Approach 1. In-depth examination of research methods from a formal, mathematical perspective. So formal measurement theory, vectors and matrices, how correlation really works, the underlying math of factor analysis, and so on.
Approach 2. In-depth, hands-on workshop on how to use the main techniques of data collection, construction and analysis in the social sciences. Mostly about the software and the actual nuts and bolts.
Approach 3. Survey of the components of a research project. Exposure to key concepts, such as measurement, validity, reliability etc, as well data collection techniques and data analysis techniques. Emphasis on what they are and what they are used for, but not how they work.
I intended the course to be a combination of Approach 1 and Approach 2. But now I am going to reorganize things to be about 70% Approach 3, and 30% Approach 2. My sense of aesthetic purity says go 100% Approach 3, but I can't resist showing you some tools you can use to analyze real data. It is too much fun.
Of course, it is hard to let go of the math stuff too. So my approach is going to be "if you don't ask, i won't tell". But I hope you do ask about the mathematical nuts and bolts underneath the techniques, and I will explain.
2 comments:
For what it is worth, I liked the in-depth view of factor analysis. It is challenging to get it all in in one class session, but I like knowing how this stuff works so I am better prepared to use it in the future (factor analysis).
Having a broad exposure to multiple techniques is important as well, so I can see the trade off. But, having some classes where we dive in to the math is helpful as well. At least for me.
Josh
So, after I saw your comment, I edited the post to emphasize that I would love it if people do raise questions about how the methods really work, and I will explain in full depth whenever possible.
Post a Comment