Learning from Case Studies

After looking at this week’s readings, I also found it surprising that there were  issues with case studies. I actually do not mind its “story-telling” nature that much because it’s what makes them interesting to read. But I understand how this can cause problems since it makes the findings seem “less scientific”.  I also found it interesting in the readings about coming across situations where using different methods in a research project can result in having data sets that reveal different things about the phenomenon that you are studying. This relates to what we have learned in class about how different methods yield different types of data; this is especially important when you use more than one method in your research. I think that Yin’s discussion on case studies reminds us that it is important to understand at the beginning what types of data that you are trying to collect with each method, and what types of analysis you can make with the data that you will collect. Yin also looks at presentation and the ways in which we articulate our findings. He thinks that in order to avoid “story-telling”, we have to resist creating elaborate narratives for some data elements during the note-taker stage of the project; since this will affect how you will articulate and analyze the data later. Even though Yin specifically talks about case studies, I think there are things that we can learn and apply to our own projects.