birger and all who responded to his challenge,







i have followed the discussion with some amusement and want to add just a few comments.







first. we seem to be prone to fashionable slogans, each time defining design anew, giving the impression of being at the cutting edge only to abandon it as soon as a new slogan appears. at some point it was



product design, then



functional design, then



styling, then



ergonomic design, then



sustainable design, then



product semantics, then



emotional design, then



interaction design, then



design as service, (although service design has a meaning unlike product design). then



design thinking, now



evidence-based design.







regarding evidence based design, birger is perfectly justified to ask the promoters of this latest slogan what they mean by evidence. don in response describes what designers normally do: exploring available information, testing prototypes, etc. -- nothing distinctly new.







i think it is a sign of intellectual weakness of the design community to chase one slogan after another, each has a kernel of validity but on closer examination it does not define the field, it is only -- as don said regarding design thinking --  a deceptive public relations (marketing) tool for designers to give the impression of doing something that others have not done before them.







about evidence, i noticed a confusion between measurement (don's examples), data, and evidence. to me:







measurement implies mapping phenomena onto the numbers of a scale. these may not have anything to do with what is important.  in the sciences, numerical accounts are preferred because they lend themselves to construct mathematical models of observation, including statistical accounts, often insisting that these are the only kind of data acceptable. tina made the valid point that design often relies on qualitative accounts. quantification is only meaningful if there are enumerable units. this is rarely the case.







data (plural) are analyzable records. they must be (1) durable, ideally (2) computable, (3) reliable (in the sense of being replicable), and (4) informative about the phenomena of interest. data may fail in one or more of these four qualities. they may vanish as does unrecorded speech, they may by biased by representing irrelevant phenomena (idiosyncrasies of observers), and they may not contain the information about the phenomena of interest needed to make a decision or answer research questions. – it is the latter that relates data to evidence. (i have written about these qualities and am happy to share it with whoever cares to read it).







evidence is always relative to a proposition. data may be unreliable and worthless by not providing the evidence that support a proposition. so evidence either supports a proposition in full or in parts. but unlike it is true for data, there is no such thing as bad evidence. the opposite of evidence is its absence.



note that propositions occur in language, in arguments, not in nature, and not in a design either.







when designers argue for their design, it surely is important to be aware of whether they have evidence for their claims (predictions of what would happen to a design, including what can be demonstrated by its use) or whether their claims are based on beliefs, visual appeals (like the icon don sent recently), or initiate a process of self-validation (self-fulfilling prophesies). to me, if evidence based design has any meaning then it refers to evidence that backs up verbal claims about a design, not the design as such (see horst rittel’s work). (this has been worked out as part of my “the semantic turn; a new foundation for design”).







best wishes for 2016



klaus



















-----Original Message-----

From: PhD-Design - This list is for discussion of PhD studies and related research in Design [mailto:[log in to unmask]] On Behalf Of Filippo Salustri

Sent: Monday, January 04, 2016 12:23 PM

To: [log in to unmask]

Subject: Re: What is *not* evidence?







On 4 January 2016 at 11:59, Bardzell, Jeffrey S <[log in to unmask]<mailto:[log in to unmask]>>



wrote:







> Yes, everything I have heard, including Filippo's response to my



> question, includes too much. (Filippo's definition, for example, would



> inadvertently but as formulated include crude intuitions based on



> subjective experience so long as they turned out after the fact to



> have been correct.)



>







Just to clarify, I wrote this in the context of my other comments. I should have been explicit about that. That is to say, even if we start with "crude intuitions based on subjective experience," it can be a starting point for research, by providing material on which to reason new research questions, and by stimulating detailed study of the crudeness of the data. There's also a question of quantity of evidence - all going back to strong vs weak evidence. If there's a huge amount of crude data that leads to predictions that turn out to be correct, then it's reasonable to hypothesize that "there's something there" and that further research may well tease out the factors that are more sophisticated and objective.







One might also ask: How do we know that the data is crudely intuitive and subjective? To answer that question, we'd need to be able to tell what is and isn't crude, and what is and isn't subjective.







For crudeness, one way of doing this is to consider ranges with respect to some context-specific scope: the data with the tightest ranges are the least crude.  For subjectiveness, one way of doing it is by establishing the extent to which the data was (or may have been) altered by human cognition.







\V/_  /fas







*Prof. Filippo A. Salustri, Ph.D., P.Eng.*



Email: [log in to unmask]<mailto:[log in to unmask]>



http://deseng.ryerson.ca/~fil/











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