Photovoice

We had a great guest presentation on the use of photovoice in an ongoing study. You can see the slides in PDF format.

Katie is just one of the generous visitors to our seminar. I am happy to report the LIS 3600 spring 2006 PhD Seminar in Qualitative Research Methods has been truly blessed with a steady supply of interesting, talented, and very edgy (as in cutting edge) guest speakers. My deep thanks on behalf of the class go out publicly to Rebekah Hamilton, Gwendolyn Hawk, Charli Carpenter, Sue Sterret, Katie Fitzgerald and Eva Marie Shiver, who who have so far given us incredibly valuable insights into their projects, and to Carrie Farmer Teh and Michelle Upvall, who are lined up for upcoming classes.

It is my sense these presenters have gotten something valuable out of the class feedback. The sessions have more closely resembled brainstorming sessions than traditional academic chalk talks. The students have loved it; it spares them having to hear too much from me.

Getting Started with ATLAS.ti

There are a number of usefull resources available at the ATLAS.ti web site. For example, you can download a free trial version or a quick start guide.

For specific answers to questions about using ATLAS, try searching their online forum or joining their listserv.

Available Data

For those in the class who are having a tough time finding data to use in the lab tomorrow, I have posted two of my public comment samples as .zip archives. You can get a saple of mercury emails or CAFE (corporate average fule economy) public comments at

http://qdap.ucsur.pitt.edu/data/cafe.zip
(CAFE comments)

http://qdap.ucsur.pitt.edu/data/ntf.zip
(mercury comments)

Is Knowing "A Lot" a Downside?

I was running my eyes over the Executive Summary of the report from a National Science Foundation-funded "Workshop on the Scientific Foundations of Qualitative Research" and found this interesting quote:

"The cornerstone of good qualitative research is in-depth knowledge. Qualitative researchers who already have background knowledge are more likely to identify promising leads than those who start from scratch. The downside of 'knowing a lot' at the start is that researchers may enter the field or archive with preconceptions that interfere with the development of new insights."

This generalization left me puzzled. What is the logical strategy in light of such a paradox? It is certainly true that familiarity with a phenomenon is likely to allow a researcher to situate specific obseravtions, or groups of observations, in a more theoretically rich and informed context. At the same time, this pre-knowledge that frames an observation will also likely push out some competing frames that either are not favored or have not been developed yet.

I notice this issue when reviewing the results of coders working in my QDAP lab. In some cases, the students with a disciplinary background in line with the coding project seem better able to distinguish subtle differences in the text and therefore make observations that are consistent with the principal investigators goals and instructions. In other cases, however, the PI will want to have a mix of students with no specific knowledge about the research domain so that they can report on the "unanticipated" observations, those untethered to any particular analytical frame.

Perhaps it boils down to this. In projects that are essentially content analysis exercises driven by the knowledgeable presuppostitions of the PI, coders are best suited when they know some of the theory and jargon of the PI's discipline. When the project employs a grounded theory approach, the need for "knowing a lot" about the subject may be diminished.