undesigned

Another issue I am thinking about is how to generate categories to characterize the different teachers I have worked with. Dr. Lancy, an experienced qualitative researcher, encouraged me to try sorting the teachers into categories just using my gut instinct. While this seems like a reasonable approach, my natural instinct is to try something more systematic.Ideas for approaches are welcomed. FYI I’m currently working from Reigeluth & Frick (1999), Yin (1984), and Miles & Huberman (1984).

Here is an approach I have dreamed up. I think it is a type of cluster analysis. Anyway, the first step is to code all textual data according to issues and propositions. Then create a metric to measure the distance between each pair of participants. The metric would work like this:

• If both participants made statements that supported a given proposition then don’t add anything to the distance score.
• If one participant made a statement that supported a given proposition and the other did not, then the add 1 (or some other magic numberto the distance score.
• If one participant made a statement that supported a given proposition and the other made a statment that opposed the proposition, then add 2 (or some other magic number) to the distance score.

I would weight each proposition according to how much of a factor I felt it was in determining the overall distance between two learners. Using a similar rubric, I could include some of my survey and background data in the calculation of difference scores.

This would result in distance scores for each pair of teachers. The hope is that clusters could be identified. If no clusters were observable, I could tweak the weights until I found some clusters (ha, ha). Really it seems like this is the process that one goes through when analyzing qualitative data. It is interesting that it seems more natural for qualitative researchers to try to come up with profiles or categories of learners than to try to describe average participant responses to a given issue. That is probably not so surprising, since it is often taken for granted that the sample is likely not representative. I think I will try to do both.

Reigeluth, C.M., & Frick, T.W. (1999). Formative research: A methodology for improving design theories. In C.M. Reigeluth (Ed.), Instructional-Design Theories and Models: A New Paradigm of Instructional Theory. (Volume II). Hillsdale, NJ: Lawrence Erlbaum Assoc.

Miles, M. B., & Huberman, A. M. (1984). Analyzing qualitative data: A source book for new methods. Beverly Hills, CA: Sage Publications.

Yin, R. K. (1984). Case study research design and methods. Beverly Hills, CA: Sage Publications.

Posted on September 5th, 2003 by joel
Filed under: research