Architects and Engineers Differences A comparison between problem solving performances of architects and engineers in the ideation phase of an analogy-based design.pdf

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Int. J. Architect. Eng. Urban Plan, 29(1): 15-25, June 2019
RESEARCH PAPER
Architectural Engineering
Architects and Engineers Differences: A comparison between problem
solving performances of architects and engineers in the ideation phase of
an analogy-based design
E. Najafi1
, M. A. Khanmohammadi*,2
, K. W. Smith3
1
PhD. Student, School of Architecture and Environmental Design, Iran University of Science and Technology
(IUST), Tehran, Iran
2
Assistant Professor, School of Architecture and Environmental Design, Iran University of Science and
Technology (IUST), Tehran, Iran
3
Postdoctoral Researcher, Department of Psychology, University of Toronto, Toronto, Ontario, Canada
Received: March 2018, Revised: May 2019, Accepted: May 2019, Available online: June 2019
Abstract
This study examines how analogy affects problem-solving in ideation phase of design among architects and engineers. For
this purpose, a design problem was given to master and Ph.D. students of engineering and architecture. They were given two
optional analogy sources to choose and be inspired by one. From the analysis of design sessions, using different coding groups
and the application of the Protocol analysis, the following results were achieved. Choosing different analogies would cause
application of different levels of abstraction by designers in design, considering their discipline. Also, choosing between two
analogies would affect mainly the behaviour of engineers in the problem space. For architects choosing between different
analogies do not affect their problem solving or structuring so much but it affects their problem space monitoring mainly.
Finally, architects benefit from analogy mostly for problem solving.
Keywords: analogy, Ideation, Problem Solving, Engineering, Architecture.
1. INTRODUCTION
Design has important contributions in different
disciplines. There exist some commonalities and
differences between various design disciplines.
Architecture and engineering are among disciplines that
involve design in their domain [1-2]. As the design
projects are getting more trans-disciplinary with more
collaboration of architects with engineers [3], there is a
need to know more about the commonalities and
differences between their design performances [4]. Also,
considering analogy as a means of fostering creativity [5],
it is important to know how different disciplines may
benefit from analogy in design problem-solving.
The design is a cognitive activity that can be seen as a
type of problem-solving [1-2]. According to General theory
of problem-solving, which was firstly defined for moving
problems, any problem consists of three components
including data, goal, and operators. Data are pieces of
information that describe the problem. The goal is the
desirable state and operator are the activities toward the
* Corresponding author: Khanmohammadi@iust.ac.ir
Tell: +982173228234
goal state [6]. Finding a solution starts from problem state,
which transfers problem state using operators to the goal
state [7-8]. There are two types of problems as well- defined
and ill-defined problems [9-10]. Well-defined
problems are the ones with clearly defined existed and
desired situation, which can be solved through an
algorithmic solution. In comparison, ill-defined problems
are complex and not clearly defined problems that involve
creative solutions. Design problems have little information
about the problem and even less about the goal or solution
and almost no information about the transformation phases
based on their nature. So, they need structuring, which is a
process of using the supply of knowledge (external
information) to compensate the missing information and
completing the problem state [11]. Consequently, design is
defined as a ill-structured problem [12-14]. Knowledge
and information are used for two purposes; i.e., structuring
the problem and solving the problem. from a cognitive
science point of view, problem solving is an information
processing activity and problem solvers are as an
information processing system [14].
Today, there is a high need for designing in
multidisciplinary teams to meet different needs more
efficiently and to achieve the systematic design. In
construction projects also there is a need for more
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corporation of different disciplines mainly architecture
and engineering. Thus, it is very important to find out how
information is processed during a design activity to help
understand more about design and how designers think to
have more efficient design results [3-4]. Architects and
engineers deal with complicated information related to the
range of abstraction levels involved in the design [15].
As an ill-structured problem, design needs creativity to
find solutions. Analogybased designs play important roles
in problem solving and generation of creative ideas [16-
18]. In addition, the analogy is a key factor to enhance
creativity because it helps to conceptual change, which is
essential for creativity [16]. Therefore, analogies are
useful in the design process and help to foster the
creativity. Accordingly, analogies have a crucial role in
different design disciplines. For a more useful application
of analogies in design teams with different disciplines and
achieving a more concrete design concept and solution, it
is important to know how different disciplines use
analogies and whether there are differences in the
application, types, and process of applying analogies. The
main goal of the present work is to investigate the
differences between engineers and architects in the
application of analogy in concept generation phase of
design.
2. ANALOGY
Analogy lies at the center of the human cognition [19].
As a cognitive process, analogy transfers meaning or
information from a source domain to a target domain. In
cognitive sciences, there are two types of analogies:
surface features analogies and generative analogies. The
former is a kind of analogy that is based on surface
features, but the latter includes structural and conceptual
analogies, which help inference from the source domain to
target domain [20]. Also as they help to create patterns
regardless of the elements that create them, we can
consider another group as the structure. It helps to create
concepts that are abstracted from patterns [19].
Using an analogy based on the multi-constraint theory,
Thagard and Holyoak introduced three main constraints
including similarity, structure, and purpose, which can
guide the analogical thinking and lead the designer to a
coherent result [21]. Gross proposed an approach to create
information for computational aid in creative architectural
design using drawing analogies. Drawing analogies are
visual references (analogies), which are indexed as a
function and form in conceptual design [22].
We concluded from these studies that there are different
analogy types that can be defined at different levels of
abstraction as form, structure, function, and concept as
shown in Fig. 1. We considered two analogies (i.e., Eye and
tree) for designers to choose one and be inspired from for
their ideation. This choice was made in order to find more
about the level of analogy abstraction. The eye is an
analogy that is more dominant in its form while tree can be
more dominant with its structure. The two analogies were
given to evoke either a superficial or a generative aspect of
analogy in designer’s mind. Also, designers were asked to
mention their reasons for choosing one of the analogies in
order to find about the retrieval data from memory at the
beginning point of design where thinking process did not
affect the designer's mind.
Fig. 1 Levels of order or systematicity of hierarchies in the application of analogies
2.1. Analogy and problem solving
Analogies would provide new insight into problems.
Even analogies may find new aspects and cause the
emergence of new solutions [21, 23]. Hey et al. discuss
how analogies and metaphors help to solve design
problems. They concluded that for design problems
metaphors help to structure and to define the problem
through understanding the needs and attributes while
analogies help to problem-solve through mapping the
causal structure of source (of inspiration) domain to target
(problem to be solved). The mapping can be in functional,
geometrical, or configurative aspects of the two domains.
Finally, they concluded that analogies can be used for
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concept generation in design [24]. Christensen found three
functions for analogies as problem identifying, problem-
solving, and explaining concept analogies. While problem
identifying analogies are mainly within domain analogies,
explaining concepts are between domain and problem
solving a mixture of the two. Analogizing uses almost
equal number of within and between domain analogies in
engineering design. Also, it was found that using sketches
increases between domain analogies [16]. Indurkhya
discussed different uses of analogy and their role in
cognition [25]. Linsey et al. concluded that the level of
abstraction for representation of prior knowledge and
design problem affects the ability of people to retrieve and
use analogous solutions. Also, the stated that having a
proper functional model of the problem affects the ability
to find and use an analogy [26].
According to the mentioned works, it is important to
find how applying an analogy may affect the problem
space and its operations.
Bonnardel conducted two studies in creative
professional space to find the role of analogy in creativity
and found the nature of sources of information in
analogical reasoning. He found the high level and inter-
domain analogies help the creation of new ideas. Then, he
classified the cognitive constraints as external (prescribed)
and internal (designer expertise) [27]. Ball et al. studied
the application of analogical reasoning according to the
designer expertise and realized that skilled designers use
schema-driven analogy while unskilled use case-driven
analogy [28]. Ball studied the nature of spontaneous
analogical reasoning related to novices and experts in
design activity and found that spontaneous analogizing is
dominating in both novice and experts practices.
Also, experts show more schema-driven analogizing
while novices do more case driven.
Most of the case driven analogizing used surface level
analogies in target problem [lbid]. Casakin investigated
how experts and novices apply visual analogy in
Architectural design. He claimed that experts retrieve
analogise from between-domain while novices retrieve
from within-domain and between-domain. Also, he
reported that novices in contrast to experts produce many
solutions with fewer constraints [17].
Although many studies have been done considering the
application of analogies in design disciplines, there exist
few studies to compare architecture and engineering
disciplines function during ideation phase of design. Also,
there is no clear study to compare designers' behaviour in
the problem space in analogy-based design. If we give
designers with different educational background
(architecture and engineering) a design problem with two
predefined analogy to choose, when they should rely on
their memory and self-information, what would be the
differences? Whether choosing different predefined
analogies make any differences in the abstraction level that
designers involve during design?
The questions to be answered in this research include:
What are the differences between Architects and Engineers
on their problem space operators when they choose different
analogies? Do Architects and Engineers differ at the
abstraction level at which they utilize the analogy in design?
It seems there are differences between Architects and
Engineers when they choose different analogies to be
inspired. They may prefer to choose different analogies as
they have different information processing methods.
Engineers mostly focus on structuring the problem, while
architects mainly concentrate on solving the problem [10, 29].
Considering analogy abstraction levels, it is possible that
choosing different analogies would affect using different
abstraction levels of analogy during problemsolving of
design. Moreover, it would cause Architects and Engineers
apply different levels of analogy abstraction.
2.2. Comparing design disciplines
Cognitive processes have similarities and differences in
different design disciplines. Differences between design
disciplines have been studied in limited studies.
Comparison of design problem space in three disciplines
of architectural design, mechanical engineering design,
and educational design with non-design problem space
represents the fixed and specific features of the design
problem regardless of the discipline field [3]. Architectural
studies relate to several key issues that include:
architectural presentation, strategic behaviour, and
creativity and innovation. Each major theme is covered by
many topics and subcategories. Some of the prominent
differences that distinguish architectural design from other
areas of design are strong presentations, the untapped use
of innovative rivals, non-standard problem mix design, and
complexity management strategies [3]. Design thinking of
architecture students is compared with industrial design at
the undergraduate and doctoral level of design. However,
there is a difference between undergraduate students in
architecture and industrial design, but the most important
difference between the PhD. students and the two
undergraduates. The results of the study question the
conventional design methods in design thinking, because it
limits the creative framework of the mind [3]. The
Understanding of the designers of design for engineering
and non-engineering disciplines and impact of this
understanding on their design behaviour is investigated,
which has led to the presentation of six views of design.
The matters and processes of design in three different
domains (architectural design, software design, and
mechanical design) are compared with the case study. The
design matters are intended function, expected behaviour,
obtained behaviour, structure representation and design
requirements, and processes are defined as frameworks,
analyzes, configuration, evaluations, documentation, and
re-framing. Design processes are achieved from changes to
design matters, in which processes are dependent on the
matters. The framework of the problem is defined as the
transformation of design requirements into functions and
functions to the expected behaviours. The configuration is
the transformation of the expected behaviour into a
structure or form. Analysis is the extraction process of the
structure from the behaviour and the evaluation is the
comparison process between expected behaviour and
obtained behaviour. Documentation is the process of
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converting matters into presentable and displayable
documents. Three re-categorization processes are also
introduced for reviewing and presenting new structures,
behaviours and functions. The study shows that different
design disciplines are comparable with the design ontology
approach and thus the design processes in different
domains can be compared. Different areas of design work
in processes differently [3]. A comparison between
architects, industrial designers, and electronics engineers
has shown that architects have more variety in
architectural design presentations than engineers. They
also produce more malicious options, and more often than
engineers are involved in fake production strategies in
creative design [35-36].
Comparison of the understanding of the design
between two disciplines of mechanical design and
industrial design in the conceptual phase of design is done
which is based on the ontological model of function-
behaviour-structure. The focus of the cognitive effort of
the designers on the argument about the design issue or the
design solution has been examined. The goal of the
research was to know whether the epistemology of design
critique is compatible with the design process. The results
have shown that design review and critiques sessions
emphasize design solutions more than design sessions.
Industrial designers are less focused on the solution than
mechanical engineers [3]. Engineers are compared with
industrial designers regarding the application of design
heuristics, which explains the effect of design heuristics on
the production of diverse, functional and creative concepts.
There are also differences in the heuristics that apply to the
production of various options [3]. The application of
design heuristics in collaborative design ideation of the
engineers (mechanical) with industrial designers has been
investigated. The role of heuristics has been identified in
creating solutions and defining new issues. Also, the
application of a heuristic often leads designers to a
different part of the problem space and facilitates the
inclusion of other heuristics [3]. A review of the common
design ideas of engineering design and marketing
professionals has shown that the use of design heuristics
produces a more diverse concept [3,33].
To find out how different design disciplines especially
Architects and Engineers benefits from analogies at first
phase of design, we examined candidates at a high level of
education from Engineering and Architecture discipline by
giving them a design problem with no familiar solution
and two familiar choices as analogies to be inspired by.
Their design thinking and behaviour were then
analyzed to achieve the results.
3. RESEARCH METHOD
3.1. Participants
Designers were chosen from master and Ph.D. students
of different disciplines of Engineering related to design
and Architecture. Among seven Engineering candidates,
three were structural Engineering PhD. students, one
mechanical Engineering PhD., one master and one
bachelor of Mechanical Engineering, and finally one
master student of Industrial Engineering. Also, three
master students of Architecture and three professional with
master degree (one instructor) were among the
Architecture candidates for the task.
3.2. Design task and procedures
To find how Engineering and Architectural designers
use an analogy (a biologic analogy) for solving design
problems and generating design concepts, a design task
was defined. The task was to design a façade for the house
of philosophy, where philosophers can gather and talk
about philosophy and make more communications with
each other. Also, two optional analogies from biology
were suggested to designers to be inspired by as Eye and
tree. These two analogies were chosen because the eye can
be referred to as seeing as a function and also its beauty
aspects. Besides, the tree is most dominant for its
appearance features and structure. Designers were asked to
say about the reason why they choose eye or tree. Then, it
was investigated which levels of analogy was applied in
reasoning during the design process and finally which one
was mainly applied to design idea creation.
3.3. Data collection
The candidates were given the design task in the
description and the way they should do the task. They
were provided with notepapers. They should first decide to
choose between two fixed concepts as Eye or Tree to be
inspired and then they must explain their reasons for why
they chose one of the two and what the benefits for
choosing that analogy are. Next, they began to design with
the chosen analogy and inspired from it during the design
and explicate their thoughts about how they benefit from
that analogy. Each designer was recorded separately. The
whole process was videotaped and recorded as their
drawings and writings were collected at the end of their
session. The time given for the conceptual phase to
produce concepts of the design was in average 30 ± 10 min
according to candidate’s decision for finishing the design.
All videotapes were transcribed and analyzed according to
coding provided.
3.4. Coding schemes
Coding was prepared based on the literature review. The
data can be coded according to designer source of
knowledge, level of analogy abstraction (form, structure,
function, concept) [24, 41-44], and how data are used for
problem space state as problem structuring (adding the
knowledge needed to structure the problem), problem-
solving (improving the design specification), and
monitoring (review of subject or comment upon the
problem-solving process) the problem [30]. The coding is
for problem state is illustrated in Fig. 2. Finally the
information is processed for each participant; the frequency
of every category code was calculated. Then, the percentage
of every frequency in each transcript was calculated.
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Fig. 2 Problem space state in design including problem
structuring, problem-solving, and monitoring the process
As there were two categories of coding, each transcript
was coded two times. The first category involves
designers' operation in the problem space. The problem
space operators consist of problem structuring (which is
crucial in design problems as they are ill-defined and lose
information), problem-solving (searching alternatives and
solutions), and monitoring (review the problem and
monitor the design process) [30].
The second category was the abstraction level of
analogy that designers benefit to deal with the problem.
The four analogy levels include form, function,
structure, and concept [21]. According to function-
behaviour-structure model Gero [45] and the principle of
“form follows function” [46], the form is the lowest level
of order than structure and function. Form refers to the
shape, but the structure is a deeper aspect that refers to
relation and hierarchy of the components in the object. So,
the structure is at a deeper level of order in comparison to
forming. Also, the function has a higher order than
structure because it refers to the function of the object as
its goal to provide something. The concept is the goal of
the designer so it is the highest level of order.
Each transcript was also coded for the abstraction level
of analogy. The first coding was to find the level of
analogies that help to reason and think through the design
process. Also, the whole transcript was coded to find the
level of analogy in design outputs. And third, the coding
was for answering the question that why designer chooses
Eye or Tree to see what level of abstraction of the
analogies first catch the designers’ Eyes.
So, there are two groups of Architects and Engineers
with a subject of design that is to be inspired by choosing
between two analogies as eye and tree. Fig. 3, gives a brief
of the two main coding scheme of the study.
Fig. 3 Research design diagram introducing dependent variables
4. RESULTS
The frequency of every category codes was calculated
for each participant and then the percentage of every
frequency in each transcript was calculated. Then,
considering two choices for inspiration (two optional
analogies as eye or tree) and two groups of expertise as
Architecture students and Engineering students, different
ANOVA tests were conducted for each coding group. The
independent variables are field of education and the
chosen analogy (eye or tree) as shown in Fig. 4.
Fig. 4 Independent variables are defined as field of education and the chosen analogy (eye or tree)
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4.1. Problem space operators
According to our first hypothesis for design problem-
solving, problem state would be different considering
choosing different analogies. Also, they benefit from
analogies for different operators in the problem space. The
coding for this hypothesis was through transcript statements.
To test this hypothesis, the discipline of designer and the
chosen analogy were consider as independent variables and
designer's behaviour in the problem space as dependant
variables. ANOVA repeated measure analysis shows that
the discipline of designers as architecture and engineering
affects designers' behaviour in the problem space. The
ANOVA result F (2.29, 18.34) =13.51, p= 0.000 shows that
there is significant difference between different problem
space operators. This difference would be confirmed when
considering the designer's discipline of design with the test
result, F(2.29, 18.34)=3.83, p= 0.036. Descriptive statistics
in Fig. 5 reflects that Architects benefit from analogies
mostly for problem-solving (Total Mean=40.23, SD=10.56)
while engineers benefit from analogies mostly for
structuring the design problem (Total Mean=37.04,
SD=20.36). Also, analogies help Architects to monitor the
problem space more than Engineers.
Fig. 5 Total mean for architects and engineers considering problem space operators
The test results for the problem space operators
considering different analogies as eye and tree without
designers' discipline was F(2.29, 18.34 )=3.73, p= 0.039.
Comparing total means of problem space operators for
different chosen analogies as eye and tree Fig. 6 shows
that designers mostly benefit from eye analogy for
structuring the problem, while they benefit from tree
analogy mainly for solving the problem. Also, using
different analogies cause different proportions between
solving and structuring the problem. For eye analogy,
designer's difference in structuring and solving is much
less than for tree analogy. This means different analogies
affect designers' problem structuring and solving
performances.
Fig. 6 Total means for predefined analogies as eye and tree considering problem space operators
Architects and Engineers behavior in the problem
space is compared considering choosing different
analogies. The test indicates F (2.29, 18.34) =5.14, p=
0.014, which means that problem space operators would
differ more when imposing the designers' discipline and
the chosen analogies. Choosing different analogies as eye
or tree causes different problem structuring and solving for
the Engineers, according to descriptive statistics in Fig. 7.
0.000000
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Eye Tree
Solving
Structuring
Monitoring
Miscellenous
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Architects Engineers
Solving
Structuring
Monitoring
Miscellenous
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Fig. 7 Comparing means for architects and engineers with chosen analogies as eye and tree in the problem space
In comparison, Architects behave not much different
when using different analogies in the problem space.
Choosing different analogies do not affect engineers
monitoring the problem space in a noticeable way. While
for architects using different analogies makes noticeable
difference in monitoring the problem.
4.2. Level of analogy abstract results
The other hypothesis states that different analogies
may impose different levels of abstraction in design
ideation. And it will affect architects and engineers
differently by using different levels of analogy
abstraction. For this hypothesis, coding was done at the
statement level. The MANOVA test with dependent
variables being abstraction levels of analogies and
independent variables being designer's discipline
(architecture and engineering) and chosen analogies
(Eye, Tree), resulted in F(1, 8)=26.9, p=0.001, suggesting
that there is significant difference between architects and
engineers in applying different levels of abstraction. The
test results also indicates that there is significant
difference between four abstraction levels as form,
structure, function and concept, F(4, 32)=296.07,
p=0.000. Comparing the total mean for Architects and
Engineers at different levels of abstraction using the
descriptive statistics Fig. 8, indicates that architects have
greater means at form and concept levels while Engineers
show a greater total mean at form and function levels.
Architects have greater means in all of the abstraction
levels, comparing to engineers.
Fig. 8 Architects’ and engineers’ mean for different abstraction levels of analogy
Designers mainly benefit from eye analogy in form
level, while they benefit the tree analogy mostly in concept
level Fig. 9. Architects and engineers noticed to eye
different abstraction levels with the same order in form
and function levels and with contrast in structure and
concept levels. The tree analogy makes completely
different set of levels for different analogies.
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Architects Engineers
Form
Structure
Function
Concept
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60.000000
Architects -eye
engineers -eye
Architects -tree
Engineers -tree
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Fig. 9 Architects’ and engineers’ means for different abstraction levels of two chosen analogies
As illustrated in Fig. 10, eye analogy mainly arise the
form and then function levels in designers' minds, while
tree analogy awoke concept and then form levels.
Fig. 10 Total mean for eye and tree analogies at different abstraction levels
5. DISCUSSION
There were two questions to be answered in this study.
The first was: What are the differences between Architects
and Engineers on their problem space operators when they
choose different analogies?
Architects benefit from analogies mostly for problem-
solving while Engineers benefit from analogies mostly for
structuring the design problem. Also, analogies help
Architects to monitor the problem space more than
Engineers.
Designers mostly benefit from eye analogy for
structuring the problem, while they benefit from tree
analogy mainly for solving the problem. Also, using
different analogies cause different proportions between
solving and structuring the problem. For eye analogy,
designer's difference in structuring and solving is much
less than for tree analogy. This means different analogies
affect designers' problem structuring and solving
performances in different ways.
Architects and Engineers behavior in the problem
space is compared considering choosing different
analogies. Problem space operators would differ more
when imposing the designers' discipline and the chosen
analogies. Choosing different analogies as Eye or Tree
causes different problem structuring and solving for the
Engineers. In comparison, Architects do not behave much
different when using different analogies in the problem
space. It means that choosing different analogies makes no
much difference in structuring and solving the problem for
the architects. While choosing different analogies affect
engineers' solving and structuring the problem much more.
This different behavior regarding different analogies is
related to the way architects and engineers benefit from the
analogies in design. Since engineers more benefit apply
analogies for structuring the problem and because different
analogies can generate different information for different
aspects of the problems so engineers behave much
differently regarding using different analogies to structure
hence to solve the problem. But because architects use
analogies mostly for solving the problems, choosing
different problems do not affect their function in the
problem space so much.
Choosing different analogies do not affect engineers
monitoring the problem space in a noticeable way. While
for architects using different analogies makes noticeable
difference in monitoring the problem. It shows engineers
have independent criteria from analogies for their
0.000000
2.000000
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6.000000
8.000000
10.000000
12.000000
Eye Tree
Form
Structure
Function
Concept
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monitoring of the problem space which means they have
more fixed and determined criteria than architects. Using
analogy helps architects mainly for solving the problems.
And the second question was: Do Architects and
Engineers differ at the abstraction level at which they
utilize the analogy in design?
Comparing the Architects and Engineers using
different levels of abstraction of analogies indicates that
architects apply more the form and concept levels while
Engineers apply form and function levels. But they apply
the form and concept levels mainly or tree analogy.
Designers mainly benefit from eye analogy in form
level, while they benefit the tree analogy mostly in concept
level. So, different analogies would take the notice on
special levels of abstraction. Different analogies can make
different structural mappings in different levels of
abstraction in designers' minds.
Eye analogy mainly excites the form and then function
levels in designers' minds, while tree analogy awoke
concept and then form levels. So designers would consider
special abstraction levels in different analogies regardless
of their design disciplines.
Architects and engineers noticed to eye more in form
and then function levels. So, eye as an analogy would be
considered in form and function level. But architects pay
more attention to concept than structure level in contrast to
engineers when they choose eye for inspiration. The tree
analogy makes different set of levels for inspiration as an
analogy. Architects consider tree as an analogy mostly in
the concept and then form level, but engineers noticed to
tree mainly in the form and then concept level. When
choosing tree for inspiration architects consider the
structure level than function in contrast to engineers. The
difference between architects and engineers are in the
abstraction levels of analogies regardless of the type of
analogy. It means the order of applying different
abstraction levels of the analogies is different for architects
and engineers.
The whole transcript were coded two times for the
level of analogy that helped the design output to be
evolved and shaped and the reason of designer for the
choice of analogy, The information is presented in Table 1.
Table 1 Results for three coding sets: choice reasoning analogy level, reference of reasoning, and design output analogy level
Eye
Choice reasoning
analogy level
Design output
analogy level
Eye
Choice reasoning analogy
level
Design output analogy
level
Arch 1 Concept Concept structure Eng 1 Function concept Structure form
Arch 2 Concept Concept function Eng 2 Structure Function
Arch 3 Concept Form Eng 3 Function Form
Arch 4 Concept function Form concept Tree Choice reasoning analogy level Design output analogy level
Tree
Choice reasoning
analogy level
Design output
analogy level
Eng 1 Function Function
Arch 1 Concept Form Eng 2 Function Form
Arch 2 Function concept Concept structure Eng 3 Function concept Form
Two third of the Architects chose Eye to be inspired
by, mostly inspire at concept level and all of them
mentioned their reason for choosing Eye at concept level.
In contrast, for choosing Tree analogy, there was an
equal inspiration for concept and form and their reasons
also were at the concept level.
Engineers have chosen two analogies in equal
numbers. For Eye analogy, they are inspired by most
levels of form, function, and structure, but the reason
behind their choice was mainly a function of the Eye. For
Tree analogy, they were inspired mostly in form but their
reason behind their choice is function. Statistical test
declares no significant differences between architects and
engineers in this level of coding.
6. CONCLUSION
In this study, we investigate the difference between
Architects and Engineers in choosing and applying two
different analogies in ideation phase of design. They have
to choose one analogy among two to be inspired by for
design ideation. In this study the different behaviour of
architects and engineers in the problem space considering
choosing different analogies in an analogy-based design
has been investigated.
Also, designers' behaviour toward applying different
abstraction levels of the chosen analogy in ideation is
studied. Results show that giving analogies for inspiration
without any provision and information about them, affect
designers’ operation in the problem space. Designers'
discipline makes differences in using different levels of
abstraction of the chosen analogy referred by the designer.
 Choosing different analogies mainly differs in
engineers' problem solving and structuring, while for
architects it mainly affects their problem space
monitoring. So choosing analogy can help engineers
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24
benefit analogies in different ways. Architects benefit
from analogies mostly for problem-solving. Engineers
have more fixed and determined criteria than
architects. But architects benefit from analogies for
monitoring the problem space and different analogies
affect their monitoring.
 Analogies have various abstraction levels for designers
to be inspired. Different analogies can make different
structural mappings in different levels of abstraction in
designers' minds. Designers would consider special
abstraction levels in different analogies regardless of
their design disciplines. The order of applying different
abstraction levels of the analogies is different for
architects and engineers.
The study addresses the educational aspects of multi-
disciplinary fields related to architectural design. It helps
to know more about designers' behaviour in the
analogybased designs such as bio-inspired design in design
teams or multi-disciplinary design subjects where
architects and engineers works together. Applying
analogy-based design in education can help architecture
students to find more solutions. Also it can help to find
educational solution for better function of architects in
multidisciplinary design teams with engineers.
This study is done with architecture and engineering
participants with no or little professional experience. We
should be cautious to generalize the results of the study to
the professional or expert designers.
For future studies, it is suggested to search what causes
that architects and engineers refer to the abstraction levels
of analogies in different orders when ideating in design
problems and whether it affects their behaviour in the
problem space or not. Also whether they refer to special
abstraction levels of the analogies regarding their
discipline or not, and if the answer is positive, what causes
this difference.
CONFLICT OF INTEREST
The authors declare that there are no conflicts of
interest regarding the publication of this manuscript.
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COPYRIGHTS
Copyright for this article is retained by the author(s), with publication rights granted to the journal.
This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/4.0/).
HOW TO CITE THIS ARTICLE
Najafi, E., Khanmohammadi, M. A., Smith, K. W., (2018). Architects and engineers
differences: a comparison between problem solving performances of architects and
engineers in the ideation phase of an analogy-based design. Int. J. Architect. Eng. Urban
Plan, 29(1): 15-25, June 2019.
URL: http://ijaup.iust.ac.ir/article-1-207-en.html
AUTHOR (S) BIOSKETCHES
Najafi, E., PhD. Student, School of Architecture and Environmental Design, Iran University of Science and
Technology (IUST), Tehran, Iran
Email: Elanajafi@gmail.com
Khanmohammadi, M. A., Assistant Professor, School of Architecture and Environmental Design, Iran University of
Science and Technology (IUST), Tehran, Iran
Email: Khanmohammadi@iust.ac.ir
Smith, K. W., Postdoctoral Researcher, Department of Psychology, University of Toronto, Toronto, Ontario, Canada
Email: KWS@yorku.ca
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