Avoiding design errors: a case study of redesigning an architectural studio

Avoiding design errors: a case study of redesigning an architectural studio G. Lee, C.M. Eastman and C. Zimring, College of Architecture, Georgia Institute of Technology, Atlanta, GA 30332, USA Most design problems have multiple interacting constraints and levels of analysis. Some designers are able to reduce errors by developing heuristics and rules of thumb that lighten the cognitive load that such design problems impose. In this study we explore these heuristics by studying three groups of experienced architects solving a one-hour design problem that involves issues of multiple levels of spatial organization. Only one group was able to solve the problem. A special coding scheme was developed to explore the use of several kinds of heuristics such as problem decomposition into design units, rules of thumb from domain knowledge and strategic design moves. The differences in heuristics were examined to identify possible causes for these errors. 쎻 c 2003 Elsevier Science Ltd. All rights reserved Keywords: design errors, design processes, design methods, design problems, architectural design

1 Ward, T, Finke, R and Smith, S Creativity and the mind: discovering the genius within Plenum Press, New York (1995) 2 Eckert, C and Stacey, M ‘Sources of inspiration: a language of design’ Design Studies Vol 21 No 5 (2000) 523–538 3 Do, E Y -L, Gross, M D, Neiman, B and Zimring, C ‘Intentions in and relations among design drawings’ Design Studies Vol 21 No 5 (2000) 483–503 4 Goldschmidt, G ‘The dialectics of sketching’ Creativity Research Journal Vol 4 No 2 (1991) 123–143 5 Lugt, R V D ‘Developing a graphic tool for creative problem solving in design groups’ Design Studies Vol 21 No 5 (2000) 505–522 6 Crismond, D. ‘Investigateand-redesign tasks as a context for learning and doing science and technology’ PhD thesis, Harvard University, 1997.

E

ven experienced architects make design errors. However, with business practices involving multiple layers of contractors and clients, errors are potentially costly and time-consuming to correct if not caught early during design, and become expensive in either construction documents or in the construction phase. While much attention has been devoted to the generation of creative and novel designs1–6 and to the development of computational models for constraint managers and other expert systems to avoid design errors7–9, little attention has been devoted to empirical approaches to avoid design errors. Design errors have many sources, including (1) miscommunication between designers in different domains and procedures or (2) cognitive limits (too many constraints and requirements to consider at a time). Cognitive limits can also be considered as resulting from ‘mental sloppiness’, distractions, and other human reasons for error. Here, we generalize all of www.elsevier.com/locate/destud 0142-694X/03 $ - see front matter Design Studies 24 (2003) 411–435 doi:10.1016/S0142-694X(03)00002-4  2003 Elsevier Science Ltd All rights reserved Printed in Great Britain

411

these, using the term cognitive limits. In this paper, we focus on how architects reduce design errors by developing heuristics and rules of thumb that lighten the cognitive load. We asked seven architects, each with over 4 years of practical experience respectively, to redesign a 30 ft by 30 ft (9.1 m by 9.1 m) design studio for 16–18 architectural students. We divided the architects into three groups to facilitate verbal communication (two teams of two architects each and one team of three). We videotaped the architects designing and laying out workstations for students in the given studio space. The architects were provided with 10 additional requirements, reflecting actual studio conditions ranging from support for computers to pin-up space. Three jurors participated in judging each segment of the protocols and in analyzing them. However, only one group of architects successfully designed a studio satisfying the spatial requirements. Designing and laying out an architectural studio and its workstations is not as straightforward a task as it seems. First, the problem of redesigning a studio cannot be simply solved by dividing up and laying out some area in a studio by the number of students because architects must consider various design constraints and pedagogical needs as well as spatial arrangement. The space for each student must allow for drafting, displaying designs, making and stacking models, and for storage of drawing tools and drawings; it must also provide secure space for personal belongings such as textbooks, notebooks, and CDs. Moreover, since CAD systems are becoming prevalent in architecture, support for personal computers also must be provided. Whether students bring a computer to their studio or a school provides computers to students, the school needs to consider additional computer infrastructure and security in the studio, as well as space for the computers. Thus, in order to respond to the design task, the participants had to consider both a spatial allocation problem and how to embody the requirements and constraints.

7

Liggett, R S and Mitchell, W J ‘Optimal space planning in practice’ Computer-Aided Design Vol 13 No 5 (1981) 277–288 8 Gross, M ‘Avoiding conflicts in architectural subsystem layout’ Concurrent Engineering: Research and Applications Vol 2 (1994) 163–171 9 Eastman, C M (ed.) Spatial Synthesis in Computer-Aided Building Design Wiley, New York, (1975)

412

Like other design tasks, this problem involves design units that need to be studied at different scales. Here there are two design units, a workstation with its parts and a studio (or building bay) including the arrangement of workstations. If the size of a workstation changes, the change should be propagated to the arrangement of workstations in a studio. Otherwise, the required number of workstations may not be accommodated in a studio as it is actually designed. Our initial intention was not to compare each group, but to collect various design processes from three expert design groups. However, only one of

Design Studies Vol 24 No. 5 September 2003

them was able to solve the problem. In order to better understand why one group was successful and the others were not, we quantitatively and qualitatively compared the design process of the group which successfully accomplished the given design task with that of one of the other groups that did not succeed. The third group was not included in the comparison because they stopped their design process at an idea-incubation phase and did not provide any specific solution that could be assessed.

In Section 1, we discuss background and problem domains. In Section 2, we describe the three design protocol charrettes and their results informally. In Section 3, we briefly describe our method of analyzing move patterns between design units, an element of design that a designer can cognitively deal with, and show the analysis results of comparing two groups using the method. In Section 4, we compare design strategies of the two teams and explore how description methods and knowledge may help architects avoid design errors in this process. In this paper, we report each design and its protocol from a functional point of view rather than an aesthetic one. Nonetheless, we fully understand that a design cannot be judged by one or two aspects. Thus, we ask the readers to understand that we are not attempting to judge any of the designs in terms of good or bad, but focusing on a certain aspect of a design and how architects solve design problems in that limited aspect.

It may be useful at the outset to define several terms:

10 Eastman, C M ‘Cognitive processes and ill-defined problems: a case study from design’ in Proceedings of the International Joint Conference on Artificial Intelligence, Washington, DC (1969)

Avoiding design errors

앫 Design unit: (1) a physical element that forms a design10; (2) an element of design that a designer can cognitively deal with. 앫 Design: structured arrangement of design units. 앫 Design error: (1) a part of a design that can only exist on a drawing, but not in the physical world because it is impossible or inconsistent (e.g. a duct that goes through solid walls8, a bridge that supposed be 91 m in reality, but denoted as 100 m on a drawing); (2) a part of a design that lacks functions it must provide. A design error occurs when constraints and requirements of the design are not satisfied. 앫 Design move patterns (or move patterns): Patterns of design moves (see Section 3 for the definitions of design arguments and design moves.) 앫 Spatial allocation problems (or space planning problems): problems of finding a space layout that satisfies a set of constraints or is optimal according to some value function. Some of these terms are described in more detail later.

413

1

Problem domains

Several studies have used protocol analysis to explore the design processes. A good review is available in Cross11. Cross, quoting the studies of Fricke and McNeil, argued whether structured design approaches are effective in designing. Later, Cross and Cross12 studied two highly regarded designers. And they concluded that expert designers had a systemic approach to the overall design task and used first principles to guide their conceptual and detail designing. Beside the Cross and Cross’s study, several studies show that experts deploy more well-structured design strategies than novice designers.

11 Cross, N ‘Design cognition: results from protocol and other empirical studies of design activity’ in C M Eastman, W M McCracken and W C Newstetter (eds) Design knowing and learning: cognition in design education, Elsevier, Oxford, UK (2001) pp 79–104 12 Cross, N and Cross, A C ‘Expert designers’ in E Frankenberger, P Badke-Schaub and H Birkhofer (eds) Designers: the key to successful product development, Springer, London (1998) 13 Simon, D P and Simon, H A ‘Individual differences in solving physics problems’ in R Siegler (ed.) Children’s thinking: what develops?, Lawrence Erlbaum, Hillsdale, NJ (1978) pp 340–345 14 Atman, C J, Chimka, J R, Bursic, K M and Nachtmann, H L ‘A comparison of freshman and senior engineering design processes’ Design Studies Vol 20 No 2 (1999) 131–152 15 Rowe, P Design thinking MIT Press, Cambridge, MA (1987) 16 Gunther, J and Ehrlenspiel, K ‘How do designers from practice design’ in H Birkhofer (ed.) Designers: the key to successful product development, Springer, London (1998)

414

Perhaps the most well-known design approach of experts is a ‘working forward13’ or a ‘breadth-first’ approach. By contrast many novice designers use a ‘depth-first’ approach. Atman et al.14 compared freshmen and seniors in an engineering school. Similar to the working forward strategy in physics13, they found that seniors spent more time on understanding and gathering requirements in the beginning than freshmen. Also they claimed that seniors generated more alternatives than freshmen. Similarly, Rowe15 informally explored the design processes of three expert architects and claimed, ‘Essentially, established guidelines or rules helped the designers plan and prepare for subsequent exploration.’ Gunther and Ehrlenspiel16 compared design processes of draftsmen without education in design methodologies with those of designers with education in design methodologies at a university. The designers showed similar characteristics to the seniors in the Atman’s study. The designers gathered more information and generated more alternatives than the draftsmen. Skilled draftsmen could finish a design task faster than skilled designers. However, since efficiency, ‘design in the minimum time with minimum effort’, is a crucial factor in problem solving, they could not conclude which approach was better. These findings suggest that various groups employ different design approaches. However, no work that we are aware of has addressed a design strategy for specific design issues especially regarding a strategy to avoid design errors. In this paper, we focus on three specific research questions: (1) how architects propagate design changes through different scales of design units so as to avoid design errors; (2) how verbalization, texts, and sketches can be deployed in this process; and (3) what is a role of knowledge in avoiding design errors. In order to acquire answers to these questions, we set up three problem domains: design units, description methods, and knowledge. The protocols from the two design groups were segmented by every 15 s.

Design Studies Vol 24 No. 5 September 2003

The segmented protocols were judged and categorized by three jurors with respect to the above three problem domains.

1.1

Design units

Even experienced architects cannot consider all the design requirements and spaces at the same time. The design requirements vary from building codes to client’s requests, and the building elements from a small conduit hole to the whole building in terms of scale. Therefore, architects, in general, decompose problems to allow them to work on a unit that they can cognitively deal with at a time. The unit is called design unit10.

Although the method of design that is based on design units may reduce the number of constraints and requirements that architects need to consider at a time, it becomes a crucial issue for architects to propagate design changes in a design unit through all the related design units (so-called ‘patch neighborhood17’) without errors. Design units are strongly related to one another by their spatial relationship. As a result, if the design of a unit is changed, then the change propagates to related design units until there is slack in the structure that can accept the change without additional propagation. For example, if the size of a room is enlarged, then some other area on the same floor should be made smaller. Otherwise, the area of the whole floor, where the room is located, should be made larger. Such a relationship between design units exists not only between design units at the same level such as rooms but also between those at different levels such as a room and a whole building. Eventually, one small change in one place may affect the design of other floors or even the whole building. If architects fail to satisfy any of the design requirements or functions of building elements during design, then any small error often results in complex and costly ad hoc adjustments in the construction phase8.

17

Eastman, C M, Parker, D S and Jeng, T S ‘Managing the integrity of design data generated by multiple applications: the principle of patching’ Research in Engineering Design Vol 9 (1997) 125–145

Avoiding design errors

In this studio redesign task, our analysis focused on two design units, studio (a design studio) and workstation (a workstation within the design studio) so that we could observe how architects would adjust design changes of these two design units, each of which is normally considered at different scales. In addition to the above two categories, we added both as a category to represent ambiguous cases which could not be classified as either ‘workstation’ or ‘studio.’ For example, Table 1 is a partial protocol of Group B. In this table, participants are discussing laptops, general storage space, and safety issues, which may or may not belong to either workstation or studio. The three jurors who participated in this study judged such ambiguous cases as ‘both’ to avoid inconsistency in their verdicts.

415

Table 1 Examples of both, two partial protocols from Group B

Laptop 03:15 M: This will take a lot more space. Do you see what I mean? But this one would be the best setting whether it’s a laptop or… 03:30 T: I mean… Michael brought the point, which is an interesting point. Are we going to assume that they only have a laptop? And what if they can’t afford it? M: I think before we further get into this technological revolution, laptops… Storage and Safety 16:30 M: Storage is a real factor because these kids come in and this whole issue of security; how many times students come to you and guess what, ‘my handbag was stolen’, ‘my camera was stolen’, ‘my CD player was stolen’

1.2

Description methods

It is known that different description methods such as verbalization, sketches, and texts play different roles in design5, however it is not known that how architects deploy description methods to avoid design errors in different design stages. In order to explore the issue, we subcategorized a description method into verbalization, texts, calculation, sketches with dimension, and sketches without dimension. In addition, we distinguished calculation from reading or writing text, because we assumed that calculation might play a different role to reading or writing in an architectural design, where dimensions and measurements are important.

1.3

Knowledge

Knowledge is an important variable in design problem solving. Crismond6 asked expert, novice and naı¨ve groups to rank-order two devices before and after use. Experts were mostly consistent with their before-use rankings even after they used the devices, whereas novices and naı¨ve groups changed their rankings after they used them. He claimed that experts could predict the rankings better because of their knowledge of physics, mechanics, and ergonomics. Similarly, one may ask in what ways expert architects’ knowledge can help them predict or picture better what a building or space will be like in advance, allowing them to avoid certain kinds of design errors. We hypothesized that especially knowledge of existing buildings and historical architecture could help architects picture what their spaces might look like more realistically while knowledge of rules, principles, and codes, could help them design buildings more practically. In order to observe the role of such types of knowledge, we adopted Crismond’s distinction between vertical and horizontal connections to knowledge. If a designer

416

Design Studies Vol 24 No. 5 September 2003

made an analogy between his/her design and the abstract level of knowledge such as physics and mechanical principles, the analogy was called a vertical connection. If a designer made an analogy between his/her design and existing cases such as other products or designer’s experience, the analogy was called a horizontal connection. Even though knowledge broadly includes common sense, we distinguish knowledge from common sense in this paper. For example, if a participant stated that a foldaway desk was not durable or an L-shaped desk had a dead corner, we regarded the segments as common sense rather than knowledge. That is, knowledge in this paper is equivalent to specialized domain knowledge, knowledge that can be gained only through a professional training and/or experience. These three categories of design units, description methods, and knowledge were mapped as shown in Figure 1 to explore the relationships between them.

2

Design charrettes

We organized three design charrettes carried out on January 6, March 6, and May 22, 2001 respectively. The first group (Group A) comprised two architects, both of who had acquired an architectural license in Europe and had 6–8 years of experience in practice. One of them used to work as a project manager in an architectural firm and was teaching and studying how to apply computer technology to architecture at a university. And the other was still working as an architect in the USA, teaching at a university,

Figure

1 Design

units,

description, and knowledge

Avoiding design errors

417

and pursuing his PhD degree in architectural history and theory. The second group (Group B) consisted of three studio instructors. Two of them had wide experience in practice and were still working as architects. And the other had a strong background in building facilities and technology. The third group (Group C) included two practicing architects at a renowned architectural firm both with more than 4 years of experience in practice. One of them won a local American Institute of Architects (AIA) award last year. Based on the knowledge and experiences of the three groups, we could define all of them as expert architect teams. In order to facilitate participants to think aloud, we asked each group to work as a team. The whole charrette including 15 min of introduction to the design problem and 60 min of a design session lasted about 75 min. Each group worked for the complete session. The design task was to redesign an existing architectural studio at a university to meet the needs of the era of computer technology. All three groups were familiar with the studio. A written design instruction, which had the following 10 requirements, was given to participants. C1: ‘The furniture consists of modular units’. C2: ‘The modular units include computer support, storage, pin-up and drawing space.’ C3: ‘The new furniture is fabricated in the new Advanced Wood Products Laboratory.’ C4: ‘Students are bringing their own computers.’ C5: ‘Security of the student-owned machines is an issue.’ C6: ‘The furniture should be durable; typical drafting tables last about 15 years.’ C7: ‘The workstation should be reconfigurable so they can be arranged in some studios for team projects’. C8: ‘The bay size is 30 ft by 30 ft (9.1 m by 9.1 m), with 5 ft (1.5 m) off the inside of the bay for storage. The corridor inside of the bay is 2.5 ft (0.8 m).’ C9: ‘Each bay needs to support 16–18 students.’ C10: ‘In some bays, a plotter may be placed for output.’ The requirements from C1 to C7 were related to a workstation and the requirements from C8 to C10 were related to a studio (bay) layout. The given requirements included several design issues such as modular coordination, reconfigurability, durability, computer support, and security.

418

Design Studies Vol 24 No. 5 September 2003

The main problem was spatial allocation. The given requirements imposed a very tight studio layout, which left little freedom in its design. The maximum area of each workstation could only be approximately 6 ft by 6 ft (1.83 m by 1.83 m) if corridor space and storage spaces are subtracted from the bay area without considering plotter space and other utility space. The area of 6 ft by 6 ft (1.8 m by 1.8 m) might be ample for one simple drawing table. But it was not an easy task even for experienced architects to include all the requirements (i.e. computer space, storage space, pin-up space, drawing space, and aisle space between workstations) in a 6 ft by 6 ft (1. 8m by 1.8 m) workstation. On the other hand, if architects increase the individual workstation area to satisfy the requirements easily, they are not likely to be able to accommodate 16–18 students within the 30 ft by 30 ft (9.1 m by 9.1 m) bay area. To solve this problem, the workstation area should be examined accurately in the given time both from the studio level and from the workstation level. Another critical design problem was how to conceptualize a near-future studio environment and to make a studio support a near-future environment involving increased use of computers and CAD tools. Group A and Group B did not have an intensive conversation on this topic although both groups had an expert in either computing or technology. They seemed to have a tacit agreement among members that the near-future architectural work environment would not be far different from that of today. A major concern of both groups was whether students would bring a PC or a laptop, which could affect the size and the configuration of a workstation. However, Group C had a very interesting idea. They assumed that students would doodle and discuss their design as a team or as an individual on a big Ushaped table, located at the center of the studio. Whenever student’s ideas became mature, they would move to computer sections on both ends of the studio and would start to specify their design using CAD tools (Figure 2, above). Group C also thought that presentations and pin-ups would be performed using an LCD projector (Figure 2, below). At the end of the design charrette, Group C added that they were working at their office in the same way as they described. Even though Group C had an interesting idea about the near-future studio environment, the group did not complete their task and left their design as a conceptual sketch. Since our interest was to observe how architects go about transforming and resolving relations among design units while turning their thought into a specific design, we decided to drop Group C’s design from our analysis. Group A and Group B finished and presented their drawings in an intelligible format with annotations and measurements on them within the allotted time. However, while reproducing Group A’s

Avoiding design errors

419

Figure 2 A plan and a section of a studio designed by Group C. (Above) A plan of a studio: a U-shaped drawing table in the center and two rows of CAD tables on both ends. Group C assumed that the other side of the display wall (screen) would be used as a pin-up space. (Below) A horizontal section and a vertical section of a studio: a presentation using an LCD projector

design with a CAD tool to analyze it, we realized that they could not accommodate 16–18 workstations in the given studio area. At the end of the design charrette, Group A settled their final design and redrew a workstation (Figure 3) and a studio (Figure 4) with measurements and annotations on them. Their final design had 16 workstations of 5 ft by 8 ft (1.5 m by 2.4 m), a resting space, and a display space in the middle of the studio. The resting space accommodated three sofas on the right side, and a refrigerator and a microwave on the left side. The display space that was surrounded by display walls had a ‘big’ table in the middle.

420

Design Studies Vol 24 No. 5 September 2003

Figure 3 Group A’s drawing of a workstation

Figure 4 Comparison between Group A’s final drawing and researchers’ CAD drawing

Based on Group A’s final drawings, we traced their workstation layout in CAD to be more accurate. Contrary to their final drawings, we could only accommodate eight workstations of 5 ft by 8 ft (1.5 m by 2.4 m) and two sofas in the resting space (Figure 4). Thus, we recalculated a workstation area based only on the scale of Group A’s drawings, ignoring their measurements. Then, the workstation area became around 3.5 ft by 7.5 ft (1.1 m by 2.3 m), which was too thin to accommodate a drafting table and a computer desk. For the display space in the middle, we arranged a normal office-desk-size table of 5 ft by 3 ft (1.5 m by 0.9 m) instead of putting a big table as

Avoiding design errors

421

Group A planned. Still, it seemed to take too much space to allow students to gather around for a pin-up (Figure 4, right). On the other hand, Group B could accommodate 15 workstations within a studio, which was slightly smaller than the given requirements (16–18 workstations). They reinterpreted and changed the given requirements because they reported during the protocol that 16 –18 heavily equipped workstations within a 30 ft by 30 ft (9.1 m by 9.1 m) studio were too dense (Figure 5). They explored from 10 to 20 workstations in a studio, and then finally decided to work with 15 as a trade-off with their own constraint, ‘Maximize space for each student’. However, Group B’s design had a critical shortcoming. They did not illustrate an access to workstations on the right side of the studio (Figure 5, left), even though a CAD drawing generated by us, based on their design and measurements, showed that they had enough space for the access (Figure 5, right). Nonetheless, we concluded that Group B was fairly successful in accomplishing the given goal overall. Moreover, during their design process, Group B showed an interesting way of specifying their design. To understand their design process better, we compared and analyzed the design process of Group B with that of Group A. The results of analysis are presented in the subsequent sections.

Figure 5 Comparison between Group A’s final drawing and researchers’ CAD drawing

422

Design Studies Vol 24 No. 5 September 2003

3

Quantitative analysis: design move patterns

To observe architects’ patterns of working on design units closely, two semantic analysis units were deployed: design moves and design arguments, which were borrowed from Goldschmidt with certain changes. Goldschmidt4 defined design moves as ‘an act of reasoning which presents a coherent proposition pertaining to an entity that is being designed’ and design arguments as ‘the smallest sensible statements, which go into the making of moves’. However, after a couple of trials to apply them to a protocol analysis, we realized that these definitions were not easy to deploy. In general, an ‘argument’ represents a course of reasoning, which can be segmented by a semantic shift between thoughts or topics. In her definition, the argument is defined more syntactically (i.e. the smallest sensible statement) than semantically. It was problematic because sometimes a protocol was unnecessarily divided into small chunks (see Goldschmidt4 for examples). Another problem arose from the definition of design moves. In her definition, design moves are defined by an act of reasoning. However, since an act of reasoning is not well classified yet, it was vague and subjective what to define as a design move. We redefined a design argument as ‘a piece of conversation on one issue related to constraints, requirements, ideas, and goals’ and a design move as ‘a shift of topic in a sequence of design arguments from one design unit to another’ similar to the traditional concept of ‘moves’ in the Towel of Hanoi Puzzle18 or in chess. To design moves and arguments, we added three suffixes, n (new), r (revised), and c (continued or repeated) to distinguish the novelty of each argument. The concept of new design arguments is consistent with that of Akin’s Novel Design Decision (NDD): (1) the NDD resolves a problem or bottleneck; (2) the NDD does not follow from previous assumptions; and (3) the designer identifies the NDD as an important feature of the overall design19. A revised design argument is a design argument, which is already stated but restated with certain changes in design such as addition of a new design unit that can add a new or different function to a current design, or changes of a value or a size of space that can affect the whole design. And a continued or repeated design argument is one with no or insignificant changes.

18

Simon, H A ‘The functional equivalence of problem solving skills’ Cognitive Psychology Vol 7 (1975) 268–288 19 Akin, O and Lin, C ‘Design protocol data and novel design decision’ Design Studies Vol 16 No 2 (1995) 211–236

Avoiding design errors

To see if there were significant differences in the number of design arguments, we counted the number of design arguments of Group A and Group B. As described earlier, we used the workstation and the studio as the design units in counting the design arguments. Surprisingly, even taking the subtle differences of judging three different design argument types (new, revised, continued) into account, there were not significant differ-

423

Table 2 The number of design arguments

New design arguments Revised design arguments Continuous or repeated design arguments Total design arguments

Group A

Group B

23 63 8 94

28 70 181 279

ences between the numbers of new design arguments and revised design arguments generated by two groups while the numbers of continuous or repeated design arguments were quite different (Table 2). These results may imply that the number of ideas generated by designers during a design session does not always correlate with the result of a design. Crismond6, in his novice-expert study, claimed that there was no significant difference in the number of ideas generated by novice, naı¨ve, and expert groups. However, we are reluctant to draw any specific conclusion from this result because the sample size was too small. We were also hesitant to conclude anything from the difference in the number of continuous or repeated design arguments because it could simply mean that Group B spoke more and faster than Group A. But the number of design moves made by Group A and Group B was quite different both in the minimum number of design moves and in the maximum number of design moves. Table 3 shows that the number of design moves counted based on the sequence of design arguments. Group B made 92 design moves between design units at the maximum and 54 design moves at the minimum while Group A made 20 design moves at the maximum and seven design moves at the minimum (Table 3). This result shows that Group B changed the design units more frequently than Group A. Design move patterns in Figure 6 illustrate this difference more significantly. We set the studio at the value of 1, the workstation at the value of ⫺1, and the both at the value of 0 simply for a graphical representation. Since Group B has more design arguments than Group A, Group B’s design move pattern looked more dense than Group A’s. However, regardless of Table 3 The number of design moves

Design moves (min) Design moves (max)

424

Group A

Group B

7 20

54 92

Design Studies Vol 24 No. 5 September 2003

Figure 6 Design move patterns

their density, we could clearly see that Group B moved from the studio to the workstation more frequently than Group A in Figure 6. In order to better understand the implications of the frequent design moves in avoiding design errors, we analyzed Group A’s and Group B’s design processes qualitatively and in more depth.

4

Qualitative analyses

As stated earlier, finding an adequate workstation area is one of the critical factors to resolve to succeed in this design charrette. In qualitative analyses, we first compare each team’s search strategies for an adequate workstation area. In this exploration, we especially focus on how they employed description methods such as conversation, calculation and sketches in finding an adequate workstation area. Additionally, we describe what role each team’s knowledge played in their design process.

4.1

Search strategies for an adequate workstation area and description methods

We explained design requirements for about 15 min and gave Group A and Group B an instruction. Members of Group A started their design session with individually analyzing the problem for 5 min. After the problem analysis, they decided to draw a 30 ft by 30 ft (9.1 m by 9.1 m) bay on a sketchbook to ‘see’ how much space each student can have (Table 4). After generating three alternatives for circulation (Figure 7), Group A

Avoiding design errors

425

Table 4 Group A’s partial protocol (from 5:30 to 5:45)

Group A (5:30–5:45) A1: No, that’s fine. But what I saw was we have given space… Why don’t we start from here and sketch circulation and see how much space each student can have

Figure 7 Reproduction of Group A’s three alternatives by authors: bold gray lines indicate circulation

decided to adopt the U-shaped circulation with workstations on the outside of the circulation and common space inside the circulation (Figure 7, right). But Group A intuitively realized that they needed more space to accommodate more workstations by looking at their drawing. Since Group A thought that they could mirror the half of a studio layout to the rest of the half, Group A worked only on the half of the studio to save time. Group A arranged 7–8 workstations on both sides of the U-shaped circulation, and then calculated an individual workstation area (Figure 7, middle). Group A thought that the workstation area was too confined. Thus, Group A decided to make the workstation larger. Group A measured the new individual workstation area and it was 6 ft by 6 ft (1.8 m by 1.8 m). However, Group A wanted to leave the center of a studio as a resting place (the common space). In that case, Group A could not put more than six workstations on the half of a studio (Figure 7, right). Thus, Group A decided to make the workstation narrower and longer. The narrower and longer workstation reduced the area of the common space in the middle of the studio but made room for more workstations on the other side of the circulation (Figure 8). After Group A elongated the workstation shape, Group A could accommodate seven units on one side of circulation. Group A added three workstations in the center of the bay (Figure 8), but soon removed them, because

426

Design Studies Vol 24 No. 5 September 2003

Figure 8 Reproduction of Group A’s draft design

they wanted to add a display space with a big table instead. The group measured a workstation area on the sketch. The measured workstation area was 5 ft by 8 ft (1.5 m by 2.4 m) (Figure 3) (this occurred around 20 min after they started to design). The design process through the first 20 min is illustrated in Figure 9. Even though each workstation on the sketch was drawn in a slightly different size (Figure 4), Group A assumed that all the workstations were drawn equally; they fixed the workstation area at 5 ft by 8 ft and elaborated each individual workstation design within 5 ft by 8 ft. Towards the end of the design charrette, Group A looked at their design at the studio-level and added one more workstation on one side of the studio and also added more furniture in the resting area. The new changes again seemed reasonable graphically (Figure 4, left), but, in reality, the design could not work (Figure 4, right). Members of Group A might have been able to realize that their measurements were wrong if they had confirmed their measurements by roughly calculating how many workstations of 5 ft by 8 ft could fit into a studio. Overconfidence in the measured dimensions and the lack of coordination between the workstation design and the studio design led Group A to a nonsensical design at the end (Figure 4). On the other hand, Group B started from brainstorming. They generated

Avoiding design errors

427

Figure 9 Group A’s search process for a workstation area until 20 min

20 Feynman, R P ‘Lucky numbers’ in E Hutchings (ed.) Surely you’re Joking, Mr. Feynman!’: adventures of a curious character, W.W. Norton, New York (1985) p 350

428

sub-goals and, what they called, ‘scenarios’: (1) designing a vertical workstation to maximize workstation volume; and (2) letting each student use their computers on their desks instead of having a centralized computer space. During the brainstorming phase of 7 min or so, Group B only used sentential description method; namely, verbalization and texts (Figure 10). Then, similar to Feynman’s mental calculation method20, Group B approxi-

Design Studies Vol 24 No. 5 September 2003

Figure 10 Group B’s early notes

mately calculated a workstation area by changing numbers to easy-to-calculate numbers: In the beginning, Group B set the number of workstations at 10 and 15 but when Group B had a workstation zone of 720 sqft (66.7 m2), Group B divided it by 18 workstations with which Group B could easily get 40 sqft (3.7 m2) as a workstation area. When Group B needed to factorize a workstation of 40 sqft (3.7 m2) to get the width and the depth of a workstation, Group B simply set them at 8 ft by 4 ft (2.4 m by 1.2 m), which was still smaller than 40 sqft (3.7 m2) but adequate for a workstation area (Figure 11, upper right corner). Mostly by mental calculation and sometimes on-paper calculation, Group B was able to quickly and easily crosscheck the changes in their workstation design and a studio layout and adjust them. As time went by and the details of design were added, Group B could refine the workstation to be more accurate. In comparison with Group A, Group B was able to recheck and revise the size of workstation three times more than Group A (see Figures 9 and 12). As Group B acquired a more specific design and the size of a workstation, they started to use a more accurate way to crosscheck the validity of their design. First, Group B drew a studio with a scale and then tried to find possible layouts. Again, Group B changed the number of workstations to 15 and adjusted the workstation size to a new design scenario. In the next place, Group B drew a set of four modular workstations on a sketchbook. Then, they cut out the set of four modular workstations with a ruler (later with a pair of scissors). And Group B arranged them within a studio drawing like a jigsaw puzzle. While arranging the paper workstations within a studio, B1, a member of Group B, lost his sense of scale once because 15 workstations did not fit in a studio as he expected (Table 5).

Avoiding design errors

429

Figure 11 Group B’s early sketches

Table 5 Group B’s partial protocol (from 43:45 to 44:00)

Group B 43:45–44:00 B1: Let’s see. O.K. There’s four. Am I right? Am I out of scale? (Checking with a scale)

After Group B confirmed, using a ruler, that their design was too wide, they modified the design of the modular workstation. They went through the same process described above again and added more details on their final workstation. Even though members of Group B had years of professional experience and knowledge in architecture, it was interesting that they did not rely only on their sense of scale, but also on the actual comparison of changes in design units. This might have to do with human limitation in vision rather than architect’s experience or other factors. For example, if an architect drew a table smaller than a normal size table, the size of a room might look larger. That is, even experienced architects can lose their sense of scale due to relativity of visual perception. Figure 12 illustrates how Group B acquired an adequate workstation area. First, we can see how complex the process is. The process became complex

430

Design Studies Vol 24 No. 5 September 2003

Figure 12 Group B’s search process for a workstation area

because Group B tried to propagate design changes through the design units of two different scales and crosscheck the validity of design whenever design changes were made. It also explains why Group B made design moves often as observed in Section 3. In order to crosscheck the validity of design through different design units, Group B had to switch from one design unit to another. Also, Figure 12 illustrates that Group B changed their description methods depending on design stages. In the beginning, Group B discussed (verbal description) alternatives (or scenarios). Then, Group B acquired an approximate size of a workstation by mental calculation. While specifying it, Group B gradually adopted more accurate description methods including sketches and paper mockups. During refinement from an approximate size of a workstation to a specific size, Group B could adjust the size of a workstation. And they could put 15 workstations into a 30 ft by 30 ft (9.1 m by 9.1 m) studio.

Avoiding design errors

431

4.2

Knowledge

In addition to the previous two analyses, we analyzed the role of knowledge in avoiding design errors using the distinction of horizontal and vertical connections defined in Section 1.3. Unfortunately we could not find any trace of Group A making a connection to their knowledge, except for those that might have been expressed tacitly in their drawings. In contrast, we could observe several cases of Group B making connections to their knowledge (Table 6). As a vertical connection, Group B recalled that there was a fire egress requirement and applied it to their design. We could not judge Group A’s and Group B’s designs by this fire requirement. But if it were a real project, fire requirements could be a significant factor to consider (Table 7). As a horizontal connection, Group B made several connections to existing spaces (Table 8). When B2 proposed to ‘go vertical’, B3 gave an example of a vertical workstation at Ann Arbor and that led B2 to other alternatives. Among the members of Group B, B1 was relatively outstanding in recalling similar examples. In a couple of cases, when B1 wanted to describe his ideas, he used specific examples of his colleague’s (Jude), Philip Stark and Heinrich Tessonow that could be shared by the other members of Group B. Also, by making an analogy between the size of a workstation with that of a ranch house bathroom, members of Group B seemed to picture a more accurate image of a workstation and to confirm if the size of a workstation was alright. Another role of knowledge observed from this case study was similar to findings of Eckert and Stacey2. Eckert and Stacey claimed that designers in Table 6 The number of horizontal and vertical connections

Horizontal connection Vertical connection

Group A

Group B

0 0

6 1

Table 7 Group B’s vertical connection to knowledge

Vertical connection

Transcription

Fire requirement

7:15–7:30 B1: Out of that 30 ft by 30 ft, we have to accommodate the fire egress requirement, which is 10 ft by 30 ft or probably 7 ft. The minimum will be 6 ft by 30 ft, I think

432

Design Studies Vol 24 No. 5 September 2003

Table 8 Group B’s horizontal connection to knowledge

Horizontal connection

Transcription

Ann Arbor Lab

12:30–12:45 B2: I think we almost have to go vertical B1: I would agree with that completely B3: They have that at Ann Arbor in the building sound lab - that situation B2: Now there are other scenarios that I have seen 15:45–16:00 B1: Yeah. I was thinking you might take a…even look at the cart settled downstairs. I think Jude made those that have some storage inside of them 22:45–23:00 B1: And then 30 divided by 6. We got 18. So we got to divide 30 by 6. We got only 5ft. So, we are getting a basically bathroom. A ranch house. A residential ranch house burger bathroom size to work in 39:15–39:30 B1: Maybe we can look at… Do you have any Heinrich Tessonow book in here that we can look at? 39:45-40:00 B1: Actually Philip Stark did folding campus carts and these basic kinds of 10 pieces that were really cool…

Jude’s cart

Ranch house Bathroom

Heinrich Tessonow

Philip Stark’s folding campus carts

their study often used ‘a language of design’ that seemed to help designers communicate more specific ideas. If we regard a language of a domain as a representation of domain knowledge, our observation is consistent with that of Eckert and Stacey.

5

Discussions

We studied the design approaches of three practicing architect groups (Group A, Group B, and Group C) to observe how design errors could be avoided. They redesigned an existing 30 ft by 30 ft (9.1 m by 9.1 m) studio in order to satisfy new requirements, i.e. accommodating 16–18 workstations with computer support. We compared and analyzed their design approaches. First, we observed and analyzed the design move patterns between two design units: the studio and the workstation. Design move patterns of two groups illustrated that Group B moved between two design units much more frequently than Group A. By changing the design units frequently, Group B could propagate design changes through two design units and crosscheck the validity of their design from two different scales while modifying their design. Group B once lost their sense of scale, but could notice that immediately in the process of crosschecking their design between two

Avoiding design errors

433

different design units. On the other hand, Group A also lost their sense of scale, but could not recover it until the end of their design process. One finding of this study is that even experienced architect groups like Group A and Group B could lose their sense of scale. Therefore, a design method that can keep architects from losing their sense of scale is essential in architectural design. Second, we analyzed Group A’s and Group B’s design process in terms of descriptive methods such as verbalization, calculation and sketches. We observed how Group A and Group B employed each description method while searching for an adequate workstation area. As a result, we found two methodological differences in the two groups: (1) Group B started to design a workstation from approximate mental calculation of a possible workstation area based on their ‘scenarios (alternatives)’. Then Group B elaborated the workstation design considering the limit of studio area as changes were made in the workstation design. On the other hand, Group A fixed a workstation area at a specific size in the beginning and carried the workstation size till the end of their design process; (2) Group B was able to acquire the adequate size of a workstation very efficiently by employing various description methods such as discussions, mental calculation, sketches, and paper mockups in a very structured way while Group A was not. In a macroscopic view, the description of Group B’s search process can be simplified as a, so-called spiral process15, p. 48, which is similar to ‘working forward’ or ‘breadth-first’ problem solving methods. However, it is much more iterative and multi-dimensional than what can be described as a single spiral process. Group B’s search process can be characterized as parallel design processes on multiple design units and complex crosschecking and coordination between the design units. The design process can be more easily explained by making an analogy to a tire-lug-nuts tightening process (Figure 13). First, position each design unit as if a technician places lugnuts on a tire. Then gradually adjust and detail them one by one as the design is elaborated. Also, it is important to select an appropriate tool according to stages. We do not need to use a wrench to fasten lug-nuts from the beginning. Sometimes fingers are more efficient. Third, we analyzed how two groups utilized their knowledge. We categorized knowledge into two sets: one set includes rules, principles and codes. And the other set includes cases, historical building and architects. We called the former a vertical connection, and the latter a horizontal connection. Group B made several analogies between their design and existing

434

Design Studies Vol 24 No. 5 September 2003

Figure 13 A lug-nut tightening analogy

designs in picturing an actual shape of their design. Group B could communicate better by sharing a more specific idea of what a member was explaining and could picture and validate a design more accurately by making analogies to bodily or indirectly experienced space. It could prevent possible design errors. Assuming that knowledge is based on learning and experiences, this finding reconfirms the importance of education and experiences in architectural design process. This paper reported the design processes of two architectural groups in detail and focused on several potential factors related to design errors. The issue of mapping between different representations, especially on different scales (or levels), appears from this study to be a factor affecting design errors. We observed that an architectural design group could overcome the mapping issue and minimize design errors by crosschecking and coordinating multiple design units and by deploying the vertical and horizontal knowledge (especially bodily experience) and the rich description methods including mental calculation and paper templates. Other factors and remedies for design errors are yet to be investigated and are research directions, which we intend to explore.

Acknowledgements The authors are grateful to the participants of this study, including Michael Gamble at Georgia Tech, and two outside jurors, Frank Wang and Aniruhd Moudal for their passion for design and exhaustive analyses.

Avoiding design errors

435