Monday, 28 July 2008

The Tetris Model of Information Seeking

The more and more I've been reading about other models of information seeking (such as Marchionini 1995 and Kuhlthau 1993 and many more), the more I've been annoyed by how limited to a sequential flow they are. In Marchionini's, for example, there's a clear progression from problem identification, to specification, to seeking action, result viewing and resolving the problem. The model has this nice step towards the end that says 'refinement' and the text has a clause to say that people may drop back to almost any previous point. I believe a text clause like that is an indication that there should be a better way to model Information Seeking.

The thing I did like, was that each step was a different rectangular shape, based on how much time and computer involvement it required, as the two dimensions. These two observations about the model have led me to my tetris model of search, which I'm going to blog about here for a bit to test the water. You'll probably see followup blogs! I've got a lot to say about it!

Now, in Tetris, different shapes fall from the top of the screen, and success is modelled by organising them so that entire horizontal lines are made, removed from the display and converted to points. Let's first take the analogy that resolving an information seeking problem is like clearing a line of the board and that solving a bigger problem is like clearing multiple lines of the board, and finally that your score is representative of the overall knowledge you have on that topic.

Let us then imagine that the pieces that fall down from the top of the screen are then any one of the stages that are found in models like those mentioned above, where the ideal is that you get a series of simple pieces, representing a simple problem, a simple spec, a simple query, and a simple answer. BAM one line, problem solved.

BUT we all know that life is not like that, and regularly you get a nice simple first block (or you think you have a simple problem to solve) and then you get a + shape answer when you view the results that tells you your problem is a little more complicated than that. What we begin to see is that the complexity of a problem is actually represented not by the pieces, but by the current depth of the board. Each piece, therefore, represents an action, such as realising a problem, performing a query, etc.

So, a simple lookup on google is represented by a series of easy bits (specing, querying, viewing, etc) fitting together nicely and a line clearing. If you have a complex problem, however, the first bit you get is complex, like a +, and then you may need a combination of queries, and results to resolve your problem, and shift the 3 lines built by the +. Exploratory search can also be modelled with this analogy. If a user starts with a simple problem and starts off by querying for 'classical music' and then the first resullt says well there are lots of types of classical music:.... this means the next piece you got was a + and so getting an answer to your first query broadens the work you have to do to better understand classical music. Then, over time, you can resolve bits of information, find new problems you need to learn about. get some simple answers to fill in the gaps. Over time you may find that there are always rows with holes in, that you might take years to get back to them and fill them.

that was long, but think about it. I think its a pretty good analogy. Comments?

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