This post started out as a few reflections on a few distance design education events I attended recently, where most of the discussions did not centre around online vs face-to-face or technology and IT services. Instead, discussion focused on learning and teaching – basic stuff, like ideas around how to make learning activities engaging (for staff as well as students…).
Because that’s a messy human problem, not a technical one, Gaston Bachelard and Christopher Alexander both came up in discussions a few times. What they both have in common is their attempt to make sense of the ‘messy space between people and things’ (Koskinen et al, 2011). In research, this is where there’s too much evidence to ignore the fact that there is something going on but it’s hard to really know what this is.
This ‘messy space’ is actually a really important type of thinking that we do as designers and that we encourage in our students. But because it’s vague, difficult and valued far less than the end product, we tend to talk a lot about it and then just hope that students ‘get it’ as they experience it through designing.
Of course, that’s not much use for education colleagues who are not learning to become designers… To respond to this challenge, I’m going to use bits of science and architectural philosophy together, and hope that the two don’t cancel each other out.
At the end, I’ll get back to how this relates to distance design education – so if you’re thinking “???”, feel free to skip to the end where there’s a list.
Ideas matter more than reality
First, the science bit.
Basically, we have a load of assumptions about how we relate to the world around us – many of them are completely wrong.
Firstly, we are not perceiving machines: for example, we don’t just ‘see’ whatever we perceive through our eyes. Our visual system is composed of a number of different cognitive systems: some dedicated to specific things (such as people’s faces) and others to more general cognition (such as our ability to use spatial thinking to more than just ‘see’). Basically, our visual system, like most of our other cognitive systems, is not a single, linear or simple process – it’s complex, convoluted and recursive (Dehaene, 2020).
Secondly, that recursive loop just mentioned is critical: what we have already perceived affects future perceptions. It’s a cognitive learning process and a deeply important part of being human (i.e. Homo Sapiens). For example, we don’t see colour until we are taught what colours is – there are no universal colours such as ‘red’; it all depends on how we learn what colour is (Lotto, 2004). And that’s before we even consider how such learning is affected by our own environment and behaviours (see The Dressfor an example).
Thirdly, all of this is before we take into account even higher order cognitive biases and prejudices. The famous study by Hastorf and Cantrell (1954) identified that people at the same sporting event saw things differently depending on which team they supported. Pretty obvious, you may think, but how often do we take this seriously and realise that people really do construct different realities based on their preferences. Our memories are not accurate facsimiles of objective facts: we make them up each and every time we ‘remember’. You will use your biases to conceive of the world around you in particular ways and, the more you do this, the more reinforced these ideas become.
The ideas (conceptions) we construct of reality are often far more important (or ‘real’) than reality itself.
Back to virtual reality
This is why we do see evidence of ‘physical’ things happening in ‘virtual’ environments – things you wouldn’t expect to see. For example, students can report feeling claustrophobic in some architecture in virtual environments (Minocha & Tungle 2008). This example has a physical analogy in the Mémorial des Martyrs de la Déportation. In both cases, being able to only see the sky, but not the horizon, can lead to feelings of claustrophobia: in the second example this is deliberate; in the first example it was accidental.
In both, it is the conception, the idea in the mind of the person, that is common.
This is quite an extreme example of a conception in two very different environments. More usefully, conceptions can be understood as effective ways of transferring ideas. Cognitively, this is the process of thinking of a generalised version of particular things – that the word dog can refer to multiple concepts involving dog, from things with four legs to Snoopy (Dehaene, 2020): what our cognitive systems are good at is thinking at these scales of concept and then applying the most appropriate version for the given context.
But more generally, we can do this at even more abstract levels. In cognitive linguistics, these abstractions, referred to as conceptual metaphors, are where we apply some common cognition (like sense or meaning) from one concept to another. For example, we talk about ‘having’, ‘losing’, ‘keeping’ ideas even though we can’t see or touch them. Lakoff and Johnson (1980) famously constructed their embodied cognitive metaphors this way, arguing that even concepts like ‘in’ are conceptual metaphors that we transfer from one thinking domain to another. Hence, we can be ‘in’ a room but we can also be ‘in’ love or ‘in’ an organisation, or even ‘in’ trouble.
Each ‘in’ has to be understood as being related to each other. This makes it really easy to translate ideas: it’s how we can talk about really complex things, like ‘justice’, ‘home’, or ‘openness’. (This is also, potentially, one of the key ways that pluriversality can emerge, rather than the either-or of difference/universality in current dominant structures and narrative. But that’s another story…)
Making things harder
So far, we’ve mostly seen examples of transferring conceptions or using them to make complex things simple.
But sometimes we simplify things far too much:
“It is simplicity that makes the uneducated more effective than the educated when addressing popular audiences.”
Hence, using conceptual metaphors can be a useful way of making simple things more complex – not for the sake of making things difficult, but nuanced enough to be of utility in the design process. This might be: representative enough of complexities; open enough to allow creative divergence; communicable enough to work with others; etc.
What we’re looking for is the optimum conception for the activity at hand: not too complex and not too simple.
Any designers reading this will get it immediately: you don’t want to jump to solutions too soon; you don’t want to over-specify; you don’t want to make the problem too distributed and complex, but you don’t want it too simple either.
All good creative design processes operate in that Goldilocks space of it being not-too-simple / not-too-complex. And we (designers) have loads of tools we use to make things more or less complex depending on the circumstances and need. In doing so we are creating a space where things are both defined and not defined at the same time. Keeping this balance is really important: defined, but not too much. Undefined, but not too much.
This is not a contradiction or a fudging of what’s true: it’s a level of cognitive conception that allows contingent uncertainty (1). At some point this uncertainty will collapse (to some specific idea) but it’s a state of thinking that we can (mostly) return to at any point and rework.
In other words, our imagination is more valuable than other cognitive processes for some complex activities – we can use our imagination to define as well as create the world, not just to come up with ideas…
Back to Bachelard
Which is where Bachelard comes back in. He deliberately writes about architecture as poetry (or I should say, poetry as architecture!) because it allows the ideas he’s talking about to be both defined and not-defined at that same time. We all ‘know’ what home is; but we might not agree on what colour it should be.
Thinking like this can be exceptionally valuable because it moves from the very specific to the very general and understands how these relate, as well as their limitations. Have a read of Ritchey’s (1991) paper on how Riemann did this to understand the mathematics behind hearing.
Bachelard is using a mix of different scales of cognitive conception. In fact, much of his work could be thought of as a series of conceptual metaphors that try to communicate the human qualities of architecture: their experience and meaning (Bachelard was writing as a phenomenologist). Critically, he was conveying this as a writer so he was necessarily using cognitive linguistic metaphors.
Beyond the technical words there is a conceptual simplicity to his work. When Bachelard describes the porch, he describes the human experience of being on a porch: what it feels like; what people do (and can’t) on porches; what the world looks like from a porch. Critically, it’s not the porch itself that enables this experience: it’s the human doing the conceiving as a result of being-in the porch (non-attribution deliberate…).
That might make you wonder whether everyone, everywhere does indeed share a similar experience of porch. Christopher Alexander took this idea further but looked at it from the ground up: if we keep seeing the same shapes in architecture all over the world and across all cultures, then that suggests a deeper pattern in human behaviour. Alexander came up with a number of patterns from human settlements and the built environment and called it a Pattern Language (Alexander et al, 1977).
But, critically, Alexander recognised that these patterns needed to be defined at the right ‘scale’ – not too defined but not too vague either. In addition, he also introduced the idea of a ‘quality without name’ (2) to refer to the underlying human value of each pattern – what it is about the pattern that people value.
This brings us back to teaching design at a distance. (you still here?)
The discussions I referred to at the start have done a similar thing. Firstly, they focused on the human value and purpose of what we intend by design education. Secondly, they use a range of scales of metaphor to discuss this, something designers are particularly good at (a two line sketch can represent The Infinite Void or a soap dispenser…).
So I suppose that what’s finally useful is to explicitly recognise and acknowledge the value of this type of thinking, knowledge and discussion. In fact, to promote its value beyond discipline conversations and use it actively to engage with others (we already do this, but perhaps don’t realise it). Especially when thinking about what you need to teach at a distance.
So here’s the List of Fun Things to Try with Conceptual Metaphors:
Start with conceptions, not solutions or tech. Instead of saying ‘I need a Virtual Design Studio’, ask yourself what the studio space should feel like (using conceptions). What is the ‘quality without name’ you’re looking for (just because you can’t name this it doesn’t mean you can’t describe it)? Have a look at the dimensions listed herefor ideas and use these to brief, specify and discuss requirements with others. You do not have to fall into the trap of using reductive tech language to ask for what you need for your students.
Use conceptual metaphors, not tech names. Someone else mentioned this at the CHEAD event, but to call a lecture a ‘Webinar’ is to deliberately draw attention to the technical medium. We don’t call seminars ‘f2f-inars’ … (OK, clunky example…). If an event is a tutorial then it’s OK to call it a tutorial regardless of where and how it’s arranged – it’s the human value that’s more useful to communicate than the medium or mode.
Make some key things more complex, not less. If you need a particular atmosphere or feeling (a ‘quality without name’) in your studio or class then state that clearly. Be confident about your uncertainty – describe this as boundaries of knowledge rather than just ignorance (you’re technically an agnotologist). But don’t hide it either – be open about how we use uncertainty with colleagues and especially students (give them something solid if they need it).
Be critical and reflective when you do this. I haven’t touched on the dark side of this type of cognition (it can be very dark indeed) so make use of the other major tool in our design toolkits – our ability to evaluate the process at the same time as engaging in that process. Using some simple, critical frames to help you critique from other perspectives.
Anyway, I hope that made some sense. Not sure if it all got a bit out of hand at one point but it ended with a list, so maybe it’ll be fine…
(1) Cognitive uncertainty may have analogies to, or even be a form of, of cognition-as-optimisation theories (error reduction; reward optimisation; etc.), where the fuzziness of uncertainty is used in conjunction with other cognitive feedback processes to ‘get to’ some cognitive resolution.
(2) This ‘quality without a name’ has been thoroughly criticised for good (and bad) reasons, so to give it a bit of life here I’ll suggest that it is “an appropriately scaled cognitive conceptual gestalt (or conception) interrelated with human experiences and phenomena that operates with sufficient similarity across large numbers of peoples to be evidenced in their constructed artefacts and habits”. Gaston would be horrified.
Alexander, C., Ishikawa, S., Silverstein, M., Jacobson, M., Fiksdahl-King, I. and Angel, S. (1977) A Pattern Language, 1st edn, New York, Oxford University Press.
Hastorf, A. H. and Cantril, H. (1954) ‘Case reports. They saw a game: a case study’, The Journal of Abnormal and Social Psychology, vol. 49, no. 1, pp. 129–134.
Koskinen, I., Zimmerman, J., Binder, T., Redström, J. and Wensveen, S. (2011) Design Research Through Practice, 1st edn, Waltham, Elsevier Inc.
Lotto, R. B. (2004) ‘Visual Development: Experience Puts the Colour in Life’, Current Biology, vol. 14, pp. R619–R621.
Oldenburg, R. (1999) The Great Good Place: Cafaes, Coffee Shops, Bookstores, Bars, Hair Salons, and Other Hangouts at the Heart of a Community, Da Capo Press.
Ritchey, T. (1991) ‘Analysis and Synthesis On Scientific Method – Based on a Study by Bernhard Riemann’, Systems Research, vol. 8, no. 4, pp. 21–41 [Online]. DOI: 10.1002/sres.3850080402.