This Text Is A Postprint Of Visser W (2009)

this text is a post-print of: visser, w. (2009). design: one, but in different forms. design studies, 30(3), 187-223. see linkinghub.els

This text is a Post-print of:
Visser, W. (2009). Design: one, but in different forms. Design
Studies, 30(3), 187-223.
see linkinghub.elsevier.com/retrieve/pii/S0142694X08001051
doi:10.1016/j.destud.2008.11.004
Design: One, but in different forms
Willemien Visser
INRIA Paris - Rocquencourt; CNRS LTCI; TELECOM ParisTech
46, rue Barrault
75634 Paris Cedex 13
France
tel: + 33 (0)1 45 81 83 19
fax:+ 33 (0)1 45 65 95 15
email: [email protected]
Abstract. This overview paper defends an augmented cognitively
oriented generic-design hypothesis: there are both significant
similarities between the design activities implemented in different
situations and crucial differences between these and other cognitive
activities; yet, characteristics of a design situation (related to the
design process, the designers, and the artefact) introduce
specificities in the corresponding cognitive activities and structures
that are used, and in the resulting designs. We thus augment the
classical generic-design hypothesis with that of different forms of
designing. We review the data available in the cognitive design
research literature and propose a series of candidates underlying such
forms of design, outlining a number of directions requiring further
elaboration.
Keywords. cognitive design research; generic design; psychology of
design; design activity; design cognition
This paper is a first step in an endeavour to assert an augmented
generic-design hypothesis (which concluded our book, The Cognitive
Artifacts of Designing, Visser, 2006b): analysed from a cognitive
viewpoint, design has specific characteristics that distinguish it
from other cognitive activities, but also takes on different forms
depending on the main dimensions of the design situation. Examination
of this hypothesis, which is the object of this paper, may have
consequences for both theory and practice in the domain of design.
Support for the hypothesis may have consequences for design
environments, assistance, and education. It may, for example, guide
the development of modalities for supporting designers when they are
involved in the construction of representations or in the management
of constraints and criteria. Given the mostly dispersed and anecdotal
discussion of the different components that make up the hypothesis,
our aim here is to articulate them in an overview paper.
Reviewing various empirical studies of activities "as diverse as
software design, architectural design, naming and letter-writing,"
Thomas and Carroll (1979/1984) stated that these different design
activities "appear to have much in common" (p. 234). A number of
authors have defended that, compared to other professionals, designers
have specific forms of knowledge (e.g., Cross, 2001b; 2002b ).
Combining the positions underlying these two claims, Goel and Pirolli
(1989; 1992) proposed the notion "generic design." Still other
studies focus on the differences between design in different domains,
examining a third aspect in this analysis concerning the nature of
design (e.g., Akin, 2001; Purcell & Gero, 1996). In this paper we
review and discuss these different aspects of design, focussing on the
third one, whose discussion seems the least organised in the design
literature. The position defended in this paper is the following:
there are both (1) significant similarities between the design
activities implemented in different situations and (2) significant
differences between design and other cognitive activities; yet, (3)
characteristics of a design situation (i.e., characteristics related
to the design process, the designers, and the artefact) introduce
specificities in the corresponding cognitive activities and structures
that are used, and in the resulting designs. We thus augment the
generic-design hypothesis (1 and 2) with that of different forms of
designing (3).
The augmented generic-design hypothesis thus connects three different
positions with respect to design and nondesign activities that have
been espoused, more or less explicitly, by different authors in the
domain of cognitive design research. Given the implicitness to this
respect that is present in many papers on design, the review and
discussion proposed in this paper seem useful. Generally, papers are
concerned with only one position, sometimes two (the generic-design
hypothesis), but the three have rarely been articulated together (but
see Akin, 2001, discussed below). In addition, corroboration of the
generic-design hypothesis is nearly exclusively grounded in Goel and
Pirolli's (1989; 1992) work. Except for these authors' research,
this double-sided hypothesis has received little substantiation
through comparative cognitive analyses.
We qualify our hypothesis as "cognitive," because in the literature
the term "generic design" most often is used in other than cognitive
acceptations. The notion is used in the domains of software
engineering (cf. Gamma's design patterns), AI and knowledge
acquisition (e.g., KADS and successor work), based, for example, on
Chandrasekaran's (1983) "generic tasks," or notions such as "generic
design methods" and other "generic design agents" (see, e.g.,
Warfield, 1994). All these references are normatively based
approaches to design, not concerned with the cognitive validity of the
proposed units, be they design patterns, tasks, or methods. The
present text focuses on cognitively oriented analyses of design
activities.
Outline of the paper. This introduction presents our augmented
generic-design hypothesis in the context of Goel and Pirolli's
(1992) generic-design hypothesis and the view of design's domain
independence defended by several other authors. Sections 1 and 2
briefly discuss the two constituents of the generic-design hypothesis,
that is, the existence of commonalities between designing in different
situations (section 1) and differences between designing and
nondesigning (section 2). In the main section of this paper, that is,
section 3, we discuss the third constituent of our hypothesis (that
is, design takes different forms depending on characteristics of the
design situation); we do so through an examination of candidate
variables underlying such forms of design, outlining a number of
directions for further elaboration. In section 4, the Conclusion, we
will discuss the augmented generic-design hypothesis and complete it
with a fourth constituent.
The generic-design hypothesis. Goel and Pirolli (1992) formulated
their "intuitions about generic design" as a hypothesis that combined
two assumptions: "problem spaces exhibit major invariants across
design problem-solving situations and major variants across design and
nondesign problem-solving situations" (p. 399). According to Goel
(1994), the authors aim to "motivate the notion of generic design
within information-processing theory" (p. 53), that is, within the
symbolic information processing framework that Newell and Simon
(1972) developed in order to analyse problem solving from a
cognitive viewpoint.
Goel and Pirolli (1989; 1992) seem to have made a strong case for
the generic-design hypothesis. Their study may, however, be criticised
on two points. On the one hand, certain flaws in the choice of
nondesign tasks considerably weaken the authors' characterisation of
design—which mainly depends on its contrast to nondesign (design is
qualified as "X" by contrast to nondesign being "not X"). First, the
nondesign tasks were brief, artificial games (that took 15 to 40
minutes). Second—something, moreover, noticed by the authors
themselves—the study "purposefully took two points (ill-structured
design tasks and well-structured game tasks) at the extremities of the
spectrum of problem types" (Goel, 1994, p. 71). The author considers
that, "given that [Goel and Pirolli] have found interesting
differences, it would be instructive to… explore the intermittent
points in the space" (Goel, 1994, p. 71), but this examination has
not been conducted, as far as we know. On the other hand, the design
tasks were examined in artificially restricted laboratory situations.
The participants in Goel and Pirolli's (1989; 1992) study were
professionals, but the design sessions, varying from 2 to 3 hours,
"simulated the 'design sketch' exercises which are an integral part of
the training program of many design disciplines" (Goel, 1994, p.
54)—tasks from which generalisation to design is not immediate, in
our opinion. Such an approach is typical for the classical
cognitive-psychology research on "problem solving" tasks. Since the
beginning of our cognitive design research, we have been questioning
the representativeness of such studies for professional design
projects (in Visser, 1987b, for example, we identified specificities
of professional design that are not observed in limited, artificially
constructed design situations). In addition, we have come to question
the appropriateness of the "problem solving" paradigm for the
cognitive analysis of design (Visser, 2006b). The present paper
focuses on cognitive design studies performed in real, professional
work situations—even if we also review data from other experimental,
less ecological research that is related to our topic. We will use,
however, the notion "problem" and "problem solving" as authors use
them, not always again questioning this view here.
The domain independence of design. Zimring and Craig (2001) present
the "domain independence" of design as a notion similar to that of
generic design. One may interpret domain independence, however, as
only referring to design being invariant across domains, not
necessarily to design differing significantly from other cognitive
activities. It is in this more restricted sense that many design
researchers and practitioners defend the idea of a domain-independent
theory of design. Certain authors indeed defend such a position
because of similarities observed between two or more domains of
design.
Zimring and Craig (2001) consider that "common descriptions of
design—that designing involves abductive reasoning, construction,
ill-defined problem solving skills—…are not always sharp enough to
both distinguish design from other types of problem solving and unite
design across different design-related disciplines" (p. 125). The
authors consider that the analysis and description of design in terms
of "mid-level constructs" "may be more profitable in scaling research
across disciplines" (p. 126). As examples of mid-level processes or
types of reasoning, the authors present mental simulation,
decision-making, and analogical reasoning.
During the 1995 "Design Dialogues: one" meeting, entitled "Universal
Theory of Design: is a domain independent theory of design possible?"1
the participants explored "the reasons for the apparent lack of
progress in design research over [the decade 1985-1995] and in
particular whether the search for an atemporal, acultural, domain
independent theory of design [was] a reasonable or realistic goal."
During this meeting, Cross stated, "a primary goal of the Design
Research Society since its founding in the 1960s [had] been a domain
independent theory of design within the context of a science of
design" (from the Meeting report, see Note 1). In her Meeting report,
McDonnell wrote, "on the question of whether theories, of whatever
kind, can be domain independent, there was a… diversity of views.…
some participants believing that some form of universal theory is
possible ranged against those who argued for the incommensurability of
different views of design or that the elimination of context necessary
for a universal theory would result in an activity unrecognisable as
design."
There has been much discussion in the design-research community around
the relations between design and science (Sargent, 1994), some
authors considering that a design science is to be developed (Hubka &
Eder, 1987), others, such as Cross (2001b; 2002b), judging that the
two are to be clearly distinguished. For Hubka and Eder (1987),
"design science addresses the problem of determining and categorizing
all regular phenomena of the systems to be designed, and of the design
process" (p. 124). Cross (2002b) wishes to develop "'design as a
discipline', based upon a 'science of design', not a 'design science'"
(cf. also Simon, 1969/1999, characterising the "science of design" in
his Sciences of the Artificial). For Cross (2002b), "design science
implies an explicitly organised, rational and wholly systematic
approach to design; not just the utilisation of scientific knowledge
of artefacts, but design in some sense [as] a scientific activity
itself.… Science of design refers to that body of work which attempts
to improve our understanding of design through 'scientific' (i.e.,
systematic, reliable) methods of investigation. Let us be clear that a
'science of design' is not the same as a 'design science'. The study
of design leaves open the interpretation of the nature of design."
(see also Cross, 2001b)
"Domain" in the context of "domain independence" is generally equated
with a "discipline (of practice)," such as engineering, architecture,
computer science, or product design2. It may be used in a wider
acceptation. Discussing domain-generality versus domain-specificity in
cognition, Frensch and Buchner (1999, p. 142, quoted in Zimring &
Craig, 2001, p. 126) define a domain as "anything that a given
constraint can potentially be generalized to and from." In this paper,
we will be concerned with design "situations" that can be
characterised on three main dimensions, that is, the design process,
the designers, and the artefact. The augmented generic-design
hypothesis translates our claim that, if we do not "eliminate the
context" of design (cf. McDonnell quoted previously), we may observe
different forms of design in different design situations.
1. Design is one: commonalities between designing in different
situations
==============================================================
From the early 1980s on, authors in the domain of design research have
started to characterise design as a cognitive activity, highlighting
the differences from design as it had been represented until then in
prescriptive models underlying design methods (e.g., Pahl & Beitz,
1977/1996). An important reference for this new, more cognitively
oriented approach to design has been Simon's (1969/1999) analysis of
design in The Sciences of the Artificial. At the end of the 1990s, the
following characterisation of design was prevailing in the domain of
cognitive design research—even if authors may differ regarding certain
characteristics (see hereunder xi. Design activity is mostly
opportunistically organised). Concerning only two qualities, authors
generally continue to adhere strictly to Simon's (1969/1999)
position and analysis of design (see hereunder i and v). For most
characteristics, authors have elaborated on Simon's characterisation,
not so much contradicting him, as extending generally his analysis
(see hereunder, especially, points iii, vi, vii, viii, ix, and x). For
a last series, they have revised considerably Simon's position (see
hereunder, especially, points ii, iv, and xi) (for a more detailed
and more critical discussion of Simon's, 1969/1999, positions, see
Visser, 2006b).
i.
Design is a type of cognitive activity rather than a professional
status. In 1969, Simon (1969/1999) states that "design" is not
restricted to engineers, who are not the only professional
designers. "Everyone designs who devises courses of action aimed
at changing existing situations into preferred ones." (p. 111)
ii.
Design is a problem-solving activity. This is one of Simon's
central stances with respect to design, based on the symbolic
information-processing framework developed in Newell and Simon
(1972). In addition, Simon qualifies design as an "ordinary"
problem-solving activity, that is, a problem-solving activity for
which no new and hitherto unknown problem-solving concepts or
techniques are necessary. According to his "nothing special"
position (presented for scientific thinking in Klahr & Simon,
2001, p. 76), "no qualitatively new components" need to be
introduced in the classic general problem‑solving mechanisms, in
order to be able to handle design problems (Simon, 1973/1984, p.
197). No "special logic" is necessary (Simon, 1969/1999, p.
115)—even if Simon "admits" that standard logic is to be adapted
to the search for alternative solution elements (p. 124). In
recent years, we have started to amend Simon's (1969/1999)
position: we have developed the idea that designing is more
appropriately qualified as the construction of representations
(Visser, 2006b, 2006c). From a formal viewpoint, design is
certainly a "problem solving" activity: based on the design
specifications, designers are rarely able to evoke from memory a
pre-existing problem-solving procedure. Numerous studies have
shown that, for many components of a design task, designers need
to construct procedures in order to formulate a solution. However,
qualifying design "simply" as problem solving is not very
informative. In this paper, we cannot further detail these ideas
(see Visser, 2006b).
iii.
Design problems are considered ill-defined (or "ill-structured"
in Simon's, 1973/1984, terms): this design feature, noticed from
the earliest cognitive design studies on (Eastman, 1969, 1970;
Reitman, 1964; Thomas & Carroll, 1979/1984; Voss & Post, 1988),
has been substantiated in many different kinds of studies since
then, and continues to be considered as a specific characteristic
of design (Akin, 2001; Michalek & Papalambros, 2002; Ormerod,
2005). Rittel and Webber (1973/1984) speak of "wicked"
problems, which have no definitive formulation: each formulation
corresponds to at least one solution (Buckingham Shum, 1997;
Conklin, 2006) (for a discussion of the distinction between
ill-defined and wicked problems, see Visser, 2006b, p. 142).
iv.
In his problem-solving approach to design, Simon (1969/1999;
1973/1984) distinguishes two stages in problem solving: problem
structuring and problem solving. Analysis, synthesis, and
evaluation are examples of another decomposition of design
proposed by authors adopting, with more or less profound
modifications, Simon's approach to design—or, more generally,
Newell and Simon's (1972) approach (Akin, 1986a, 1986b; Baykan,
1996; Goel, 1994; Goel & Pirolli, 1992; Hamel, 1995; Lebahar,
1983). However, such stages can be distinguished only in theory
as distinct activities: problem analysis and solution elaboration
progress in parallel, rather than in separate, consecutive stages.
Furthermore, designers constantly generate new task goals and
redefine task constraints. Even if they are cognisant of
prescriptive models distinguishing analysis and synthesis,
designers do not follow them systematically (Akin, 1979/1984;
Carroll & Rosson, 1985; Cross, 1984; Dasgupta, 1989; Visser,
1987a). Authors who analyse design problem solving in terms of
"problem space" and "solution space" have proposed the notion of
"co-evolution" of these two spaces (Dorst & Cross, 2001; Maher,
Poon, & Boulanger, 1996; cf. also our idea of problem/solution
pairs, Visser, 1991).
v.
Design is a "satisficing" activity: rather than to optimize, that
is, to calculate the optimum value, or to choose the best solution
among all possible solutions, designers "settle for the good
enough" (Simon, 1971/1975, p. 1), accepting a satisfactory
solution (Simon, 1987/1995, p. 246). As they have to decide
without complete information, they have no other choice. This
characteristic has been observed by various authors (Akin, 2001;
Ball, Lambell, Reed, & Reid, 2001). According to Akin (2001),
however, designers from different disciplines vary on this point:
while architects indeed proceed to satisficing, engineering
designers adopt more objective methods in their selection among
possibilities and may proceed to optimisation.
vi.
Design generally involves complex problems that are rarely
decomposable into independent subproblems. Of course, designers
proceed to decomposition, in order to make their problems more
manageable and easier to solve. In our view, Simon and many design
researchers who follow him overestimate, however, the role of
systematic problem decomposition, especially through balanced,
stepwise refinement. In other than relatively routine design
projects, designers rarely decompose in a systematic way (cf. our
critique of Simon's "overestimating the role of systematic problem
decomposition," Visser, 2006b, pp. 68-70). Moreover, one and the
same design component often can be decomposed in different ways
(Reitman, 1964, p. 296). Simon himself notes that the
interdependencies among the subproblems resulting from problem
decomposition "are likely to be neglected or underemphasized."
"Such unwanted side effects accompany all design processes that
are as complex as the architectural ones" that he considers in his
text (Simon, 1973/1984, p. 191). According to Akin (2001),
architects use idiosyncratic strategies to decompose a problem
into subproblems and to integrate their solutions into a global
solution afterwards, whereas in electronic hardware or mechanical
design, the interaction between the parts are "theoretically
determined." Notice that Simon (1973/1984, pp. 200-201) analyses
complex systems such as social systems as "nearly decomposable"
and that Goel (1995) considers the modules resulting from
decomposition as "leaky."
vii.
Designers often tend to generate, at the very start of a project,
a few simple objectives in order to create an initial solution
kernel to which they then are sticking in what is going to become
their global design solution. Such an initial solution kernel,
which Darke (1979/1984) qualified as "primary generator," has
been identified by many other authors and has received labels such
as "kernel idea," "central concept," "early solution conjecture,"
"primary position," and "guiding theme" (Cross, 2001a, 2004b;
Guindon, Krasner, & Curtis, 1987; Kant, 1985; Lawson, 1994; Rowe,
1987; Ullman, Dietterich, & Staufer, 1988). The ensuing process
has been qualified as "position-driven" design, "early fixation,"
"premature commitment," "early crystallisation," or "solution
fixation" (Ball, Evans, & Dennis, 1994; Cross, 2001a; Goel,
1995) (we will come back upon this characteristic, arguing that
it requires inspection).
viii.
Rather than one solution, which would be "the" "correct" solution,
design problems have several, acceptable solutions, which are more
or less satisfying. This characteristic of design problems,
related to their ill definedness and the satisficing character of
designing, has been observed in many studies and domains, for
example, architecture (Akin, 2001; Eastman, 1970), mechanical
design (Frankenberger & Badke-Schaub, 1999), software design
(Malhotra, Thomas, Carroll, & Miller, 1980), and traffic-signal
setting (Bisseret, Figeac-Letang, & Falzon, 1988).
ix.
Design problems and solutions lack pre-existing, objective
evaluation criteria (Bonnardel, 1991; Ullman et al., 1988). As
evaluative references are forms of knowledge, designers' expertise
in a domain influences how they use them (D'Astous, Détienne,
Visser, & Robillard, 2004). Given that, in a collaborative design
setting, designers may have different representations of their
project, solution proposals are evaluated not only based on purely
technical, "objective" evaluative criteria; they are also the
object of negotiation, and the final agreement concerning a
solution often results from compromises between designers
(Martin, Détienne, & Lavigne, 2001). In addition, not only
solution proposals, but also the evaluation criteria and
procedures themselves undergo evaluation (D'Astous et al.,
2004).
x.
Reuse of knowledge (from specific previous design projects)
through analogical reasoning has been observed in many cognitive
design studies as a central approach in design (Ball &
Christensen, 2007; Ball, Ormerod, & Morley, 2004; Bhatta & Goel,
1997; Burkhardt, Détienne, & Wiedenbeck, 1997; Casakin &
Goldschmidt, 1999; Détienne, 2002; Maiden, 1991; Sutcliffe &
Maiden, 1991; Visser, 1995, 1996). Of course, this use of
specific knowledge is combined with that of generic knowledge
(especially, from design methodology, the application domain, and
the technical domains that underlie the design project). Most
examples of reuse concern software design (Détienne, 2002;
Visser, 1987b), but we also observed it on product design (in
the Delft study, Visser, 1995).
xi.
Design activity is mostly opportunistically organised: designers
proceed in a non-systematic, multidirectional way (at moments
top-down, at others bottom-up, at moments in breadth, at others in
depth), formulating plans that are more or less local, at both
high, abstract and low, concrete levels. The basis for such
organisation is designers taking into consideration the data that
they have at the time: specifically, the state of their design in
progress, their representation of this design, the information at
their disposal, and their knowledge (cf. the qualification of
design as "situated").
This last point needs some discussion, because not all researchers
share our conclusion that design is opportunistically organised
(for a detailed discussion, see ch. 21.4 The opportunistic
organization of design: Decomposition and planning, and especially
its section "Discussion of our opportunistic-organization
position," in Visser, 2006b, pp. 163-177). Especially Davies
(1991) and Ball and Ormerod (1995) adopt other positions.
According to Davies (1991), "expert programmers adopt a broadly
top-down approach to the programming task, at least during its
initial stages" (p. 186; see our discussion of expertise below in
Section 3.2). Ball and Ormerod (1995) claim, "much of what has
been described as opportunistic design behavior appears to reflect
a mix of breadth-first and depth-first modes of solution
development" (p. 131), even if design is also "subject to
potentially diverging influences such as serendipitous events and
design failures" (p. 145). Obviously, designers may proceed
top-down and depth-first, or top-down and breadth-first—or
bottom-up combined with depth-first or breadth-first. What we wish
to emphasise is that (1) they often do so occasionally and
locally, rather than systematically throughout the entire design
process; (2) a top-down - bottom-up mix can take different forms,
and even if a mix pattern has several occurrences—and thus gets a
systematic character—these will generally be interspersed with
other ways of proceeding, so that "top-down" and "bottom-up" are
inappropriate as general qualifications of designers' activity;
and, especially, (3) an occasional, local top-down - bottom-up and
or breadth-first - depth-first mix are just some of the various
forms in which opportunism can reveal itself in design.
As regards the "broadly top-down with opportunistic local
episodes" (Davies, 1991) versus "opportunistic, with
hierarchical episodes" (Visser, 1994a) issue, we follow
Hayes-Roth and Hayes-Roth (1979, p. 307). These authors have
proposed that the systematic refinement model be considered as a
special case of the opportunistic model, which allows various
organisational structures of an activity—rather than only one, or
a mix of two structures. An opportunistically organised activity
may have hierarchical episodes at a local level, but its global
organisation is not hierarchical (Visser, 1994a).
With respect to the structured character of design organisation,
opportunism proponents (Guindon et al., 1987; Kant, 1985; Ullman
et al., 1988; Visser, 1987a; Voss, Greene, Post, & Penner, 1983)
question the systematic implementation both of a depth-first (or
breadth-first) and of a top-down refinement (or bottom-up)
approach.
Notice that Goel (1995), who presents design as a quite
systematic process, also remarks that "designers differ
substantially in the path they take through [the design problem]
space and how quickly or slowly they traverse its various phases"
(p. 123). In addition, he notices that "problem structuring" (in
his model, the first phase of design development) "occurs at the
beginning of the task,… but may also recur periodically as needed"
(p. 114).
These 11 qualifications, based on studies in different application
domains, have contributed much to the development of the position that
there are important commonalities between the implementations of
design in different domains, that is, one of the two components of the
generic-design hypothesis. Despite the more or less implicit adherence
to this hypothesis in the design literature, there has been little
systematic empirical research, however, to corroborate it—that is,
apart from Goel and Pirolli's (1989; 1992) work. In the rest of this
section, we present some rare studies concluding to the existence of
more or less similar features between designing in different
situations.
There is a series of early cognitive design studies conducted by
Carroll and various colleagues in different design disciplines. In
their review of this work, Thomas and Carroll (1979/1984) conclude
that software design, architectural design, naming, and letter writing
have many commonalities (as noticed in our introduction).
Bringing together observations gathered on product design (in the
Delft study, Visser, 1995) and on software design (Visser, 1987b),
we concluded that designers from these two disciplines proceeded to
reuse.
Reymen et al. (2006) have performed empirical case studies in three
design disciplines—architectural, software and mechanical design—in
order to develop domain-independent design knowledge. The authors
conclude that the supposed "important differences" between these
design disciplines "concern mainly differences in terminology" (p.
151). One may notice, however, that the authors did not observe
designers at work. They conducted interviews with designers concerning
particular projects and analysed the documentation of these projects.
In his paper How is a piece of software like a building? Toward
general design theory and methods, Gross (2003) advances the thesis
that these two types of artefacts are alike on several dimensions:
their size, level of complexity, lifetime, and degree to which their
components are subject to change, the proportion of reusable
components in their structure, the sanitary risks and safety concerns
that particular uses or states of these artefacts may introduce, the
type of their use or user, and the differences between their client
and user. However, Gross (2003) does not refer to empirical work. We
will come back to most of these dimensions below.
Notice that in the abovementioned studies, presented in order to show
commonalities between designing in different situations, these
different "situations" were always different domains of
discipline—never different conditions of age, sex, expertise, or
working conditions (e.g., process variables), for example.
2. Design is different from nondesign
=====================================
The idea that design significantly differs from nondesign activities
is stated explicitly less often than its counterpart in the
generic-design hypothesis (that is, that design activities implemented
in different situations are significantly similar). Cross (2001b;
2002b ) contends—as the underlying axiom of the design discipline he
defends— that there are "forms of knowledge special to the
competencies and abilities of a designer." Yet, it is not trivial to
indicate what makes design specific.
Expertise: design versus nondesign. In his overview paper on design
expertise, Cross (2004b) concludes that "expertise in design has
some aspects that are significantly different from expertise in other
fields" (p. 427). Referring to results from several empirical studies,
he observes that the classical depth-first (novices) - breadth-first
(experts) (or top-down - bottom-up) difference is not as
systematically displayed in design as in other problem-solving tasks.
The other main characteristics identified by Cross (2004b) are the
following. A key feature of design expertise is "problem framing,"
that is, structuring and formulating the problem. Expert designers are
solution-focused rather than problem-focused, especially in their
particular domain of expertise (cf. also Lawson's, 1979/1984, results
differentiating students from architecture and science on the
solution-focused - problem-focused dimension). Expert designers
frequently switch between different types of cognitive activity.
Contrary to what is considered "good practice" in design methodology,
they readily commit to an early solution concept that they elaborate,
at all costs, patching it, if necessary: they do so instead of
generating and examining a large number of alternative solution
concepts, and of abandoning their solution concept when confronted
with problems in its development (cf. point vii in Section 1).
Advocating that, from a cognitive viewpoint, design is definitely
different from other activities, Goel and Pirolli (in Goel, 1994;
Goel & Pirolli, 1989) quoted the examples of chess and medical
diagnosis. These were, however, not the nondesign tasks examined by
the authors in order to corroborate their generic-design hypothesis.
To this aim, they compared protocols (collected by Newell & Simon,
1972, and published in their Human Problem Solving) concerning
cryptarithmetic and the Moore-Anderson logic task with protocols the
authors themselves had collected in three design disciplines,
architecture, mechanical engineering, and instructional design (Goel,
1994; Goel & Pirolli, 1989). In their conclusion, the authors notice
that, now that results have been obtained with such extreme
well-structured tasks (cryptarithmetic and the Moore-Anderson logic
task are two perfectly defined play problems), other activities need
to be examined.
In The Sciences of the Artificial, Simon (1969/1999) presents as
different the cognitive activities implemented in economics and in
design. Analysing economic theories, he is very sensitive to the way
in which economists idealise human rationality and neglect its limits.
With respect to design, however, Simon seems to underestimate human
cognitive limitations—something we illustrated in some detail in The
Cognitive Artifacts of Designing (Visser, 2006b).
Several authors discuss differences between design and science (cf.
also our introductory section). According to Archer (1979) "there
exists a designerly way of thinking and communicating that is both
different from scientific and scholarly ways of thinking and
communicating, and as powerful as scientific and scholarly methods of
enquiry when applied to its own kinds of problems" (p. 18). This idea
of "designerly ways of knowing" is further developed by Cross (1982)
(see also Cross, 2006).
Lawson (1979/1984) compared students from architecture and science
(using artificial tasks supposed to represent architectural-design
activities). He observed that the science students analysed their
problems in order to discover their structure, whereas the design
students generated "a sequence of high scoring solutions until one
proved acceptable" (p. 218). Lawson's (1979/1984) conclusion has
constituted one of the bases for distinguishing architects from
scientists, encountered in papers qualifying architects as
"solution-focused" and scientists as "problem-focused" (see also
Kruger & Cross, 2006). Other studies seem to show, however, that a
solution-focused approach is related to one's experience (Cross,
2004b; Lloyd & Scott, 1994).
In addition, various authors perceive elements of similitude between
scientific and design activities. In his analysis of the structure of
design processes, Dasgupta (1989), for example, considers design
problem solving a special instance of scientific discovery. In The
Sciences of the Artificial, Simon (1969/1999) establishes a
correspondence between social design (social planning) and scientific
discovery: they share a type of search, that is, a "search guided by
only the most general heuristics of 'interestingness' or novelty" (p.
162). Cagan, Kotovsky and Simon (2001) point out the cognitive and
computational similarities between the "seemingly disparate
activities" of scientific discovery and inventive engineering design
(p. 442). They notice that highly creative design activities are often
labelled invention. The major conclusion of the authors' comparison is
that, "at a deep level, the cognitive and computational processes that
accomplish [design and discovery] are virtually identical" (Cagan et
al., 2001, p. 463). These underlying cognitive activities are based
on "problem solving, pattern recognition, analogical reasoning, and
other cognitive knowledge retrieval mechanisms" (pp. 452-453). The
authors thus defend, with respect to scientific-discovery and
inventive engineering-design problems, their "nothing special
position" (see point ii in Section 1). They establish, however, a
"fundamental difference" between the two: "the goal of the process:
Scientific explanation versus creation of a new artifact. . . . Design
starts with a desired function and tries to synthesize a device that
produces that function. Science starts with an existing function and
tries to synthesize a mechanism that can plausibly accomplish or
account for that function" (Cagan et al., 2001, p. 455). We do not
share this reserve concerning the goals of the two activities: in our
view, ultimately science (be it discovery or invention) is a design
activity, the artefact aimed here being a theory.
In short, except with respect to expertise, there is little direct
evidence for design differing significantly from nondesign. Indirect
evidence might come from the previous section. Implicitly, our stance
is that the characteristics presented in Section 1 are specific to
design and make design differ from nondesign. However, we cannot refer
to empirical studies that show this.
3. Design is one, but takes different forms
===========================================
The idea that there may be different forms of design has been hinted
at in informal discussions, generally without empirical or theoretical
evidence (Löwgren, 1995; Ullman et al., 1988). Without any such
underpinning, for example, the engineering-design methodologists Hubka
and Eder (1987) assert that "the object of a design activity, what
is being designed… substantially influences the design process." This
assertion expresses a rather generally—more or less
implicitly—accepted idea, that is, that the artefact product,
characterising the design discipline (architecture, mechanical, or
software design) is the variable underlying the differences we are
examining here.
In "Variants in design cognition," Akin (2001) states that "in
different fields of design, cognitive processes have both similarities
and differences" (p. 105). The author focuses on architectural design,
generally contrasting it with engineering design in his paper.
Compared to other designers, architects are more inclined to use (i)
"rich representations," (ii) creative, inventive strategies, (iii)
non-standard problem decomposition schemata, (iv) complexity
management strategies, and (v) search for alternative solutions.
i.
On the basis of his extensive research on architects, Akin
(2001) affirms that these designers use many forms of both
analog and symbolic, "naïve," everyday and physical, technical,
and domain-specific representations.
ii.
Confronting both informal observations and experimental work
(Akin, 1986a) on architects and experimental results concerning
electrical engineering designers obtained by Ball et al. (1997,
quoted in Akin, 2001), Akin (2001) considers as plausible that
"architects tend towards creative design strategies while
engineers tend to routine design." His comparison between the
architects in his Akin (1986a) study producing a richness in
novel solutions to constrained, closed problems, and the engineers
observed by Ball et al. (1997, quoted in Akin, 2001) generating
remarkably low numbers of solutions, leads him to suppose that
"these engineers tend to apply routine-design strategies even when
the problem calls for a novel solution."
iii.
Akin (2001) opposes the conclusion reached by himself and by
colleagues that architects adopt individual decomposition
schemata, to that formulated by research colleagues
(Frankenberger, 1997, and Dörner, 1997, quoted in Akin, 2001)
that mechanical engineers and industrial designers use
standardised schemata. This holds for both the decomposition of
the global design process into design phases and that of a larger
problem into smaller ones.
iv.
For Akin (2001), the way in which designers recompose a
comprehensive design solution from partial ones as an indicator of
the way in which they manage complexity. Based on a study he
conducted in 1994 (referred to in his chapter), Akin (2001)
explains how architects use ad hoc strategies to integrate partial
solutions into global ones. He opposes this approach to the
predetermined procedures that electronic or mechanical designers
use to handle the interaction between the parts of a VLSI circuit
or a mechanical assembly.
v.
Akin (1986a) observed that architects continue their search for
alternative solutions even if they have already formulated a
satisfactory concept. They do not commit themselves prematurely to
an early selected kernel idea, something that is often considered
a general characteristic of designers (cf. characteristic iv in
Section 1).
Concerning the second point: various authors have observed that other
designers than architects—for example, product designers (Dorst &
Cross, 2001; Rodgers, Green, & McGown, 2000; Van der Lugt, 2002)—may
also act in creative, flexible ways (something distinctive for
architects, according to Akin).
Concerning the last point, we have requested more inspection of the
basis for the conclusions about premature commitment that are
generally advanced in the cognitive design research literature
(Visser, 2006b). There are experimental results supporting Ball and
Ormerod's (2000) hypothesis that design induces early fixation on a
kernel idea when designers are working individually and/or in
artificially restricted situations, and that professional designers
collaborating in "natural," real work situations may come up with more
alternative solutions (Visser, 1993a). There are, however, also
studies (1) on teams working in de-contextualised situations that show
designers willing to reconsider early concepts (Smith and Tjandra,
1998, referred to in Cross, 2001a), and (2) on individually working
designers who come up with several solution ideas, (2a) while they are
working in artificially restricted conditions (Eastman, 1969:
bathroom design; Fricke, 1999: engineering design; Whitefield, 1989:
mechanical design), but also (2b) in natural situations (Reitman,
1964: musical composition) (see also Atman, Chimka, Bursic, &
Nachtmann, 1999, quoted in Cross, 2004b). The apparent contradiction
between these observations might be removed in at least two ways.
i.
Designers may aspire—or simply think or declare—to refrain from
premature commitment, but in fact not put these ideas in practice
(see also Malhotra et al., 1980; cf. our observation that
designers' accounts about their activity often do not coincide
with their actual activity, Visser, 1990).
ii.
Early on in the design process, working at a conceptual level,
designers may select a kernel idea, but afterwards they may
refrain from premature commitment at a more concrete or detailed
level, for example, by not fixing all values for its variables.
Purcell and Gero (1996) have observed a difference between
mechanical and product designers as regards their susceptibility to
use features of example designs. In certain situations, mechanical
designers showed "[design] fixation in the traditional sense of
reproducing the characteristics of [an example] design, including
incorrect features" (p. 381). They did so when "the example shown
embodied principles that were typical of the knowledge base of the
discipline" (p. 381). However, when they received innovative design
examples, they seemed to "identify [the core innovative principle
involved in the example] and then explore how this could be used in
the particular design situation" (p. 381), leaving out of the designs
they produced many of the specific aspects of the example. With the
product designers, the fixation effect was completely absent. However,
to produce innovative designs, these designers did not use the
innovative examples either. Maybe they became "fixated" "on being
different" (p. 381); maybe their search was for difference rather than
for innovation (p. 380). The authors suggest two sources for the
observed differences between the designers from the two disciplines.
First, education: that of product designers may emphasize creativity
and the search for many different ideas. Second, the more or less
varying and/or articulated character of knowledge in a domain: "the
areas of knowledge that make up industrial design are more diverse
than those studied in mechanical engineering" (p. 374) and many of
them "are associated with less well articulated bodies of knowledge
than those that make up the knowledge base of mechanical engineering.
For example, aesthetics plays a prominent role in industrial design
education…, while it plays little formal role in mechanical
engineering" (pp. 374-375).
Through several studies of designers from different domains working in
their daily professional situation (software and various types of
mechanical design), we have been able to identify differences between
such professionals working on industrial or other commercial design
projects and design-knowledgeable participants (generally students)
solving design problems in artificially restricted situations
(generally laboratory experiments) (Visser, 1995, 2006b, 2006c).
Three notable differences are the following. (1) In software,
mechanical, or other professional design projects, designers organise
their activity in an opportunistic way, whereas in simpler, more
restricted situations, designers are often able to follow systematic
decompositional approaches (as generally prescribed by normative
methods, e.g. top-down, breadth-first; cf. our discussion above in
Section 1). (2) Reuse of elements from previous projects seems a
specific professional design approach—even if it has also been
observed in experimental research (Détienne, 2002). (3) In our study
of a professional software designer (Visser, 1987b), we noticed that
user considerations were among his guiding principles (leading him,
for example, to adopt certain variable-naming strategies), an
observation that has not been mentioned by researchers studying design
in artificially restricted situations. These observations, which do
not seem specific to a particular domain of design, may point to the
influence that is exerted on the activity of design by (1) design
education, (2) the complexity of a design project, and (3) the design
setting.
In the cognitive design research literature, one frequently encounters
allusions to, or implicit testimonies of the specific character of
software design compared to other types of design (see Visser, 2006b;
2006c for a discussion of these attitudes). Even if design of HCI is
much less the object of discussion in this context, researchers
studying software design or HCI have themselves also contrasted their
domain of research with other domains. The responsible variables
remain, however, unexplored. In their bibliographic cocitation
analysis, Atwood, McCain, and Williams (2002) found that a set of
authors representing Software Engineering design methodologies was
"essentially unconnected with the remainder of the author set" (p.
129). They noticed, "software design has its own design literature"
(p. 132). On the other hand, generic design journals, such as Design
Studies, Design Issues, or The Journal of Design Research rarely
publish papers on software or HCI design. The separation between
software and HCI, and other types of design holds for scientific
events as well. Conferences in the domain of design research concern
either software design and/or HCI (i.e., treated either together or
singly), or other types of design. Of course, there are specialised
conferences in many domains of design, but when they announce, as
their object, "design" without any further specification, conferences
generally do not expect papers on software or HCI (for a list of
example references, see Visser, 2006b, Section. 22.1).
Refining our analysis initiated in Visser (2006b; 2006c) and
continued in Visser (2006a), this paper proposes three dimensions
that we suppose underlie differences between forms of design: the
design process, the designer, and the artefact. Under each of these
dimensions, we propose several variables.
3.1 Process
-----------
Various process-related variables may affect designers' cognitive
structures and activities, and the designs they produce. We identified
the organisation of the design process, the tools used, and the place
of the user in the design process, possibly specified into two or more
variables that are more specific.
3.1.1 The organisation of the design process
The way designers plan to organise their task or the process they are
involved in is liable to influence their activity. Be the organisation
imposed by one's hierarchy, or devised by oneself, it works as other
tools: it not only structures, but also guides people's activity,
through immaterial and material means, such as design methods and
other tools, be they representational, or calculation and simulation
aids (cf. subsection 3.1.2, Tools in use).
The time scale of the design process. Design is considered an off-line
activity. One might thus naively suppose that designers, contrary to,
for example, controllers of dynamic situations, have all their time to
think over their projects, to analyse and change views, to discuss and
confront their opinions with colleagues. The reality is different.
First, most industrial, or other professional design projects
generally take place under temporal constraints. Their stringency,
however, may differ depending on external organisational (due to the
workshop or the client), artefactual, and other factors. Second,
planning—both as a design activity in itself and as a component of
other design activities (Visser, 1994b)—is obviously subject to
temporal variables. Several early empirical studies have examined the
role of temporal constraints in the context of planning, for example,
the famous study on route-plan design by Hayes-Roth and Hayes-Roth
(1979). We will come back to temporal constraints in our discussion
of "designing in space versus designing in time" (section 3.3.3).
Individual versus collective design. Certain artefacts are designed
generally by an individual designer, others are usually the work of a
team. Complexity and size of the artefact (two dimensions mentioned
by Gross, 2003) may play a role in this association, but are
certainly not the only variables. Product design is often performed by
individual designers, whereas many engineering design projects are
conducted collectively—but, of course, these are only tendencies.
We have defended elsewhere that there is no reason to suppose that
cooperation modifies the nature of the basic cognitive activities and
operations implemented in design (i.e., generation, transformation,
and evaluation of representations) (Visser, 1993a). Because
cooperation proceeds through interaction, it introduces, however,
specific activities and influences designers' representational
structures (both on sociocognitive and emotional levels). Some
examples of such activities are coordination, operative
synchronisation, construction of interdesigner compatible
representations, conflict resolution, and management of
representations that differ between design partners through
confrontation, articulation, and integration. Activities involving
argumentation—that is, in our view, activities aiming to modify the
representations held by one's interlocutors—obviously play a
particularly important role. The construction of interdesigner
compatible representations (Visser, 2006b, 2006c), their existence
beside designers' private representations, and their management
introduce factors that may add complexity to collective design
situations compared to individual design.
3.1.2 Tools in use
Given our view of design as the construction of representations, we
privilege representational tools in this discussion, especially
concerned with external representations and the means to produce them.
Designers' internal (mental) representations evidently also play a
crucial role in their activity, but these representations are mainly
dependent on other components of the situation and on individual
factors.
Design methods. By definition, designers proceed differently depending
on the method they follow. In the domain of software design, several
authors have compared the use of different design paradigms (in the
sense of design methods) and observed differences, both with respect
to activities and to resulting designs.
Lee and Pennington (1994), for example, have shown these two types
of differences between software design using an object-oriented and
using a procedural paradigm. With respect to the activity, the
differences concerned the domain and solution spaces developed, the
duration of problem domain analysis and of solution evaluation. As
also observed by other authors (see references in Lee & Pennington,
1994), the resulting designs "[reflected] fundamentally different
models of the solution. Procedural design methodologies result in
designs in which the modules represent procedures that complete
subparts of the task, whereas object-oriented methodologies result in
modules that represent objects in the environment" (p. 581; for other
differences, see the paper).
Kim and Lerch (1992), in their comparison between object-oriented
(OOD) and "traditional functional decomposition" (TFD) methodologies,
expected "OOD to radically change the cognitive processes in logical
design" (p. 491). Based on the preliminary results obtained in a pilot
study, the authors noted that "OOD may achieve substantial time
savings over TFD in logical design.… 1) by simplifying rule induction
processes used in functional decomposition; 2) by guiding designers on
how to build more effective problem spaces; and 3) by allowing
designers to run mental simulation more efficiently and more
effectively" (p. 489).
The maturity of a domain may influence the availability—and thus the
use—of tools. In 2004, the NSF launched a "Science of Design" program
aiming to "develop a set of scientific principles to guide the design
of software-intensive systems" (Science of Design, 2004). An
underlying idea was that "in fields more mature than computer science
[such as architecture and other engineering disciplines, for example,
civil or chemical engineering], design methodology has traditionally
relied heavily on constructs such as languages and notational
conventions, modularity principles, composition rules, methodical
decision procedures and handbooks of codified experience .… However,
the design of software-intensive systems is more often done using
rough guidelines, intuition and experiential knowledge."
As noticed above, research in the domain of software design has shown
that design methodologies may have an influence on the activity and
the resulting design. One may suppose that being familiar with the
constructs and other tools that have been developed in a domain may
influence, probably facilitate, a designer's activity—even if
cognitive design research has shown the difficulty of designers'
effectively working according to design methodology prescriptions
(Carroll & Rosson, 1985; Visser, 2003; Visser & Hoc, 1990).
One may notice that related to the idea that underlies the present
variable and that is only touched upon here, is the question of
well-defined versus ill-defined problems and the implications for the
nature of the activities involving these problems (see Visser, 2006b,
2006c). From a cognitive-activity viewpoint, most or all ill‑defined
problems might be analysed as design problems (Visser, 1993b). Going
one step further, Falzon (2004) proposes to adopt design as a
paradigm for analysing all problem‑solving activities. Eventually,
Falzon posits, each design problem becomes a state-transformation
problem (the type of problem typically examined in classical
cognitive-psychology laboratory research), because of people's
acquisition of expertise and habits, and of technological evolution.
Falzon nevertheless also notes the possibility that there will always
remain multiple situations in which people refuse themselves to refer
to procedures and routines. As an example, he refers to a study by
Lebahar concerning painters who try to establish conditions that rule
out the possibility to refer to routines.
External representations. According to Zhang and Norman (1994),
external and internal representations differentially activate
perceptual and cognitive processes. With Scaife and Rogers (1996),
we presume that things are less systematic, and more complex.
Nevertheless, we suppose that the use of internal and that of external
representations involve processing differences. Therefore, designing
may differ between situations depending on the importance of certain
types of representations. One may suppose that, for example, design of
physical artefacts (e.g., architectural or mechanical design) differs
from design of symbolic artefacts (e.g., procedures or organisations).
Indeed, one of the factors underlying the differences between software
and other types of design that are often stressed may be due to the
different types of representations primarily used. A classical result
in cognitive psychology research on external representations concerns
the influence of representation "formats" on problem solving. The
standard approach to show this effect has been to compare the way in
which isomorphic problems were solved (for example, the Tower of Hanoi
and the Tea Ceremony). Another difference in format is that between
alphanumeric and figurative representations. The possibilities
provided by sketches and other types of drawings compared to those
offered by purely alphanumeric representations, for example, with
respect to the ease of visualisation and manipulation and their
corollaries may facilitate simulation and other forms of evaluation of
what are going to become physical artefacts.
This observation surely does not only apply to classical (i.e.,
nonvisual) forms of software design. It probably also holds for other
symbolic artefacts, such as other types of procedures, plans, and
organisational structures.
According to Akin (2001), architects differ from designers in other
domains with respect to their relatively more frequent use of (1)
analogue compared to symbolic representations and (2) varying
representations. The author attributes this greater representational
variety to architectural design's situated and user-dependent
character. Akin also points to the lack of universally accepted
representational standards in architecture (cf. other elements of
Akin's position presented in the introduction of Section 3). We
already put into perspective Akin's view that architectural designers
are particularly resourceful and flexible. However, the lack of
standards, be they universally accepted or not, may indeed be of
influence (see also our remark concerning The maturity of a domain,
Section 3.1.2).
According to Zimring and Craig (2001), disciplines of practice
differ with respect to the ease or even the possibility for users to
understand the intermediate and final representations of the artefact
generally used in the domain. They assert that, for example,
architectural drawings of layout or appearance of the building to be
designed "are at least theoretically understandable by end-users…,
resulting in patterns of collaboration, testing and accountability
that differ significantly from those associated with more 'invisible'
design processes. An engineer, for example, working on a car engine is
not likely to collaborate with end users directly, given the
difficulty the average car driver has in understanding the mechanics
of engines." (p. 128)
With respect to the role of representation, we wish to state
explicitly that the importance of its role undeniably also depends on
the designer (discussed in Section 3.2).
Possible means for evaluation. Domains differ in the methods and other
tools that may be used in order to evaluate design proposals
(Malhotra et al., 1980, pp. 129-130). In engineering, more or less
"objective" measures and other criteria for future artefacts'
performance can be used and different proposals can be ranked rather
objectively. One can calculate whether a particular design (e.g., a
bridge) meets particular functional requirements, such as
accommodation and maximum load. The results of qualitative evaluation
used in other domains, based on subjective criteria such as
aesthetics, for example, may be more difficult to translate into a
"score," and thus to compare. In between the extremes of completely
objective and entirely subjective evaluation, exist different types of
simulation, physical and mental.
3.1.3 The user in the design process
Designers design for other people, the "users" of the artefact
product. In each domain of design, users are central—even if not
always for the designers and even if the use of artefacts may (seem
to) be more or less direct (cf. also The artefact's impact in Section
3.3.2). Naïvely, one might think, for example, that industrial design
products (such as, pens, chairs, household boxes) are in "direct" use
by their users, whereas the relation between the product of a
city-planning project and its users is much less direct. Yet, domains
differ with respect to their common practices regarding the way in
which designers usually take into account the potential, future users
and their use of the artefact product.
Integration of user data into the design. In HCI, for example, there
is a tradition and, correspondingly, considerable effort towards
developing methods to integrate user data into the design. This has
varied from such data being introduced into the design by design
participants who "know" the users but are not users themselves, to
approaches such as participatory design in which the users have
themselves a voice in the design process (Carroll, 2006).
It seems likely that the number and variety of participants who take
part in a design process influence this process, probably more its
socio-organisational than its cognitive aspects (see also Section
3.1.1, Individual versus collective design). Yet, on a cognitive
level, the difficulty of integration may increase with the number of
different representations to be integrated—thus with the number of
types of participants. In addition, the participation of
"nontechnical" design participants (what users generally are) may
introduce a specific difficulty, both for the nontechnical
participants themselves and for their professional design colleagues.
Gross (2003) mentions two specific user-related variables on which a
piece of software is like a building: the difference or equivalence
between client and user, and the type of use or user, which may change
more or less, or may remain constant. These two variables get a
particular weight in the context of the abovementioned influence that
number and variety of participants may have on the design process.
3.2 Designer: Interindividual Differences
-----------------------------------------
Differences between designers may affect both their activities and
their representations. This influence may occur by way of one or more
of the variables proposed hereafter. The use of certain types of
representations or other tools may influence design thinking, but a
particular designer may be more inclined to adopt a particular type of
representation, or feel more at ease with its use.
3.2.1 Design expertise
A classical cognitive-psychology result confirmed in cognitive design
research is that experts and novices in a domain differ as to their
representations and activities. Experts, for example, "recognise
underlying principles, rather than focusing on surface features of
problems" (Cross, 2004b, p. 432). Expertise has been examined in
many experimental studies on design (Chi, Glaser, & Farr, 1988;
Cross, 2004a, 2004c; "Expertise in Design," 2004; Glaser, 1986; Glaser
& Chi, 1988; Reimann & Chi, 1989). In Section 2, we saw that besides
novice designers differing from expert designers, design expertise in
itself differs from that in other fields (Cross, 2004b).
We have proposed to distinguish, in addition to levels of expertise,
types of expertise (Falzon & Visser, 1989; see also Visser & Morais,
1991). We have indeed observed how designers who were "experts" in
the same domain, but had different prior experience in that domain
(workshop vs. laboratory), exhibited (1) different types of knowledge
and (2) different organisations of their knowledge—a result comparable
to that regarding levels of expertise.
3.2.2 Routine character of a task
The routine character of a task is not an objective characteristic of
the task, but depends on the representation that people construct of
it. This task characteristic is thus dependent on interindividual
differences.
Most design projects comprise both routine and nonroutine tasks. In a
comparative analysis of three of our empirical design studies, we have
established a link between the more or less routine character of a
design project and the way in which analogies are used (at the
action-execution and at the action-management levels) (Visser,
1996). This, in turn, influences, at least in part, the possibilities
a designer has for reuse in a design project.
3.2.3 Idiosyncrasies
"The reality of professional design practice seems to be that
individual designers have differing design abilities—some designers
just seem to be better than others, and some are outstandingly good."
(Cross, 2002a, p. 14) In addition to studies comparing experts and
novices, there are clinical studies on experts that have led
researchers to identify specific characteristics of particular experts
(Cross, 2001c, 2002a). It seems, for example, that, contrary to most
architects, Frank Lloyd Wright could imagine and develop a design
entirely without using external representations, not sketching or
drawing, be it until an advanced stage of the project (Tafel, 1979,
quoted in Ball & Christensen, 2007), or even until the very end of
the design process (Weisberg, 1993, quoted in Bilda & Gero, 2005).
Cross (2002a), who mentions several studies on exceptional
designers, presents three case studies he has performed himself on
creative design in engineering and product design. Concerning the
three designers whom he considers "exceptional," Cross (2002a)
notices that "there appear to be striking similarities in their design
strategies, which suggest that general models might be constructed of
design expertise and creative processes in professional design
practice" (p. 14).
3.2.4 Different "types of people"
An idea often encountered, especially among architects themselves, is
that, rather than possessing idiosyncratic characteristics, architects
(as members of the architectural profession) are of a "special kind,"
a different "type of people" than other designers, especially,
software designers or engineers. Architects would have a different
"personality": they would be, for example, more creative and more
aesthetics-oriented. Several researchers, architects themselves or
not, also defend such an idea. Akin (2001), for example, considers
that architects attribute another value to creative and unique designs
than other designers do. Besides advancing more tangible differences
presented above (see the introduction of Section 3), Akin (2001)
claims that "the profession of architecture rewards the heart while
engineering rewards the brain" (p. 105). He notes explicitly, however,
that the specificities of architects are not biological or
physiological, "or even fundamental intelligence related." Akin
(2001) believes that "it is a matter of ethos and culture fostered
in a given profession, its educational philosophy and the
predisposition of its participants."
"Personality" is a familiar notion in psychology (nearly every
theoretical tradition in psychology has its own personality theory),
which, as many notions from the social sciences and humanities, is
widely used outside of this discipline. The personality-related
difference between architects and other designers, however, does have
no scientific basis: we are unaware of any empirical study concerning
possible "personality differences" between designers working in
different domains.
3.3 Artefact
------------
We have identified three artefact variables: social embeddedness, type
of artefact (instantiated by structures versus processes), and
artefacts' evolution. Gross (2003) proposes the proportion of
reusable components in the artefact's structure as one of the factors
that make "a piece of software like a building," but we do not have
any data or hypotheses concerning such a variable.
3.3.1 Social embeddedness
Referring to Rittel and Webber (1973/1984), Zimring and Craig
(2001) point to the social embeddedness of planning and design
problems. In their analysis of societal planning problems as "wicked,"
Rittel and Webber (1973/1984) indeed attribute the major part of
this wickedness to the social embeddedness of these problems. Neither
Rittel and Webber (1973/1984), nor Zimring and Craig (2001) define
the notion. Our definition is based on Edmond (1999)s'
constructivist approach: social embeddedness refers to the extent to
which an appropriate characterisation of an agent's activities and
representations requires that one include the agent's social
environment ("the society of agents" in Edmond's terms) as a whole in
the characterisation.
We consider that it is not an externally defined task that is more or
less socially embedded, but people's representations involved in
dealing with it. Qualifying a design project as socially embedded is
then shorthand for qualifying as such the designer's representations
of that project (an analogous remark holds for "a project's ill
definedness" as shorthand for "the ill definedness of the
representations that the designer has constructed of the project"). A
project can become socially embedded because the designers or other
stakeholders consider necessary to take into account the insertion and
future position of the artefact in its environment (characterised by
its users and/or the global society).
In apparent opposition with what we advanced above concerning user
involvement in design, one might think that a product design project
is less socially embedded than an urban project; that development of
HCI involves more social embeddedness than traffic signal design, for
example. Given our view that the view held by the designers or other
stakeholders makes a project socially embedded, this quality is not
limited to what are generally considered "social" or "societal"
problems. Even if societal planning problems generally will be
socially embedded, this characteristic is not specific to planning
problems: for example, planning one's route through a city (Chalmé,
Visser, & Denis, 2004; Hayes-Roth & Hayes-Roth, 1979) or planning a
meal (Byrne, 1977) are not necessarily typical instances of socially
embedded problems. Yet, planning a meal can become socially embedded
depending on the meal "designers"' view of their guests and of the
consequences occasioned by the meal's more or less greater
"success"—and as such, designers' activity will be influenced by their
view.
The influence of social embeddedness on a designer's activities is
probably similar to that of ill definedness. For example, socially
embedded problems probably have various, different solutions. These
solutions may be considered more or less appropriate, more or less
acceptable, depending on the criteria adopted by the person who judges
them.
A related issue in which societal questions play an important role is
the consideration of an artefact's user in the design of the artefact
(see Section 3.1.3, The user in the design process). Winograd (1996)
considers that its user-oriented character makes software design
comparable to architectural and graphic design, and different from
engineering design. He considers, however, that the design of
interactive software is completely different from other software
design (Winograd, 1997). Among the arguments advanced for these
claims, none is based on cognitive analyses of the activity.
Simon (1969/1999), in Sciences of the Artificial, implicitly
establishes a radical distinction between design activities in
engineering and in social design. In his discussion of social
planning, Simon (1969/1999) states that "representation problems
take on new dimensions" in this form of design (and, maybe, also in
inventive engineering design, see Visser, 2006b, 2006c) compared with
the "relatively well-structured, middle-sized tasks" of engineering
and architectural design (p. 141), which he presents—implicitly—as the
prototypes of design. For "real-world problems of [the] complexity" of
social planning, Simon considers that designers may refer to "weaker"
criteria than in the case of standard design. Processes such as
"search guided by only the most general heuristics of
'interestingness' or novelty" may provide "the most suitable model of
the social design process" (Simon, 1969/1999, p. 162). With respect
to the sources of social design problems' greater "complexity," Simon
suggests that differences of at least three types may be involved:
problems' degree of structuredness (here qualified as "definedness"),
their size, and the nature of their object (see our detailed
discussion of these differences in Visser, 2006b, 2006c).
It seems that only when he discusses social problems (and perhaps
scientific discovery problems, see the introduction to Section 2
Design is different from nondesign) that Simon seriously considers
human bounded rationality and takes into account the role of what he
calls "representations without numbers," generative constraints such
as "interestingness" or "novelty," and critical constraints such as
the "defensibility" of a decision. The hypothesis that we have
formulated in order to explain—at least, in part—this view of design
adopted by Simon is that he considers (1) (routine) engineering and
architectural design as standard design, and (2) social planning as
radically different from standard design.
In ever more domains, people become convinced of the societal aspects
of their action. One may suppose that this evolution will have its
influence on design. "The common thread in the new approach to traffic
engineering is a recognition that the way you build a road affects far
more than the movement of vehicles. It determines how drivers behave
on it, whether pedestrians feel safe to walk alongside it, what kinds
of businesses and housing spring up along it." (McNichol, 2004)
(see also tendencies such as ecodesign, ecological design, and
sustainable design, see, e.g., Méhier, 2005) (cf. the next
subsection, where we discuss the influence of users' interaction with
artefacts on designers' activities—especially those related to the
anticipation of the artefact's behaviour over time).
3.3.2 Artefacts' evolution
"Interactive systems are designed to have a certain behavior over
time, whereas houses typically are not," according to Löwgren (1995,
p. 94). Even if this assertion is questionable with respect to
"behaviour" in general, behaviour over time is a variable on which
artefacts differ—and the types of behaviour of different artefact
products are quite diverse. An artefact's behaviour over time may be
related to its impact on people (the "transformative" nature of
artefacts, see Carroll, Rosson, Chin, & Koenemann, 1998), through the
interaction that people engage in, and to its use by people who are
not necessarily transformed by this use. It may also be due to its
deterioration, dependently or independently of people. Two variables
introduced by Gross (2003) are the degree to which components of the
artefact may be subject to change or renewal, and the more or less
extended lifetime of the artefact.
All artefacts change over time. Houses may not display "behaviour"
over time, but they change. Systems such as organisations or
interactive systems are subject to specific types of change. Designers
are supposed to anticipate the transformation that their artefact
products undergo—be it of deterioration or another evolution type. The
possibility of anticipation may vary between situations (domains), not
necessarily depending on the degree of impact. It depends, among
others things, on the possibility to simulate the artefact, or to test
it in another way. For interactive artefacts, anticipation may be
performed through simulation. The future behaviour of certain
technical artefacts may be anticipated based on calculations.
The artefact's impact on people's activity and the possibility to
anticipate it. Predicting people's future use of an artefact product
and further anticipating the impact of the product on human activity,
is one of the "characteristic and difficult properties" of designing
(Carroll, 2000, p. 39). Indeed, "design has broad impacts on people.
Design problems lead to transformations in the world that alter
possibilities for human activity and experience, often in ways that
transcend the boundaries of the original design reasoning" (Carroll,
2000, p. 21). Gross (2003) mentions sanitary risks and safety
concerns that particular uses or states of an artefact may introduce.
Even if all design has impact on people, certain domains seem more
sensitive than others are. HCI, with which Carroll (2000) is
especially concerned in his discussion quoted above, is an example of
a domain in which design has particularly broad impacts on people.
Yet, this holds for all design with societal implications.
Distance between intermediary representations and final product. The
design of an artefact is a different activity than its implementation
(Visser, 2006b, 2006c). For certain types of artefacts, however,
there seems to be a relatively fluid, steady transition between the
different forms that the design concept may take and the final
artefact product—what may be qualified as a shorter "distance" between
the two. Symbolic artefacts, such as software, are an example. This
might elucidate somewhat our observation that software designers find
it particularly difficult to separate design from coding (Visser,
1987b). It does not imply, however, that design and implementation
are not distinct for symbolic artefacts.
It is with respect to the distance between the design concept and the
final artefact product that Löwgren (1995, p. 94) opposes
architectural and engineering design to "external" software design
("design of the external behavior and appearance of the product, the
services it offers to users and its place in the organization").
Delay of implementation. Design is by definition concerned with
artefact products that do not yet exist. A central aspect of designing
is thus, once again, anticipation. The bases of this anticipation may
vary depending on other variables (users' taking part and designer's
knowledge, experience, and activities, such as simulation), but anyhow
the conditions of existence, the behaviour, and the use of the
artefact products will be more or less different from those
anticipated: the world changes without possibility of being completely
controlled.
The implementation of certain types of artefacts is much longer in
coming than that of others—and not because of laziness or indifference
of the workshop or the client, or due to lack of resources. Voss et
al. (1983) have noticed that the solving of social-science problems
is particularly difficult because of the "delay from the time a
solution is proposed and accepted to when it is fully implemented" (p.
169). Such a delay clearly complicates the anticipation of the
artefact's evolution and other matters involved in its evaluation
(through simulation or other means). Even if this observation is
particularly applicable to social-science problems, it may also hold
for other types of design.
3.3.3 Type of artefact
"Type of artefact" may seem an evident explanatory variable for the
existence of different forms of design. As noticed already, however,
few elements are available concerning underlying variables. An example
is software design—often considered as "essentially different" from
design in other domains, but without discussion or examination of the
responsible variables. One candidate variable could be the difference
between structures and processes. Data concerning the influence of
this variable may come from results obtained in studies concerning
what may be considered particular instances of structures and
processes, that is, spatial and temporal entities.
Designing in space versus designing in time. Studies comparing
problems governed by temporal and problems governed by spatial
constraints have shown that designers deal differently with these
constraints (Chalmé et al., 2004; detailed in Visser, 2006b). An
example of design that preferentially implements temporal constraints
is planning (meal planning, see Byrne, 1977; route planning, see
Chalmé et al., 2004; Hayes-Roth & Hayes-Roth, 1979). Research,
however, has not yet settled clearly the specificity of the relative
ease and difficulty involved in the corresponding types of design—it
has even less identified the underlying factors.
Structures (which may correspond to states) are not necessarily
spatially constrained, but processes have systematically temporal
characteristics. By analogy to the differences between the cognitive
treatment of spatial and temporal constraints, one may expect that
structures and processes are represented differently (especially
mentally, but also externally), thus processed differently, and
therefore lead to different design activities (cf. Clancey's, 1985,
distinction between configuration and planning).
4. Conclusion
=============
In this section, we will first briefly review the generic-design
hypothesis and then focus on the component of our augmented
generic-design hypothesis that has been central in this text, that is,
design also takes different forms.
The validity of the generic-design hypothesis. Given the scarcity of
empirical evidence, the generic-design hypothesis needs more research.
We formulated above several points of reserve concerning the only
systematic study (Goel & Pirolli, 1989; 1992), but we have
presented, in Sections 1 and 2, various elements of support for the
hypothesis' two components. The hypothesis requires, however, more
research, especially more systematic research.
The validity of the hypothesis that design also takes different forms.
If because of the rare and disseminated empirical evidence, the
generic-design hypothesis needs more research, this holds a fortiori
for our hypothesis that design also takes different forms. Most
variables proposed were based on a broad knowledge and analysis of the
results of some 25 years of cognitive design research; they would need
comparative studies about the hypothesised differences between design
situations. For some of them, we were able to present precise
empirical data: for differences between architectural design and
engineering design (Akin, 2001), and between mechanical and product
design (Purcell & Gero, 1996), between design in a professional
project and design in an artificially restricted situation (Visser,
1995, 2006b, 2006c), between design activities and resulting designs
in projects adopting different design methods (Kim & Lerch, 1992; Lee
& Pennington, 1994); for differences due to designers' expertise
(for levels of expertise, see especially Cross' work; for types of
expertise, see Falzon & Visser, 1989); for the influence of design
projects' routine character on the way in which designers use analogy
(Visser, 1996), and the influence of idiosyncratic differences
between designers (shown for certain experts, see several references
in the text).
Therefore, in the analysis presented in this paper, we have introduced
material that still requires further analysis, and indicated a number
of directions—to be followed, modified, completed, and developed, in
other research.
It is conceivable that not all variables proposed have the same degree
of influence. Given our view of design as the construction of
representations, we suppose that variables related to representational
structures and activities are particularly influential. Referring to
classical research on the influence of representation formats on
problem solving, we formulated the hypothesis that sketches and other
types of drawings may facilitate certain activities (such as
simulation and other forms of evaluation), due to the augmented ease
of visualisation and manipulation offered by such figurative external
representations. Yet, variables may also depend on other underlying
factors and their influence on the activity may exert itself by way of
representational structures and activities.
The variables and the characteristics of the different forms of
activities and cognitive structures­—if their influence were to be
confirmed—may have implications for design support. Given the
centrality of representation in designing, the development of
appropriate support modalities for representational activities and
structures already suggests itself—be such modalities technological
(generally, computerised) or methodological. However, according to the
role of representation, and the type of representation preferentially
used in specific design tasks and/or in specific design situations,
the development of specific support modalities may be worthwhile.
Research on these questions may take advantage of the progress already
obtained in other domains, for example, those of software and HCI
design. In those domains, there has been considerable research on
visualisation and other visual tools, for example, on diagrammatic
reasoning (see Blackwell, 1997, and the Diagrammatic reasoning site;
see also the research on multiple —external—representations, e.g. by
Van Someren, Reimann, Boshuizen, & De Jong, 1988).
A question that might be asked after the presentation of all
these—possibly­—different forms of design is: if there are so many
differences between the implementations of design thinking in
different situations, then what about the idea that design is a
"generic" activity? In order to answer this question—and counter the
underlying opposition to the generic-design hypothesis—we now come up
with the fourth member of our augmented cognitively oriented
generic-design hypothesis. In its complete form, we see this
hypothesis as the following.
1.
Design thinking has distinctive characteristics from other
cognitive activities.
2.
There are commonalities between the implementations of design
thinking in different design situations.
3.
There are also differences between these implementations of design
thinking in different situations.
4.
However, the commonalities between all the different forms of
design thinking are sufficiently distinctive from the
characteristics of other cognitive activities, to consider design
a specific, generic cognitive activity.
Given the hypothetical character of the third member, which was
examined here, we did not mention this fourth member before. If one
defends the idea of design as a generic cognitive activity, it is,
however, the counterpart of the third member. At the end of this
paper, this fourth member remains completely hypothetical and requires
new empirical research comparable to Goel and Pirolli's (1989)
work—but preferably, in our opinion, performed in real, i.e.
professional design situations.
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1 "Design Dialogues: one" was "the first in an occasional series of
discussion meetings on design theory sponsored by the Design Research
Society," organised by McDonnell and Logan at University College
London, on May 17, 1995. We quote McDonnell's meeting report, which
until recently could be retrieved via internet, but is no longer
accessible.
2 We use the term "product design" where many authors use "industrial
design," because we reserve "industrial design" in a more general
acception, that is, for design perfomed in a professional, industrial
situation.