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PHD-DESIGN  March 2013

PHD-DESIGN March 2013

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Subject:

SV: Verification, Falsification, validation, design and wicked problems

From:

Birger Sevaldson <[log in to unmask]>

Reply-To:

PhD-Design - This list is for discussion of PhD studies and related research in Design <[log in to unmask]>

Date:

Mon, 25 Mar 2013 22:01:26 +0100

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Birger Sevaldson (PhD, MNIL)
Professor at Institute of Design
Oslo School of Architecture and Design
Norway
www.birger-sevaldson.no
www.systemsorienteddesign.net
www.ocean-designresearch.net
________________________________________
Fra: PhD-Design - This list is for discussion of PhD studies and related research in Design [[log in to unmask]] p&#229; vegne av Luke Feast [[log in to unmask]]
Sendt: 20. mars 2013 15:55
Til: [log in to unmask]
Emne: Re: Verification, Falsification, validation, design and wicked problems

Dear Birger,



Thank you for your useful dialogue and conversation. Your posts have
challenged some of my assumptions and given me inspiration to consider some
further aspects of design research and design research programmes. To me,
these exchanges show the value of the PhD Design list.



I wish to offer some thoughts on understanding and explanation in design
research.



Both your (Sevaldson, 2010, p. 13) description of research by design
“[producing] knowledge by engaging in the generative, in the act of
designing", and Horvath’s (2001, p.1) description of design research
"generating knowledge about design and for design", point to generating
knowledge as integral to research. Here we agree. Furthermore, both
descriptions, I think, point to the purpose of generating knowledge as a
means to understand design.



In some faculties of architecture and design in Australia that privilege
Research by Design (often called Practice Research or Practice based/led
Research), it is common for the PhD candidate to undertake a series of
design projects accompanied by reflection, to understand their own design
practice.



Moreover, I can imagine that a researcher who is a not a “design native”
may engage in the act of designing to gain some understanding of what it
means to do design work – an approach similar to participant observation in
anthropology. A similar situation would be where someone seeks to
understand the practice of sky diving: you could stay on the ground and
observe a skydiver jump out of a plane through a small telescope or you
could jump out of the plane yourself, and then you might, arguably, gain a
more contextualised understanding of the practice of skydiving.



I can accepts that generating knowledge in the act of designing - research
by design - can produce understanding, in the first case in terms of
self-reflexivity and in the second case in terms of empathy. These two
forms of understanding are useful.



However in contrast, the sort of understanding that "generating knowledge
about design and for design" concerns, is focused on explanation. Here I
believe our two definitions of design research diverge. While
self-reflexivity and empathy can produce useful forms of understanding,
they do not explain.



[In the following section I draw on Gaspar (1990, pp. 285-295)]



A common sense view holds that to explain something is to say how it is
caused. For example a designer might reason that the handle of a coffee mug
is designed to be easy to grasp because otherwise the user’s hand could
slip and spill hot coffee on them. This simple teleological form of causal
explanation is not particularly satisfactory and has worried philosophers
going back at least as far as Hume. A better account of causation would be:
an event of a certain kind is explained by citing a general law that
relates events of that kind to events or conditions of some other kind.
This is the classic-covering law model of explanation. It has been
extremely influential in the natural sciences and is one of the motivations
behind structuralism in anthropology. The value of the covering-law model
is that its explanatory power is evidential. If we have adequate
explanation of something then we could have predicted it before it took
place. Accurate prediction is important evidence in favour of a theory.



However, as nice as the covering-law model of explanation is, there are
several problems. One such problem is where deriving an explanation fails
to provide adequate depth. For example, suppose given suitable laws and
background knowledge, we predicted when World War One would break out based
on the assassination of Archduke Ferdinand in Sarajevo. Such a prediction
would still not constitute a satisfactory explanation because the
Archduke’s assassination is at best an immediate trigger and not an
underlying cause. It is likely that, had the war not broken out in this
way, underlying factors would have ensured that war would have broken out
in some other way instead. A satisfactory explanation should surely appeal
to those underlying factors.



In my view, a realist account of explanation is preferable. A realist view
holds that a theory should do more than tell us about observable
regularities, rather it should tell us about what sorts of mechanisms,
processes, etc. exist, and also something about the relations between them.
The realist search for explanations is the search for systematic factors
operating in the world. Theory illustrates the relationship between factors
and predicts what happens when they interact. Causal relations are
irreducible features of the universe that we can learn about through
empirical research. The choice between competing theories can be based on
explanatory power. If a theory initially introduced to explain one sort of
phenomena is found to explain other unconnected phenomena, then that is
evidence that it is an accurate description of the world. The best
explanation of a theory’s success, i.e. the predicted interaction between
factors, is that the mechanisms and events that it postulates actually
exist (or closely resemble what actually exists).



If we accept that the aim of design research is to arrive at accurate
descriptions of design, that design research should uncover causal powers,
and that explanatory power is a useful guide to the accuracy of our
theories, then I believe that a realist account of explanation is
significant.



Design research that produces understanding in terms of self-reflexivity or
empathy has less explanatory power than design research that produces
understanding in terms of a theory that explains and predicts. I argue that
theory rich design research is more likely to produce an accurate (or at
least approximately accurate) description of how design works and why.


best,

Luke



Gaspar, P. (1990). 'Explanation and Scientific Realism' in Dudley Knowles
(ed.) *Explanation and its Limits, *Cambridge: Cambridge University Press.


Horvath, I. (2001, August 21-23). *A contemporary survey of scientific
research into engineering design.* Paper presented at the International
Conference On Engineering Design ICED 01, Glasgow.


Sevaldson, B., (2010). Discussions & Movements in Design Research: A
systems approach to practice research in design. FORM*akademisk, *3 (1),
8-35


--

Luke Feast | Early Career Development Fellow | PhD Candidate | Faculty of
Design, Swinburne University of Technology, Melbourne, Australia |
[log in to unmask] | Ph: +61 3 9214 6165 |
http://www.swinburne.edu.au/design/


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