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DESIGN INSIGHT—A KEY TO STUDYING DESIGN CREATIVITY

TOSHIHARU TAURA

AND

YUKARI NAGAI

Abstract. The objective of this article is to systematize the methods for studying design creativity by focusing on design insight, which underlies and governs the thinking process of the designer. In other words, the main topic of this article is to study the something that can explain how and why the design process proceeds. In this article, it is shown that the essence of design insight is constituted in three viewpoints: perspective, criteria, and motive. Perspective involves the ability to look at or perceive things or concepts, criteria involves the ability to evaluate the design process as well as things and concepts, and motive involves the ability to promote the des-ign process. Based on the reviews and discussions on design insight, the design process is classified into three categories: artistic design process, creative design process, and systematic design process. The creative des-ign process is defined as a combination of the artistic and systematic des-ign processes. Furthermore, the notion of differentia is revealed to be the key to the design process. Finally, the methods for studying design creativ-ity are systematized and it is shown that mathematical modeling, computer simulation, and extended protocol analysis method are effective methods for studying design creativity.

T.TAURA AND Y.NAGAI 2

Introduction

Currently, design researchers are displaying a high level of interest in crea-tivity. Recently, a large number of remarkable studies have been conduct-ed and various arguments with regard to creativity in design process have been presented, for example, research on the meta-cognitive level of des-ign knowledge among people or research in the context of the behavior of designers [11], [20]. In order to understand creative design knowledge, which is complex and involves multiplicity, research approaches that adopt advanced computational modeling [23], [16], [36] and those that involve a formal representation of design concepts based on the ontology theory [14] have been utilized. Moreover, a theoretical approach to the features of des-ign strategy has been adopted on the basis of the relationship between con-cept and knowledge [19]; this approach has demonstrated a framework for innovation from the perspective of knowledge creation. Moreover, several notable investigations have been reported on design cognition using ana-lytical approaches targeting the important factors or conditions for high creativity of actual expert designers [5], [49], [4], [22]. Furthermore, re-search methods have been obtained for establishing the means of support-ing creativity in design [32], [7]. Thus, the trend of conducting research on creativity in design process has become increasingly prominent.

This article systematizes the methods for studying “design creativity” from a different viewpoint. We focus on the notion of “something,” which not only underlies the thinking process of the designer (hereafter referred to as design process) deep in the mind but also governs it; we term this no-tion “design insight.” The term “insight” is considered to be an important factor for creativity. For example, insight is defined as “a distinctive and apparently sudden realization of a strategy that aids in solving a problem, which is usually preceded by a great deal of prior thought and hard work; it often involves reconceptualizing a problem or a strategy for its solution in a completely new way, frequently emerges through the detection and combination of relevant old and new information, to gain a novel view of the problems or a solution, and is often associated with finding solutions to ill-structured problems” [37]. In fact, the phenomenon of sudden appear-ances—for example, inspiration—is an interesting and important factor for creativity.

On the other hand, “insight” involves the meaning of “ability to under-stand and realize” as well as “phenomenon of sudden appearance” [8]. In this article, we focus on “ability” in the meaning of insight and extend the original definition of the term insight used in creativity in order to capture the “something” that underlies and governs the creative nature of the des-

DESIGN INSIGHT—A KEY TO STUDYING DESIGN CREATIVITY 3

ign process. In other words, we use the term “design insight” to imply the “something” that can explain how and why the creative thinking process in design progresses.

Therefore, the objective of this article is to systematize the methods for studying design creativity by focusing on design insight.

In this article, the notion of “ability” is captured as a “driving force” that pushes the design process. There may be two types of driving forces for the design process—push and pull (Fig. 1). The pull-type driving force refers to the force due to which the design process appears to be “pulled” externally by a goal, while the push-type driving force refers to the force due to which the design process appears to be “pushed” from within the person, by the “something” that deeply underlies the mind. In this article, we focus on the latter driving force, paying special attention to the process of creating a new concept, since this process is the initial stage of the des-ign process and is believed to be governed by the push-type rather than the pull-type driving force.

Fig. 1 The notion of design insight

In this article, as a framework for capturing and determining the essence of design insight, we adopt a concept-synthesizing process in which a new concept is created from two original concepts (hereafter referred to as base concepts), since this process is the simplest and most suitable for investi-gating the characteristics of the initial stage of the design process. Here, the term “concept” is used in order to represent the image corresponding to an object (natural and artifactual objects) that is held in the mind and that existed in the past, exists now, and will exist in the future. How and why the two base concepts are selected, and how and why a new concept is cre-ated from these two base concepts are the main topics of discussion in this article.

Further, we assume that design insight can be examined in terms of three viewpoints: perspective, criteria, and motive. The viewpoint of per-spective involves the ability to look at or perceive things or concepts. The viewpoint of criteria involves the ability to evaluate the design process as


well as things and concepts. The viewpoint of motive involves the ability to promote the design process.

In general, it is extremely difficult to study design insight because this activity occurs deep in the human brain and cannot be directly observed. Until now, the protocol analysis method has been used for observing the thinking process. However, it is difficult to apply the conventional proto-col analysis method to study the design insight that deeply underlies the thinking process. Therefore, we used the extended protocol analysis method developed by Taura et al. [41] in certain experiments. This method comprises two analyses: the conventional protocol analysis, and the analy-sis on the explanation of each action of the subject; the analysis is con-ducted through questions and answers while showing the subject the action that is recorded on video during the design process. Asking the subject for an explanation of each action is expected to capture the “something” that underlies the thinking process deep in his/her mind. On the other hand, modeling is another effective method for analyzing design insight in the case that the activity cannot be directly observed. There are two methods for modeling the design insight: mathematical modeling and computer simulation.

Based on these experiments and discussions on design insight, we clas-sify the design process into three categories: artistic design process, crea-tive design process, and systematic design process. The creative design process is defined as the combination of the artistic and systematic design processes. Further, design creativity is defined as the nature of the creative design process.

Finally, we systematize the methods for studying design creativity and indicate that mathematical modeling, computer simulation, and the extend-ed protocol analysis method are effective for identifying the notion of “dif-ferentia” as a key factor in the design process; it is rather difficult to iden-tify this notion by using other methods.

Framework for studying the design process

In this article, as mentioned above, the process of synthesizing two base concepts is adopted as a framework for discussing design insight. The rea-sons for adopting this process are provided in greater detail below in terms of three aspects: empirical, framing, and theoretical.

The first reason is related to the empirical aspect. The concept-synthesizing process is found in an actual field. Empirically, the invention of the art knife—the first snap-off blade cutter—is a good example. The


inspiration for this incredible concept originated from the synthesis of two concepts—chocolate segments that can be broken off and the sharp edges of broken glass (Fig. 2) [42].

Fig. 2 Innovation of an art knife by combining two concepts – broken glass and chocolate segments

Analogical reasoning Concept blending Concept integrating in the-

matic relation e.g., “white tomato” for

snow-tomato e.g., “powdered ketchup”

for snow-tomato e.g., “humidifying refrig-

erator” for snow-tomato

Fig. 3 Three types of concept-synthesizing processes (snow tomato

The second reason is related to the framing aspect. The concept-synthesizing process involves the typical important characteristics of the design process. Nagai and Taura indicated that the essential processes of creating a new concept, such as “analogy,” can be captured in the frame-work of the concept-synthesizing process [25]. As a result, they systema-tized the concept-synthesizing processes by classifying them into three types: analogical reasoning, concept blending, and concept integration in thematic relation.

Chocolate bar Broken glass

Innovation of the art knife (the first snap-off blade cutter)


Analogical reasoning is known to play a crucial role in design [17], [15]. Analogical reasoning is considered to be a method for concept creation in-volving the transfer of certain features from an existing concept to another. For example, the concept of a “white tomato” can be created from two in-dividual concepts, “tomato” and “snow” (Fig. 3).

On the other hand, in studies on cognitive linguistics, Fauconnier ana-lyzed how conceptual integration creates mental products and the manner in which one can position mapping and blending systems between mental spaces (Fig.4) [12]. He demonstrated that conceptual integration operates on two input mental spaces to yield a third space, which is termed “the blend.” This blended space inherits partial structural features from the in-put spaces and also possesses its own emergent structural features. This conceptual blending process is also a type of concept-synthesizing process. For example, from “tomato” and “snow,” the concept of “powder-type ketchup,” for use on the table like powder-type cheese and can be added to food, can be created.

Fig. 4 Structure of mental space blending (given by Fauconnier)

Further, in the research on recognizing the relation between two con-cepts, it has been revealed that there are two types of relations—taxonomical and thematic [34]. Taxonomical relations are those that repre-sent the physical resemblance between two objects. Thematic relations are those that represent the relation between two concepts through a thematic scene. In design, its outcome (hereafter referred to as design product) must be meaningful to people. Therefore, the designer must carefully consider not only the attributes of the product (shape, material, etc.) but also its function and interface; in other words, it is important for the designer to


consider the situation (thematic scene) in which the design product will be used.

Consequently, the concept integration process, in which concepts are synthesized in terms of the thematic relations among them, was found to play a considerably important role in the design process [25], which was verified by using the extended protocol analysis method. With regard to the example of “tomato” and “snow,” the concept of a “refrigerator that can humidify the food in it” is created based on the thematic scene of the following situation: a tomato being stored in the snow.

As mentioned above, it is found that the essential characteristics of the design process can be discussed within the framework of the concept-synthesizing process.

Fig. 5 An example of the paradigm model

The third reason is related to the theoretical aspect. The concept-synthesizing process can be analyzed theoretically. The General Design Theory (GDT) is a theory on design [50]. In GDT, the entity concept (natural and artifactual objects) is modeled as an element, and the abstract


concept (function and attribute) is modeled as a class (subset of elements), as design knowledge in topological space. Furthermore, GDT defines the design process as a mapping from function space, where the design re-quirement is described, to attribute space, where the design solution is sought. Previous studies on GDT have derived numerous theorems that can explain the characteristics of design knowledge and the design process. In GDT, the concept-synthesizing process is theorized as a paradigm model. This paradigm model is described in the following manner.

Given a specification

!

T = T1" T

2" T

3LT

n, assume that a solution s1 is

proposed, which satisfies

( ) .TTTTTTsTs212111 !" LL !!!!!=" ++ kkk

In this case, s1 satisfies only a part of the specification. Then, assume the

next proposal s2, which is obtained by synthesizing the two concepts T(s1) and Tk+1.

( ) .TTTTTTsTs

212122 !"# LL !!!!!=" ++ kk

This proposal also satisfies only a part of the specification; however, it

represents an improvement over s1. In this case, the move from s1 to s2 will satisfy the characteristics of a directed series of points. An example of the paradigm model is presented in Fig. 5. Here, a new animal that can run fast, peeps, and swims fast is designed by synthesizing the body of a dog, the beak of a bird, and the webbed feet of a frog. In GDT, this synthesizing process is discussed in a rigorously mathematical manner. Some of the re-sults are explained in subsequent sections.

For the abovementioned reasons, the process of synthesizing certain (two) concepts is adopted as a framework for discussing design insight.

Structure of design insight

In this section, the outline of the structure of design insight is described, while each item is explained in detail in the following sections. We attempt to capture the essence of design insight from three viewpoints—perspective, criteria, and motive.

The first viewpoint refers to the ability to determine the manner in which things or concepts are looked at and perceived. In this study, we fo-cus on the similarity and/or dissimilarity between two concepts, particu-


larly comparing the design process with the linguistic interpretation proc-ess, which is another generative but non-design process. Based on this comparison, the notion of differentia, which is defined as the recognition of difference between two concepts, is found to be an important factor for design. This ability is believed to be related to design insight, since the manner in which things and concepts are looked at and perceived is as-sumed to come from inside the person rather than from external sources.

The second viewpoint refers to the ability to determine the criteria based on which the design process as well as things and concepts are evaluated. When synthesizing two concepts, the main steps are the determination of the criteria for selecting the two base concepts and focusing on the features of each base concept that is to be synthesized. In order to capture the es-sence of the criteria, we classify the criteria into three categories: deduc-tive, inductive, and abductive. Furthermore, from the viewpoint of systems theory, we classify the criteria into inner criteria and outer criteria. Inner criteria are related to the manner of viewing design in terms of autopoiesis (self-creation; a term originally coined by Humberto Maturana) or self-reference, while outer criteria are related to the manner of viewing design in terms of problem-solving. In the context of this article, abductive and inner criteria are closely related to design insight. Based on this discussion, it is also found that the notion of differentia is a key for criteria, since the introduction of a metric into the design space and conservation of the simi-larity between the two spaces can convert the abductive criteria into de-ductive criteria (explained subsequently), while the metric space is formed based on a mathematically separated space, which involves the notion of differentia.

The third viewpoint with regard to design insight is motive. Motive has been discussed by psychologists as an important factor for creativity. It has been reported that highly creative work is produced by those who have strong intrinsic motivation to engage in an activity [1], [2]. Therefore, whether the motive is intrinsic or extrinsic is a topic for discussion in the case of design insight. Furthermore, whether intrinsic motive is coherent or noncoherent is also discussed. It is suggested that the incoherence-driven intrinsic motive is related to design insight (explained subse-quently). Just as in the case of criteria, mathematical discussion suggests that the formation of a separated space, which implies the notion of differ-entia, generates the potential to promote the design process, which appears to be related to the motive. This discussion suggests that the notion of dif-ferentia is also a factor for the motive in the design process.

As mentioned above, the essence of the “something” that underlies and governs the design process is systematized from three viewpoints: perspec-


tive, criteria, and motive. The relationship between them is explained as follows. Perspective, which refers to the ability to determine the manner in which things or concepts are looked at, is located between the mind of the designer (which is inside him/her) and his/her external environment; on the other hand, criteria underlies the design process in the mind. Therefore, criteria are believed to underlie the design process more deeply than per-spective. Similarly, motive is believed to underlie the design process more deeply than criteria.

Fig. 6 Structure of design insight

Overall, the relationship among perspective → criteria → motive has a layered structure and indicates the degree of depth of the “something” that underlies and pushes the design process.

This article addresses the notion that design creativity involves the inte-gration of the “abductive/inner criteria and intrinsic motive” and the “de-ductive/inductive/outer criteria and extrinsic motive” as well as the per-spective on differentia.

The structure of design insight is summarized in Fig. 6.

Perspective—similarity or dissimilarity: the first viewpoint for design insight

In the field of linguistic studies, it has been revealed that a novel noun-noun phrase may be interpreted in three ways: property mapping, hybrid linking, and relation linking [48]. For example, a knife-fork can be inter-preted as follows: a knife-shaped fork in property mapping, one half being


a knife and the other half being a folk in hybrid linking, and a knife and fork set being used together for eating in relation linking (Fig. 7).

Taura et al. were able to clarify and categorize the three types of linguis-tic interpretation processes corresponding to the concept-synthesizing process in design, as presented in Table 1 [43]. By using this correspon-dence, the design process can be compared to the linguistic interpretation process. In this section, the term analogy is used to represent the type that involves property mapping in the linguistic interpretation process and analogical reasoning in the design process. Similarly, the term blending is used for hybrid linking and concept blending, thematic relation for relation linking and concept integration in thematic relation.

Fig. 7 Three types of recognition processes for the combination phrase (knife-fork)

Taura et al. revealed that the proportion of analogy was lower (fewer design products were categorized as analogy) in the design tasks than in the interpretation tasks and the proportion of blending was higher in the design tasks than in the interpretation tasks, while the proportion of the-matic relation is not so different between the design and interpretation tasks [43]. This result indicates that the nature of the design process is based on blending in context of comparing it with the interpretation proc-ess. The reason for this result is assumed to be as follows: the concept cre-ated by analogical reasoning is limited in terms of originality, since analogical reasoning cannot extend beyond the domain of the given con-cept. In contrast, concept blending can create a truly new concept, because the concept created by this process does not belong to the domain of either of the base concepts. Therefore, concept blending is assumed to character-ize the design process, which pursues high originality. On the other hand,

knife-shaped fork

“one half is a knife and the other half is a fork”

knife and fork set


in the interpretation process, the given phrases are interpreted naturally. Therefore, it is assumed that concept blending is used more in the design process as compared with the interpretation process.

Further, we focus on the types of recognition (commonalities, alignable differences, and nonalignable differences) [24]. Markman and Wisnieski explained the notions of alignable and nonalignable differences in the fol-lowing manner: “Alignable differences are coded for both references to values along a single dimension, such as a sled carries more than one per-son and a ski carries only one person, as well as for implicit references, such as sleds and skis carry different number of people. Nonalignable dif-ferences are coded for all other differences that were listed. These differ-ences simply focused on a disparity between the two items without high-lighting a common dimension. An example of a nonalignable difference would be that an airplane is solid but a puddle is not” [24]. Further, it was reported that more commonalities and alignable differences were listed for similar than for dissimilar pairs, while more nonalignable differences were listed for dissimilar than for similar pairs [24], [46].

Table 1 Classification of the linguistic interpretation and design processes Analogy Blending Thematic relation

Linguistic interpretation process

Property mapping (e.g., “a knife-shaped fork” for knife-fork)

Hybrid linking (e.g., “one half is a knife and the other half is a folk” for knife-fork)

Relation linking (e.g., “a knife and fork set” for knife-fork)

Design process Analogical reason-ing (e.g., “white to-mato” for snow to-mato)

Concept Blending (e.g., “powder ketchup” for snow tomato)

Concept Integration in thematic relation (e.g., “non-drying refrig-erator” for snow tomato)

We assume that the types of recognition also play a rather important role

in the concept-synthesizing process, and that they can be a key for access-ing the characteristics of the design process.

Now, let us focus on the recognition types in the concept-synthesizing process.

First, we consider analogical reasoning. Analogical reasoning is consid-ered to involve the transfer of certain features from an existing concept to another concept. Therefore, the certain features recognized in analogical reasoning are assumed to be alignable differences, since in analogical rea-soning, the feature recognized in the existing concept displaces the corre-sponding feature in another concept, and this displacement implies that


both these features involve different values along a single dimension. For example, “white tomato” in Fig. 3 is obtained by transferring the feature of “white” to “tomato.” Here, the recognized feature “white” is classified as an alignable difference, since “white” is the value of color and tomato has another value of color, i.e., “red.” On the other hand, in concept blending, the features recognized in the synthesized concept need not be alignable between the base concepts. For example, in “powdered ketchup” in Fig. 3, the recognized feature “powder” is classified as a nonalignable difference, since the corresponding feature of “powder” is believed to be non-recognizable in “tomato.” Therefore, the nonalignable difference is assum-ed to be related to concept blending in the design process.

0% 20% 40% 60% 80% 100%

Design Task

Interpretation

Task

Analogy Blending Thematic

0% 20% 40% 60% 80% 100%

Design Task

Interpretation

Task

Commonality Alignable difference

Nonalignable difference

Fig. 8 Comparison between the design process and recognition types (commonal-ity, alignable differences, and nonalignable differences)

Further, Taura et al. found that if the base concepts are rather dissimilar, a highly creative concept may be obtained [42]. By reconsidering this find-ing from the viewpoint of recognition types, we can assume that creativity


in concept blending is related with recognizing the features as those with nonalignable differences.

Fig. 9 Relation between originality and proportion of nonalignable differences in blending

In order to verify the above assumption, we conducted an experiment in which the subjects were required to perform the following tasks: interpret a novel noun-noun phrase (interpretation task) and create a new concept from the same noun-noun phrase (design task) [27]. The interpretation task comprised two sub-tasks. First, the subjects were asked to naturally inter-pret the noun-noun phrases. Second, they were required to enumerate cer-tain words to explain each interpretation. The responses to the first sub-task were categorized according to thought types (analogy, blending, and thematic relation). The responses to the second sub-task were categorized according to recognition types. The design task also comprised two sub-tasks. First, the subjects were required to design a new concept from the noun-noun phrases. They were required to not only draw a sketch of the concept but also to explain the concept by using the terms in a sentence. Second, they were required to enumerate certain words in order to explain each designed concept. The outcome of design (sketch and sentence) are categorized according to thought types and evaluated from the viewpoint of creativity (originality and practicality). The responses to the second sub-task were categorized according to recognition types.

The results revealed that blending and nonalignable differences charac-terize the design process (Fig. 8). Furthermore, it was found that focusing on nonalignable differences is related to creativity (originality) in the con-cept-blending process, which characterizes the design process (Fig. 9). Here, originality was evaluated based on the creativity evaluation of Finke et al. [13].


This result indicates that nonalignable difference recognition is essential for originality.

Criteria: the second viewpoint for design insight

The important steps in synthesizing two base concepts are determining the criteria for selecting the two base concepts and focusing on the features of each base concept to be synthesized. We classify the criteria into three categories: deductive, inductive, and abductive.

The deductive criteria are determined according to certain deductive rules. With regard to the deductive rules for selecting the base concepts, Taura and Nagai have identified the following two rules. The first rule is with regard to the distance between the two base concepts. In other words, if the base concepts are rather dissimilar, a highly creative design product may be obtained [42]. This rule was derived in the following manner. In the concept-synthesizing process of the two base concepts, a more creative new concept can be produced when the notions, features, and situations are combined at a more abstract level, and this abstraction is caused by the dissimilarity between the two base concepts (Fig. 10). This derivation can be verified by using the extended protocol analysis method [41].

Although this rule is derived from the field of design, its essence is the same as the findings in the field of linguistic interpretation, that is, a lower level of similarity between two combined nouns results in more emergent features being found in their interpretations [46].

The second rule is concerned with the property of a base concept. That is, if each base concept has a greater number of associative concepts, a highly creative design product may be obtained [26]. Here, the number of associative concepts involves the number of concepts that are associated with each base concept in a natural manner. This rule was verified by a design experiment in which two base concepts were synthesized in two cases—each of the two base concepts with a high (Task B in Fig. 11) or low number of associations (Task A in Fig. 11). The evaluation method for the creativity of the design product was also based on the experiments of Finke et al. [13], and the evaluation items were determined on the basis of two dimensions: “practicality” and “originality.” Among the subjects, all but one demonstrated high originality in synthesizing the two base con-cepts, each of which had a large number of associative concepts.

Inductive criteria are derived from experience. The following is an ex-ample: when a person designs a creative concept from “tomato” and


“snow,” he/she will select either the same or similar base concepts in dif-ferent situations.

Fig. 10 Relationship between dissimilarity and creativity

On the other hand, the focus of abductive criteria is on foreseeing the appropriate base concepts. Let us consider the example of the art knife pre-sented in Fig. 2. Although this example is rather attractive, the problem of focusing on the chocolate remains unsolved. In other words, why is the chocolate focused on? Generally, chocolate is not associated with a knife. As shown in this example, it is extremely difficult to select the concepts to be synthesized before designing because the appropriateness of the base concepts can be evaluated only after they have been synthesized and the design product has been judged. This problem is a back and forth problem and is expected to be the most closely related to design insight. This is be-cause it is difficult to explicitly recognize the abductive criteria, and these criteria are believed to deeply underlie the mind of the designer, while the deductive and inductive criteria are more explicitly available, being gov-erned by factors in the external environment of the designer.

However, in certain cases, the back and forth problem can be converted into a spatial problem; in other words, abductive criteria can be converted to deductive criteria [44].


Fig. 11 Relationship between the number of associative concepts and design crea-tivity

Fig. 12 An example of converting a time issue to a space issue – travelling path of a light beam

For example, let us consider the path of the light beam shown in Fig. 12, wherein we attempt to identify the light beam that passes from A to B through a reflection in the mirror. If we attempt to predict the path of the


beam based on the knowledge that “a light beam travels along the path that takes the shortest time,” we are unable to evaluate whether or not the path takes the shortest time before the beam has travelled. However, if we apply the knowledge that “the angle of incidence is equal to the angle of reflec-tion,” then it is possible to calculate the path of the light beam before ob-serving the travelling beam. In this case, the back and forth problem from the viewpoint of time is converted into a spatial problem.

GDT provides a hint in this direction for the design process. In GDT, the design process is defined as a mapping from the function space to the attribute space. In order to effectively seek a design solution, it is neces-sary to determine an appropriate attribute space, in particular to determine the classes (subsets of entity concepts) that are used to describe the attrib-utes. However, when initiating the design process, it is extremely difficult to determine the appropriate attribute space since it is impossible to evalu-ate what type of attribute space is effective without searching for the des-ign solution. Therefore, this is a back and forth problem. With regard to this problem, it is expected that the introduction of a metric into the design space and the conservation of the similarity between function space and at-tribute space affords an effective design solution search. In other words, if two concepts are close to each other in the attribute space, under the condi-tion that the same concepts are close to each other in the function space, the design solution search may be effective (Fig. 13). This rule is valid on-ly when the design solution is searched for using a neighborhood search method. This finding can be applied to convert the abductive criteria to de-ductive as follows. If the attribute space is formed such that a similarity is conserved with the function space, then an effective design solution search may be performed.

Mapping Mapping

Fig. 13 Similarity conservation between two spaces

Taura identified the above method of converting the back and forth problem into a spatial one by applying it to the function decomposition

Degree of similarity conservation between

two spaces is high

Degree of similarity conservation between

two spaces is low


process in design [44]. In the initial stage of the design process, the re-quired functions are generally decomposed into a few partial functions. Although this decomposition process is not always necessary in finding design solutions, it is well known that it is useful in the design process. Not only has its importance been indicated in an empirical study [30], its rationale has also been analyzed in a theoretical study [40].

Although the importance and necessity of the function decomposition process is accepted in both industry and academia, its methodology has not been thoroughly clarified. Considering that the function decomposition process is divided into (1) the process of forming a function space for de-scribing the decomposed functions and (2) the process of establishing a decomposed function structure for the design solution search, the former process, in particular, has not been clarified. Taura analyzed the design space forming process for the decomposed functions as an example of the back and forth problem; this analysis is particularly conducted by focusing on the problem of determining the classes that are used to describe the de-composed functions. A computer simulation, in which a machine compris-ing three components (concepts in the context of this article) that satisfies the required function is searched, was conducted in order to investigate the manner in which the degree of similarity conservation between the space for the required function description and that for decomposed function de-scription is related to the efficiency of a design solution search.

Fig. 14 Relation between the average degree of similarity conservation of space and search efficiency

The result shows that the conservation of the similarity between the two spaces throughout the search is related to improvement in the search effi-ciency (Fig. 14). This result indicates that forming an appropriate space for the decomposed functions for an efficient design solution search is re-


placed by the criterion of similarity conservation. In other words, it is pos-sible to analyze the back and forth problem in the design process by con-verting it into a spatial problem.

When this theory is applied to two concept-synthesizing problems, the following rule will be derived. If a space in which the two base concepts are searched for is formed such that the similarity between the two base concepts in that space and that in the evaluating space (in which the origi-nality and practicality of the design product created from the two base concepts are evaluated) is conserved, then the appropriate two base con-cepts may be searched for effectively.

On the other hand, from the viewpoint of the systems theory, the criteria can be divided into the inner and outer criteria. According to this view-point, the design process can also be identified as that which involves the inner or outer criteria. Inner criteria refer to the viewing of design in terms of autopoiesis or self-reference, while the outer criteria refer to the viewing of design in terms of problem-solving. Whether the criteria are inner or outer depends on whether or not the ability to determine the criteria is de-pendent on the design process itself. In other words, if the criteria change during the design process only according to the design process or the des-ign product, then the process is regarded as one involving inner criteria. On the other hand, the criteria can either remain unchanged or change ac-cording to outer information; in this case, the process is regarded as one involving outer criteria.

In general, the creative work of artists can be expressed as autopoiesis because the interaction between an artist and his/her works is continuously regenerated. Winograd termed this process “instructive interaction” [47]. From the viewpoint of personal creativity, knowing or learning a process by changing views through experience is also addressed as the continuous re-cognition process [18], [29]. During learning, the boundary conditions can be recognized as becoming increasingly wider based on inner views; this was reported as an “interactive redesign process” [35]. In general, creativity is also considered to be related to self-reference or self-recognition [33], [9]. Such an individual creative/learning process and or-ganization can be explained as a structure-determined system [47]. Since Winograd addressed design as an issue related to an “interaction process of understanding and creation” from wider social views, the function of in-formation/communication design can be considered as the creation of a new experience [28]. It is necessary that these processes be experienced, which can be achieved only through inner views. Therefore, the inner cri-teria have been considered to be integral to design insight; however, the objectification of inner criteria is considered to be difficult.


In contrast, the problem-solving process is also used to represent the design process. There is one famous reference for design process in engi-neering, which was originally represented as a model by Asimow [3]. Sub-sequently, interest in design methodology was activated in the 1960s. This perspective is similar to the viewpoint of a problem-solving process in that they are both goal-oriented. Their objective views are suited to represent productive processes. Since Jones illustrated the design process as a three-step model (analysis-synthesis-evaluation) [21], it (design process) has been considered to have a sequential circulation structure [31], [6].

Motive: the third viewpoint for design insight

In order to capture the very essence of design insight, it is necessary to fo-cus more on the motive that is deeply related with the ability to promote the design process. Motive has been discussed by psychologists as an important factor for creativity. It has been reported that highly creative work is produced by those who have strong intrinsic motivation to engage in an activity [1], [2]. Whether the motive is intrinsic or extrinsic is a topic for discussion. An extrinsic motive is a stimulus from the outside (i.e., from an external source, e.g., a reward), which leads to humans channeling all their activities toward a particular goal. An intrinsic motive is an inner motive (i.e., from an internal source) that is responsible for human (personal) behavior, spanning from the bionic level, for example, “hun-ger,” to a higher cognitive level, for example, an artist’s “flow” (a state of concentration or complete absorption with the activity at hand and the situation) [10]. The function of intrinsic and extrinsic motivation involves a reciprocal action in individuals. Intrinsic motive is believed to play an important role in design insight.

Although it is highly difficult to directly understand the nature of the in-trinsic motive, we can discuss it theoretically to a certain extent from the viewpoint of its potential to promote the design process. Let us consider the paradigm model presented in Fig. 5. This process is illustrated by the arrows in the right-hand side figure in Fig. 15.

Mathematically, the movement in Fig. 5 can be modeled as the neigh-borhood searching process in a topological space, as shown in Fig. 15 [39].

In GDT, the concept (entity) is modeled as an element, and the function and attribute are modeled as a class (subset of elements) in set theory, as introduced in the previous section. The concept-forming process is mod-eled as the process of finding an element. Furthermore, the process of syn-thesizing two concepts is modeled as the process of finding the intersection


of the two classes corresponding to each concept. Let us name these classes A (for example, color is red) and B (for example, shape is round) (Fig. 16).

Fig. 15 Paradigm model for neighborhood searching

Fig. 16 Development of design space

The condition of topological space can promote the process of synthe-sizing concepts up to a particular point; that is, the intersection of two con-cepts (A B) (red and round) is defined in topological space. A new con-


cept (red ball) can be recognized and created in this intersection. However, the neighborhood searching process given in Fig. 15 cannot be induced merely with this condition. In order for such a neighborhood process to be recognized, the space must be a mathematically separated space. That is,

BA! (non-red and round) and BA! (red and non-round) must be de-fined. According to the discussion of GDT, the ideal design space is de-fined as one wherein all the elements of the entity set are known and each element can be described by abstract concepts without ambiguity. The ideal design space is found to be a Hausdorff space, which is a separated space, where, for example, a red pencil (red and non-round) can be distin-guished from a red ball (red and round). Furthermore, the condition of separated space enables the design space to be a metric one, which is the basis of the conservation of the similarity between spaces. This discussion suggests that the formation of the ideal design knowledge, which implies the notion of differentia due to the mathematical nature of separated space, generates a potential to promote the design process.

Whether the intrinsic motive is coherent or noncoherent can be another topic in the discussion on intrinsic motive.

Conceptual coherence has been explained by using connectionist mod-els, such as impression formation of people (IMP), and is classified into two types: coherence driven and incoherence driven [45]. Based on the as-sumption that every concept possesses a network of associated concepts, abstract relations, and constraints, an attempt can be made toward deter-mining the relationships among the associated concepts, which then form the knowledge of the world (as in the case of IMP). Then, the problem of “how people select the appropriate relations in framing conceptual combi-nations” can be expressed using a coherence-based computational model. It can be said that the selection of the relation of the connection itself is a driving force behind the formation of networks, that is, the coherence-driven process.

GDT, as discussed above, is considered to be a case of the coherence-driven process.

However, “incoherence-driven conceptual combination” is distinguished from “coherence-driven conceptual combination,” from the perspective of creativity. As indicated by Thagard, creative thoughts such as abductive inferences occur when a solution to a mundane problem cannot be ob-tained and leaps beyond the coherence-driven process and necessitates constraint-satisfying reconciliation. Thagard suggested that the high poten-tial of incoherence-driven creativity is “beyond” the coherence-driven process.


As explained in the previous section, abductive criteria can be converted into deductive criteria in certain cases, and this conversion entails the pos-sibility that certain incoherence-driven processes are captured as coher-ence-driven processes.

Discussion on the creative design process and design creativity

Based on the above discussions, we classify the design process into the following three categories (Table 2).

The artistic design process refers to the viewing of design as an art, and it focuses on representing the inner feelings of the artist. Thus, the artistic design process is closely related to design insight.

Table 2 Classification of the types of design processes

Criteria (1) Criteria (2) Motive

Class 1: Artistic design process

Abductive Inner Intrinsic

Class 2: Creative design process

Abductive and Deductive

Inner and Outer Intrinsic

Class 3: Systematic design process

Deductive Outer Extrinsic

The systematic design process is a type of problem-solving process in

which a problem is solved by the pull-type driving force, which stems from the external environment of the designer.

The creative design process is a combination of the artistic and sys-tematic design processes. Design is a social activity; it is not only related to the user but is also associated with culture or society. On the other hand, it is important to represent the inner feelings of the designer. Therefore, an ideal design process is one that not only involves representing the inner feelings of the designer but also fulfilling the request of the user or satisfy-ing the demands of society. We define this design process as the creative design process and the nature of this process as design creativity. Its im-portant function is that it must change the viewpoint of the outer and inner criteria as well as that of the abductive and deductive criteria while inter-nalizing the extrinsic motive and making it intrinsic. Generally, creativity in design is considered to be evaluated by originality (novelty) and practi-


cality (utility) [13]. With regard to the creativity in design, based on the above discussion in this article, we would like to stress that “novelty” does not involve the notion of “strangeness”; rather, it must be one that resonates with that which comes from the integration of “push-type” and “pull-type” driving forces. From this viewpoint, we capture the essence of design creativity in the integration of the “abductive/inner criteria and in-trinsic motive” and the “deductive/inductive/outer criteria and extrinsic motive” as well as the perspective on the differentia. We believe that this integration is difficult, and a key element of design creativity lies in this difficulty.

Studying design creativity

Based on the abovementioned discussions, we systematize the methods for studying design creativity. The methods can be organized as shown in Ta-ble 3, which refers to the relevant papers.

Table 3 Types of methods for studying design creativity

Criteria (1) Criteria (2) Motive

Deductive Inductive

Abductive Outer Inner Extrinsic Intrinsic

Extended Protocol Analysis

[25], [26], [42] [41] [41] x x Observing

Query-answer Space Strain [38]

x x

Mathematical [44] x [39] Modeling Computer Simula-tion

[44] x x

Here, “space strain,” which is not explained in this article, is a study in which the resulting strain of the design space when synthesizing two con-cepts was observed. Before and after the design experiment of synthesizing the two base concepts, the subjects were asked to answer queries related to the similarity-dissimilarity between one base concept and the concepts re-lated to the other base concept. As a result, after the process of synthesiz-ing two base concepts, it was observed that the distance between the two base concepts was reduced. Since the obtained results appear to be useful for discussing design insight, the method developed to measure the strain of design space is added for studying design creativity.


In this table, “x” signifies the possibility of the application of a particu-lar method for studying design creativity.

As a result, it is shown that the mathematical modeling, computer simu-lation, and the extended protocol analysis method are effective for study-ing design insight that is an essential constitution of design creativity, in particular by finding the notion of “differentia” to be a key factor in the design process; it is rather difficult to find it by using other methods.

Conclusion and future extension

In this article, we illustrated that design insight comprises three view-points: perspective, criteria, and motive. Particularly, it was discussed that the perspective on differentia, abductive and inner criteria, and intrinsic motive are related with design insight.

Based on these discussions, we were able to classify the design process into three categories: artistic, creative, and systematic; the creative design process is defined as the combination of the artistic and systematic design processes, and design creativity is defined as the nature of the creative des-ign process.

Furthermore, we revealed that the notion of differentia is a key factor for the design process, which could be confirmed in all the three view-points, namely, perspective, criteria, and motive.

Based on the above discussions, we systematized the methods for study-ing design creativity. Specifically, we were able to verify mathematical modeling, computer simulation and the extended protocol analysis method, through which the notion of differentia was found to be a key factor in the design process; however, it is rather difficult to study it using other meth-ods.

Since the essence of design creativity exists deep inside the mind of the designer, we assume that another effective method for capturing the es-sence of design creativity is to permit the researcher to experience the des-ign process. However, the conventional introspection method was criti-cized for its lack of objectivity; therefore, merely permitting the researcher to experience the design process cannot constitute a scientific method. It is expected that an extended introspection method will be developed in the future.


References

1. Amabile TA (1996) Creativity in context: update to the social psychology of creativity, Westview

2. Amabile TA (1988) A mode of creativity and innovation in organization. Re-search in Organization Behavior 10: 123-167

3. Asimow M (1962) Introduction to design, Prentice-Hall 4. Bonnardel N, Marmeche E (2004) Evocation processes by novice and expert

designers: towards stimulating analogical thinking. Creativity and Innovation Management 13(3): 176–186

5. Casakin H (2004) Visual analogy as cognitive strategy in the design process. Journal of Design Research 4(2)

6. Chakrabarti A, Bligh TP (1994) Functional synthesis of solution-concepts in mechanical conceptual design. Research in Engineering Design 6(3): 127-141

7. Chakrabarti A, Langdon P, Liu Y-C, Bligh TP (2002) Supporting composi-tional synthesis on computers, engineering design synthesis: understanding, approaches and tools, Springer Verlag

8. Collins COBUILD on CD-ROM, ver.3.1, Lingea s.r.o, (2001) 9. Csikszentmihalyi M (1997) Finding flow: The psychology of engagement

with everyday life, Basic Books 10. Csikszentmihalyi M (1988) Motivation and creativity, toward a synthesis of

structural and energistic approaches to cognition. New Ideas in Psychology 6(2): 159-176

11. Dong A (2006) Concept formation as knowledge accumulation, artificial in-telligence for engineering design, analysis and manufacturing, Cambridge University Press: 35-53

12. Fauconnier G (1997) Mappings in thought and language, Cambridge Univer-sity Press

13. Finke RA, Ward TB, Smith SM (1992) Creative cognition, MIT Press Cam-bridge

14. Gero JS, Kannengiesser U (2007) An ontology of situated design teams, AIEDAM 21(3): 297-310

15. Gero SJ, Kazakov V (1998) Using analogy to extend the behavior state space in design. In JS Gero and ML Maher (eds), Computational models of crea-tive design IV: 113-143

16. Gero JS, Fujii H (2000) A computational framework for concept formation in a situated design agent. Knowledge-Based Systems 13(6): 361-368

17. Gero SJ, Maher ML (1991) Mutation and analogy to support creativity in computer-aided design. In GN Schmitt (ed), CAAD Futures ’91, ETH, Zu-rich: 241-249

18. Goldschmidt G (1999) Visual analogy, a strategy for design reasoning and learning. In C Eastman, W McCacken, and W Newsletter (eds), Design knowing and learning: cognition in design education, Avebury: 53-74


19. Hatchuel A, Le Masson P, Weil B (2004) C-K theory in practice, lessons from industrial applications, Proceedings of DESIGN2004, Dubrovnik: CD-ROM

20. Jin Y, Chusilp P (2006) Study of mental iteration in different design situa-tions. Design Studies, Elsevier, 27(1): 25-55

21. Jones S (1984) A method of systematic design. In N Cross (ed), Develop-ments in design methodology, Jone Wiley & Sons

22. Kim MH, Kim YS, Lee HS, Park JA (2007) An underlying cognitive aspect of design creativity: limited commitment mode control strategy. Design Studies 28(6): 585-604

23. Maher ML, Poon J (1996) Modelling design exploration as co-evolution. Special Issues of Microcomputers in Civil Engineering on Evolutionary Sys-tems in Design 3(3): 167-196

24. Markman AB, Wisnieski EJ (1997) Similar and different: the differentiation of basic-level categories. Journal of Experimental Psychology: Language, Memory & Cognition, 35: 54-70

25. Nagai Y, Taura T (2006) Formal description of conceptual synthesizing process for creative design. In JS Gero (ed), Design computing and cognition ‘06, Springer: 443-460

26. Nagai Y, Taura T (2006) Role of action concepts in creative design process. In Y-S Kim (ed), Symposium International Design Research Symposium 2006: 257-267

27. Nagai Y, Mukai F, Taura T (2008) Concept Blending and dissimilarity: fac-tors for creative design process—a comparison between the linguistic inter-pretation process and design process, Proceedings of DRS2008: CD-ROM

28. Norman D (2007) The design of future things, Basic Books 29. Oxman R (1999) The mind in design, a conceptual framework for cognition

in design education. In C Eastman, W McCacken, and W Newsletter (eds), Design knowing and learning: cognition in design education, Avebury: 269-296

30. Pahl G, Beitz W (1988) Engineering design—a systematic approach, Springer-Verlag

31. Roozenburg NFM, Eekels J (1991) Product design: fundamentals and meth-ods. Chichester: John Wiley & Sons

32. Shah JJ, Kulkarni SV, Vargas-Hernandez N (2000) Evaluation of idea gen-eration methods for conceptual design: effectiveness metrics and design of experiments. Journal of Mechanical Design 122(4): 377-384

33. Schon DA (1987) Educating the reflective practitioner, Jossey-Bass 34. Shoben EJ, Gagne CL (1997) Thematic relation and the creation of com-

bined concepts. In TB Ward, SM Smith, J Vaid (eds), Creative thought, American Psychological Association, Part I

35. Simina M, Kolodner JL (1997) Creative design: reasoning and understand-ing, case-based reasoning, research and development, ICCBR97

36. Sosa R, Gero JS (2005) A computational study of creativity in design, AIEDAM 19(4): 229-244


37. Sternberg R, Davidson JE (1999) Insight. In Runco MA and Pritzer, S (eds), Encyclopedia of creativity (Vol. II), Academic Press: 57-69.

38. Takeuchi Y, Nagai Y, Taura T (2005) Transformation of concept space in design thinking, Proceedings of the 1st International Design Congress IASDR 2005: CD-ROM

39. Taura T, Yoshikawa H (1992) A metric space for intelligent CAD, Intelligent Computer Aided Design, Proceedings of the IFIP WG5.2 Working Confer-ence on Intelligent CAD 91, North-Holland: 33-157

40. Taura T (1995) Design science for functional design process modeling. Pro-ceedings of the 10th International Conference on Engineering Design—ICED95-: 456-464

41. Taura T, Yoshimi T, Ikai T (2002) Study on gazing points in design situa-tion—a proposal and practice of an analytical method based on the explana-tion of design activities. Design Studies 23(2): 165-185

42. Taura T, Nagai Y and Tanaka S (2005) Design space blending, Proceedings of ICED 2005: 14th International Conference on Engineering: CD-ROM

43. Taura T, Nagai Y, Morita J, Takeuchi T (2007) A study on design creative process focused on concept combination types in comparison with linguistic interpretation process, Proceedings of ICED2007: CD-ROM

44. Taura T (2008) A solution to the back and forth problem in the design space forming process—a method to convert time issue to space issue. Artifact 2(3), to appear

45. Thagard P (1997) Coherent and creative conceptual combinations. In TB Ward, SM Smith, J Vaid (eds), Creative thought, American Psychological Association: 129-141

46. Wilkenfeld MJ, Ward TB (2001) Similarity and emergence in conceptual combination. Journal of Memory and Language 45: 21-38

47. Winograd T, Flores F (1986) Understanding computers and cognition—a new foundation for Design, Norwood

48. Wisniewski EJ (1996) Construal and similarity in conceptual combination. Journal of Memory and Language 35: 434-453

49. Wu Z, Duffy AHB (2004) Modeling collective learning in design. Artificial Intelligence for Engineering Design, Analysis, and Manufacturing 18: 289-313

50. Yoshikawa H (1981) General design theory and a CAD System. In Sata & Warman (eds), Man-Machine Communication in CAD/CAM, Proceedings of the IFIP WG5.2-5.3 Working Conference 1980 (Tokyo): 35-57

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