Seven Issues for
Creativity Support Tool Researchers
Kumiyo Nakakoji,
University of Tokyo
Workshop participants
discussed several concepts, types of practices, and aspects of human cognition
as important ingredients for research on tools for supporting creativity. There
were lively discussions as participants from different disciplines learned
about each others’ perspectives and approaches to research. We made progress in
coming to a more coherent view of tools supporting creativity. This section
lists seven diverse concepts that appeared repeatedly in our discussions.
Although not completely woven within the research framework, these issues in
some sense constitute the idiosyncratic nature of research on tools for
supporting creativity.
The workshop
participants had lively discussions on the roles of tools for supporting
creativity. Such tools may be positioned in terms of three dimensions,
analogous in sports to dumbbells, running shoes, and skis.
The first dimension
includes tools to train people to develop creativity, or skills of creative
thinking (for instance, see tools by Resnick et al. and Eisenberg et al. in
Section xxx-CompositionTool). Such tools aim at
helping people to develop skills to engage in creative ways of looking at
problems and framing solutions by using these tools, and to maintain such
skills even without using the tools. In this sense, tools in this dimension are
like dumbbells used to develop muscles — once developed, muscle can be used for
other kinds of physical exercise than merely using dumbbells. The second
dimension includes tools to support people's creative process while engaging in
a creation task (for instance, tools by Myers and Pausch in Section xxx-CompositionTool, Terry et al. [2002][2004] and
Nakakoji & Yamamoto [2005]). These tools are like high-tech running shoes,
with which runners, especially skilled ones, can run faster and/or more
comfortably. People can still run without wearing such shoes, but they would
have different kinds of running experiences, and probably better ones, by
wearing the shoes. The third dimension includes tools to enable people to have
new kinds of experiences that they would not be able to have without using
these tools (for instance, see interactive media art systems, such as those
described by Edmonds & Candy [2002] and Giaccardi [2005], as described in Section xxx-MediaArt), allow people to engage in
completely new experiences of producing expressions. For our analogy, the act
of skiing cannot take place without wearing skis.
These three dimensions
are by no means exclusive. Each tool, described within the research framework
of supporting creativity, simultaneously embodies multiple aspects. Yet, it is
important to be aware of the differences among them. The workshop has seen the
beginning of a taxonomy emerging, and we need to further develop it to more
adequately refer to each aspect of the research field.
In the field of human-computer
interaction (HCI) research, usability and learnability have been studied
regarding the quality of computational tools. Those concepts have been
primarily measured in terms of efficiency and productivity.
Designing tools for
supporting creativity (in all of the three aspects described above), in
contrast, needs to take into account new concepts that have not been considered
within the traditional HCI framework. Studies suggest that supporting
creativity requires people to experience a “flow” [Csiksentmihalyi 1990], which
needs tools engaging. The
relationship between users and a tool might be better described as embodiment rather than use [Fels 2004]. Information provided by
tools needs to be trustful for people
to use it as a source for nurturing creativity [Nakakoji, et al. 2000]. Logical
aesthetics of systems [Hallnaes,
Redstroem 2002] play an important role for people to regard tools as expressive
media. The utility of such tools may be described in terms not necessarily of
objective measurements, such as productivity and efficiency, but of subjective
ones, such as values [Gaver et al.
2004].
Software development,
especially programming, was referred to a number of times during the workshop
as a representative design practice in a knowledge-intensive domain. However,
many participants were also aware of the existence of counter arguments, such
as “programming is boring.”
In fact, although the software engineering community has changed
its focus not only on organizations but also on individuals (such as with
Personal Software Processes [Humphrey 1997]), the predominant view still holds
that there should be no fundamental differences among individual programming
processes. The psychology of programming has primarily looked at the
differences of programming productivity and efficiency between experts and
novices, and studied the benefits of programming features (e.g. IF statement
design), methods (e.g. object oriented), and usage (e.g. mnemonic variable names)[Shneiderman
1980][Soloway 1984], but not so much on individual differences in programming
processes.
Having seen the
emergence of the eXtreme Programming (XP) style [Beck 1999] being accepted
within the industry, especially the successfully deployed pair-programming
style, researchers in the software engineering community have started to seek
scientific accounts for why such free-form working styles outperform more
rigid, structured, process-oriented styles. This trend has made the focus
slowly shift more to the human side of programmers, and to programmers’
creative thinking processes. It should also be noted that studies have been
reported on how open-source software developers work collectively, which
demonstrates the aspect of social creativity [Ye et al. 2004].
The workshop
participants believed that there is a research opportunity in studying the
usability and design of programming languages, notations, and CASE
(Computer-Aided Software Engineering) tools (such as Cognitive Dimensions by
Green [2000]) by looking at programming as a creative endeavor. We need to
study and identify elements of creative programs, strategies, and individuals
to support more effective software development.
The first phase of the
four-phased creativity model is collection.
People have historically developed the idea of “cabinets of curiosity,” which
display things that look curious. Such cabinets seem to help people in the
collection phase leading to creative thinking and creative artifacts. Architectural
designers as well as industrial designers put large numbers of sketched sheets
of papers on walls surrounding their desks, collect magazine clips in albums,
and carry their sketch books all the time. These practices also imply that
people need to collect “stuff” and be surrounded by it to help them engage in
creative practice.
Despite the existence of
these practices, however, we still do not have empirical evidence of how they
work, and we still do not know what the computational tools deliberately
designed to support such a collection process would be. Browsing the Web would
certainly serve the purpose, but would it be sufficient? Would carrying their
working environment on a laptop PC help? What else could we design for tools to
support the collection process?
Creativity is often
associated with art, and research on tools for supporting creativity is often
naively viewed as supporting artists. None of the workshop participants,
however, believed that we could develop tools supporting creativity of artists
if we take a romantic account of design by which a creative process is viewed
as a result of “magical abilities of creation” by “imaginative masterminds”
[Fallman 2003]. Rather, our target users have been, and will be, design
practitioners and children, taking a pragmatic account of design [Fallman 2003]
by which a creative process is viewed as a reflective practice [Schoen 1983].
Arts, especially media
arts in this context, become relevant to the workshop by looking at media arts
as tools for supporting creativity (as more thoroughly elaborated in Section xxx-MediaArt). As stated above, concepts that have
not been well understood, such as engaging, embodiment, aesthetics, or trust,
need to be taken into account in designing and evaluating tools for supporting
creativity. As researchers, our goal is to develop rigorous accounts and
identify scientific evidence for how such concepts are instantiated within
tools.
Although we do not yet
know how to do it, some media art works achieve some of the concepts, such as
engaging experience for participants (see Section xxx-MediaArt
for further explanation). Our research could then treat them as success cases
and draw scientific accounts for which aspects of the works achieve what concepts,
by deconstructing them and re-appropriating them. This type of deductive
reasoning could be one way to address the challenges of research on tools to
support creativity.
Many of the workshop
participants take the view that creative practice is a never-ending endeavor.
Producing an artifact should not be regarded as a one-shot affair, but rather
as formulating a growing experience engaging in the development of creating
generations of artifacts.
In this regard, a
statement of “tools supporting creativity” might have to be restated as “tools
supporting creativity in what context.” This aspect was brought up when Gary
Olson reported the result of a study, saying that the sum of the outcomes of
individuals’ brain storming sessions outperforms the outcome of a group brain
storming session in terms of quality and speed. Yet, the real value of group
brainstorming seems to be not within the quality of the brainstorming per se
but within information sharing and value sharing. The subsequent processes
would work better having such shared experience during a group discussion.
Tools for supporting
creativity could also face the same challenge. Some tools work well for a user
to produce a creative artifact at a certain stage. However, if the user needs
to keep working on the artifact in subsequent stages, different tools might
work better as a whole. In modeling, designing, and evaluating tools for
supporting creativity, therefore, we need to identify what contexts of the
creativity our tools are aiming at. Otherwise we could easily fall into a
fruitless discussion by referring to creativity in different contexts.
As discussed above,
aspects conventionally associated with the quality of tools do not necessarily
hold for tools supporting creativity. If the quality of creativity support
tools could be measured only in terms of subjective factors such as values,
then since different individuals have different value systems, there may be
creativity support tools not for all of us but only for a subset of people who
share the same value systems. For instance, when designing creativity support
tools for programmers, the ease of use might not necessarily be a requirement
for professional programmers; skilled professional programmers often find pride
in their being able to use complex notations within difficult-to-learn
environments, and some may not like to use too-easy-to-learn tools that may
threaten their professional identity.
This seems to suggest
almost a paradigm change for existing HCI research, which has been seeking
“appropriate” models and tools for certain domains. Adaptive mechanisms and
end-user modifiability have been explored as ways to allow people to adjust
tools for individual differences, but such minor adjustments cannot afford the
variety of tool needs. End-users cannot modify a Porsche to turn it into a
Mercedes; they are two fundamentally different tools, both of which are for
those who are fond of high-quality driving experiences, but each designed with
a completely different philosophy than the other.
Because creativity is
such a humane matter, designing, developing, and evaluating tools for
supporting creativity will uncover issues and challenges that have not been so
obvious in the traditional HCI research framework. Research on tools for
supporting creativity would make computer technologies truly
human-centered.
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