To criticize a particular subject, therefore, a man must have been trained in that subject (1.3) … not everybody can find the center of a circle, but only someone who knows geometry. (2.9) … We learn an art or craft by doing the things that we shall have to do when we have learnt it (2.17).
Aristotle, Nicomachean Ethics
The ancient Greek philosophers believed that education produces good or moral behavior. Aristotle divided education into two domains: reason and habit. The former involves understanding “the causes of things” while the latter derives from his belief that “anything that we have to learn to do we learn by the actual doing of it.” This division continues to today. Students need to learn facts and theories, to have and organize experience (Bagley 1907), while repetition of certain actions helps convert them to muscle-memory, allowing higher-order thinking to guide their use. Donald Schön, one of architecture’s most important educational theorists, emphasizes the role of the studio mentor as a live model for the “reflective practitioner” (Schön 1990) who demonstrates both execution skill and contextual understanding. This model recognizes that education may flow from either theoretical or practical wellsprings, reinforced by explanation and reflection in the case of theory, and by repeated practice in the case of the practical. In the process of teaching someone, we equip him or her with conceptual and sometimes physical tools and skills with which they understand the world and address its problems.
Traditional design curricula, and architecture in particular, have emphasized a well-rounded education balancing practical knowledge and theoretical understanding in a number of subjects, skill with representational media such as drawing, painting, and sculpture, but dominated by the repeated practice of design problem solving.
Unfortunately, these curricula often view digital technology as simply another medium in which to complete traditional work within the academic program and to secure employment. There is often little room for the topics discussed in this book, nor for development of the habits, skills, and knowledge needed to advance their study—the study of design computing. As things stand, developing robust curricula prototypes is one of the field’s challenges, though implementation is probably a larger obstacle.
As far back as 1969 economist and Nobel laureate Herbert Simon proposed a “Science of Design” that would complement the “Natural Sciences” of physics, chemistry, biology, and so on (Simon 1969). Such a discipline would bring a scientific methodology to many of the questions this book has sought to tease out, including understanding the challenge of problems and the cognitive needs of design, data structures for representing design problems and artifacts, problem definition and search of design-space, generation and refinement of candidate solutions, plus synergy and leverage opportunities to combine human and machine intelligence.
Unfortunately, while mastery of representational media is essential to both pedagogy and practice of architecture, digital media are rarely embraced with enthusiasm. While most faculty members have historically had some level of skill with traditional media, digital media has been the realm of expertise. As a result, schools have tended to separate and isolate digital media, often focusing solely on skills in the operation of particular software packages, and offering the material in auxiliary digital media courses. This has reinforced a tendency to define the subject in terms of production, a task-oriented approach to design computing that equates CAD with AutoCAD, 3D modeling with Rhino or 3DS Max, and BIM with Revit. In particular, this approach has not challenged a common conceit from the 1980s that CAD is “just another pencil,” that it doesn’t matter, because digital tools can be exchanged on a one-for-one basis with traditional practices and tools, and that such swaps are “neutral” with regard to individual cognition or broader professional impact. I recall a faculty meeting in the mid-1990s, during which a colleague asserted that we did not have to provide computer-literacy instruction at all, because the next-generation student would bring the relevant knowledge with them. How this argument could be made in a profession that routinely teaches grown-ups how to use a pencil is a mystery, but it is consistent with the anxiety-reducing notions of one-to-one substitution and tool-neutrality.
However, when new tools are fundamentally different from old tools, new behaviors and new ways of thinking about problems tend to emerge. In the past, constructing a perspective was laborious, so students tended to stick to plan and elevation views, with occasional axonometric drawings. When they did construct a perspective, care was taken in finding an appropriate viewpoint in order to compose a powerful image. Modern 3D rendering software makes production of realistic perspectives straightforward, but it doesn’t help select revealing viewpoints, and sophisticated rendering can give both clients and students the impression that a design is further along than it really is. Aristotle would have recognized that both situational insight and operational skill are required to make best use of the new tools.
One prominent exception to the neutral-tool view that has had significant press exposure is found in two publications from 2001 in which Marc Prensky developed a distinction between “digital natives” (meaning those born after 1980 or so) and “digital immigrants” (those born earlier), with particular attention to education (Prensky 2001a, 2001b). To paraphrase: The digital natives have grown up with computers and personal access to computing and multi-media. Their manipulation of the technology is said to be missing the “accent” (clumsiness?) of the immigrants, but (alas!) the immigrants are in charge of the classroom. Overall, the articles argue for rethinking how material is presented to “digital natives” in favor of hyperlinked multi-tasking multimedia games. That the “Myth of Multitasking” has been largely debunked (Rosen 2008) in the subsequent decade has not stopped the natives vs. immigrants dichotomy from entering common usage.
Oddly, students often seem attracted to this theory. One reason might be that the theory justifies their attraction to cellphones and laptops, and relieves them of responsibility for engaging the challenging changes wrought by digital technology and adjusting their own behaviors in response—they are, after all, unable to escape their own accent.
Implicit in the dichotomy is a kind of manifest destiny—a belief that natives are more competent users than their predecessors. This certainly resonates with the broader cultural adulation of technology consumption in general and youth in particular, and my observations above about digital media courses. My own observation is that modern students are much more comfortable with technology than are their predecessors, which is very good, but that their education in the fundamental principles of the technology has been ad hoc and haphazard, focused on task-completion rather than deep understanding. As a result, most students are unafraid of the technology and familiar with the first-level affordances, but may not be comfortable with more subtle subjects and don’t completely “own” their technology.
The debate sparked by Prensky’s articles continues, as does related discussion and research about whether the multi-tasking enabled by modern technology is a good thing or a bad one, whether premature materialization made possible in modern 3D visualization software seduces students into thinking they have done good design, etc. It is perhaps telling that Prensky wrote a follow-up piece that focused on digital wisdom rather than skill, on reason rather than habit (Prensky 2009).
Traditionally, architectural education has focused on questions of design, set against a backdrop of technical assessment and augmented by media manipulation skills offered in what are all-too-often called “support” courses. As noted above, with the exception of a few schools where “digital” or “paperless” studio experiments were undertaken, the advent of digital analysis and media options has been addressed with specialized course content focused on acquiring skills with the new tools, each one an option on top of the traditional structure. As more and more of these courses have been launched, covering more and more of the content material from the traditional curriculum, they function less as specialized advanced-skills conduits and more as entries to the mainstream of the profession. Unfortunately, because of the elective and ad-hoc nature of this coursework, appropriate skills and expectations are rarely integrated across mainstream course and studio content in an appropriate fashion, often because the instructors of these less-technical courses lack paradigms for such instruction in their own backgrounds, being, themselves, digital immigrants. The result of these entrenched interests (both within universities and their accreditation bodies) means that many students are ill-prepared to work with the full range of tools available in the workplace, and their exposure to them is haphazard.
As a profession, architecture in the Western world has not expected to graduate finished architects directly from school; there has always been an expectation of experience and polish to be developed during internship, working under the direction of senior designers. As discussed in Chapter 10, however, these relationships have changed as firms seek new knowledge and skills through hiring. Who is best prepared to teach this material? When is the best time to learn it? How do we get beneath the surface froth of change to the deeper currents of transformation? These are some of the questions that beset teachers and stewards of curricula in design and computing. Waiting for the previous generation to retire will not be enough; we need good models that address real design challenges with appropriate digital media skills in a reflective and considered fashion that takes advantage of the technology’s affordances and avoids the pitfalls. In their absence, other models will take hold, models that will likely continue the mercenary task-oriented view of the technology.
Where is the knowledge of design computing best located in a design school curriculum? Perhaps the changes are so ubiquitous that traditional media should be abandoned and digital media use should be integrated across the entire curriculum? Such an approach would require that faculty have motivation, time, and opportunity to rethink and restructure their own teaching. Nonetheless, teaching the teachers might make the most sense. Such an approach would help with another problem as well—reliance on the elective course model means few students can take and few curricula can offer well-organized subject-area sequences in design computing within a professional degree program without becoming overlong.
The curriculum is a reflection of the faculty, and managing the faculty resource is a challenge for department administrators. In the pre-digital era, most teachers of design had, like their practitioner cousins, substantial skill with traditional media, and were not hesitant to guide students in their representational choices. Presently there are many different software packages available, but a fairly small population of instructors with broad skills in the use of software, and very few who have mastered more than a handful. It is difficult for instructors to maintain broad mastery when speed and arcane knowledge are most valued, and it is difficult to staff a generalized presentation of the material.
It is important that we try to persuade students to take a longer view, to understand that the tools they are learning to use now will be replaced several times during their careers, that there is long-term value to focusing on more generalized knowledge in addition to mastery of the current tools. Aristotle’s conclusion that damage occurs as often from too much as from too little of something is relevant here—finding a balance point is important.
In response to the complexity of the industry and the limitations of tight curricula, schools often adopt simplifying policies, selecting a limited palette of software for use in their courses. While effective in reducing the learning curve that students must climb, and saving money on software licenses, this strategy renders some opportunities inaccessible, reinforces the one-size-fits-all task-oriented tunnel-vision of students at the expense of deeper understanding, and incurs risks associated with selecting or sticking with software that fails to enter, or falls out of, the mainstream of professional practice.
A university-level design computing course needs to offer knowledge with a longer shelf-life than most software study guides, counteracting the cultural drift of the ad-hoc informal learning environment while injecting deeper knowledge into a task-oriented culture (Senske 2011). A software technology such as BIM is built on foundations of data-management, representation, interface affordances, and cultural integration. Including such general knowledge in a “BIM class” would be appropriate because it informs questions of data exchange, technology trends, and possible add-ons, but touching on the many constituent parts in other courses would begin building the foundation and enhance understanding.
Students do have legitimate task-oriented design computing skill needs, as well as interests that lie outside of design computing. It is fortunate that they are comfortable seeking out and using learning resources wherever they find them, because they may not have time to study the subject more deeply. In schools where students spend many hours in the studio doing tasks together, this means they often learn these skills either from one another or from the web. Unfortunately, it is difficult for this learning to get beyond surface knowledge and second- or third-hand knowledge often becomes corrupted or distorted in plausible but misleading ways.
Self-directed learning should be an element of life-long learning, a pattern that should include setting aside time to learn and expecting to share insights or skills with others. Small student-run workshops, faculty-led short course modules, term-long exercise sequences, and explicitly theoretical reflective seminars that address foundational questions—these are each important components of a habit of continuous learning.
Learning to design involves learning a vocabulary. Traditional design dealt in symmetry, proportion, light, history, and material. Digital design adds to or displaces these with concepts rooted or transformed by the vocabulary of computers—sometimes referred to as algorithmic or computational thinking. The most obvious way to learn this vocabulary is through the experience and craft of scripting—generating form or image using computer code (Senske 2011). With the advent of visual programming languages, scripting is seen as much more accessible and interesting than that found in text-based environments, a change that significantly broadens its appeal.
In the 1980s the only way to study computing in architecture was to learn to code, whether in a language like FORTRAN or an embedded language like AutoLISP. Code was the primary way to explore design computing ideas. There was an explosion of code, some of which has coalesced into current end-user tools, allowing the next generation to adopt the task-orientation mentioned above. The current popularity of parametric design reflects a similar interest in personal control and expression, but it also responds to the widespread appearance of application programming interfaces (APIs) in software, and resonates with a national portrayal of code as a driver of innovation and economic development.
Algorithms have been around far longer than computers. Any pattern or sequence of actions that is designed to produce a predictable result can be thought of as an algorithm. Weaving patterns on looms, cooking, cutting or bending patterns in metal and wood, brick-laying, parquetry—all of these utilize repeated patterns of action. Designers often acknowledge thinking systematically, working from some set of principles or rules to a complete design. What is different today is the potential for the patterns themselves to change across the body of work, something that wasn’t commonly done in the past. Where Renaissance architects might create intricate nested arrangements of proportion, today’s designer may well design a building skin where every panel responds to the unique conditions of its orientation and solar exposure in a specific way, as on the façade of the London City Hall. This kind of thinking calls on the mind as well as the eye, a kind of thinking that has not been central to architecture for some time. It consists of variable geometry and relationships in a dance with fabrication and erection. Learning to create, think about, and control these complex structures is important in the modern world.
There are deeper questions in the area of pedagogy than whether to teach coding or require a course in BIM. Once we understand that digital tools are not simple one-for-one substitutes for their antecedent tools, we have to ask about the cognitive and social side-effects of using these new tools. In reviewing the cognitive aspects of design, the link between sketching and design has already been discussed. What new self-delusion traps does the technology create? What new work disciplines are required besides “save often!” and “make backups”? What is the impact on the social community of the studio? Is digital work different from paper work? What pedagogic guidelines should we adhere to?
The affordances of a modern GUI are seductive. Nigel Cross, a noted design researcher in the UK, has observed: “Some student designers can seem to get stuck in gathering information, as a kind of substitute for actually doing any design work” (Cross 2011). The rendering speed and ease of manipulation available in modeling software today makes it easy to postpone the difficult business of design in favor of spinning the model a bit for a slightly different view, zooming in for a look over there, and so on. Even at schools that traditionally privilege technology, such as Carnegie Mellon University, in subjects that hinge on technology, such as interaction design, an interest in developing communication and thinking skills has led at least one instructor to a “pencils before pixels” approach (Baskinger 2008).
Observations of students using 3D modeling programs in design raise similar questions—after encountering a problem in design development, students are often seen to change their focus to another part of the model, or simply spin the model this way and that in what appears to be a random fashion, rather than isolate the problem and focus on resolving it. In the face of uncertainty regarding appropriate action, it seems possible that the affordances, or opportunities for action inherent in the interface, are so compelling that action trumps contemplation.
On top of this, the imagery produced by today’s software is remarkable—textures, light sources, diffuse and specular reflections—all readily available whether or not the underlying design is good. It is easy to see how someone could confuse high-quality rendering with high-quality design. In his recent book, The Death of Drawing, architect and academic David Scheer (2014) criticizes the limited, self-defined world of (digital) “simulation” in contrast to the conceptually engaging realm of “representation.” Design education involves learning to critique your own work, to look deeply at a project, learning to see not only in visible light but at the “abstract” end of the spectrum. This requires context.
Though we describe design as a cyclic or iterative process, a description that paper drawings supported through tracing and re-drawing (at different scales), our digital tools do not. The coordinates in an initial sketch, perhaps drawn at a very small scale on the screen, are indistinguishable from those of a carefully reviewed plan. What role does tracing play in developing a design? Redrawing, though inefficient in terms of drawing production, directs focused attention to selected areas of the project, offering a chance to recapitulate design rationale and reinterpret existing or emergent conditions. What, if anything, has taken its place?
While David Scheer’s book confronts the possibility that overreliance on digital tools and simulation is diminishing architecture conceptually, there is another disturbing possibility linked to the modern reliance on digital tools. There is research with children that links hand-lettering and development of writing skill (Richards et al. 2009). This raises the possibility that sketching by hand is actually critical to learning to function as a designer. If so, it would explain the observation by James Cutler, mentioned in Chapter 7, that recently hired interns in his office seemed less able than their pre-digital peers to develop design ideas from sketches. Further, Cutler said that principals in firms located all across the United States had noted the same decline. It is, of course, very hard to verify such an observation, as each generation of observers is different, but if it is true, then schools of architecture should be concerned regardless of the cause. Cutler attributed the decline to under-involvement in sketching. If the cognitive decline is real, it might equally well be a question of how the discipline of creating or using digital representation is dealt with in the studio, not as a question of simple technical prowess, nor as a buzz-term to enhance reputation, but as a serious question engaged by studio mentors and students alike. The theory of desirable difficulty has been used to explain how students taking lecture notes using pen and paper learn better than students using a laptop (Mueller and Oppenheimer 2014). Perhaps something similar happens with sketching.
It is time to jettison the comforting notion that CAD is “just another pencil” once and for all, and develop evidence-based approaches to teaching design that fully acknowledge the changes that are accompanying the adoption of digital tools.
Digital technology has disrupted much in design, construction, and inhabitation of the built environment. Approaching design computing as simply a means of document production is shortsighted and simple-minded. These tools change what we can make and also seduce us into new mistakes. Developing a longer-range view that provides students with judgment, heterogeneous skills, seed knowledge, and habits to support a lifetime of ongoing disruption and change should be our goal. This is not a question of what a design computing curriculum should be; rather, it is a question of what a design curriculum should be.
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