Our group has been thinking and talking a bit about ethnography as a research method. The discussion was started when we read a paper from CHI 2006, called Why We Tag: Motivations for Annotation in Mobile and Online Media. This paper investigates the motives of a small group of people for tagging photos they upload to Flickr via a mobile app called ZoneTag.
As our group uses mostly quantitative methods (with some exceptions), this paper was a departure for us. As a result, our paper meeting quickly digressed from a discussion of tagging activity in online systems to a generic discussion of methodology. One of the most interesting points made in the discussion was: there is deep learning that happens in an ethnography, but it is very hard to communicate that deep learning in a peer reviewed publication.
I agree with this. It is hard to understand what is generalizable from the set of quotes or the (often unsupported) theoretical models that tend to appear in ethnographic studies. However, ethnographies appear to be among the more nuanced of research methods. Thus, I have several thoughts about the value of these studies to me.
Perhaps ethnographers have deep insights, and are therefore in a unique position to contribute design implications.
Darn it. I read more about this one, and it turns out that a preeminent voice in the field has argued directly against my intuition. Paul Dourish wrote a CHI paper (as well as a follow-up to appear in DUX 2007) arguing that ethnographies should not be evaluated on the basis of their arguments for design implications. Rather, design implications are shallow, whereas human culture and thought is deep. A very interesting perspective, that to me argues for rethinking the design of ethnographic studies in many cases. Ethnographic studies should be designed to understand people rather than design – but I fear that (HCI-focused) ethnographic studies are usually designed to understand design rather than people.
Perhaps ethnographies are useful up front for understanding ways of designing technology.
Clearly, there are different methodologies for different reasons. There is no single method that dominates others. They are situational. Thus, we might ask where ethnography fits into this puzzle. One answer is that ethnography is a useful way of gaining a deep understanding of people to guide early design decisions. One could base survey questions on the results of an ethnography, or design user interaction based on users’ existing practices.
However, I often wonder if users really know what’s best. Users cannot see innovations, but they can illustrate ways of making existing practices better, or perhaps ways of applying new techniques to old problems. Thus, I am torn.
Perhaps ethnographies are interesting and a good vehicle for initiating discussion.
This is clearly true. Stories are more interesting than numbers to most people.
All this has become particularly relevant to my thoughts as I contribute to a paper based on the work that I conducted over the summer. While our research is not based on ethnographic methods, we do try to learn from observations, and through open-ended survey and interview methods. It’s my belief that using several methods together (quantitative methods + qualitative methods) makes for strong and interesting research. I am curious how we will tie stories to data, and the extent to which we will feel at liberty to generalize from a relatively small sample of users in a unique setting.