—that led to the creation of tools which seek to organize the concurrent
processes and timelines and to document progress through time (see the section
“Transaction Tools”).
A second question that emerged was, How can the stories of living lab research be
documented and shared more easily? Although new research was often documented
carefully on websites, or in recently published articles, the retrieval of older work
was more challenging. As a result, details of the front-line stories of research and the
place in which it occurred may only be available in the minds of those who did the
work, or who remember it as a bystander. In response to these challenges, a concept
was conceived as a means to collect and share the stories of living lab research (see
the section “The Learning Adventure Card Concept”).
A third question in response to the observed collection and retrieval challenges
was, how can the findings of campus-based research be scaled to be accessible
for wider audiences (including novices, experts, and a growing cadre of “digital
natives
1 ”)? The solution that emerged was an idea for a dynamic digital tool that
allows large amounts of structured and unstructured data to be collected, stored, and
retrieved via an interactive, app-like interface (see the section “A Vision for a Digital
Storytelling Machine”).
4 Transaction Tools
Scholars have described the messy, unpredictable nature of campus-based research
as “in-the-wild” experimentation and have examined the influence of context on the
user experience (Ballon and Schuurman 2015). A similar variety of processes were
observed in the 62 living labs that were examined for this study, but three were
the most prevalent: a research process (research questions, literature review, design
methodology, and data collection/analysis), an ideation process (intake/define, collaborate, digest, prototype, connect/reconnect, and test/outcomes), and a filtering
process utilized as a means to make strategic decisions about the prioritization of
new work (scales of impact, alignment with institutional goals, capacity for formal or
informal learning, risk assessment, etc.). So, in an effort to collect these simultaneous
processes in one device and as an aid to the application of new knowledge, I imagined
the Process Wheels, which are meant to support deep learning and high-level skill
development such as analysis, synthesis, and creative problem solving required for
active participants in living lab research (see Fig. 1).
The Process Wheels were inspired by the analogy of an artist’s color wheel—a
device that collects large amounts of complex information related to color physics and
1 “Digital natives” are those born after 1980, who have grown up with video games, instant messaging, and smartphones and who prefer to learn from hyperlinked, random access, digital sources and
with the assistance of online cameras, simulations, games, wikis, and blogs that they help create
(Kelly et al. 2009).