ArticlePDF Available

Creative Processes during a Collaborative Drawing Task in Teams of Different Specializations

Creative Education, 2020, 11, 1751-1775
ISSN Online: 2151-4771
ISSN Print: 2151-4755
10.4236/ce.2020.119128 Sep. 23, 2020 1751 Creative Education
Creative Processes during
a Collaborative Drawing
Task in Teams of Different
Olesya Blazhenkova1*, Maria Kozhevnikov2
1Sabancı University, Istanbul, Turkey
2National University of Singapore, Singapore
The present research examined creative drawing processes
in teams of gifted
adolescents with different educational specializations, including teams with
homogeneous (the same specialization) and heterogeneous (mixed specializa-
tion) composition. Based on the converging evidence from protocol and Lin-
kography analy
ses, we identified the differences in frequency and dynamic
distribution of distinct creative processes between the different teams special-
izing in visual art, natural science, humanities, as well as mixed specialization
teams. Visualization processes play
ed a crucial role for visual art, science,
mixed, but not for humanities teams. All teams except humanities had visual
planning earlier in the creative process. Visual artists’ visualization processes
developed prominently and continuously throughout all s
tages of creative
production with the main focus on visual aesthetics while for scientists, they
developed more discreetly, and in conjunction with understanding of func-
tion. Mixed and visual art teams shared many similarities, and they had the
highest lev
el of integration between the ideas expressed during their creative
processes. Mixed team had higher frequency of organizational processes, in-
dicating coordination and organization challenges due to their diversity. The
results of this research show the im
portance of considering differences in
visualization profiles while composing teams of different specializations.
Creative Processes, Visualization, Teamwork, Linkography, Artistic
Creativity, Scientific Creativity
How to cite this paper:
Blazhenkova, O.,
Kozhevnikov, M. (2020). Creative Proc-
esses during a Collaborative Drawing Task
in Teams of Different Specializations
tive Education
, 11,
August 4, 2020
September 20, 2020
September 23, 2020
Copyright © 20
20 by author(s) and
Research Publishing Inc.
This work is
licensed under the Creative
Commons Attribution International
License (CC BY
Open Access
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1752 Creative Education
1. Creative Processes during a Collaborative Drawing Task
in Teams of Different Specializations
The present research examined creative processes during collaborative drawing
task in teams of different specializations. Over the last two decades, professional
work in different fields, including artistic and scientific domains, has increa-
singly involved collaborative practice, while solo authors producing creative
works become less frequent (Wuchty, Jones, & Uzzi, 2007). The growing interest
in interdisciplinary collaborations creates new educational and professional de-
mands, and preparedness to work in multidisciplinary teams becomes a required
skill expected from both engineering (Hirsch et al., 2001; Terenzini, Cabrera,
Colbeck, Parente, & Bjorklund, 2001) and visual art and design (Stevelt-Kaser,
Pennington-Busick, & Rhoades, 2004) schools. Along with development of new
technologies and new visual media, the role of visual communication is con-
stantly growing, bringing together specialists from various creative fields (e.g.,
visual art, design, computer science, engineering etc.) to work in mono- and
multidisciplinary teams and to share visual information. However, understand-
ing of collaborative processes behind interdisciplinary team interaction, and how
visual information is processed and shared among the team members with dif-
ferent visualization profiles such as visual artists and scientists has been limited.
Most previous studies on collaborative team performance were conducted in
the fields of design research and organisational psychology. Design research has
been mostly interested in the description of creative processes in architectural
and engineering domains. To discover general patterns emerging in different
collaborative design situations, it examined the characteristics of design activi-
ties, team interaction processes as well as communication behaviour that sup-
ports collaboration during the creative process (Austin, Steele, Macmillan,
Kirby, & Spence, 2001; Dong, 2005; Kvan, 2000; Sonnenwald, 1996). In particu-
lar, it has explored how the characteristics of creative processes (e.g., dynamics
of idea development and their interconnectedness) can predict the quality of a
creative product (e.g., based on experts’ estimates). Linkography analysis of in-
terconnectedness between the ideas during design process (Goldschmidt, 1990,
1992; Kan & Gero, 2008) has been frequently implemented in this research to
examine creative processes either in a single designer or in a team of designers.
Linkography research reported that the most creative and productive works,
highly evaluated by the experts, had denser and more integrated structure of
Linkographs (Goldschmidt & Tatsa, 2005; Van der Lugt, 2003). Moreover, Lin-
kograph metrics were found to reflect the differences between expert and novice
designers (Cai, Do, & Zimring, 2010; Kan, Bilda, & Gero, 2007).
While design research primarily focused on qualitative descriptions of team
creative processes, organizational psychology research focused more on how
team composition factors (e.g., heterogeneity vs. homogeneity) and team proc-
esses (e.g., implemented strategies and communication) affect team performance
(Aggarwal & Woolley, 2013; Hackman & Hackman, 2002; Salas, Sims, & Burke,
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1753 Creative Education
2005; Woolley, Hackman, Jerde, Chabris, Bennett, & Kosslyn, 2007; Woolley,
Chabris, Pentland, Hashmi, & Malone, 2010). It has been argued that greater
similarities between team members’ mental representations (shared mental
model) lead to better communication, improved anticipation of each other’s ac-
tions, and better coordination of activities, eventually resulting in more efficient
performance (Banks & Millward, 2000; Cannon-Bowers, Salas, & Converse,
1993; Klimoski & Mohamed, 1994; Kraiger & Wenzel, 1997; Mesmer-Magnus &
DeChurch, 2009). At the same time, dissimilarities between team members
might allow to bring unique perspectives to the task and tap a broader array of
relevant information (Egan, 2005; Milliken, Bartel, & Kurtzberg, 2003).
Overall, the majority of the previous studies on team creativity explored crea-
tive collaborative processes of either artists, architects, engineers or scientists
(Atman, Chimka, Bursic, & Nachtmann, 1999; Bilda, Costello, & Amitani, 2006;
Dunbar, 1999; Hagaman, 1990; Kan & Gero, 2005; Stokols, Hall, Taylor, &
Moser, 2008) but did not explicitly compared creative processes in homogeneous
and heterogeneous teams composed of individuals with different specializations
whose work involve visualization. At the same time, cognitive psychology and
neuroscience studies demonstrated qualitative and quantitative differences be-
tween visual art, sciences, and humanities professionals in their ways to process
visual information (Blazhenkova & Kozhevnikov, 2010; Kozhevnikov, Kozhev-
nikov, Chen, & Blazhenkova, 2013; Kozhevnikov, Kosslyn, & Shepard, 2005). In
particular, research showed the dissociation between object visualization (i.e.,
processing visual information about the object or scene appearances in terms of
their visual properties such as color, shape and texture) and spatial visualization
(i.e. processing visual information about spatial relations, performing mental
spatial transformations and manipulations). It was reported that visual artists
excel on object imagery tasks, while scientists and engineers excel on the tasks
that require spatial visualization. Furthermore, the dissociation between object
and spatial visualization has been related to artistic and scientific creativity, re-
spectively, and these two types of creativity appeared to be significantly different
in terms of visualization processes they involve (Kozhevnikov et al., 2013). Re-
cent research (Blazhenkova & Kozhevnikov, 2016) has shown that the drawings
created by teams of different visualization profiles were different in their visual
object vs. spatial characteristics as well as they were evaluated differently by the
experts from different professional domains. Visual art and mixed teams’ draw-
ings were evaluated as the highest in artistic quality, science teams were evalu-
ated as the highest in concept clarity, whereas humanities drawings were evalu-
ated as the lowest on both criteria.
The present research is a part of a larger study (Blazhenkova & Kozhevnikov,
2016). This previous study showed that different specialization teams, composed
of individuals with diverse visualization profiles, produced qualitatively different
creative outputs. The drawings produced by these teams were found to be dif-
ferent in terms of their visual characteristics as well as they were evaluated dif-
ferently in terms of artistic quality and conceptual clarity by the experts from
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1754 Creative Education
different professional domains. While the focus of that study was on the analyses
of team’s drawn outputs in terms of their visual characteristics, the main goal of
the present research was to explore creative
, with a specific focus on
visualization, in teams composed of individuals with different visualization pro-
files (specializing in visual arts, sciences, or humanities), including groups with
homogeneous (the same specialization) and heterogeneous (mixed specializa-
tion) composition. In particular, we were interested in the differences between
these teams’ communication processes, level of integration between the ideas
expressed during the creative processes as well as the process of idea develop-
ment. Based on previous research findings that creativity of individuals with dif-
ferent visual profiles are different (Kozhevnikov et al., 2013), we expected crea-
to be considerably different in teams of different specializations
(visual artists, scientists, humanities). We also expected creative processes of he-
terogeneous groups to be different from those of homogeneous groups.
The first goal was to investigate the role of visualization in creative processes
of teams specializing in visual art, sciences, and humanities as well as mixed spe-
cialization team. The second goal was to explore the differences between the
teams’ visual and non-visual collaborative processes throughout the duration of
the entire creative activity. In the current study, we implemented protocol analy-
sis of participants’ communications during their collaborative creative work. The
protocol analysis categories were examined and compared between the teams in
terms of their frequency distribution as well as dynamic frequency distribution
throughout the duration of the creative process. Furthermore, to examine the
teams’ differences in the level of integration between the ideas expressed during
the creative process, we used the Linkography method (Goldschmidt, 1990). Fi-
nally, we explored the relationship between the characteristics of team processes
(i.e., Linkography metrics tapping different parameters of idea development
examined in the current study) and team performance characteristics (i.e., ex-
pert’ estimates of the drawings, revealed in Blazhenkova & Kozhevnikov, 2016,
2. Method
The current study is a part of a larger study (Blazhenkova & Kozhevnikov, 2016)
which implemented a collaborative open-ended creative task (drawing an “un-
known planet”) and used adolescent sample (students from schools for gifted
children, specializing in visual arts, science, humanities or multiple disciplines).
Using schoolchildren allowed to examine creative drawing in members of dif-
ferent specializations and to present them a comparable level of challenge to the
teams with different specializations in ecologically valid settings school settings
(otherwise, such a creative drawing task may be not ecologically valid for adult
professionals) Previous research showed that adolescents’ visualization abilities
are nearly developed (Blazhenkova, Kozhevnikov, & Becker, 2011), and their
object or spatial visualization abilities relate to their aptitudes in visual art or
sciences specializations (Kozhevnikov, Blazhenkova, & Becker, 2010).
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1755 Creative Education
2.1. Participants
The participants were recruited from Russian specialized schools for gifted chil-
dren, which use advanced curricula, concentrating on a specific discipline (visual
art, science, or humanities), and involving university-level faculty as teachers.
Overall, 28 adolescents (16 females; 11 - 17 years old;
age 14.60) formed four
specialization teams (with 6 - 8 participants in each team): “visual art”, “science”
and “humanities” homogeneous teams (from schools for gifted with the above
specializations) as well as “mixed” heterogeneous team (from a school that ad-
mits gifted students from a variety of domains and offers an advanced multidis-
ciplinary curricula).
2.2. Procedure and Materials
The study was conducted in the students’ typical school environment such as
classrooms. Each team received a large piece of paper (A1 size) placed on a table
and various drawing materials (e.g., pencils, crayons, pastels, and gouache). Par-
ticipants were instructed to imagine and to draw an unknown planet as a team.
The current creative task allowed a variety of approaches encouraging the use of
representations from different domains (e.g., science, visual art, and humanities)
and divergent outcomes. Participants could move freely around the table while
drawing and use any materials and any space on the paper. Students were en-
couraged to share and communicate with each other. The maximum time allot-
ted to the task was 45 minutes (a typical time of a school lesion), and they could
finish their work earlier upon agreement. After completion of the drawings, par-
ticipants were briefly interviewed about their experiences. Drawing processes
and the subsequent interviews were video recorded and transcribed.
3. Results
3.1. Protocol Analysis of Collaborative Processes
The main goal of the current protocol analysis was to examine and compare col-
laborative processes in teams of different specializations. First, a coding scheme
that distinguished between different categories of collaborative processes was
developed. Second, the frequency of the identified categories was examined.
Third, the dynamic distribution (frequency in time) of different categories was
analyzed across the duration of teams’ creative processes.
Coding scheme development. The coding scheme was developed based on
an examination of video recordings from all the teams. The coding scheme was
modified from Kan & Gero’s (2009) creative design model to include more ela-
borated categorization of visualization processes and other aspects of collabora-
tive activities during the drawing task. While developing the present coding
scheme, we paid attention to visualization processes as well as to participants’
discussions related to drawing activity. First, the three main stages of creative
processes were identified: Planning (discussions about future drawing and con-
sidering different possibilities before their execution), Drawing (implementing
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1756 Creative Education
the ideas in the actual drawing), and Evaluation (interpreting and evaluating the
drawings). In our protocol analysis, we further identified different categories
representing specific processes occurring during each stage, as described below.
. During this stage, participants discussed their future draw-
ings in terms of visual appearances. They mentally simulated different possible
visual outcomes as well as planned how their future planet would function.
Thus, the main three categories of teams’ activities during Planning Stage were:
Planning of Visual Appearances, Mental Simulations, and Discussion of Func-
category included suggestions regarding
the planets’ appearances, e.g., in terms of color, shape, size, detail, specific visual
properties, or object presence [“Make it like Saturn, but with two rings”; “Let’s
draw things on the planet in an enlarged size, with some particular sights”]. The
category included visualizations of possible outcomes of
manipulating visual appearances. For example, it included imagining the results
of mixing colors [“If we mix these colors it will be a mess”], changing visual
properties [in response to a suggestion to help in drawing cracks: “If I draw this,
then it would be a different style and width”], altering composition and locations
[“If we place a cube here, then we could turn it like this, and could draw here as
well, from this sideand in different directions …—Look how coolif this is
water here, then here would be its cross-section”]. The
category included discussions of planet functioning, in terms of the nature or
physics governing the planet [“It can be a liquid planet with very strong attrac-
tive forces”; “This planet will have off-centre gravity”] as well as descriptions of
living forms and possibilities of life [“No one can survive on this planet”; “Liz-
ards and the penguins and whales inhabit the planet”].
. Drawing stages were often accompanied by different organi-
zational processes controlling participants’ collaborative activities and guiding
the flow of the drawing process, as well as by discussions of restrictions and set-
ting constraints on the content of the drawing in terms of its aesthetic appear-
ance or functional value. Thus, two main categories were identified during
drawing stages:
category included communications regulating
the organization of work process, e.g., task delegation, start/stop commands,
distributing roles, votes, encouragements, and control or fairness [“We should
start drawing now”; “Wait to drawwe need to discuss first”; “Who is gener-
ally agreed that we draw only landscape? (voting with raising hands) Yeah …”].
category included discussions of different constraints
on the content of the drawings and on the drawing process itself: functional re-
strictions, related to the violation of physics laws and logical rules [“This is too
big for a tree …—If here are couple thousands of kilometres, then how is it pos-
sible to be a tree?”]; aesthetic requirements, related to the violation of the laws of
aesthetics) [“Blue splashes on the blue sky will be invisible”; Light should go
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1757 Creative Education
from this angle, so here it will be darker; No! Don’t use violet, it’s too bright for
this]; material/technical constraints (e.g., limited given drawing materials, allot-
ted space etc.); instructional restrictions (rules and restraints that participants set
for themselves based on their interpretation of the task instruction, e.g., what
can be considered as unknown planet, the given time limit to draw the planet);
and restrictions related to difficulties drawing a proposed object (e.g., due to lack
of drawing skills).
. Evaluation stages included only one category
, which comprised of interpretations and evaluations of already
drawn content in terms of their visual characteristics and interpreted conceptual
meanings of the drawn [“—Are you sure that these are apples?Maybe
notMaybe these are berries …”]. All other discussions irrelevant to the crea-
tive processes were assigned to an
(IR) category which included dis-
cussing personal issues, school activities, etc. Since
categories consisted of dis-
cussions related to visual appearances and visual characteristics of the drawings,
we grouped them into a
combined category for further
analysis. It should be noted that these three categories emphasized different as-
pects of visualization.
was formulated declara-
tively, implying the execution of the proposed idea.
formulated as questions, which required performing visualization of possible
outcomes and inspecting how the future drawing would look like in case of cer-
tain drawing actions.
also required visualization and image
interpretation; however, the inferences were made from already drawn content,
based on external visual representations.
Frequency distribution of protocol analysis categories. Two judges seg-
mented the transcripts into separate meaningful utterances, usually a length of a
sentence [“It is not clear why the atmosphere is green” or “Let’s draw a ring
around the planet”]. Each segment represented a separate act of reasoning or a
coherent proposition related to what is being drawn. Overall, 442 segments were
identified in the visual art team transcript, 341 segments in the science team
transcript, 310 segments in the humanities team transcript, and 388 segments in
the mixed team transcript. Then, each segment was assigned to one of the cate-
gories described in the coding scheme development section by two independent
judges. The agreement between judges was 86%. All the discrepancies in classi-
fying the segments into the categories were resolved by consensus. The frequen-
cies of each category across different teams are presented in Figure 1.
For the
team, the most distinct and prevalent category was
(47.7%), so that about a half of the visual artists’ discus-
sions were devoted to visual properties of the planet and its appearance, e.g., in
terms of color and detail of the proposed objects. The next frequent category was
(16.1%), followed by
(12.9%), and
(12.3%). It is interesting that
was most-
ly related to visual appearances and aesthetic requirements (e.g., color blending
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1758 Creative Education
Figure 1. The frequencies of each category of protocol analysis.
rules, light source, rules of rendering 3D objects, use of the golden ratio etc.).
Overall, 76% of all the discussions were devoted to the three categories related to
. Visual artists had very little
In the
team, in contrast to visual artists, the most distinct and preva-
lent category was
(24%). Most of the scientists’
(80.5% within this category) were related to their planets’
physical nature, and they often referred to knowledge about physical laws and
astronomy (e.g., how the planet would spin, its gravity, chemical makeup, mag-
matic activity, presence of rings etc.), or devoted to descriptions of living forms
and possibilities of life. Interestingly,
tuted only (21.7%) of all the discussions, while in all other teams
was the most frequent category. Notably,
in the science team were also often related to functional properties
[“So, the atmosphere will be dark-green because it is made from chlorine”; “Let’s
make it blue, it will be a blue giant”].
(12.9%) discussion
were almost 9 times more often related to functional rather than aesthetic re-
In the
, about half (56.5%) of all the discussions belonged to
the two
such as
(27.4%) or to
(26.8%). Interestingly, the hu-
manities team was the only team that almost did not have MS (2.3%). During
, the humanities team did not explicitly discuss
either pictorial details or spatial configuration, but rather simply named differ-
ent objects to be drawn. The highest number of
in the hu-
manities team in comparisons with all other teams resulted from their attempts
to interpret the meaning of what they had drawn only after it was drawn (and in
some cases, they were unable to unambiguously identify the drawn object). The
less frequent categories in the humanities team were
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1759 Creative Education
category (12.3%), and
The profile of the
was similar to the visual artists’ profile which
was somewhat surprising, given that there was only 1 visual artist and 5 scien-
tists in this team. Overall, more than half (63.4%) of their discussions were de-
voted to
was the most
distinct and frequent category (33.5%), while
was the
least frequent (5.7%). In comparison to the other teams, they had relatively large
number of discussions on
(15.5%), possibly due to the
need for an extra effort in the coordination of different individuals’ views
throughout the drawing process. As for
(13.1%), mixed
teams had the most frequent discussions of instructional restrictions, which in-
dicated that they regularly attempted to reinterpret the task instructions and to
follow them. Their discussions of aesthetic requirements were only about 1.5
times more frequent than discussion of restrictions related to functions, which
suggests that, in contrast to visual artists, the mixed team was both concerned
about aesthetic and functional restrictions to a comparable level.
Dynamic distribution of all the categories defined in protocol analysis.
Figure 2 represents the dynamic distribution of all the defined categories during
the whole period of creative process.
in visual art, science, and mixed teams were
more frequent in the beginning, and then dropped off towards the end of the
drawing process. In contrast, the humanities team did not follow this trend, and
there was a considerable proportion of
at the
end of the process. PE in visual art, science, and mixed teams appeared later in
the process of drawing and became more frequent towards the end of their
drawing. In contrast, the humanities team had the opposite trend: their evalua-
tions started at the very beginning of the process and dropped at the end.
had various dynamic frequency fluctuations in different teams;
however, in the visual art, mixed team, and science teams, they were more or less
present throughout the whole drawing process, while in humanities they were
only present in several rare occurrences.
in the visual
art, mixed and humanities teams, appeared mostly in the middle and at end of
their creative process. In contrast, the science team started to discuss functions
along with
from the very beginning (the dy-
namic distribution of these two categories was quite similar), and finally
dropped at the end. In the science team,
either preceded
or developed along with
, suggesting that their
visualization and planning of functions were closely related processes. Possibly,
was constructed based on their understanding
of planet functioning.
and OP in visual art and mixed teams steadily contin-
ued throughout the process, with a gradual decline towards the end. However, in
science and humanities teams, restrictions appeared in more pronounced and
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1760 Creative Education
Figure 2. Dynamic distributions of all categories of protocol analysis. Note: All Visualiza-
tion Processes are represented in the shades of blue, and Non-Visual Processes are
represented in the shades of gray.
discrete peaks. Overall,
were continuously prevalent over
non-visual processes and were relatively equally distributed throughout the
process of drawing for the
as well as for the
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1761 Creative Education
but less equally distributed for the science and humanities teams.
Time spent for planning activities. While analyzing video recordings, we
noticed the difference between teams in time devoted to
, that
is, the time from getting instructions to starting drawing (i.e., discussions and
planning of future drawings or drafting some preliminary sketches of planets’
appearances), and the time that they spent for
itself. Humanities team
had almost no preliminary activities (6% of the total time) and started to draw
right after getting the instructions, in contrast to all other teams that spent con-
siderable amount of time for preliminary activities (visual art team51%,
science team30%, and mixed team27% of the total time). Notably, during
these preliminary planning activities, humanities team did not do any drafting
and sketching while visual planning was a typical for visual artists, scientists and
mixed teams.
Discussion. The results of protocol analyses revealed that all teams differed in
their categories’ frequency profiles and their dynamic distribution, although
there were some similarities between specific teams. The team of humanities had
a distinct frequency profile and dynamic distribution of categories in compari-
sons with other teams. In particular, the humanities team had remarkably low
frequency of
, but it had the highest frequency of
category, suggesting that the humanities team used visual imagery
primarily for analysis. Furthermore, the humanities team had the opposite pat-
tern of dynamic distribution across all
categories from
that of visual artists, scientists, or mixed teams. In contrast to all other teams, the
humanities team did not have
early in the
process, but tended to have more planning towards the end, and they had more
at the very beginning and less towards the end of their crea-
tive process. These results suggest that imagery of the humanities team might
have a different function than imagery used by other teams. Specifically, the
humanities team might not use visualization to create or predict new knowledge,
but rather for interpretation of already created visual representations. In con-
trast, the teams of visual artists, scientists, as well as the mixed team were plan-
ning visual appearances early in the process, which preceded drawing, and
tended to evaluate and interpret the drawings after their completion. This indi-
cates an important functional role of visualization in creative processes of these
teams, consistent with Blazhenkova and Kozhevnikov’s (2010) findings that vis-
ual artists and scientists used visual imagery at the very early stages of their work
to guide and inspire their further creative process.
Despite the above similarities, there were also marked differences in the cate-
gories’ frequency profiles and their dynamic distribution between the team of
scientists and the visual art and mixed teams. In visual art and mixed teams,
was the most frequent category, while the most
prevalent category for scientists was
, which either pre-
ceded or developed along with other
. Thus, scientists
were especially concerned with the functions of their drawn objects, consistent
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1762 Creative Education
with previous research (Blazhenkova & Kozhevnikov, 2010; Gooding, 2004) that
the main function of visual imagery for scientists is to facilitate their under-
standing of functionality of the system (e.g., outline its structures, schematize the
parts of a system and their interactions, and understand relationships among its
parts). Furthermore, while visual art as well as mixed teams had more smoothly
and continuously distributed
suggesting the continuous
role of visualizations at different stages of creative process, the team of scientists
exhibited more discrete and abrupt development of
suggesting that they use visualization only during specific periods of the creative
process. Previous research (Blazhenkova & Kozhevnikov, 2010) reported that
professional scientists use visual imagery primarily during specific stages of their
work (e.g., planning, problem solving), while visual artists use visual imagery
continuously during all stages of their art-making creative work (e.g., as inspira-
tion for beginning artwork, during the planning, execution, and estimating the
The mixed team shared many similarities with visual artists, both in terms of
frequency of different protocol categories and their dynamic distribution. Like
visual artists and unlike scientists, they had a high frequency of
and a low frequency of
. The mixed
team had the highest frequency of
in comparison to
other teams, probably because they made an extra effort in coordination of their
different individuals’ views throughout their creative process.
3.2. Linkography Analysis
In order to examine the teams’ differences in the level of integration of their
ideas expressed during the creative process and idea development, we used
analysis method (Goldschmidt, 1990, 1995; Kan et al., 2007). This
method is widely used in research field that studies creative processes in design
(e.g., Goldschmidt, 1990, 1995; Kan et al., 2007). It aims to reveal the conceptual
interconnectedness between the ideas, i.e., a meaningful relationship between
the ideas reflected in different protocol segments across the whole length of the
creative process. In the Linkography analysis, same as in the above protocol
analysis, the transcripts are decomposed into segments (also referred as
“moves”) and then all the conceptually related segments were linked. The links
are established based on determining meaningfully associated ideas that oc-
curred in the time sequence of the protocol and then by connecting these related
ideas, identified in one or more segments, to each other. A graphical representa-
tion which displays the structure of a creative process by tracing the associations
of every idea, called a
, is constructed to represent the patterns of as-
sociations between the ideas proposed during the creative process.
links that connect to previous segments and indicate the paths that had led to
idea generation, while
connect to subsequent segments and bear evi-
dence about contribution to the production of further ideas (see an example of a
fragment of a Linkograph in Appendix A).
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1763 Creative Education
There are several common structures identified in a Linkograph such as
(i.e., a group of segments that are almost exclusively linked among
(i.e., a large number of links among a relatively small number
of segments), and
(i.e., successive segments, each of which is
linked only to the preceding and following segments). Sawthooth tracks charac-
terize the sequential, stepwise development of ideas without referring to earlier
ideas, while chunks and webs characterize meaningful clusters of ideas that were
developed in connection with each other. Goldschmidt (1992) reported that
Linkographs of the most creative and productive work (those that were highly
evaluated by the judges) had more chunks and more webs.
indicates the degree of the “completeness” or the level of integra-
tion between the ideas in a creative process. It is computed as the ratio between
the number of links and the number of segments, thus representing the density
of a Linkograph (Goldschmidt, 1995).
are segments which have
the greatest number of links in the Linkograph, representing important or key
strategic decision points that appeared during the creative process. High values
of Link Index and Critical Moves were found to be related to higher estimates of
creative products by experts (Goldschmidt & Tatsa, 2005; Van der Lugt, 2003).
measure was introduced by Kan and Gero (2005) as a measure of link
integration, based on Shannon’s (1948) information theory. In this theory, the
amount of information carried by a message is based on the probability of its
outcome. The assumption is that the least predictable (or most random) se-
quence of events should carry the maximum information. The assumption be-
hind the computation of Entropy is that a randomly linked Linkograph (neither
poorly linked nor fully saturated) represents a balanced process that holds both
integration and diversification of ideas. Based on their findings that expert de-
signers had higher entropy than novice designers, Kan et al. (2007) proposed
that Entropy represents the opportunities for idea generation. Entropy correlates
with Link Index only until it reaches its maximum, and after its peak, Entropy
decreases as more links are formed, implying that in the case of a fully linked
linkography, there are no possibilities for the development of new ideas and less
opportunity for creative outcomes.
Two types of Entropy could be distinguished:
, which are measured separately in rows of forelinks and backlinks.
conceptually reflects the idea generation opportunities in
terms of new initiations that lead to the subsequent ideas, while
reflects the opportunities in building upon previous ideas (Kan & Gero,
2005). Thus, if an idea is completely novel, it will not have backlinks, and if an
idea is weak and do not provide any basis for further idea development, it will
have no forelinks. Based on the shape and structure of the Linkograph, re-
searchers can make inferences about the level of integration between the ideas
and patterns in their development (see examples of possible Linkograph struc-
tures and their interpretations in terms of Entropy in Appendix B).
For the current analysis, all the segments identified in the previous protocol
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1764 Creative Education
analysis were assigned sequential numbers. Then, two independent judges iden-
tified all the conceptually related segments. The agreement between the judges
was 92%, and all the discrepancies were resolved through consensus. Then, using
LiNKODER software (Pourmohamadi & Gero, 2011) we constructed a Lin-
kograph for each team. Furthermore, we computed Link Index and Entropy
measures (Table 1). We also identified Critical Moves as those segments that
had both high (exceeding one SD from the mean number of links per segment
for the current team) number of backlinks and forelinks. Additionally, we ex-
amined to which categories identified in the previous protocol analysis, the crit-
ical moves were related as well as the function of Entropy versus time across the
whole length of the creative process. Using the LiNKCODER software, we
created the graphs for dynamic forelink and backlink Entropy along the se-
quence of segments (Figure 3).
Figure 3. Linkographs and Entropy dynamics of (a) visual art, (b) science, (c) humanities, (d) mixed teams. Filled triangles
indicate Critical Moves.
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1765 Creative Education
Table 1. Linkographs statistics for all teams.
Visual art Science Humanities Mixed
Total link number 806 496 336 753
Link Index 1.83 1.46 1.08 1.95
Forelink Entropy 31.42 32.09 29.86 36.55
Backlink Entropy 47.03 39.81 25.98 45.06
Visual art team. The visual art team had many connections between the Lin-
kograph segments (Figure 3(a)). Compared to other teams, they had a high
value of
indicating a high level of integration between the ideas pro-
posed during the process of drawing. Large clusters, chunks, and webs indicate
that visual artists’ ideas have developed in meaningful complexes with high in-
terconnectedness between each other. There were widespread clusters that
linked the ideas proposed at the very beginning of the creative process with the
ideas proposed at the end, indicating that visual artists retained an awareness of
their initial thoughts and developed them throughout the entire process. There
were 19
, 1DF).
tended to appear more in the beginning and in the middle of the Linkograph,
suggesting that many critical decisions were made early in the creative process.
Artists had high values of both mean
indicating a high potential for idea development. Furthermore, the investigation
revealed the two peaks in the beginning and in the middle
of the process that corresponded to the beginning of sketching and actual draw-
ing respectively, and then decreased towards the end. According to Kan and
Gero (2005), this suggests that visual artists created many opportunities for idea
development at the beginning of drafting, and then these opportunities gradually
whittled down.
Science team. The science team had a fairly connected structure of the Lin-
kograph (Figure 3(b)). Scientists, compared to other teams, had an intermediate
, indicating an intermediate level of link interconnectedness. Scien-
tists’ Linkograph consisted of webs and sawtooth tracks, which indicates that
they had both clustered as well as the successive development of ideas. Similar to
visual artists, they also had widespread clusters that linked the ideas proposed at
the very beginning of the creative process with the ideas proposed at the very
There were 8
, 3DF). The
were relatively equally distributed in the process. Scientists, as compared
to other teams, had relatively high
. Interestingly, scientists, as compared
to visual artists, had somewhat higher
, and lower
. This may indicate that scientists tended to have more idea generation op-
portunities in terms of new initiations, unlike visual artists who tended to create
more opportunities based on the previous ideas. The
demonstrate that
tended to peak in the begin-
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1766 Creative Education
ning of the process, to drop off when drawing commenced, and then to stabilize
at an average level. Such dynamics of Entropy indicate that scientists, similar to
visual artists, had created the opportunities for idea development in the begin-
ning of the process, but unlike artists, they still had the opportunities at the end
of the process.
Humanities team. The humanities team had a poorly connected structure as
compared to other teams, most densely connected towards the end of the proc-
ess (Figure 3(c)). The humanities team, among other teams, had the lowest
which indicates a low level of integration between their ideas. Their Lin-
kograph primarily consisted of successive sawtooth tracks, with only a few webs
and chunks, reflecting the predominance of sequential, stepwise development of
ideas. There were no widespread clusters that persisted throughout the whole
creative process and there were only a few single long links, indicating that the
humanities team’s ideas were rather transient. Only 3
were iden-
tified (1
, 1—DF, 1OP). All of them were positioned
towards the end of the Linkograph, when the actual drawing was almost com-
The humanities team had the lowest
among other teams. Unlike
other teams, the humanities team had
higher than
. The
graph demonstrated that Entropy was relatively
low at the beginning of the process and tended to peak at the end of the process
in contrast to all other teams. This reflects that humanities team discovered their
opportunities only towards the end of the creative process.
Mixed team. The structural patterns of the mixed team were very similar to
those of visual artists (Figure 3(d)). They had a highly connected structure,
most densely connected in the beginning of the creative process. The mixed
team also had a high value of
. Similar to the artists, their Linkograph
had a clustered structure consisting of chunks and webs, as well as sawtooth
tracks. A mixed team also had two noticeable large clusters with elaborated con-
nections; one appeared during the initial planning, and the second during the
planning preceding the drawing of the substantial elements of the picture. There
were also many long link connections and clusters that ran throughout the whole
process. There were 10
, 2OP). Over-
all, their Critical Moves tended to appear both in the beginning and at the end of
the process.
Furthermore, the mixed team, similar to visual artists, had high values of both
measures. The examination of
dynamics revealed two main peaks.
revealed the two peaks,
one in the beginning and one in the middle of the process, which corresponded
to the beginning of sketching and actual drawing, respectively, and then de-
creased towards the end. This reflects that the mixed team, similar to the visual
artists, created the most opportunities for idea development at the beginning
and middle of the process.
Discussion. The examination of the Linkographs’ structure revealed the dif-
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1767 Creative Education
ferences between the teams in the
of their
ideas. Visual and mixed teams had the highest level of interconnectedness and
integration between their ideas (as reflected in Link Index and Entropy meas-
ures). According to the literature (Cai et al., 2010; Goldschmidt, 1990; Kan &
Gero, 2008; Van der Lugt, 2003), Linkographs of the most creative and produc-
tive work (those that were highly evaluated by the experts) have higher link in-
terconnectedness. Indeed, in our study, Link of Index and Entropy measures as
well as number of chunks and webs were consistent with professional estimates,
which rated artists and mixed teams as the highest on Artistic Quality (Blazhen-
kova & Kozhevnikov, 2016). However, these Linkograph measures were not re-
lated to the experts’ estimates of Conceptual Clarity, indicating that not all as-
pects of creative productivity can be tapped by Linkograph measures of link in-
As suggested by Kan and Gero (2007), a highly integrated Linkograph may re-
flect more holistic processing, while a more discretely clustered structure may
represent a sequential process of trying different possibilities and developing
ideas one after another. This could explain the results of our study. As was evi-
dent from the analysis of videorecordings, visual artists and mixed teams, who
had the most highly integrated Linkographs, used a more holistic approach to
drawing; started from a global scene and then filled in the details while drawing
several objects concurrently. Scientists and humanities, in contrast, drew in dis-
crete units, rendering one thing at a time, and they sequentially proceeded from
one element of the drawing to the next one. The humanities team’s drawing, al-
though sequential, was less coordinated than that of the scientists, so that many
elements of the drawing were not related to each other. Our findings are consis-
tent with Kozhevnikov et al. (2005) reporting the differences between artists and
scientists’ holistic versus sequential visual processing and relating these differ-
ences to different types of visualization.
The examination of Linkograph Dynamic Entropy further revealed the
between the teams of different specializations.
Both visual art and mixed teams had two Entropy peaks, one at the very begin-
ning of the process, during planning and sketching phases, and the second one
before actual drawing. We suggest that such a pattern occurs because the par-
ticipants create more opportunities at the beginning of the process, but while
approaching the end, they tend to converge on a particular approach (see also
Kan & Gero, 2007). Similar to visual artists and mixed teams, scientists had a
high level of Dynamic Entropy at the beginning of the process, however, they did
not have the second peak during the drawing, suggesting that the highest level of
their idea development happened during the initial planning stage (prior to
drawing), and they later created their drawing mainly from these originally gen-
erated ideas. Unlike the artists and mixed team, they did not have a decrease in
Entropy towards the end; it remained rather stable, indicating that they kept
generating ideas and developing new opportunities at some level until the end of
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1768 Creative Education
the process. The Dynamic Entropy of the humanities team increased only at the
end, indicating that the humanities team discovered their opportunities and
made critical decisions based on the analysis of already drawn pieces, whereas in
the beginning they were unable to generate new opportunities based on visuali-
zation alone.
4. General Discussion
The current research examined creative collaborative
in teams of dif-
ferent specializations during a creative drawing task. Based on converging evi-
dence from the protocol and Linkography analyses, we identified considerable
differences in visualization and non-visual processes between the teams special-
izing in teams of different specializations.
The results suggest that, overall, visualization plays a significant role for crea-
tive processes of visual art, science, mixed teams, but not humanities teams. It
was evident from the high frequency of visualization categories in the protocol
analysis, from the majority of critical moves of these groups related to visualiza-
tion, as well as from the frequency of visualization processes involved in plan-
ning and prediction. Previous research also supports the crucial importance of
visualization in creative work of visual artists and scientists (Blazhenkova &
Kozhevnikov, 2010, 2016; Kozbelt, 2001; Miller, 1996).
Furthermore, the analysis revealed differences between the teams in their use
of visualization. For visual artists, visualization processes developed prominently
and continuously throughout all stages of creative production, while for scien-
tists, visualization processes developed in conjunction with understanding of
function. Current findings further support Blazhenkova & Kozhevnikov (2016)
conclusions that visualization plays a different role and it is used for different
purposes in teams of different specializations. In particular, visual artists tend to
use their visual imagery as a source of creative inspiration for generation of vis-
ual aesthetic representations, while scientists tend to use imagery for solving
problems and communication of unambiguous meanings that have functional
relevance (see also Gooding, 2004; Rosenberg & Trusheim, 1989). In contrast to
scientists, both visual artists and mixed teams were more concerned with visual
appearance than with functional characteristics of a creative work, which is pos-
sibly happened, because the task was interpreted as more artistic than scientific
challenge. Furthermore, the relatively high proportion of organizational proc-
esses in mixed groups is likely to reflect the challenges that they had to deal with
due to their diversity. Indeed, literature suggested that diversity, even while be-
ing potentially beneficial to team performance, may cause coordination difficul-
ties (Cronin & Weingart, 2007; Milliken, Bartel, & Kurtzberg, 2003). As was evi-
dent in our study, coordination difficulties may have resulted in the increased
number of organizational collaborative processes that involved votes and regula-
tions. Moreover, the case of mixed teams demonstrated that the presence of
members who are competent in a certain domain of knowledge (e.g., visual art)
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1769 Creative Education
may be beneficial for all other members in the group, and may lead to success in
at least some aspects of team performance (e.g., increasing artistic quality of the
collaborative product). Indeed, there is growing evidence that both, artists and
scientists, can benefit from their collaboration (Edmonds & Leggett, 2010; Keefe,
Karelitz, Vote, & Laidlaw, 2005; Meyer, Staples, Minneman, Naimark, & Glass-
ner, 1998). For example, Keefe et al. described benefits of artistic collaboration in
designing virtual reality scientific visualizations and claimed that artists can pro-
vide a unique source of visual insight in tackling difficult visual problems, as well
as in analysing and refining visual works. However, the present research suggests
that such collaboration may not equally benefit the team performance in all as-
pects. In particular, the presence of visual artists in the team may provide visual
insights and considerably improve the artistic quality of the creative product;
however, this can happen at the expense of scientific clarity of the creative out-
put or at the expense of time devoted to coordination and organizational activi-
Compared to all other groups, humanities team had the lowest frequency of
mental simulation visualization category in the protocol analysis. Besides, the
majority of humanities team critical decisions (as reflected in critical moves)
were unrelated to visualization processes. Moreover, humanities team did not
use visualization for either predicting the contents of a creative drawing or for
creating new knowledge. The protocol analysis of visualization categories and
their dynamic distribution suggests that humanities team did not use visualiza-
tion for planning and prediction, but rather for interpretation of already drawn
content. Markedly, humanities team generated their main ideas only at the end
of the drawing. Unlike humanities team, visual art, mixed, and science teams
generated their key creative ideas at the very beginning of the creative process
(as reflected by the entropy dynamics). In addition, the examination of time
spent for planning activities showed that humanities team did not spend much
time for planning prior to drawing and did not use visualization for planning,
while other teams, before the start of their drawing, devoted a significant portion
of time for planning that involved visualizing and drafting of a future work.
These results are consistent with other research that compared experts versus
novices’ performance and reported that expert scientists and designers employ
earlier planning and prediction during the problem solving as compared to
non-experts. For example, Atman et al. (1999) found that expert engineering
students, compared to novices, paid more attention to ‘problem scoping’ or
adequately setting up the problem before beginning the analysis. Similarly, in the
field of design, Christiaans and Dorst (1992) compared junior and senior indus-
trial design students and found that that senior students tended to clarify priori-
ties early on in the process. In the present study, humanities team could be con-
sidered as non-expects, since their skills may be incongruent to the current crea-
tive task requirements, involving more visual rather than verbal processing.
Furthermore, the present study supported the link between the team processes
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1770 Creative Education
and performance. Linkography metrics of different specialization teams ap-
peared to be partially consistent with professionals’ evaluations of these draw-
ings reported in Blazhenkova and Kozhevnikov (2016). This previous study
showed that visual art and mixed teams’ drawings were estimated as the highest
in artistic quality, science teams were estimated as the highest in concept clarity,
whereas humanities drawings were evaluated as the lowest on both criteria. The
present results suggest that common Linkography measures, Link Index and
Entropy, can predict professionals’ estimates of creative outputs only in specific
aspects of productivity: artistic quality, but not conceptual clarity. Thus, Lin-
kograph link interconnectedness and completeness measures may not be rele-
vant for a prediction of all aspects of the idea development and creativity. Over-
all, the present research shows the possibilities of Linkography method for un-
derstanding cognitive processes underlying group creative performance. At the
same time, the present findings have potential applications for the field of de-
sign. The structure of a Linkograph (dynamics of its density, location of critical
moves) can provide useful information about the group dynamic processes and
employed strategies. The possibility to detect and quantify the strategical char-
acteristics of a team processes can be very critical for predicting team perform-
ance. This would considerably contribute to the existing research examining the
characteristics of team creative processes and aid understanding how the im-
plementation of successful strategies contributes group performance (Cronin &
Weingart, 2007; Hackman & Hackman, 2002; Salas et al., 2005). Furthermore,
our study provides the case of integrative examination of the relative frequency
of protocol categories (parsing out different visualization and non-visual proc-
esses), their dynamics throughout the creative progress, and Linkograph metrics
(e.g., critical moves) considered in relation to the identified protocol categories.
Such an approach may inspire the development of new methods and measures
in the field of design research for assessing different aspects of creative produc-
tivity (e.g., not only artistic creativity, but also scientific creativity related to
functional characteristics) as well as for assessing cognitive processes (e.g., dif-
ferent aspects of visualization). Our research shows the possibilities of Lin-
kography methodology for understanding cognitive aspects of creative team
processes and suggests new perspectives in implementing Linkography meas-
One of the major limitations of the current study is implementing the case
approach and using adolescents, which put restrictions on the possible generali-
zations for adult population. Nevertheless, the present study brings new knowl-
edge about the role of visualization for the creative processes in teams of differ-
ent specializations. Our research sheds light on understanding creative visual
processes and dynamics behind multidisciplinary creative team interaction, and
in particular, how visual information is processed and shared among the mem-
bers of the teams with different visualization profiles. Our research emphasizes
the importance of considering differences in visualization profiles while com-
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1771 Creative Education
posing teams of different specializations. Here we show the case that such dif-
ferences have a considerable impact on team process characteristics, which in
turn are related with the quality characteristics of the final creative outputs. In
response to growing interest in art-science interdisciplinary collaboration, cur-
rent research brings new insights about the possibilities and limitations of crea-
tive collaboration between individuals with different specializations. Present
findings should be interesting for a broad audience from cognitive, educational
and organizational psychology as well as design research and other applied
This work was partially supported by National Institute of Education (Singapore)
under the MOE Academies of Fund, AFR 0117 MK to Maria Kozhevnikov.
Conflicts of Interest
The authors declare no conflicts of interest regarding the publication of this pa-
Aggarwal, I., & Woolley, A. W. (2013). Do You See What I See? The Effect of Members’
Cognitive Styles on Team Processes and Errors in Task Execution.
Organizational Be-
havior and Human Decision Processes, 122,
Atman, C. J., Chimka, J. R., Bursic, K. M., & Nachtmann, H. (1999). A Comparison of
Freshman and Senior Engineering Design Processes.
Design Studies, 20,
Austin, S., Steele, J., Macmillan, S., Kirby, P., & Spence, R. (2001). Mapping the Concep-
tual Design Activity of Interdisciplinary Teams.
Design Studies, 22,
Banks, A. P., & Millward, L. J. (2000). Running Shared Mental Models as a Distributed
Cognitive Process.
Journal of Psychology, 91,
Bilda, Z., Costello, B., & Amitani, S. (2006). Collaborative Analysis Framework for Evalu-
ating Interactive Art Experience.
CoDesign, 2,
Blazhenkova, O., & Kozhevnikov, M. (2010). Visual-Object Ability: A New Dimension of
Non-Verbal Intelligence.
Cognition, 117,
Blazhenkova, O., & Kozhevnikov, M. (2016). Types of Creativity and Visualization in
Teams of Different Educational Specialization.
Research Journal, 28,
Blazhenkova, O., Kozhevnikov, M., & Becker, M. (2011). Object-Spatial Imagery and
Cognitive Styles in Children and Adolescents: Developmental Trajectories in Relation
to Ability.
Differences, 21,
Cai, H., Do, E. Y.-L., & Zimring, C. M. (2010). Extended Linkography and Distance
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1772 Creative Education
Graph in Design Evaluation: An Empirical Study of the Dual Effects of Inspiration
Sources in Creative Design.
Design Studies, 31,
Cannon-Bowers, J. A., Salas, E., & Converse, S. (1993). Shared Mental Models in Expert
Team Decision Making. In N. J. Castellan Jr. (Ed.),
(pp. 221-246). Hillsdale, NJ: Lawrence Erlbaum.
Christiaans, H., & Dorst, K. (1992). An Empirical Study into Design Thinking. In N.
Cross, K. Dorst, & N. Roozenburg (Eds.),
(pp. 119-126).
Delft: Delft University Press.
Cronin, M. A., & Weingart, L. R. (2007). Representational Gaps, Information Processing,
and Conflict in Functionally Diverse Teams.
Management Review, 32,
Dong, A. (2005). The Latent Semantic Approach to Studying Design Team Communica-
Studies, 26,
Dunbar, K. (1999). The Scientist
in Vivo
: How Scientists Think and Reason in the Labo-
ratory. In L. Magnani, N. Nersessian, & P. Thagard (Eds).
(pp. 89-98). New York: Plenum Press.
Edmonds, E., & Leggett, M. (2010). How Artists Fit into the Research Processes.
nardo, 43,
Egan, T. M. (2005). Creativity in the Context of Team Diversity: Team Leader Perspec-
Resources, 7,
Goldschmidt, G. (1990). Linkography: Assessing Design Productivity. In R. Trappl (Ed.),
(pp. 291-298). Singapore: World Scientific.
Goldschmidt, G. (1992). Criteria for Design Evaluation: A Process-Oriented Paradigm. In
Y. E. Kalay (Ed.),
(pp. 67-79). New York: Wiley.
Goldschmidt, G. (1995). The Designer as a Team of One.
Design Studies, 16,
Goldschmidt, G., & Tatsa, D. (2005). How Good Are Good Ideas? Correlates of Design
Studies, 26,
Gooding, D. (2004). Cognition, Construction and Culture: Visual Theories in the Sci-
and Cognition, 4,
Hackman, J. R., & Hackman, R. J. (2002).
. Brighton, MA: Harvard Business Press.
Hagaman, S. (1990). The Community of Inquiry: An Approach to Collaborative Learn-
Art Education, 31,
Hirsch, P. L., Shwom, B. L., Yarnoff, C., Anderson, J. C., Kelso, D. M., Olson, G. B., &
Colgate, J. E. (2001). Engineering Design and Communication: The Case for Interdis-
ciplinary Collaboration.
Engineering Education, 17,
Kan, J. W. T., Bilda, Z., & Gero, J. S. (2007). Comparing Entropy Measures of Idea Links
in Design Protocols: Linkography Entropy Measurement and Analysis of Differently
Conditioned Design Sessions.
Artificial Intelligence for Engineering Design, Analysis
and Manufacturing, 21,
Kan, J. W., & Gero, J. S. (2005). Can Entropy Indicate the Richness of Idea Generation in
Team Designing. In
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1773 Creative Education
(pp. 451-457). New Delhi, India: TVB.
Kan, J. W. T., & Gero, J. S. (2007). Can an Objective Measurement of Design Protocols
Reflect the Quality of a Design Outcome? In
(pp. 1-12). Paris: Ecole Centrale
de Paris.
Kan, J. W. T., & Gero, J. S. (2008). Acquiring Information from Linkography in Protocol
Studies of Designers.
Studies, 29,
Kan, J. W. T., & Gero, J. S. (2009). Using the FBS Ontology to Capture Semantic Design
Information in Design Protocol Studies. In J. McDonnell, & P. Lloyd (Eds.),
Designing. Analysing Design Meetings
(pp. 213-229). Boca Raton, FL: CRC Press.
Keefe, D., Karelitz, D., Vote, E., & Laidlaw, D. H. (2005). Artistic Collaboration in De-
signing VR Visualizations.
Graphics and Applications, 25,
Klimoski, R., & Mohammed, S. (1994). Team Mental Model: Construct or Metaphor?
Journal of Management, 20,
Kozbelt, A. (2001). Artists as Experts in Visual Cognition.
Cognition, 8,
Kozhevnikov, M., Blazhenkova, O., & Becker, M. (2010). Trade-Off in Object versus Spa-
tial Visualization Abilities: Restriction in the Development of Visual Processing Re-
Psychonomic Bulletin & Review, 17,
Kozhevnikov, M., Kozhevnikov, M., Chen, J. Y., & Blazhenkova, O. (2013). Creativity,
Visualization Abilities, and Visual Cognitive Style.
chology, 83,
Kozhevnikov, M., Kosslyn, S. M., & Shepard, J. (2005). Spatial versus Object Visualizers:
A New Characterization of Visual Cognitive Style.
Cognition, 33,
Kraiger, K., & Wenzel, L. H. (1997). Conceptual Development and Empirical Evaluation
of Measures of Shared Mental Models as Indicators of Team Effectiveness. In M. T.
Brannick, E. Salas, & E. Prince (Eds.),
(pp. 63-84). Mahwah, NJ: Lawrence Erlbaum Associates.
Kvan, T. (2000). Collaborative Design: What Is It?
Automation in Construction, 9,
Mesmer-Magnus, J. R., & DeChurch, L. A. (2009). Information Sharing and Team Per-
formance: A Meta-Analysis.
Applied Psychology, 94,
Meyer, J., Staples, L., Minneman, S., Naimark, M., & Glassner, A. (1998). Artists and
Technologists Working Together (Panel). In
Proceedings of the 11th Annual ACM
Symposium on User Interface Software and Technology
(pp. 67-69). New York: ACM
Miller, A. I. (1996).
. Cam-
bridge, MA: MIT Press.
Milliken, F. J., Bartel, C., & Kurtzberg, T. (2003). Diversity and Creativity in Work
Groups: A Dynamic Perspective on the Affective and Cognitive Processes That Link
Diversity and Performance. In P. B. Paulus, & B. Nijstad (Eds.),
Group Creativity
32-62). Oxford: Oxford University Press.
Pourmohamadi, M., & Gero, J. S. (2011). Linkographer: An Analysis Tool to Study De-
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1774 Creative Education
sign Protocols Based on FBS Coding Scheme. In S. Culley, B. Hicks, T. McAloone, T.
Howard, & Y. Reich (Eds.),
(pp. 294-303). Glasgow:
Design Society.
Rosenberg, H. S., & Trusheim, W. (1989). Creative Transformations: How Visual Artists,
Musicians, and Dancers Use Mental Imagery in Their Work. In P. Robin, & J. E. Schorr
(pp. 55-75). New York: Plenum Press.
Salas, E., Sims, D. E., & Burke, C. S. (2005). Is There a “Big Five” in Teamwork?.
Group Research, 36,
Shannon, C. E. (1948). A Mathematical Theory of Communication.
Technical Journal, 27,
Sonnenwald, D. H. (1996). Communication Roles That Support Collaboration during the
Design Process.
Stevelt-Kaser, K., Pennington-Busick, S., & Rhoades, M. (2004).
. Columbus, OH: Ohio State
Stokols, D., Hall, K. L., Taylor, B. K., & Moser, R. P. (2008). The Science of Team Science:
Overview of the Field and Introduction to the Supplement.
ventive Medicine, 35,
Terenzini, P. T., Cabrera, A. F., Colbeck, C. L., Parente, J. M., & Bjorklund, S. A. (2001).
Collaborative Learning vs. Lecture/Discussion: StudentsReported Learning Gains.
Journal of Engineering Education, 90,
Van der Lugt, R. (2003). Relating the Quality of the Idea Generation Process to the Qual-
ity of the Resulting Design Ideas. In
DS 31: Proceedings of ICED 03, the 14th Interna-
tional Conference on Engineering Design
(pp. 601-602). Glasgow, UK: Design Society.
Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2010). Evi-
dence for a Collective Intelligence Factor in the Performance of Human Groups.
ence, 330,
Woolley, A. W., Hackman, J. R., Jerde, T. E., Chabris, C. F., Bennett, S. L., & Kosslyn,
S.M. (2007). Using Brain-Based Measures to Compose Teams: How Individual Capa-
bilities and Team Collaboration Strategies Jointly Shape Performance.
science, 2,
Wuchty, S., Jones, B. F., & Uzzi, B. (2007). The Increasing Dominance of Teams in Pro-
duction of Knowledge.
Science, 316,
O. Blazhenkova, M. Kozhevnikov
10.4236/ce.2020.119128 1775 Creative Education
Figure A1 provides an example of linking in a fragment of the Linkograph,
where the segments identified in the protocol analyses are represented as a se-
quence, and the links between meaningfully associated segments are drawn.
Segments 16 and 17 are linked to segment 8, because they all express the idea of
cubical/squared shape of the planet, and additionally, segments 16 and 17 are
connected to each other because they both present the idea of rings surrounding
the planet. A node represented as a filled circle indicates a relation between any
two segments, and it appears at the intersection of the links. Segment 17 is back-
linked to segments 16 and 8, and segment 8 is forelinked to segments 16 and 17.
Figure A1. Example of a Linkograph fragment.
Figure A2 provides examples of some possible Linkograph structures and their
Figure A2. Examples of some possible linkograph structures and their in-
terpretations. Note. This Figure was modified from Kan and Gero, 2008.
... This indicated that the generation of new ideas was more active at the beginning of design, and the probability of the generation of new ideas decreased gradually as the design process progressed. This result was consistent with the study of Blazhenkova and Kozhevnikov [41]. Combined with the intensive long forelinks that appeared at the early stage of design in the linkograph shown in Figure 2, it can be concluded that the new ideas generated in this period largely inspired the subsequent design processes. ...
Full-text available
To unravel the complex challenges addressed by product innovation, it is oftentimes essential for users to participate in the design process. However, there is a paucity of research in terms of in-depth exploration of the cognitive patterns and dynamic design processes of co-design with user participation in the existing design cognition research. The current study aimed to investigate the cognition activities involved in the process of co-design between user and designer at both the individual and team levels. The combination method of linkography and the situated function–behavior–structure (FBS) co-design model was carried out to encode and analyze the protocol data. The results showed that, at the individual level, designers and users adopted different design strategies to promote the progress of the design. In addition, the interaction activities among users and designers varied in different co-design processes. However, at the team level, the collaborators showed systematic thinking modes, and each design move was two-way. This cognitive strategy of the innovation team ensured the continuity and effectiveness of the co-design process. Theoretically, these findings will bring new insights for studies on team cognition activities and contribute to building user-centric design theory by uncovering the dynamic design processes of co-design with user participatory. In addition, the study makes a methodological contribution by illustrating how linkography and the situated FBS co-design model can be utilized to analyze the team cognition during co-design activities.
Interactive whiteboards have become more popular and also essential tools for teaching and learning, especially in basic education classrooms. Studies have been reported on high levels of student motivation, teacher enthusiasm and whole-school support associated with these technological tools. Many researches have reported about the potential of interactive whiteboards (IWBs) to improve the quality of teaching and learning processes by enhancing levels of interaction, communication and collaboration. However, even nowadays, these IBWs suffer some difficulties at drawing time, in other words, are not suitable for freehand drawing, since they require more precision than the traditional input devices like mouse. Meanwhile, it is the preferable form and direct style to use at the teaching or explaining time. These difficulties are inherent to the input device, since the mouse still is the most used and the vast majority of people have no possibilities to get more expensive devices with support to stylus pen. Thus, considering that the mouse is the input device to draw, to do a freehand draw in any popular software is very tedious and frustrating experience. In this research work, we present the incorporation of the old well know DynaDraw drawing technique, into a online collaborative drawing application, which is able to produce drawings in a similar way to do with a pen, using the mouse. The results, on freehand style drawing, compared to other current software, are very satisfactory considering nor special software neither additional hardware are needed. For the implementation, traditional coding frameworks like node.js, express.js, io.js and MongoDB were used, since the main goal is share a drawing work collaboratively. Finally, our implementation is easy to install in other popular teaching and learning platforms like Moodle.
Full-text available
This chapter develops a dynamic model of how a work group's actual creativity may be affected by its composition and by how its early interactions unfold as members develop ways of working together in order to perform their assigned tasks. The chapter is organized into five sections. The first section presents a perspective on creativity in work groups. It then discusses different forms of diversity relevant to creativity. The third section develops a conceptual model of how diversity might affect a work group's early functioning; it focuses on how diversity may influence members' affective reactions to one another as well as the cognitive processes they use. The fourth section shows how these early interactions combine with variables - such as performance feedback and a group's self-monitoring activities - to affect a work group's subsequent interactions and its creative performance. The discussion targets work groups in organizational settings that have fairly stable membership, or at least have a core set of members who remain with a group for multiple phases of its work life. The chapter concludes with a discussion of the implications of the dynamic process model for future research on work group creativity.
Full-text available
In this paper we develop a method for measuring the design process and correlate it with the assessment of the design outcome. We used linkography - a technique used in analyzing design protocols - which is reported to reveal the quality of design ideas and to capture the interconnectivity of ideas in the design process. Previous studies found that Shannon's entropy as a measure of a linkograph might indicate design outcomes. This paper reports on an empirical verification that design outcomes can be correlated to the entropic interpretations of a linkograph. Experimental data from protocol studies of six designers performing two similar design tasks in two different conditions were analysed. In one condition the designers were blindfolded during designing, and then given a relatively short time to draw their design at the end of the session. In the other condition the designers were allowed to sketch. We focus on the three highest scored and the three lowest scored design sessions. Their verbalization during the design session were segmented and coded to produce linkographs. The entropy and the change of entropy over time of these linkographs were studied in relation to the design outcomes. Our results demonstrate that entropy measurement of linkographs provides a way of to study design protocols and show that the design outcome is more related to the rate of change of entropy than to the entropy alone.
Full-text available
2 Kelly Stevelt-Kaser is a Masters student in the Arts Policy and Administration program at The Ohio State University and a graduate teaching assistant in the department of Art Education. An intern for the Ohio Arts Council Arts Learning Program, she played an integral role in planning the 2004 National Endowment for the Arts Summer Institute for School Leaders. Kelly received her Bachelor of Arts Magna Cum Laude in the Liberal Arts with Honors from The Ohio State University in 2003 and was inducted into Phi Kappa Beta. Sara Pennington-Busick is currently pursuing a Master's degree in Arts Policy and Administration at The Ohio State University. She is employed as a Graduate Administrative Associate at the Wexner Center for the Arts and is working as a research assistant to the Director of Career Resources at Columbus College of Art and Design. Sara holds a Bachelor's degree in Art with a concentration in photography from Morehead State University and has exhibited her artwork in numerous shows and competitions. Sara received a 2003-2004 Graduate Fellowship from The Honor Society of Phi Kappa Phi. Mindi Rhoades is a current Ph.D. student in the Art Education program at The Ohio State University with a B.A. in English and an M.Ed. in Language Education from the University of Georgia. She taught high school English for six years in Athens, Georgia and served as a consultant with American College Testing (ACT) and Education Testing Services (ETS), including work on National Board Certification materials. Mindi has also worked for the Philadelphia School District, administered a 21st Century Community Learning Center grant and program in Philadelphia, and administered a computer-based testing and evaluation center at Columbus State Community College.
Full-text available
This paper proposes methods to acquire information from linkography in protocol studies. The paper commences with an introduction of linkography together with its use and then presents two cases of collaborative designing. A qualitative analysis of these cases and their linkographs is presented. Two different strategies to abstract information from the linkographs are described: one based on clustering and the other based on Shannon's entropy. The abstracted information is interpreted and mapped to the qualitative analysis of the protocols. The results are promising; cluster analysis is able to group the linkograph into meaningful clusters, while entropy measures the opportunities for idea development of a team and can also reflect the opportunistic contributions of individual
This research is the first to examine different types of creativity dimensions in relation to different types of visualization on a team level, by comparing adolescences’ teams of different specialization (visual artist, scientists, and humanities) during a complex creative task in an ecologically valid educational setting First, the difference between all teams’ creative outputs (drawings) was compared in terms of their visual characteristics and represented content based on parameters derived from the content analysis of visual media. Second, the teams’ creative performance was compared using evaluations of experts from different professional domains. Based on the evidence from examination of teams’ creative products (final drawings) and their evaluations by professionals, this research suggests that object visualization is related to artistic creativity and spatial visualization is related to scientific creativity on the team-level. Furthermore, the findings provide a clear indication that assessing general creativity independently of the domain, as it has been done so far in most team creativity literature, might be somewhat limited.
“Imagination whirls me around.” So stated GD, a choreographer who was interviewed as part of the following package of research studies that focuses on how artists use mental imagery in making or performing art. And like GD, what all the various visual, musical, and dance artists, interviewed in the three studies reported here have in common is that imagination whirls them around. Imagination is a major force in the creative processes of all of these artists.
Sociocognitive theorists have stressed the importance of both teacher and peer collaboration in learning and academic achievement. Such collaboration may be lacking in an art education modelled on the tradition of the solitary artist producing original works of art in the studio. This paper describes the Philosophy for Children program in critical thinking, its pedagogical approach involving the community of inquiry, and the sociocognitive learning theories upon which it is based. This program may serve as a pedagogical model for development of collaborative learning approaches in art education, especially within the discipline of aesthetics.