Theme 6: Qualitative and case study research (Before)

Qualitative methods paper

"Living the VirtuReal: Negotiating Transgender Identity in Cyberspace", Marciano, Avi; Journal of Computer-Mediated Communication (2014)

This paper is about how transgender individuals use the internet to extend their social network and/or the space within which they lead their lives. The author uses discourse analysis and virtual ethnography as analysis methods. I think this paper is interesting because of its emphasis on the implications of technology and I thought it would be interesting to read a paper with qualitative methods which I am not confident with.

The author studied content and commentary on a popular webpage and forum respectively. One of the foremost benefits of doing so is that the author could get information on what people say and think when they are acting within a natural context. The author won't affect the study "participants". However, there is no possibility of asking for clarification. Further, observing multiple instances of the same kind might prove hard. Specific questions might have to be abandoned or accepted to have unspecific answers based on a small representation of subjects. 

For me it was interesting to understand that even with methods that seem purely analytical at first, there is often an element of quantifying. Like the categorization in the discourse analysis method. I am starting to see that there is a relatively large grey zone where qualitative and quantitative meet or maybe overlap.

I think this paper could have been improved by making a survey or interview people to see more of how they potentially differ in personality between offline and online and to provide deeper understanding of some of the issues that come up. However that would be beyond the aim for this study. 

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Case study paper

1. A case study is a broad range, often open ended study that involves several methods of gathering data. The study is conducted by choosing a few places where the topic of interest can be observed. The study may include experiments that are set up by the researchers but it might also just be the "natural" situation that is being observed in several ways by the researchers. It is good to chose different places that represents different categories or qualities of the topic of interest, each of these are one case. The gathering of data may be anything from structured to unstructured  or both and may change during the course of the study as new phenomena are observed. 

I chose the paper:

"Student experiences of virtual reality: A case study in learning special relativity", McGrath, Dominic and Wegener, Margaret and McIntyre, Timothy J. and Savage, Craig and Williamson, Michael; American Journal of Physics, 78, 862-868 (2010)

This paper is about using a visual software to help university students to understand special relativity phenomenon. The study is divided into two major cases, one at each of two universities, but is partially subdivided by the different categories of students that are taking the two similar courses (the setup of the courses differ a bit between universities).

This is one of the weaknesses that I observed. Since they basically only have to cases they cannot compare the impact on different styles of education. It would have been good with one or two more universities or other courses of similar content at the same university. However their results do not present complex theory but rather binary theory, basically if their visual software will or will not help students in their learning process. They do use the fact that they have different categories of students to help them to their conclusion. But stronger theory could possibly have been achieved with more cases.

They use multiple ways of gathering data like observation, questionnaires and interviews in a structured way with questions integrated into the laboratory task. They also compare results on the final exam between students who used their software and those who didn't. This combination is one of the strengths of this study I think, since they are able to verify the preliminary results from the laboratory sessions with the comparison of exam results. Some of the data is quantifiable and is therefor subject to statistical analysis which helps them further in building their theory.

They do very little to extend their theory by investigating reasons behind the fact that student seem to benefit from using their software. They retrieve some data that points to how the learning process continues for students who participate but no attempt is made to understand the mechanisms. Neither do they extend their theory by referencing to previous work that might explain why visualization, or some other part of their experimental setup, will help the students.