ArticlePDF Available


Clarifying what creativity is the first step towards answering the question: could a computer be creative?Margaret Boden is Research Professor of Cognitive Science, in the Centre for Cognitive Science, University of Sussex. How to Cite This Article Link to This Abstract Blog This Article Copy and paste this link Highlight all Citation is provided in standard text and BibTeX formats below. Highlight all BibTeX Format @article{THI:3224284,author = {Boden,Margaret A.},title = {Creativity in a nutshell},journal = {Think},volume = {5},issue = {15},month = {9},year = {2007},issn = {1755-1196},pages = {83--96},numpages = {14},doi = {10.1017/S147717560000230X},URL = {},} Click here for full citation export options. Blog This Article Blog This Article : Highlight all Creativity in a nutshell Margaret A. Boden (2007). Think , Volume 5 , Issue15 , September 2007, pp 83-96 The code will display like this Creativity in a nutshell Margaret A. Boden September 2007 Think, ,Volume5, Issue15, September 2007, pp 83-96 Margaret A. Boden (2007). Creativity in a nutshell. Think, 5, pp 83-96. doi:10.1017/S147717560000230X. //JOU-13771 - ndomingo :: ensure mathjax process will proceed function mathJaxRerender(){ if(!mathJaxScript){ loadMathjax(); loadCookie(); } } function openCommentBox(){ jQuery('.comments-holder-helper').toggleClass("inactive"); jQuery('#commentbox3224284-box').slideToggle(); } jQuery(document).ready(function() { if('' == 'Y'){ openCommentBox(); } if('' == 'Y'){ openTabs(); } //JOU-13771 - ndomingo :: ensure mathjax process will proceed if('N' == 'Y'){ mathJaxRerender(); } }); Copyright Statement Rights and Permissions Privacy Policy Terms of Use Feedback Press Releases
Margaret A. Boden
university of Sussex
*This article is reprinted from pp. 1-10 of M. A. Boden, The Creative Mind: Myths and
Mechanisms (London: Routledge, 2004).
Creativity and computers: what could these possibly have todowith one another? "Nothing!,"
manypeople would say.Creativity is a marvel of the human mind. But computers, with all due
apologies to Mario, Sonic, and friends, are basically just tin-cans. It follows -- doesn’tit? -- that
the twoare related only by utter incompatibility.
Well, no. Computers and creativity makeinteresting partners with respect to twodifferent
projects. One, which interests me the most, is understanding human creativity.The other is trying
to produce machine creativity -- or anyway,machine "creativity" -- in which the computer at
least appears to be creative,tosome degree.
What is Creativity?
First things first. Human creativity is something of a mystery,not to say a paradox. One newidea
may be creative,while another is merely new. What’sthe difference? And howiscreativity
possible? Creative ideas are unpredictable. Sometimes, theyevenseem to be impossible -- and
yet theyhappen. Howcan that be explained? Could a scientific psychology help us to understand
howcreativity is possible?
Creativity is the ability to come up with ideas or artefacts that are new, surprising,and
valuable. "Ideas," here, includes concepts, poems, musical compositions, scientific theories,
cooking recipes, choreography, jokes ... and so on, and on. "Artefacts" include paintings,
sculpture, steam-engines, vacuum cleaners, pottery,origami, penny-whistles ... and you can name
As these highly diverse examples suggest, creativity enters into virtually every aspect of life.
It’snot a special "faculty," but an aspect of human intelligence in general. In other words, it’s
grounded in everyday abilities such as conceptual thinking, perception, memory,and reflective
self-criticism. So it isn’tconfined to a tinyelite: every one of us is creative,toadegree.
Nor is it an all-or-none affair.Rather than asking "Is that idea creative,Yes or No?," we should
ask "Just howcreative isit, and in just which way(s)?" Asking that question will help us to
appreciate the subtleties of the idea itself, and also to get a sense of just what sorts of
psychological process could have brought it to mind in the first place.
Creative ideas, then, are new. But of course, there’snew --and there’s new. Ask a teacher,for
instance. Children can come up with ideas that are new to them, ev e nthough theymay have been
Dagstuhl Seminar Proceedings 09291
Computational Creativity : An Interdisciplinary Approach
in the textbooks for years. Someone who comes up with a bright idea is not necessarily less
creative just because someone else had it before them. Indeed, if the person who had it first was
Shakespeare, or Euclid, we’dthink evenmore highly of the achievement.
Suppose a twelve-year old girl, who’dnev erread Macbeth, compared the healing power of
sleep with someone knitting up a ravelled sleeve.Would you refuse to say she was creative,just
because the Bard said it first? Perhaps, if you’dbeen talking around the topic with her,
encouraging her to come up with non-literal ways of speaking, and evenputting one or more of
the three key ideas into the conversation. Otherwise, you’dhav e to acknowledge her remark as a
truly imaginative one.
What you might do, and what I think you should do in this situation, is to makeadistinction
between "psychological" creativity and "historical" creativity.(P-creativity and H-creativity,for
short.) P-creativity involves coming up with a surprising, valuable idea that’snew to the person
who comes up with it. It doesn’tmatter howmanypeople have had that idea before. But if a new
idea is H-creative,that means that (so far as we know) no-one else has had it before: it has arisen
for the first time in human history.
Clearly,H-creativity is a special case of P-creativity.For historians of art, science, and
technology -- and for encyclopaedia users, too -- H-creativity is what’simportant. And in daily
life, we appreciate it too: it really isn’ttrue that "The old jokes are the best ones". But for
someone who is trying to understand the psychology of creativity,it’sP-creativity that’scrucial.
Nevermind who thought of the idea first: howdid that person manage to come up with it, given
that they had neverthought of it before?
If "new,"inthis context, has twoimportantly different meanings, "surprising" has three.
An idea may be surprising because it’sunfamiliar,orevenunlikely -- likea100-to-1 outsider
winning the Derby.This sort of surprise goes against statistics.
The second sort of surprise is more interesting. An unexpected idea may "fit" into a style of
thinking that you already had -- but you’re surprised because you hadn’trealized that this
particular idea was part of it. Maybe you’re evenintrigued to find that an idea of this general type
fits into the familiar style.
And the third sort of surprise is more interesting still: this is the astonishment you feel on
encountering an apparently impossible idea. It just couldn’t have entered anyone’shead, you feel
-- and yet it did. It may evenengender other ideas which, yesterday,you’dhav e thought equally
impossible. What on earth can be going on?
The Three Ways of Creativity
"What is going on" isn’tmagic -- and it’sdifferent in each type of case. Forcreativity can
happen in three main ways, which correspond to the three sorts of surprise.
The first involves making unfamiliar combinations of familiar ideas. Examples include poetic
imagery,collage in painting or textile art, and analogies. These newcombinations can be
generated either deliberately or,often, unconsciously.Think of a physicist comparing an atom to
the solar system, for instance, or a journalist comparing a politician with a decidedly non-cuddly
animal. Or call to mind some examples of creative associations in poetry or visual art.
In all these cases, making -- and also appreciating -- the novelcombination requires a rich
store of knowledge in the person’smind, and manydifferent ways of moving around within it.
The journalist or newspaper-reader needs a host of concepts about both politics and animal
behaviour,and some "personal" knowledge about the individual politician in question.
Cartoonists who depict Ken Livingstone (the first publicly-elected Mayor of London) as a newt
are tapping into manydifferent conceptual streams, including gossip about what he keeps in an
aquarium in his home. The surprise you feel on looking at the cartoon is largely caused by seeing
ahuman figure with a newt’screst and tail: a combination of ideas that’sevenless probable than
the outsider winning the Derby.
If the novelcombination is to be valued by us, it has to have some point. It may or (more
usually) may not have been caused by some random process -- likeshaking marbles in a bag. But
the ideas/marbles have tohav e some intelligible conceptual pathway between them for the
combination to "makesense." The newt-human makes sense for manyreasons, one of which is
Ken’sfamed predilection for newts. (What are some of the others?) And (to return to the example
from Macbeth) sleep is a healer,asknitting can be. Even if twoideas are put together randomly
in the first place, which I suspect happens only rarely,theyare retained/valued only if some such
links can be found.
The other twotypes of creativity are interestingly different from the first. Theyinv olvethe
exploration, and in the most surprising cases the transformation, of conceptual spaces in people’s
Exploring Conceptual Spaces
Conceptual spaces are structured styles of thought. They’re normally picked up from one’sown
culture or peer-group, but are occasionally borrowed from other cultures. In either case, they’re
already there: theyaren’toriginated by one individual mind. Theyinclude ways of writing prose
or poetry; styles of sculpture, painting, or music; theories in chemistry or biology; fashions of
couture or choreography, nouvel cuisine and good old meat-and-two-veg ... in short, any
disciplined way of thinking that’sfamiliar to (and valued by) a certain social group.
Within a givenconceptual space, manythoughts are possible, only some of which may have
been actually thought. Some spaces, of course, have a richer potential than others. Noughts-and-
crosses is such a restricted style of game-playing that every possible move has already been made
countless times. But that’snot true of chess, where the number of possible moves, though finite,
is astronomically large. And if some sub-areas of chemistry have been exhausted (every possible
molecule of that type having been identified), the space of possible limericks, or sonnets, has not
-- and neverwill be.
Whateverthe size of the space, someone who comes up with a newidea within that thinking-
style is being creative inthe second, exploratory,sense. If the newidea is surprising not just in
itself but as an example of an unexpected general type, so much the better.And if it leads on to
others (still within the same space) whose possibility was previously unsuspected, better still.
Exploratory creativity is valuable because it can enable someone to see possibilities theyhadn’t
glimpsed before. Theymay evenstart to ask just what limits, and just what potential, this style of
thinking has.
We can compare this with driving into the country,with an Ordnance Survey map that you
consult occasionally.You can keep to the motorways, and only look at the thick red lines on your
map. But suppose, for some reason (a police-diversion, or a call of nature), you drive off onto a
smaller road. When you set out, you didn’tevenknowitexisted. But of course, if you unfold the
map you’ll see it marked there. And perhaps you ask yourself "I wonder what’sround that
corner?," and drive round it to find out. Maybe you come to a pretty village, or a council estate;
or perhaps you end up in a cul-de-sac, or back on the motorway you came offinthe first place.
All these things were always possible (and they’re all represented on the map). But you’dnev e r
noticed them before -- and you wouldn’thav e done so now, ifyou hadn’tgot into an exploratory
frame of mind.
In exploratory creativity,the "countryside" is a style of thinking. Instead of exploring a
structured geographical space, you explore a structured conceptual space, mapped by a particular
style of painting, perhaps, or a specific area of theoretical chemistry.
All professional artists and scientists do this sort of thing. Even the most mundane street-
artists in Leicester Square produce newportraits, or newcaricatures, every day.Theyare
exploring their space, though not necessarily in an adventurous way.Occasionally,theymay
realize that their sketching-style enables them to do something (convey the set of the head, or the
hint of a smile) better than they’dbeen doing before. Theyadd a newtrick to their repertoire, but
in a real sense it’ssomething that "fits" their established style: the potential was always there.
Transforming the Space
What the street-artist may also do is realize the limitations of their style. Then, theyhav e an
opportunity which the Sunday driverdoes not. Give ortakeafew years, and ignoring earthquake
and flood, the country roads are fixed. Certainly, you can’tchange them. Your Ordnance Survey
map is reliable not only because it’sright, but because it stays right. (Have you bothered to buy a
newbook of road-maps within the last fewyears?) But the maps inside our heads, and favoured
by our communities, can change -- and it’screative thinking which changes them.
Some changes are relatively small and also relatively superficial. (Ask yourself: what’sthe
difference?) The limits of the mental map, or of some particular aspect of it, are slightly pushed,
slightly altered, gently tweaked. Compare the situation in geographical space: suppose everyone
in that pretty village suddenly added a roof-extension to their cottage. It may ruin the prettiness
of the village, but it won’tchange the dimensions of the map. At most, the little "portrait" of the
village (assuming that it’s that sort of map) will have toberedrawn.
The street-artist, then -- or Picasso, in a similar position -- has an opportunity.Inprinciple, he
(or,asalways, she) could do the psychological equivalent of adding roof extensions, or building
anew road (a newtechnique, leading to newpossibilities), or evenre-routing the motorway.
Re-routing the motorway (in "real life" as in the mind) is the most difficult of all. The surprises
that would engender could be so great as to makethe driverlose his bearings. He may wonder if
he’sbeen magically transported to a different county,orevenadifferent country.Maybe he
remembers a frustrating episode on his last trip, when he wanted to do something but his
passenger scornfully said: "In England, motorways are like this: theysimply don’tallowyou to
do that. Youwant to do it? Tough! It’simpossible."
Agiv e nstyle of thinking, no less than a road-system, can render certain thoughts impossible --
which is to say,unthinkable. The difference, as remarked above,isthat thinking-styles can be
changed -- sometimes, in the twinkling of an eye.
Someone skilfully writing a limerick won’tfind iambic pentameters dropping from their pen.
But if you want to write a newsort of limerick, or a non-limerick somehowgrounded in that
familiar style, then maybe blank verse could play a role. The deepest cases of creativity involve
someone’sthinking something which, with respect to the conceptual spaces in their minds, they
couldn’t have thought before. The supposedly impossible idea can come about only if the creator
changes the pre-existing style in some way.Itmust be tweaked, or evenradically transformed, so
that thoughts are nowpossible which previously (within the untransformed space) were literally
inconceivable. -- But howcan that possibly happen?
Machine-Maps of the Mind
To understand howexploratory or transformational creativity can happen, we must knowwhat
conceptual spaces are, and what sorts of mental processes could explore and modify them.
Styles of thinking are studied by literary critics, musicologists, and historians of art, fashion,
and science. And theyare appreciated by us all. But intuitive appreciation, and evenlifelong
scholarship, may not maketheir structure clear.(An architectural historian, for instance, said of
Frank Lloyd Wright’sPrairie Houses that their "principle of unity" is "occult".)
This is the first point where computers are relevant. Conceptual spaces, and ways of exploring
and transforming them, can be described by concepts drawn from artificial intelligence (AI).
AI-concepts enable us to do psychology in a newway,byallowing us to construct (and test)
hypotheses about the structures and processes that may be involved in thought. For instance, the
structure of tonal harmony, orthe "grammar" of Prairie Houses, can be clearly expressed, and
specific ways of exploring the space can be tried out. Methods for navigating, and changing,
highly-structured spaces can be compared.
Of course, there is always the additional question of whether the suggested structures and
processes are actually implemented in human heads. And that question isn’talways easy to
answer.But the point, here, is that a computational approach givesusaway of coming up with
scientific hypotheses about the rich subtleties of the human mind.
Computer Creativity?
What of the second link between machines and creativity? Can computers be creative?Orrather,
can theyatleast appear to be creative?
Manypeople would argue that no computer could possibly be genuinely creative, no matter
what its performance was like. Even if it far surpassed the humdrum scientist or street-artist, it
would not be counted as creative.Itmight produce theories as ground-breaking as Einstein’s, or
music as highly valued as McCartney’s"Yesterday" or evenBeethoven’sNinth ... but still, for
these people, it would’nt really be creative.
Several different arguments are commonly used in support of that conclusion. For instance: it’s
the programmer’screativity that’satwork here, not the machine’s. The machine isn’tconscious,
and has no desires, preferences, or values -- so it can’tappreciate or judge what it’sdoing. A
work of art is an expression of human experience and/or a commmunication between human
beings, so machines simply don’tcount.
Perhaps you accept at least one of those reasons for denying creativity to computers? Very
well, I won’targue with you here (but see Chapter 11 of Boden 2004). Let’sassume, for the
purpose of this discussion, that computers can’treally be creative.The important point is that
this doesn’t mean that there’snothing more of interest to say.
All the objections just listed accept, for the sakeofargument, that the imaginary computer’s
performance is indeed very likethat of human beings, whether humdrum or not. What I want to
focus on here is whether it’strue that computers could, in fact, come up with ideas that at least
appear to be creative.
Computer Combinations
Well, think of combinational creativity first. In one sense, this is easy to model on a computer.
Fornothing is simpler than picking out twoideas (twodata-structures) and putting them
alongside each other.This can evenbedone with some subtlety,using the (connectionist)
methods described in Chapter 6. In short: a computer could merrily produce novelcombinations
till Kingdom come.
But would theybeofany interest? Wesaw,above,that combining ideas creatively isn’tlike
shaking marbles in a bag. The marbles have tocome together because there is some intelligible,
though previously unnoticed, link between them which we value because it is interesting --
illuminating, thought-provoking, humorous ... -- in some way.(Think sleep and knitting, again.)
We saw also that combinational creativity typically requires a very rich store of knowledge, of
manydifferent kinds, and the ability to form links of manydifferent types. (Here, think
politicians and newts again.)
And we don’tonly form links, we evaluate them. For instance, we can recognize that a jokeis
"in bad taste." In other words: yes, the links that the joker is suggesting are actually there (so it is
areal joke). But there are other links there also, which connect the ideas with sorrow,
humiliation, or tragedy.The joker should have noticed them, and should have refrained from
reminding us of them.
Foracomputer to makeasubtle combinational joke, nevermind to assess its tastefulness,
would require (1) a data-base with a richness comparable to ours, and (2) methods of link-
making (and link-evaluating) comparable in subtlety with ours. In principle, this isn’timpossible.
After all, the human mind/brain doesn’tdoitbymagic. But don’thold your breath!
The best example of computer-based combinational creativity so far is a program called JAPE,
which makes punning jokes of a general type that’sfamiliar to every eight-year-old (see Chapter
12). But making a one-offjest is usually more demanding. Ask yourself, for instance, what Jane
Austen had to knowinorder to write the opening sentence of Pride and Prejudice: "It is a truth
universally acknowledged that a single man in possession of a good fortune must be in want of a
wife." (And why, exactly,isitfunny?)
Artificial Explorers and Self-Transforming Machines
What about exploratory creativity? Several programs already exist which can explore a given
space in acceptable ways.
One example is AARON, a drawing-program described in Chapter 7. AARON can generate
thousands of line-drawings in a certain style, pleasing enough to be spontaneously remarked
upon by unsuspecting visitors -- and to be exhibited in galleries worldwide, including the Tate.
(The most recent version of AARON is able to paint its drawings, too: see Chapter 12.)
Another is David Cope’s"Emmy," discussed in Chapter 12. This composes music in many
different styles, reminiscent of specific human composers such as Bach, Vivaldi, Mozart ... and
Stravinsky. Still others include architectural programs that design Palladian villas or Prairie
Houses (also mentioned in Chapter 12), and programs that can analyse experimental data and
find newways of expressing scientific laws (Chapter 8).
Afew AI-programs can eventransform their conceptual space, by altering their own rules, so
that interesting ideas result. Some of these ideas were already known to human beings, though
not specifically prefigured within the program. (See the discussion of the automatic
mathematician, AM, in Chapter 8.) But others are first-time-fresh. "Evolutionary" programs, for
instance, can makerandom changes in their current rules so that newforms of structure result. At
each generation, the "best" structures are selected, and used to breed the next generation.
Tw o examples that evolvecoloured images (some of which, likeAARON’s, are exhibited in
galleries world-wide) are described in Chapter 12. In each case, the selection of the "fittest" at
each generation is done by a human being, who picks out the most aesthetically pleasing
patterns. In short, these are interactive graphics-environments, in which human and computer
can cooperate in generating otherwise unimaginable images. These computer-generated images
often cause the third, deepest, form of surprise -- almost as if a coin being tossed repeatedly were
suddenly to showa wholly unexpected design. In such cases, one can’tsee the relation between
the daughter-image and its parent. The one appears to be a radical transformation of the other,or
ev e nsomething entirely different.
Anyone who has watched TV regularly overthe past fewyears, or who has visited museums
of contemporary art, will already knowthat manynovelgraphic images have been produced by
self-transforming AI-programs of this kind. The problem is not to makethe transformations: that
is relatively easy.What’sdifficult is to state our aesthetic values clearly enough to enable the
program itself to makethe evaluation at each generation. At present, the "natural selection" is
done by a human being (for example, the gallery-visitor).
In more well-regulated domains, however, the value-criteria can often be stated clearly enough
to allowthe evolutionary program to apply them automatically.Anearly example, a program for
locating leaks in oil-pipelines, is mentioned in Chapter 8. Now, scientists are starting to use these
techniques to enhance their own creativity.Biochemical laboratories in universities and
pharmaceutical companies are using evolutionary programs to help design newmolecules for use
in basic research and/or medicine. Even the "brains" and "bodies" of robots can nowbeevolved,
instead of being designed (see Chapter 12).
Values and Creativity
One huge problem here has no special relevance to computers, but bedevils discussion of human
creativity too.
Isaid earlier that "new" has twomeanings, and that "surprising" has three. I didn’tsay how
manymeanings "valuable" has -- and nobody could. Our aesthetic values are difficult to
recognize, more difficult to put into words, and evenmore difficult to state really clearly.(Fora
computer model, of course, theyhav e to be stated really, really clearly.)
Moreover, theychange: who will proudly admit, today,tohaving worn a beehive hairdo or
flared trousers in the 1960s? Theyvary across cultures. And evenwithin a given"culture," they
are often disputed: different sub-cultures or peer groups value different types of dress, jewellery,
or music. And where transformational creativity is concerned, the shock of the newmay be so
great theat evenfellow-artists find it difficult to see value in the novelidea.
Even in science, values are often elusive and sometimes changeable. Just what "simpliity" or
"elegance" mean, as applied to scientific theories, is something that philosophers of science have
long tried -- and failed -- to pin down precisely.And whether a scientific finding or hypothesis is
"interesting" depends on the other theories current at the time, and on social questions too (might
it have some medical value, for instance?).
Because creativity by definition involves not only novelty but value, and because values are
highly variable, it follows that manyarguments about creativity are rooted in disagreements
about value. This applies to human activities no less than to computer performance. So even if we
could identify and program our aesthetic values, so as to enable the computer to inform and
monitor its own activities accordingly,there would still be disagreement about whether the
computer even appeared to be creative.
The answer to our opening question, then, is that there are manyintriguing relations between
creativity and computers. Computers can come up with newideas, and help people to do so. Both
their failures and their successes help us think more clearly about our own creative powers.
Further Reading:
Boden, M. A. (2004), The Creative Mind: Myths and Mechanisms (London: Routledge). 2nd
edn., revised/expanded.
... PBL's specific attempts at integrating 'open-endedness' into the problem space (Moallem et. al 2019), both factors into designing for one's creative need to work within an 'unknown' (Gero and Kumar 1993;Boden 2007) yet contrasts well against a rigid design educational framework (Wilson and Zamberlan 2017) that includes expectations attributed to learning outcomes and technical skill acquisition (Kelly 2019). In terms of designing for one as a form of making through collaboration, the engagement required can neither be fully placed within participatory design, in which a marginalised participant is accepted as a full design partner as a means to empower them (Muller and Druin 2002;Ehn 2008;Bratteteig and Wagner 2016) nor as co-design, in which a design is created through a collective process (Sanders 2002;Sanders and Stappers 2008). ...
... Because the literature study looking at creativity suggested that shifting elements of the design process to increase 'the unknown' within the design process might increase creativity (Runco and Jaeger 2012;Boden 2007;Gero and Kumar 1993), this raised the question of what variables within the designing for one process might be doing just that. ...
... The design squiggle itself alludes to the inherent 'possibility' that exists within the design process; the possibility for different influences to lead to alternative directions and therefore other designs. It is precisely these alternatives and new influences (illustrated in the Design Squiggle with lines intersecting and looping back upon themselves) that are central to the surprise and unexpectedness that creativity requires (Boden 2007) and what creativity counters against expectations (Becattini 2017). ...
Full-text available
Designing for one is a form of design participation in which a designer works together with one individual. The result of this interaction is a bespoke design that is responsive to the needs, abilities, preferences and situation of the individual. Applied with design education, this research sought to understand the ways this approach impacted a) student learning, b) the generation of empathy and c) the traditional design educational space. This study involved six methods of inquiry for examining the impact of designing for one on the student experience: four Student Module Cases Studies, one expert design educator workshop with 21 participants, 28 student interviews, seven expert design educator interviews and included mapping (a method used within the workshop), observations and post analysis thick descriptions. In terms of student learning, the study identified seven key learning experiences that students had when designing for one, with the most prevalent being: Process (the students developed knowledge about the design process, research methodology and the act of designing), Design Skills (they learned about and applied specific skills related to their discipline), Soft-Design Skills (they developed understanding regarding using and incorporate soft-skills into their design process) and Interaction (they identified the value of the interaction between themselves and their participant). Regarding empathy, the study identified 11 factors that influence the forming of an empathetic relationship between designer and participant, resulting in a set of empathy factors that can be referred to when seeking to build relationships within design participation. In terms of impacting the routine design space, the study identified 11 variables that design educators can use to disrupt a traditional educational setup with the most important variables identified being participation with real users (bringing students in contact with real users) and the location of the module situation (taking the ‘classroom’ off site into a situation of use). By purposefully placing students within these individual situations of an ‘other’, the result is a form of design participation that emerges from the orchestrated relationship and the exchange. The result of this thesis, then, is the offering of designing for one as pedagogical approach that increases levels of complexity, planning, research and collaboration serving to complement existing design educational practice.
... Cognitive fatigue is mental exhaustion resulting from tasks requiring deep thinking and could occur within 30 min of commencing a cognitive task [45,46]. An EDPE process, as explained by the "garbage can" model, involves creating unfamiliar concepts through stochastic information combinations, transformations, and/or explorations [47]. Cognitive fatigue could be induced during EDPE tasks and manifest as creative burnout, frustration, and/or tiredness leading to withdrawal from the task [48][49][50][51][52]. ...
Identifying new problems and providing solutions are necessary tasks at early-stage product design and development for design engineers. A new problem fosters innovative and inventive solutions. Hence, it is expected that engineering design pedagogy and practice should equally focus on Engineering Design Problem-Exploring (EDPE) – a process of identifying or coming up with a new problem or need at the early stage of design, and Engineering Design Problem-Solving (EDPS) – a process of developing engineering design solutions to a given problem. However, studies suggest that EDPE is scarcely practiced or given attention to in academia and industry, unlike EDPS. The aim of this paper is to investigate the EDPE process for any information relating to its scarce practice in academia and industry. This is to explore how emerging technologies could support the process. Natural models and phenomena that explain the EDPE process are investigated, including the “rational” and “garbage can” models, and associated challenges identified. A computational framework that mimics the natural EDPE process is presented. The framework is based on Markovian model and computational technologies including machine learning. A case study is conducted with a sample size of 43 participants drawn worldwide from the engineering design community in academia and industry. The case study result shows that the first-of-its-kind computational EDPE framework presented in this paper supports both novice and experienced design engineers in EDPE.
... Though the precise terminology can vary (e.g., novelty may be referred to as originality or uniqueness, while usefulness may be referred to as appropriateness, relevance, or effectiveness), the twin criteria of novelty and usefulness have formed principal components of numerous definitions of creativity dating back at least 70 years (Amabile, 1982;Plucker et al., 2004;Stein, 1953). The definition is not without conceptual issues (see Corazza, 2016;Martin & Wilson, 2017), and some have suggested additional requirements including surprise (Boden, 2007;Simonton, 2018), discovery (Martin & Wilson, 2017), and aesthetics and authenticity (Kharkhurin, 2014). However, especially within cognitive psychology and neuroscience, the standard definition continues to provide a theoretical foundation for vast amounts of creativity research, and to serve as a guide when raters evaluate the creativity of ideas, products, or responses. ...
Full-text available
According to the standard definition, creative ideas must be both novel and useful. While a handful of recent studies suggest that novelty is more important than usefulness to evaluations of creativity, little is known about the contextual and interpersonal factors that affect how people weigh these two components when making an overall creativity judgment. We used individual participant regressions and mixed-effects modeling to examine how the contributions of novelty and usefulness to ratings of creativity vary according to the context of the idea (i.e., how relevant it is to the real world) and the personality of the rater. Participants (N = 121) rated the novelty, usefulness, and creativity of ideas from two contexts: responses to the alternative uses task (AUT) and genuine suggestions for urban planning projects. We also assessed three personality traits of participants: openness, intellect, and risk-taking. We found that novelty contributed more to evaluations of creativity among AUT ideas than projects, while usefulness contributed more among projects than AUT ideas. Further, participants with higher openness and higher intellect placed a greater emphasis on novelty when evaluating AUT ideas, but a greater emphasis on usefulness when evaluating projects. No significant effects were found for the risk-taking trait.
... Unlike PBL's concept of triggers in which students begin with a set of predetermined information that is used to engage and motivate students toward a particular problem (Moallem et al. 2019), designing for one utilizes the relationship between student and participant as a context that offers motivation, engagement, problem definition, and learning. Like PBL's attempts to integrate "open-endedness" into a problem space (Moallem et al. 2019) designing for one also relies on working within the "unknown" (Boden 2007;Gero and Kumar 1993). This positions both PBL and designing for one as a counterweight against rigid design educational frameworks (Wilson and Zamberlan 2017) that have predetermined expectations attached primarily to learning outcomes and technical skill acquisition (Kelly 2019). ...
Full-text available
This article shares the results of research into the designing for one approach, a term referring to a (student) designer designing for one individual in which the individual’s specific interests, accessible tools, capabilities, etc. shape the designer’s process and are reflected in the resulting bespoke design. This particular study looked at four individual case studies in which design students of diverse design disciplines and educational levels from universities in the US and in Belgium used this approach. The cases were analyzed by a panel of twenty-one design education experts looking specifically to identify factors that were different within this approach from that of the educator’s own practice, factors that potentially had shifted the educational context and student experience from the known and routine into areas that were unfamiliar. Next to this, the analysis included over 200 pages of interview transcripts from students in the four cases, looking to identify how these identified factors impacted the student’s experience. Using the participant’s own voice to provide context to these points of difference, this article offers readers a list of eleven variables that were identified as factors which set the designing for one approach apart from standard, skills-based design education. A call to action for educators, the article proposes how these variables can facilitate a shift in learning to bring students experiences that challenge their discipline, medium, and processes.
In this work we combine aspects of implicit learning with novelty search in an evolutionary algorithm with the aim to automatically generate melodies with improvisational flavour. Using Markov chains, the technique we present combines implicit statistical knowledge, extracted from musical corpora, with an adaptive novelty search mechanism. The algorithm is described along with the main design choices. Preliminary results are shown in two different musical contexts: Irish music and counterpoint compositions.KeywordsEvolutionary artComputational creativityStatistical learningMusicNovelty
Full-text available
The research examines and compares public and private secondary school teachers’ perceptions about creativity as a skill that can be cultivated in their class room practices. The researcher adopted PBA, a psychological model of professional behavior analysis for analyzing professionals’ perception. Any professional expert’s positive perception is essential regarding the strategies, to handle the task properly and achieve its maximum objectives. In the present study secondary school teachers of Malir district were taken as population of the study and were divided into two clusters; public and private. For selecting the sample of 560 sizes, each sub group of the sample remained equal by using probability technique. All the clusters were collected randomly. Mixed Method was the adopted research method; quantitative analysis contributes 80% and qualitative analysis contributes20%. Survey was the research design to collect the data. Close ended questionnaire was developed for collecting quantitative data. In-depth Interview was developed for collecting qualitative data. Independent sample t-test was used to compare the groups quantitatively and thematic analysis for qualitatively. The data triangulation determined the degree of strength of their perceptions. Obtained findings depict that private school teachers’ perceptions are stronger than public school teacher regarding the issue.
Creativity has always been attributed to human being as a certain kind of innate quality; however, until now there is no general consensus on what this term really means. In this sense, nothing would prevent it from being considered a contextualist attribution. On the other hand, the current state of technological development has led to several questions about the possibility that any system could be creative; as regards the significant development of the growing intersection produced between design and artificial intelligence will imply multiple legal challenges that intellectual property must address.
Full-text available
Although creativity constitutes a central human ability that needs to be fostered in school, research in didactics of philosophy hasn’t so far developed accounts of how to train creativity systematically. In this paper I will provide the foundations for a didactics of creativity for philosophy and ethics education. The approach is based on the insight that creativity is an important competence to be promoted in philosophy and ethics classrooms. I will define the concept of creativity and review key empirical findings from the field of educational psychology and psychology of learning which will help me working out a framework for fostering creativity in the philosophy classroom. Central to this is the idea that creativity can only be taught if the use of creative task types is preceded by a phase of acquiring domain-specific philosophical and ethical competences and knowledge. I will then argue that this objective can be implemented particularly well through the design thinking method. In this context, task types that promote divergent thinking are particularly effective. I will use three classroom examples to illustrate how creativity could be fostered in philosophy and ethics classes.
Research indicates that creative cognition depends on both associative and controlled processes, corresponding to the brain’s default mode (DMN) and executive control (ECN) networks. However, outstanding questions include how the DMN and ECN operate over time during creative task performance, and whether creative cognition involves distinct generative and evaluative stages. To address these questions, we used multivariate pattern analysis (MVPA) to assess how the DMN and ECN contribute to creative cognition over three successive time phases during the production of a single creative idea. Training classifiers to predict trial condition (creative vs non-creative), we used classification accuracy as a measure of the extent of creative activity in each brain network and time phase. Across both networks, classification accuracy was highest in early phases, decreased in mid phases, and rose again in later phases, following a U-shaped curve. Notably, classification accuracy was significantly greater in the ECN than the DMN during early phases, while differences between networks at later time phases were non-significant. We also computed correlations between classification accuracy and human-rated creative performance, to assess how relevant the creative activity in each network was to the creative quality of ideas. In line with expectations, classification accuracy in the DMN was most related to creative quality in early phases, decreasing in later phases, while classification accuracy in the ECN was least related to creative quality in early phases, increasing in later phases. Given the theorized roles of the DMN in generation and the ECN in evaluation, we interpret these results as tentative evidence for the existence of separate generative and evaluative stages in creative cognition that depend on distinct neural substrates.
This integrative review was conducted to summarize the knowledge pertaining to the effects that serotonergic psychedelics can have on creativity, a multi-dimensional construct referring to the ability to produce original and valuable artifacts. Psychedelics, which have long been hailed as substances that can enhance the creative process in their users, have experienced a recent resurgence in research, allowing the opportunity to better understand this relationship. To this end, I reviewed literature which attempted to study the effects of serotonergic psychedelics on creativity through psychometric methods. A total of eleven studies were reviewed, with four psychedelic compounds represented. Every study assessed components and subcomponents of divergent and convergent thinking, with only one instance of product assessment. Results suggest that convergent thinking may increase during the post-acute phases of the drugs' intake, fostering the capacity for development of previously generated ideas. However, this evidence may be circumstantial based on the low number of studies available, small sample sizes, overall lack of randomized controlled trials, and significant methodological limitations throughout most studies. Potential mechanisms underlying these effects are discussed, along with the current state of the research and implications for future studies.
ResearchGate has not been able to resolve any references for this publication.