This week's theme was an eye-opener for me. I have always put more value in quantitative research rather than qualitative research. After having read the recommended literature, and selected one paper for our pre-seminar, I realized I couldn't have been more wrong.
Indeed, during the seminar we talked about objectivity: just like in last week's theme, we're generally very quick to brandish words like "truth", "objective", "false", "subjective"… But in research, it's best not to resort to that, as we very often realize that the results we get can't help but be related to the way we've designed the study, within our certain framework, set of data, decisions and starting concepts. Why have we chosen drums, and not piano? Why white people and not black people?
In this sense, while the general preconception would be that because quantitative studies often produce results in the form of numbers (which we, as scientists, love, worship, and more specifically don't question… sadly), we think they're more "reliable", more likely to be accepted. I was in this case as well. Thankfully, the seminar and lecture changed my point of view: now that I know the design of the study is the one subjective, questionable, deniable, point, I realize that a big part of the study's reliability boils down to the skills of the researcher - might the study be quantitative or qualitative. Best would be that it's a mix of both.
In this sense, deciding to conduct a quantitative/qualitative study generally comes parallel to the design process - there are things more adapted to be quantified than others, for example character and personality traits generally would be difficult to reduce to just a few numbers. The same goes in terms of "wicked problems" : trying to quantitatively design a product to solve that problem only using measurements isn't enough, we have to go into many more aspects - and thus, controlling the outcome becomes much more hazardous. That's why we have to use a mix of quantitative and qualitative. While the standardization of the quantitative methods offers the possibility to have a uniform metric for different people, the benefits of having the possibility to vary our measurements sure show when we use a qualitative method. By doing this, we get deeper knowledge, and an interrelation between the results that quantitative and qualitative methods give us. An example that illustrates the benefits of the comparison would be conducting a qualitative method to measure the amount of candy you ate last week (do you feel you ate a lot of candy? Or little ?) then, conducting a quantitative method, and comparing results: this would shed light on our perception of quantity, on the concept of guilt, or want… But of course, it still depends on sample selection (for the quantitative method), question and test implementation… Everything that makes research interesting, captivating, and of course, complicated.