The most notable aspect of Colleen Brice’s critique of qualitative researching techniques was the sheer depth that the qualitative research methods exhibited. With little formal training in usage of qualitative data, I was not entirely familiar with the coding concept that sat in the heart of Brice’s piece, and just as well I have no experience in L2 language studies. Because of this, much of the information Brice presented was fairly new to me.
Though I haven’t had much interaction with the concepts Brice is treating, which is sensible, considering her critique would only really be useful and interesting to researchers who plan to utilize or analyze qualitative data and as such didn’t really need to explain much- it was a reasonable expectation the general audience would understand her terminology and logic, I can see how her critique would be beneficial. The coding method’s usefulness is derived from a perceived need to categorize different aspects of qualitative data to examine connections and/or patterns to interpret meaning with respect to the investigation or experiment as a whole.
The necessity of this process places a great deal of responsibility on the researcher to both provide a good methodology of codification, and to prove that this methodology is valid. This was the most striking element of Brice’s piece- the latter half in which she went out to prove the reliability and validity of her coding methodology. It seems as though Brice and researchers who were trained like her came from a semi-rigid background that parallels to the rigidity of quantitative researchers. This is an odd concept, considering that qualitative data and its interpretations are inherently creative; there’s no hard and true way to say what data means what, unlike quantitative data.
Brice provided credence to her claims through illustration of how her experience in interacting with her subjects would lead to different interpretations on how a piece of datum should be coded. The thing that Brice left me with is modes of qualitative data collection, categorization and analysis can be as creative as the elements the data are being pulled from.
In that respect, I feel that the best way to approach data collection for my research is to a sequential method, collecting qualitative data from my subjects, and then using this qualitative data to influence and explain the quantitative data. Considering that I’m working in a team of 3, with a total of 50 subjects, work division can be organized via Google’s cloud-based programs such as docs, spreadsheets and forms for analysis, quantitative collection and qualitative collection specifically. All the data needs to move through all 3 members of the team, and these programs would facilitate interaction between the researchers, and between the researchers and the subjects in the most efficient manner.
Devising a method of reading and coding qualitative data is simple: the data will be collected in a google forms document that is accessible by all 3 members of the team, with all relevant information organized by name of the participant. This should allow all 3 members to read the data individually, which incorporates an evaluatory aspect to the pre-defined research methodology as a whole. In terms of writing and interpreting the categorized qualitative data, this should be done in direct respect to how it influences the quantitative data, and as such, can be presented in an almost pair-wise fashion. The specifics of this will not be clear until tangible data is present, and as such, the actual methods of dealing with the data will most definitely be subject to change.