Sequence of activities for the experiment A Logitech digital pen and paper note book was used to convert and store a digital copy of the design sketches and written notes that the desig
Trang 1and coding could not begin until the design activity
had finished
Table 2 Sequence of activities for the experiment
A Logitech digital pen and paper note book was used
to convert and store a digital copy of the design
sketches and written notes that the designer created
though the process The digital notebook also
contained a column that was used by the researcher to
code the design outputs Almost all of the design
outputs were also modeled using computer-aided
design (CAD), and it is these representations, which
were then presented in sequence with significant
descriptive notes, that were formally coded
The design task itself is not described in this paper,
as it is a real task previously performed in industry and the researchers are planning to compare the outputs from the experiment with those from industry
Table 2 above describes the sequence of activities that took place in the experiment and highlight the particular roles that the various researchers (referred to
as HY, TJH and EAD) played
Figure 1 below shows an example of how the design ideas were presented in sequence and how they were formally coded The first two columns show the numbering system used for the design ideas B1 represents an initial, unique design idea B2, B3 and B4 show the iterations of this design idea The last five columns show how each of the design ideas were coded using both the 1st and 2nd coding schemes developed in this research
3 Results
Looking at the whole data set in the first round showed that, for 18 out of the 30 design ideas coded the researchers agreed, whilst in 12 cases the coders were not in agreement It was this disagreement and the following discussion that lead the development of the 2nd coding scheme
Table 3 below shows a sample of the discussion from the 12 cases where the coders were not in agreement
Table 3 Sample of the coding disagreement discussion
Some observations and recommendations were drawn from the disagreements above:
A reference design that the new design idea is compared to should be specified before coding This seems obvious in retrospect, as it is impossible to code the initial set of ideas without a reference design: a change needs to
be coded relative to something Once the initial
Resear-cher ID
role played (designer-researcher)
st round
Development of the
1st coding scheme:
Creative Modes of
Change
TJH researcher
Briefing on the
highly-constrained
Development of
Review and iteration
of the design ideas
HY TJH designer Coding the design
ideas using 1st coding
scheme
HY researcher Assessing the quality
of design ideas using
company’s Criteria
Decision (MCDA)
table
HY TJH designer
Inter-observer coding
of the design ideas
using 1st coding
scheme
TJH EAD researcher
nd Ro
Development of
design ideas – With
creativity tools
HY designer Coding the design
ideas using 2nd
coding scheme
HY researcher Assessing the Quality
of design ideas using
the company’s
MCDA table
HY TJH designers Analysis of results all researcher
Trang 2ideas are coded, subsequent design iterations
can be coded relative to each one preceding it
Although all coders were given definitions for
each code, coders should be trained in advance
using an example to elicit queries and tease out
any problems with the coding scheme
One of the requirements of New Auxiliaries
(NA) is to bring in new functions that are not
listed in the original functional requirement
This caused some disagreements when new
elements were added to the system, and
highlighted the need for clear definitions of
‘system’, ‘element’ and ‘function’ (see section
3.1.2) The coding scheme could be improved
by defining New Auxiliaries as an additional
element/module instead of additional function
For differentiating whether a new function is
added, the outcome of the modification can
also be coded as Additional Function or
Reduced Function;
Quite often Technology Pull (TP) or Improved
Understanding (IU) cannot be indentified
without knowing the rationale from the
designer who made the modification For
example in design idea E2, researcher HY coded the concept as New Design (ND) since being the designer, he knew that the reason for the modification was the need to integrate a hinge to a flap However, the other researchers (TJH and EAD) considered the change as the result of new material (thin and flexible plastic) therefore coded that change as Technology Pull (TP) In idea F2 a very similar situation arose, but the other way round It is therefore clearer to separate Improved Understanding (IU) and Technology Pull (TP) from rest of the modes of change and code them as the factors that drive the design modification (or design rationale)
Researcher TJH suggested Modularization as a new mode of change when coding design idea A2, in order to provide a mode of change that
is opposite to Functional Integration (FI)
A similar approach was applied to New Auxiliaries (NA) where; Trimming could be introduced as a new MOC that describes the modification that discards unnecessary element to improve performance
Fig 1 Sample of design idea formal coding sheet
Trang 33.1 Introducing the 2nd coding scheme
The modified scheme comprises three ‘levels’ of
design change to be coded: the factor that drives the
modification, the design modification itself, and the
final resulting effect on the system from the
modification Figure 2 shows the three levels used in
this 2nd coding scheme
Fig 2 Three levels of the 2nd coding scheme
3.1.1 Factor that drives the design change
The coding in this section describes the various types
of rationale which can drive the specific design
modifications Design rationale includes ‘not only the
reasons behind a design decision but also the
justification for it, the alternatives considered, the
trade-offs evaluated and the argumentation that led to
the decision’ (Lee, 1997) These are not obvious by
simply looking at the design modifications themselves
Even for the same design modification, the underlying
rationale may be different and therefore usually best
described by the designer who made the modification
New requirement (NR) - One or more new
requirements raised by
market/organization/designer, or any other
party, that requires new design ideas to
achieve
Improved understanding of design
performance parameter (IU) - Through
modelling and empiricism engineers benefit
from the discovery - or better understanding -
of relationships between the design parameters and the performance This understanding can then go on to drive various design modifications
Technology Pull (TP) - The adoption of a novel and appropriate technology or material
to expand the design space, which can then in turn drive various design modifications This may simply have a direct relationship to performance, such as changing material to reduce weight However, it could lead to more complex relationships One example observed
in recent research, was where a new material coating was adopted, which enabled a different spray coating process, and eradicated post process machining, thereby producing substantial benefits
Design Improvement (DI) - Without adding any new requirement, the rationale of the modification is only to further improve the performance of the system During the iterations of design ideas, the designer sometimes sees opportunities to set higher targets for the system This raises the standard for the design ideas without adding any new requirements
3.1.2 Design Modification
These define the ways in which each design idea presented differs with respect to the reference design
In this study, the initial unique design idea presented (e.g B1) was compared to a common solution already
on the market The subsequent design iterations (e.g B2, B3, etc.) were coded relative to each one preceding it The codes presented below are based on the assumption that in highly-constrained design tasks, the designer is usually designing ‘elements’ (parts) of
a sub-system, which perform particular ‘functions’ for the ‘system’ (or super-system) The different types of changes that are seen as the design ideas evolve are defined as:
Parameter Change (PC) - In this change the parameter of an existing design element is modified However the ‘performance - attribute’ relationships governing the design are not changed as a parameter is adjusted Thus changing the ‘number of wheels on a car’
is not a parameter change, as new
‘performance – attribute’ relationships are inevitably formed when changing the number
of wheels
New Auxiliaries (NA) - In this change a new function which was not a part of the system,
Trang 4and is distinct from any other function within
the system, is added into the system
Modularisation (MD) - In this change the
functional requirements of a system are
fulfilled by an increased number of
sub-systems, parts or features This may for
example, be beneficial to the design in terms
of: increasing reliability, adaptability, or
performance Suh (1990) for example,
advocates decoupling functions such that each
function has a single associated part or feature
Functional integration (FI) - In this change any
two or more elements within the system are
combined into a single element that performs
the same function
New Design (ND) - In this change an existing
function is performed by a completely new
element
Trimming (TM) - This change occurs when
any element is discarded
3.1.3 Modification outcome
Codes in this section describe the different types of
outcome observed for the overall system These
describe changes in the overall function or
performance or the final resultant benefits to the
system from the creative design modifications
Better performance (BP) - The existing system
performs better
Additional function (AF) - Extra function is
added to the system The function may or may
not have been part of the original functional
requirements A creative design modification
occurring during the process may add
additional beneficial functions to the system
Reduced function (RF) - Function is discarded
from current design, a direct opposition to Additional
Function, in order to improve the overall performance
of the system
3.2 Reviewing the coded concepts on a timeline
Figure 3 on next page presents all the design ideas on
the project day-by-day timeline For example, A3 (PC)
means the third iteration of the initial idea A1, where
Parameter Change is the Mode of Change evident in
the design Only the agreed coding from round 1 is
included in brackets behind the concept numbers In
order to use the 1st and 2nd round of design and
analysis as a single data set, only the Design
Modification codes of the 2nd Coding scheme are
presented in this diagram as they are coded at the same
‘level’
There were 6 days between the two rounds were no new concepts were generated It is possible to detect some patterns of modes of change that occur throughout a creative design process, these are discussed in section 4.2 Each of the final concepts (e.g A9, B5, C3, etc) was given a Quality score from the company’s Multi Criteria Decision Analysis (MCDA) table The company’s MCDA table consists
of eight criteria against which each concept is scored, these are added up to generate the Quality score The MCDA includes functional criteria such as ‘hold low vacuum’ and ‘hygienic’ as well as business criteria such as ‘product cost’ and ‘development time required’ The Quality score is shown below in bold and is out of maximum of 72 Whether particular patterns lead to more successful outcomes in terms of solution quality is discussed in section 4.2
4 Discussion
This section discusses the design modification codes (middle ‘level’) from the 2nd coding scheme as these were analysed in more depth than the results from the other two levels It also makes general observations about the modes of change observed
4.1 Discussion of the 2nd coding scheme
In practice in the study, the codes were created through the action research cycle, using a type of content analysis, where definitions of codes were adjusted, and new codes were created, in order to be able to code the entire data set In retrospect, it is possible to view the codes created in this research as describing two fundamental aspects that change: the functions that are performed by the design and the actual designed elements that perform those functions They change by creating, discarding or integrating Figure 4 below shows how the definitions of the codes presented in section 3.1.2 can be placed in the matrix
Fig 4 Matrix of Design modification codes relating to
changes in elements and functions
existing new integrate discard
n existing PC
ND
Trang 5This helps to highlight the difference between New
Design (existing function is performed by a new
element) and New Auxiliaries (new function is added
into the system) The matrix also highlights an
anomaly in one of the codes Functional integration
(FI) is actually defined as the integration of elements,
and should perhaps be relabeled as Element
Integration (EI) The table also points towards the
opportunity to define other Design Modifications that
did not arise in this experiment but could be useful
both for coding future experiments, for example: the
integration of existing functions through the design of
a new element (a); or creation of a new function by
integrating existing elements (b)
Although the single case presented here does not
allow detailed analysis of the three ‘levels’ coded in
the 2nd coding scheme they do provide some insights
into the nature of creativity in highly-constrained
design tasks At the top level, it may be possible to
develop/specify tools that stimulate designers to think
of strategies that then drive successful design
modifications These types of tools would have to
work through stimulating/guiding design rationale
Looking at the middle level where the design ideas
themselves are coded, it may be possible to specify
particular creativity tools to stimulate particular design
modifications This experiment was able to initiate this
work which is reported in (in preparation for ICED11)
It is worth noting that before this can be done, a much
larger study is needed to understand the design modifications - or patterns of them - that deliver the most creative results in highly-constrained design tasks At the third (outcome) level it may be possible
to develop/specify tools that stimulate designers to think of strategies for the system that then drive successful design modifications at the sub-systems level
4.2 Patterns in Modes of Change
Studying the data in Figure 3, it is possible to detect some patterns of modes of change that occur throughout a creative design process These findings are tentative observations due to the limited number of coded instances In most cases it is clear that the initial idea (e.g B1, C1, D1, etc) starts with a New Design (ND) (round 1) or a New Auxiliary (NA) (round 2) followed by iterations of the ideas in the form of Parameter Change (PC) In some cases this works the other way round where successive iterations of Parameter Change (PC) lead to New Designs (ND) in the final instance (e.g A8 and F6) This may happen where the designer feels they have pushed the idea to its limits and thus comes up with a totally new direction to explore The difference between the number of New Design (ND) and a New Auxiliary (NA) codes between the two rounds is likely to be mainly due to changes in the coding scheme
A1, B1(ND)
A2,C1 (ND)
D1 (ND), E1 (ND)
C3 (PC)
32 , D2
(PC) 38 , E2, E3 34
A3 (PC), A4 (PC)
B2 (PC), B3 (PC)
A6, A7(PC), A8(ND),
A9 42 ,
B4(PC), F4, F5(PC), F6(ND),
F7 24
B5 40
G1 (ND)
46 , H1
(NA)
I1 (NA)
27 ,
J1(NA)
K1(NA), K2 (ND)
38
L1 (NA), M1 (NA)
35 ,
N1(NA)
H2 (PC)
44 , L2
(NA), L3
(PC) 21 ,
O1 (NA)
31
J2
(PC)26 ,
N2 (PC)
35
2nd Round of design
1st round of design
1st round of design
Fig 3 Overview of all design ideas, coded on the project timeline day-by-day
Trang 6Each of the final concepts (e.g A9, B5, C3, etc) was
given a Quality score from the company’s MCDA
table The score is shown in Figure 3 in bold and is out
of maximum of 72 From this data there is no clear
quality difference between the design output from
round 1 without creativity tools (average score: 35)
and round 2 with creativity tools (average score: 34)
However the pattern in which solutions were generated
was significantly different, where in round 1 most
initial ideas (6 in total) were iterated several times
(usually through Parameter Change), round 2 yielded
many more initial ideas (9 in total) There was
however no pattern in the quality scores linked to the
time spent (number of days) or any benefit of ‘carrying
the ideas’ through (number of iterations)
Coding design output in this way may contribute
one way of mapping the way designers move around
the design space, and particularly the strategies that are
used by creative designers to skip from one ‘train of
solutions’ to new avenues
5 Conclusions
This paper shows that it is possible to categorise
design changes into different creative modes of change
using the coding scheme developed The coding
scheme can be made more robust by: ensuring design
change is always coded relative to a reference design;
tightening up definitions of ‘system’, ‘element’ and
‘function’; and using a matrix, such as the one
presented in Figure 4, to develop a more complete set
of codes
A much larger study with more designers working
on different types of highly-constrained design task is
needed, in order to draw conclusions on the modes of
change and their relationship to creativity Design
research would benefit even more if such a study was
conducted in industry The single case presented here
does show that there can be creative steps in each type
of mode of change One promising area identified for
further research is to look at the patterns of modes of
change that occur throughout a creative design
process Some common patterns were identified in this
paper, but there were no links between patterns and
final outcomes in terms of solution quality The methodology could be made more robust if the designers and researcher coded separately and data was triangulated with direct observations, ‘thinking aloud’ protocol or reflective interviews
Although in this case we did not measure creativity
as part of the study, the coding tool developed will help to map the way designers move around the design space, and particularly the strategies that are used by creative designers to skip from one ‘train of solutions’
to new avenues
The coding scheme can ultimately perform two functions for design research: firstly by understanding existing practice in greater detail (e.g conducting a study of particularly talented/creative designers working on highly-constrained design tasks); or using even early outcomes iteratively to specify/develop tools to stimulate creativity in highly-constrained design tasks (e.g cycles of action research that develop and test tools stimulating/guiding particularly creative design rationale)
References
Bjork E, Ottosson S, (2007) Aspects of consideration in product development research Journal of Engineering Design 18(3):195–207
Brown DC, (2010) The Curse of Creativity In proceedings
of DCC10: The 4th International Conference on Design Computing and Cognition, Stuttgart, Germany, 12–14 July
Hales C, (1986) Analysis of the engineering design process
in an industrial context Mechanical Engineering: Cambridge, University of Cambridge
Lee J, (1997) Design rationale systems: understanding the issues IEEE Expert 12(3):78–85
McMahon CA, (1994) Observations on modes of incremental change in design Journal of Engineering Design 5(3):195–209
Pahl G, Beitz W, (1984) Engineering Design Design Council/ Springer: London
Suh N, (1990) The Principles of Design Oxford University Press: USA
Vincenti W, (1990) What Engineers Know and How they Know It John Hopkins University Press: Baltimore, MD
Trang 7Effectiveness of Brainwriting Techniques: Comparing Nominal Groups to
Real Teams
Julie S Linsey and Blake Becker
Texas A&M University, USA
Abstract Engineering designers need effective and efficient
methods for idea generation This study compares the
effectiveness of group idea generation techniques to the
combined efforts of individuals working alone with
redundant ideas removed, so called “nominal groups”
Nominal groups compared to real interacting groups is a
standard approach for determine if a group idea generation
method can produce better solutions then individuals
working alone This study compares nominal group data to
existing data on a series of group idea generation techniques
Results show that groups using rotational viewing and
representing their ideas with words & sketches, a hybrid
6-3-5 method, outperform nominal groups in number ideas and
have an equal level of quality This result is in contrast to
comparing Brainstorming groups to nominal groups where
nominal groups outperform Brainstorming groups These
results indicate that a team can be more effective than
individuals working separately
Keywords: creativity, idea generation, brainwriting
1 Introduction and Background
Over one hundred formal idea generation techniques
have been developed in areas such as psychology,
business, and engineering (Adams, 1986; VanGundy,
1988; Higgins, 1994) Some methods like Osborn’s
Brainstorming have received significant evaluation
whereas for many graphical methods there is little data
available
One of the first studies using Osborn’s
Brainstorming method in engineering design included
engineering professionals working on a realistic
engineering problem and showed that groups using
brainstorming produced fewer ideas than the combined
efforts of an equivalent number of individuals working
alone (Lewis, et al., 1975) This result, called
productivity loss, is consistent with the vast majority
of studies on variations of Osborn’s Brainstorming
(Mullen, et al., 1991)
While the data on Brainstorming techniques is
extensive, there is far less data available on
brainwriting techniques where communication is
through written words or sketches For brainwriting techniques, some data suggests that groups can be more effective than the combined individual efforts (Gryskiewicz, 1988; Paulus and Yang, 2000) Recent studies have focused on the development and evaluation of more effective idea generation methods
in engineering and design related fields, including industrial design and architecture (Shah, 1998; Shah,
et al., 2000; Van der Lugt, 2002; Shah, et al., 2003; Vidal, et al., 2004) These studies have used a mixture
of sketches, verbal descriptions of ideas, and physical models in the idea generation process Prior work on graphical brainwriting techniques (e.g., Brainsketching, C-Sketch, Gallery), has not compared nominal groups (non-interacting individuals whose non-redundant results are combined) with real interacting groups
Our study compares nominal groups with group ideas generation methods: Brainsketching, C-Sketch, 6-3-5, and the first phase of the Gallery method These methods are gaining popularity and exposure in the engineering research community, in addition to industrial application They also form a diverse set of group idea generation techniques that vary in how ideas are exchanged and in the types of representations used (written words, sketches, etc.) To understand the theoretical basis of these method, we dissect them into two key factors (1) how a group’s ideas are displayed
to other members (“rotational view” or all are posted
in “gallery view”) and (2) the form of communication between group members (no communication, written words only, sketches only or a combination of words and sketches.) All other method parameters are kept constant for all experimental conditions
1.1 Osborn’s Brainstorming
The term “brainstorming” is frequently applied to idea generation techniques in general and not just to the technique developed and named by Osborn Osborn’s Brainstorming begins with a facilitator explaining the problem A group then verbally exchanges ideas
Trang 8following four basic rules: (1) criticism is not allowed,
(2) “wild ideas” are welcomed, (3) building off each
others’ ideas is encouraged, and (4) a large quantity of
ideas is sought Despite the face validity of these rules,
much research demonstrates productivity loss in
brainstorming compared to an equal number of
individuals working alone (nominal groups) (Mullen,
et al., 1991)
Silent Sketching
More Silent Sketching Review and Discussion
Fig 1 Illustration of Gallery method
1.2 Brainsketching
In Brainsketching, individuals begin by silently
sketching their ideas on large sheets of paper including
brief annotations Group members exchange drawings
and silent sketching continues for another period of
time (VanGundy, 1988) This technique allows for a
visual means of expression, and so it is well suited for
product design Van der Lugt used teams of advanced
product design students to compare Brainstorming to a
variant of Brainsketching (that included the
explanation of ideas between exchanges) (Van der
Lugt, 2002) The Brainsketching variant led to more
cases in which group members built on previously
generated ideas than did Brainstorming
1.3 Gallery
In the Gallery method, individuals begin by sketching
their ideas silently on large sheets of paper After a set
amount of time, participants discuss their ideas and
move about the room studying others’ ideas This
review phase is followed by a second stage of silent
sketching (VanGundy, 1988; Pahl and Beitz, 1996; Shah, et al., 2001) The review phase allows team members to clarify their ideas, and it provides social interaction
Fig 2 Illustration of 6-3-5 and C-Sketch Six people
silently describe three ideas on a sheet of paper and then exchange papers
1.4 C-Sketch / 6-3-5
For 6-3-5 (Shah, 1998; Otto and Wood, 2001; Shah, et al., 2001) and C-Sketch (Shah, 1998), six (“6”) participants are seated around a table, and each silently describes three (”3”) ideas on a large sheet of paper The ideas are then passed to another participant This exchange goes on for five (“5”) rounds For the original 6-3-5 method, ideas are described using only words In contrast, the C-Sketch, method permits only sketches One advantage of C-Sketch over 6-3-5 is that sketches are typically ambiguous, and so one person may misinterpret aspects of someone else’s sketch, which may lead to new ideas (Shah, et al., 2001) Other variations of 6-3-5 have also been proposed (VanGundy, 1988; Otto and Wood, 2001) One variation permits annotated sketches (Otto and Wood, 2001) In experimental comparisons with different conditions than those reported in this paper, C-Sketch and Gallery outperformed 6-3-5 (words only) for variety, quality and novelty of ideas (Shah, et al., 2001) Novelty is how unique a particular idea is and variety is how much of the design space is captured by
a set of ideas This previous study used groups of mechanical engineering undergraduates, mechanical engineering graduate students and professional designers Each group was evaluated on all three techniques and a different design problem was solved for each of the techniques This design eliminated individual differences as a noise variable but caused the technique results to be confounded with the design problem
Trang 92 Experimental Approach and Research
Questions
Engineers seek a robust idea generation method for
predictably producing a large quantity of high quality,
novel product solutions Using a factorial design of
experiments, our study explores the influence of the
representation used to communicate ideas and how
ideas are displayed to individuals We seek to answer
the following research questions:
Research Question: How do the nominal
groups compare to real groups in terms of
quantity and quality of ideas?
This research questions is addressed systematically in
the following sections We discuss our experimental
method, metrics for evaluation, data analysis approach
and the results
3 Experimental Method
We conducted a factorial experiment in order to
explore the effects of two key factors on the outcome
of group idea generation The first factor controls how
participants view the ideas, either all ideas are posted
via gallery (on the wall), sets of ideas are rotated
between participants, or they are not exchanged
(individual idea generation-nominal groups) The
second factor controls how participants represent their
ideas Participants either use written words only,
sketches only, or a combination of written words and
sketches to communicate ideas to their teammates A 2
(Display of ideas: “gallery” or “rotational view”) X 3
(Representation: words only, sketches only, or words
combined with sketches) factorial experimental design
is used (Table 2) No oral discussions are allowed
during the session; all communication is written This
approach produces methods similar to 6-3-5 (Pahl and
Beitz, 1996), C-Sketch (Shah, 1998), Brainsketching
(VanGundy, 1988), or Gallery Method (Pahl and
Beitz, 1996), as shown in Table 3 All participants solved the peanut sheller problem (Linsey, et al., accepted)
3.1 Factor 1: Display of Ideas
One key factor in this study is whether ideas are displayed all at once or whether participants see only a subset at any given moment In the “gallery view” condition, all ideas generated by the team are posted
on the wall, so all participants can see all of the ideas
at the same time This approach results in a method similar to Gallery Method or Brainsketching (VanGundy, 1988; Pahl and Beitz, 1996) In the
“rotational view” condition, ideas are passed around the table, so that each participant sees only a subset of the ideas at any given moment This condition is similar to 6-3-5 or C-Sketch (Pahl and Beitz, 1996; Shah, 1998; Otto and Wood, 2001)
3.1.1 Gallery View Condition- Similar to Brainsketching or Gallery Method
For the first 10 minute period, each student is given a number of paper sheets and told to write down at least two ideas on separate sheets of paper Sheets are collected as participants finish, but are not displayed until the end of the period The time period length is based on the available time and recommendations from the literature, which vary from five to 15 minutes (VanGundy, 1988; Baxter, 1995; Shah, et al., 2000) The ideal time period for the methods under evaluation
is not explicitly known and is not one of the experimental parameters At the end of the first period, all sheets are numbered and posted gallery style on the wall In the four subsequent 7.5 minute periods, ideas are posted as they occur and participants are told to execute one of the following options:
2 Add new ideas to one of the posted drawings Participants can request a drawing by writing down its number on a small sheet of paper
7 Make a separate drawing that is related to the
Table 1 Experimental conditions
Factor 2: Representation
Words Only Sketches Only Words and Sketches
Factor 1: View
Gallery View
Trang 10ideas that are already posted, and write the
number of the linked idea on the new sheet
8 Start a completely new sheet after reviewing
the posted ideas
For the first 10 minute period, each participant is given
a number of paper sheets and told to write down at
least two ideas on separate sheets of paper similar to
the “gallery view” condition At the end of the period,
the experimenter collects all sheets and systematically
redistributes them such that each participant views
each set of papers once Participants cannot identify
which one of their teammates had the sheets
previously In the four subsequent periods, lasting 7.5
minutes each, participants have the same options as in
the “gallery view” condition: to add ideas to an
existing sheet, to create a new product solution linked
to another sheet or to start a completely new product
solution The exception here is that participants focus
on the specific set of papers given to them at a
particular instance in time
Table 2 Experimental conditions and similar formal method
Experimental
(Aiken, et al., 1996)
2 6-3-5
3
4 C-Sketch
5 Gallery
6 Brainsketching
3.1.2 Rotational View Condition- Similar to 6-3-5 or
C-Sketch
For the first 10 minute period, each participant is
given a number of paper sheets and told to write down
at least two ideas on separate sheets of paper similar to
the “gallery view” condition At the end of the period,
the experimenter collects all sheets and systematically
redistributes them such that each participant views
each set of papers once Participants cannot identify
which one of their teammates had the sheets
previously In the four subsequent periods, lasting 7.5
minutes each, participants have the same options as in
the “gallery view” condition: to add ideas to an
existing sheet, to create a new product solution linked
to another sheet or to start a completely new product
solution The exception here is that participants focus
on the specific set of papers given to them at a
particular instance in time
3.1.3 Nominal Groups
For the nominal groups, individual were assigned to
work alone and were given the same amount of time
3.2 Factor 2: Representation
The second experimental factor prescribes how the participants communicate their ideas to other participants (words only, sketches only with no words,
or a combination of words and sketches) At the end of the sessions and after completion of the surveys, participants in either of the group sketches-only conditions labeled their sketches with brief descriptions to facilitate evaluation American mechanical engineers are typically not taught to draw free-hand and therefore their sketches are usually difficult to interpret without annotations The prior study (Linsey, et al., accepted) shows that the sketches only data shows a different pattern of results likely due
to the poor sketch quality and effort required by teammates to interpret the drawings For this reason, individual data was not taken and therefore no nominal groups
Boiling Water
Water Mill
by a Waterfall
Cam
Vertical Crushing Plate
Grate Hopper
Graduated Concentric Crushing Surfaces
Conveyor
Collection Bin
Hand Crank
Conveyor Drive
Grate
Fire
Water Inlet Hopper
Vertical Crushing Plate
Hopper
Fig 3 Set of examples which were briefly and accidently
shown in class to the nominal group participants
The nominal group data was taken two semesters after the group data was collected The same professor taught the class and the same experimenter collected the data During the semester the nominal group data was collected and prior to data collection, the participants in the nominal groups were accidently shown example peanut shelling machines (Fig 3) These ideas were only shown briefly in class and the participants’ data does not appear to be influenced The nominal groups were formed by randomly assigning the results from five individuals to a group and removing redundant results Data is from twenty-four individuals whose results were used to create forty nominal groups