Learning Design Through Designerly Thinking. Holistic digital modeling in a graduate program in architecture.

Abstract

[Full video presentation at: vimeo.com/156914143]

The paper presents the author's experiences in architectural design education as answers to questions that, for some years, have been hovering around Design as the Third Culture and its relationship with Science. More precisely, the paper proposes to address the following questions: Can Design itself be used as a tool for scientific research? If so, what are its characteristics and features? Can research through Design be used as an educational method? If so, with what results? In addition, and as a complementary aspect, the paper also focuses on Modeling as a core language of Design that, in its recent digital nature, can bring accuracy to the production process, and " makes Science visible " so that an holistic approach in learning can be reinforced and usefully adopted.

Full text

Prof. Giuseppe Ridolfi, Arman Saberi
School of Architecture – University of Florence (I)
LEARNING DESIGN THROUGH DESIGNERLY THINKING. HOLISTIC
DIGITAL MODELING IN A GRADUATE PROGRAM IN ARCHITECTURE.
ABSTRACT: The paper presents the author’s experiences in architectural design
education as answers to questions that, for some years, have been hovering around
Design as the Third Culture and its relationship with Science. More precisely, the
paper proposes to address the following questions:
! Can Design itself be used as a tool for scientific research? If so, what are its
characteristics and features?
! Can research through Design be used as an educational method? If so, with
what results?
In addition, and as a complementary aspect, the paper also focuses on Modeling as a
core language of Design that, in its recent digital nature, can bring accuracy to the
production process, and “makes Science visible” so that an holistic approach in
learning can be reinforced and usefully adopted.
I. Designerly Thinking as a research and learning methodology
“I do not believe that there is a single paradigm for research ‘through design’ but I am
confident that we now have the means to conduct research that is appropriate to our
profession and discipline, which makes a distinctive contribution to knowledge that
complements that of other disciplines and, crucially, has the potential to inform professional
[and educational] practice.” (Rust, 2009: 6)
The relationship between Science and Design has a long and controversial story intimately connected
with the beginning of design practice when the need for a scientific method, De Stijl, arose in the early
Modern Movement and evolved within the cybernetic research of the 50’s and the futuristic visions of the
60’s. The Conference on Design Methods, held in London in 1962 (Jonas and Thomley, 1963) is
generally recognized as the climax of this debate and the point from where Design starts to assume its
own peculiar identity distinguished by Science and Humanities. This question was revamped with the
article Research in Art and Design, published in 1993 by Sir Christopher Frayling. The article renovated
the question about the fundamental nature of Design (Margolin, 1982), and the possibility for Design to be
a scientific research discipline: more specifically, if Research through Design can be considered a way of
knowing but also a way of thinking to investigate and disseminate knowledge which are the main

elements through which Science is defined.
Addressing the above issues, this paper adopts the term Designerly Thinking (Cross, 2001) to designate
the operational specific nature of Design. It also identifies two questions as relevant topics to evaluate the
scientific nature of Design, consequently assessing Designerly Thinking as a useful approach in Learning
Design. These two questions are:
■ Does Designerly Thinking employ a rigorous and, above all, transmissible methodology?
■ Does the product of Designerly Thinking modify systems of knowledge?
Historically, many scholars and practitioners have defined diverse and fragmented methodologies for
Design, and as a result, we must therefore accept that Designerly Thinking does not seem to employ a
rigorous and transmissible methodology. However, because Science and Humanities have moved closer
together, Science has opened itself to qualitative domains and concerns itself with ill-defined problem
solving which are viable through multiform methodologies, even unorthodox ones, if they are reasonable
and consistent. Based in this approach, we can accept Designerly Thinking as a scientific practice with its
own multiform methodology but on the condition that the process is explicit, coherent and communicable.
Concerning the second question, whether or not the product of Designerly Thinking modifies existing
systems of knowledge we can start from the seminal distinction between Science and Design (Simon,
1969) where the former is seen as a transformation process of knowledge and the latter a transformation
process of utility. From this we conclude that Design cannot modify systems of knowledge. But this is not
definitive. In fact according to Brown and Chandrasekaran (1985) and Gero (1990), Design, when it is
not addressed as a routine product but innovative or creative, can produce different kind of changes in
knowledge. In addition for others including Archer (1995), design artifacts can produce knowledge
facilitating – sometimes – major changes in people’s perceptions and values. The hypothesis that Design
can be assimilated to Science is therefore valid under the condition that the changed state of knowledge
does not remain tacit, but conscious and transmissible. In addition, this hypothesis is more relevant and
effective in education where knowledge transformation can be considered its primary output even if it is
not related to the scientific community or the whole of humanity but limited to a specific group of students
in a class. Therefore, in this specific and limited field, Designerly Thinking can be considered a cognitive
and scientific activity as well, if methodologies and products of research are explicit, consistent, and
formalized.
II. Digital Modeling in Designerly Thinking as a medium of learning
From the above discussion it is clear that the questions “if Designerly Thinking can be based on a
transmissible methodology and can produce a significant transformation on knowledge” are both related
to the condition that all the activities, analysis, guessworks and outputs must be unambiguously
expressed.
We believe Modeling, with pattern recognition and synthesis as the main and distinctive methods of
Design, can be considered the answer. As we can see in the following examples, Modeling represents
the materialization of assumptions, methods and outputs: the medium through which students can
objectify research, exchange experiences, and acquire knowledge.
Modeling has a long tradition based mainly on figuration: a personal sketching process (Laseau, 1989)
developed by trials and errors, informed by tacit knowledge and controlled by pondere et mensura that, in
the past, was typically analogical. In fact, with the exception of some drawings of Francesco di Giorgio
Martini (see: School of Marco Varrone in Casinum) and the architectural firm of the San Gallo family,

design modeling was mainly run through geometrical proportions. Famous examples are Livre de
Portraiture designed by the Picard architect-engineer Villard de Honnecourt in the decade from 1225 to
1235, the beautiful mock-ups realized by renaissance hatchers, or lately the elegant buildings of Palladio
modeled using musical harmonic proportions. Even Vitruvio tells us of different measuring instruments but
it is quite evident that the Past reasoned and worked differently. It worked through the analogical
syllogism of descriptive geometry and the ineffable knowledge of quality based on evidence.
Despite these historical antecedents, however, it was not until the Sixteenth century that The Number
would start to accompany drawings in a more stable manner. While Perspective in architecture was
playing its baroque exaggerations, the Scientia Mathematica revolutioned design and architecture
supporting Cartesian Space where objects and functions were describable with the elegance of numbers
and mathematical formulas. From this moment onwards, Aristotelian geometry was threatened by a new
approach which was no longer syllogism but numerical modeling. The forerunners of this new approach
were the abstract ballistic calculations and crossfire lines that shaped urban fortifications.
The Matema paradigm-shift marked the passage, as stated by Fulvio Carmagnola, “from a qualitative
quality to a quantitative quality” where also analogical representations and high fidelity models are
derived from the quantitative logic of digital computation (Maldonado, 1992). As a result, nowadays, forms
and behaviors of materials can be shaped and crafted to achieve particular design goals fitting exactly the
visualization that designers are able to produce with their computer software. The standardization of
elements is no longer a technique to build in an industrial way. Digital information has become the
standard and designers, industry and craftsmen are using this standard to model, to share knowledge
and, more than that, to formalize ideas: to give evidence of the design research process and Designlerly
Thinking as well.
Rooted in this theoretical basis, three teaching examples from a Graduate Program of the School of
Architecture in Florence are presented. Common elements of these examples are the use of exploratory
research and Digital Modeling able to produce a great number of tests and corrections especially if it is
parametric or evolutionary and therefore more effective compared to the physical modeling. Furthermore,
reflecting the same principle that distinguishes Research through Design from Research for Design, the
examples share the criterion that the artifacts made by students are not evaluated for the quality of the
product in itself but for the degree of knowledge enabled through the artifacts.
III. Form manufacturing
The first example comes from the «Architecture and Structure Design Lab», specifically the Form
Manufacturing Class, where learning proceeds from a free intuitive activity towards a more formalized
approach ending in the digital fabrication of prototypes. The course begins with Origami/Kirigami
manipulation inspired by the paper exercises of Josef Albers and his quote: “All art starts with a material,
and therefore we have first to investigate what our material can do”.
This introductory exercise (Forming through Matter), is based on free exploration and intuitive perception
about matter’s behaviors in order to gain awareness of the relationships between the materia prima (in
Latin definition or materia rudis, corpora materia in Lucrezio’s acception: contents without form but
factive) and the form through which materiality (materia operata) emerges.
Form Modeling is the second step, where students are first required to induce, from their experiments,
forming regulatory diagrams such as mountain & valley-fold, or consistent methodologies such as
tessellation to test, control and refine ideas. Eventually this formalistic part ends with digitalization where
experiments are run in a virtual way using 2D patterning, 3D and parametric modeling.

After the exploratory phase, the class enters the conclusive stage with the final assignment (Form
Fabrication) where students are required to produce a mock-up in rapid prototyping for a structural or
envelope system. The mock-up and its evaluation are not related to its capacity to represent qualitative
aspects and the morphology of the real building system (the form in itself). Instead, the goal is to model,
to let emerge, the materiality of the constructability: relationships, procedures, and criteria that must be
observed in the designing activity finalized for fabrication. To reinforce this goal some constraints were
deliberately imposed: exclusive use of flat elements obtained from laser cutting; assembly process not
using glue, nails or screws.
IV. Holistic learning through HI-FI modeling
Modeling, as operational research and learning tool, is also the main concentration of the second
teaching example. In this class, from the «Environmental Design Lab», modeling entirely refers to the
digital prototyping. Explorations are carried out inside the virtual dimension simulating and testing
performative matter of materiality. In this case, the model is used, not as a mere presentation of
phenomena, but as a cognitive artifact that allows the student to interact and become familiar with the
theoretical foundations that the prototype incorporates: expression of concrete thought and formalization
of the traditional sketching in a way it can be now used as a shareable instrument of scientific research
(Papert, 1996). The goal of the class is the architectural and environmental retrofit of an existent building
to approach in a performative and computational manner.
As in Form Manufacturing class, in the first phase (Forming through performances) students are asked to
carry out a theoretical exploration through which they could acquire foundational knowledge about matter,
in this case concerning the physical determinant of building elements versus environmental behaviors,
and form, concerning their state configurations. As a basic activity, from this preliminary exploration,
knowledge about theoretical and instrumental fundamentals is also produced.
The second assignment titled Options Building, concerns the decision-making process to be formalized,
in a scientific manner, through the preliminary definition of assumptions, criteria, outputs and the adopted
system for alternatives comparison as well. In some advanced cases and in very limited aspects of the
projects, evolutionary computation is also solicited. The objective is not the identification, tout court, of a
preferred solution, but the acquisition of the Design Optioneering methodology: the design optimization
process recently redefined and practiced through a parametrical approach (Shea and Gourtovaia, 2005;
Holzer, 2007). In this phase attention is devoted to communication and requires the translation of the
digital entities of modeling in analogic shapes. For this goal students are asked to convert numerical
reports in more understandable and shareable info-graphics and to give evidence of immaterial aspects
of design such as temperature, wind, light, ... through 3D visualizations and HI-FI models that, because
the digital information (the untouchable material) stored and processed in it, is able to give us a tangible
and qualitative experience of the quantitative analyzed phenomena.
Materializing relationships and emerging effects between building and environment is also the final
assignment titled Materializing Behaviors where students are asked to finalize their experience showing
the changing state of this intra-active system under different conditions of forms, building elements,
weather and time as the complementary entity of form and matter. Virtual representation through video
animation is the required medium to show this relationship, but students are also encouraged to produce
an interactive physical prototype using Arduino microcontrollers. For the realization of adaptive mock-ups
students are supported by Mailab (www.mailab.biz) a university spin-off research laboratory on
Multimedia Architecture and Interaction, giving them the opportunity to expand their learning experience
in a professional research context.

V. Staging inhabitants’ behaviors
The last example is the workshop “La casa di …” focused on designing a private house where the main
goal is to invalidate the current use of standardized users’ requirements and, more importantly, to disrupt
the traditional approach in design-lab teaching where students work with a problem-solving attitude. For
the final presentation students are required to realize an architectural video-mapping installation where
the architecture (a Communal Condo resulting from the assemblage of all the individual houses) is in the
background: a simple three-dimensional support to stage the daily life of each user or “different
biographies of many weak identities. (A. Branzi, 2009: 39)
According with this goal, the assignment starts with the brief definition (Client profile). A problem setting
task that students are asked to cover using uncommon approaches for architects such as creative writing
and daily activities scoring or other unorthodox instruments such as virtual shadowing (e.g. Vito Acconci's
Following Piece). The goal is to provide a design program emerging from people as human beings: a
complex anthropological subject, more than ergonomic and psychophysical entities where provocative
and ironic approaches (e.g. Munari’s Method, Architettura Radicale, Critical Design) were also solicited to
restructure the problem.
In the second step (Design Development) students were asked: first, to work individually designing a
private house fitting some assigned morphological constraints and users’ requirements as set in the
previous phase; second, to work as a group in order to realize a unique model reassembling all the
individual houses in a Communal Condo to be manufactured in rapid prototyping.
The third step (the Spectacular Communal Condo) was devoted to reveal the daily behaviors of the
houses and their inhabitants through videoclips. With the assistance of Mailab, these videoclips were
assembled, edited and mapped on the physical model in order to obtain a video-installation staging the
life of the Condo and to materialize a metaphor of the condition of contemporary design where objects are
vanishing in a new scenario that “pushes material artifacts to the background in favor of the actors within
the system, […] will invite designers to look for the ‘dark side’ of the object […] that correspond, not only
to the needs, but also to the aspirations, hopes, and life projects of their users!” (Findeli, 2001: 14-15)
VI. Conclusions
The discussed examples show how learning can have effective benefit from practices informed by
scientific research or, in other words, by formalized and consistent methodologies supported by Modeling.
According to Epron et alii (1977) the better impact of modeling compared to other approaches based on
regulatory methods or stylistic observation is also demonstrated in learning. In a broader context, some
other corollaries concerning the adoption of the Designerly Thinking and Digital Modeling adopted in
explorative more than experimental attitude, in Bardram’s et al. (2004) interpretation, can be also
highlighted in the following:
■ form, matter and time are mutually interrelated in the manufacturing process and they can be
effectively modeled through information materiality;
■ problem setting and the construction of ad-hocratic tools are strategic and determinant in design
practice facing new problems;
■ HI-FI analogical representation can be a powerful tool to acquire awareness and to support the
decision-making process as well as learning;
■ qualitative and analogical comparisons allowed by digital computation, more than analytical
measurements, can produce evidence and effective evaluation of alternatives in the early stage
of design;

■ provocative and disruptive approaches can stimulate students to interplay, to identify new
directions and to expand their knowledge;
■ new knowledge emerges from the interplay between the environment, artifacts and actors and,
as a consequence, each learning project has different goals, methods and outputs.
References
[1] Archer, B. (1995). The Nature of Research. Codesign 1: 6-13
[2] Bardram, J., Christensen, H., Hansen, K. (2004). Architectural Prototyping: An Approach for
Grounding Architectural Design and Learning. Proceedings of 4th Working IEEE/IFIP
Conference on Software Architecture, WICSA 2004: 15-24
[3] Branzi, A. (1984). We are Primitivives. In Margolin, V. (ed.), Design Discourse. History |
Theory | Criticism. Chicago: The University of Chicago Press, 37-41.
[4] Brown, D.C. and Chandrasekaran, B. (1985). Expert Systems for Class of Mechanical
Design Activity, Knowledge Engineering. In Gero, J.S. (ed.). Computer-Aided Design. North
Holland: 259-282
[5] Carmagnola, F. (1991). Luoghi della qualità. Estetica e tecnologia nel postindustriale.
Milano: Domus Academy
[6] Cross N., (2001) Designerly Ways of Knowing: Design Discipline Versus Design Science.
Design Issues 17(3): 49-55.
[7] Dunne, A. (2005). Hertzian Tales. Electronic Products, Aesthetic Experience and Critical
Design. Cambridge, Mass.: The MIT Press.
[8] Epron, J.P., Gross, D., Simon, J.M. (1977). Essai sur la formation d'un savoir technique : le
cours de construction. Villers-lès-Nancy: École d'architecture de Nancy.
[9] Findeli, A. (2001). Rethinking Design Education for the 21th Century: Theoretical,
Methodological and Ethical Discussion. Design Issues 17 (1): 5-17.
[10] Frayling, C. (1993), Reasearch in Art and Design. London: Royal College of Art Research
Papers.
[11] Gero, J.S., (1990), Design Prototypes: A Knowledge Representation Schema for Design. AI
Magazine 11 (4): 26-36.
[12] Godin D. and Zahedi, M. (2014) Aspects of Research through Design: A Literature Review,
Design. Research Society's 2014 Conference, Umea.
[13] Jonas, J. C. and Thomley, D. G. (eds) (1963). Conference on Design Methods. Oxford:
Pergamon.
[14] Laseau, P. (1989). Graphic Thinking for architects and designers. New York: Van Nostrand
Reinhold.
[15] Maldonado, T. (1992), Reale e virtuale. Milano: Feltrinelli.
[16] Margolin, V. (1989). Introduction. In Margolin, V. (ed.). Design Discourse. History | Theory |
Criticism. Chicago: The University of Chicago Press, 3-28.
[17] Papert, S. (1996). A word for learning. In Kafai, Y. and Resnick, M. (eds.). Constructionism in

Practice: Designing, thinking and learning in a digital world. Mahwah, NJ: Lawrence Erlbaum
Association, 9-24.
[18] Rust, C. (2009). In the Eating: Grounding the validation of investigative designing in the
experience of stakeholders International Association of Societies of Design Research
Conference 2009, Coex, Seoul, Korea.
[19] Shea, K. and Gourtovaia, M. (2005). Towards integrated-performance-driven degenerative
design tools. Automation in Constroction 14 (2): 253-264.
[20] Simon, H. A. (1969). The Science of the Artificial. Cambridge, MA: MIT Press.
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