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And that seems to be what we're getting from Rashmi Sinha, in her project, "Methods of Information Architecture.". Rashmi's background in cognitive psychology, with particular interests in how humans categorize, is perfect for approaching problems of information architecture.
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COMMENT #1
And speaking of that, there is a fairly good methodology that was new-to-me and (seemingly) better than card-sorting described in that new UIE best practices report on navigation design (yes, I know what you think of Jared; I don't think he's half bad and I like the cheapo reports -- great for presenting to clients). Anyway, it works like this: the items that you would normally write on cards, you put in the leftmost column in a three column page. The second and third columns are left blank and headed "Top-level" and "Second-level" respectively. You present the page to [research subject] and ask them to come up with names for the categories where they would expect to find the item described in the leftmost column. The idea is, rather than imposing (a) your categorization and (b) your terminology, you get an idea of the classification schemes that [research subject]s would come up with AND what they would label such things. Invaluable, IMO (and maybe a good preface to card-sorting, if you want to do that later -- this the way to research coming up with the categories and their labels in the first place). I'm trying this for the first time today with live subjects (in the departure gates and arrivals area of an airport). I'll report back in on the results if they warrant ...
Posted by stewart @ 10/26/2001 12:50 PM PST [link to this comment]
COMMENT #2
Well, that sounds like the same thing as an "open" card sort, no? Where you give n number of research subjects a set of cards and have them do their own categorizations, then have them group those categorizations in to larger categories, and have them name them all with post-it notes on the tops of the piles as they go along...? Same methodology, different methods. Or am I missing something? And then you use EZ Sort, which sucks on the input side of things but works really well if you just use it for analysis, to draw pretty cluster-analyzed graphs which you can then drop on the client. And then they love you forever. Mostly, however, I'm wondering what and why and how you're doing all this at the airport...
Posted by lane @ 10/26/2001 09:57 PM PST [link to this comment]
COMMENT #3
Airport = client > Same methodology, different methods. Or am I missing something? No, not missing anything. (I'm no sorting expert, and I may not have been explaining it well -- thanks for the reference to EZ Sort, btw.) There are two differences: (1) Less time and space intensive, so it is possible to do it in intercept-mode (which is what I did). This is an advantage. (2) The results are crappy ;) -- since people don't actually have to do the sort, they are very careless with the categories, usually just abstracting away whatever part of the item description that made it specific and using the general term, resulting in as many categories as there were items to categorize (or pretty close). This is a disadvantage. Perhaps with more careful design on my part, the results would have been more useful (this was my first attempt -- limiting the # of categories they could create is an obvious constraint which I'd use next time). However, I'd say that it is useful only where there isn't time/space/money for going the whole 9 card sorting yards.
Posted by Stewart @ 10/28/2001 09:35 PM PST [link to this comment]
COMMENT #4
Peter's posting a link to my IA page shamed me into posting some actual content there rather than just ideas for the future! SO here's a proposed IA method that does not involve card sorting. SOme of my students (Monica Fernandes and Yisong Chen) had collected survey data as background research for designing a website to help users find nighttime entertainment in San Francisco. They had asked users to rate the importance of 13 factors such as (location of club / bar, type of music, cover charge, price of drinks etc.) in making decisions about what club / bar to visit (Yes, thats the kind of research we do at UC Berkeley :) ). We had thought of doing some basic analysis of the data, i.e., simply get means etc. But we also tried Factor ANalysis (a technique that can help show natural groupings of variables), and realized that the 13 decision factors grouped into three core sets of factors.
Results of the Factor Analysis showed clear evidence that there were three main factors that people use to make decisions about bars / clubs to visit. ALso people care about the below factors to different degrees. Factor 1: PRACTICAL ISSUS: drinks price, directions/maps, location, parking, facilities (pools, darts etc.), how crowded, cover charge Factor 2: BAR / CLUB ATMOSPHERE: age of crowd, type of crowd, atmosphere, how crowded, dj, facilities (pools, dats) Factors 3: MUSIC / OTHER FACILITES: music type, DJ, facilities (pools, darts etc.) For details about this analysis and comparison with card sorting go to http://www.sims.berkeley.edu/~sinha/InfoArch.html I am interested in feedback about this proposed technique. Does it seem useful? What kind of problems could it help the Information Architect with? All comments are welcome.
Posted by rashmi @ 10/30/2001 01:13 PM PST [link to this comment]
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