Post theme 4.
Sadly, there was no seminar this week to
have discussions regarding the subjects which were at hand. With that said, it
did feel like a seminar which was a lot easier to grasp than the previous ones.
The reason for this being that both quantitative and qualitative research is
something that students who are currently studying a master’s program has
already undergone a bachelor’s degree – in which we wrote a thesis. When
conducting our bachelor’s theses, we read some information regarding both of
these subjects – so it was more tangible.
Without a seminar, it has been hard to have
discussions regarding the subject – but I have tried discussing it with people
who read the course last year to get some more insight into the area. And one
of the recurring subjects has been how quantitative data is extremely hard to
deal with in an objective meaning. No matter which pool of data you have, it is
next to impossible to be completely objective about it, and put it into the
exact context in which it belongs. One way of doing this is categorizing the
data into different groups. An example could be that different answers would be
categorized to “Positive”, “Negative” or “Neutral” depending on the type of
data which was given. However, this is also a thin life to walk, and in the end
these categorizations might come down personal interpretations – which might
not be objective.
Because of the above, I have reflected
about the fact that there might never be a completely objective approach to a
problem, and in the end it all comes down to how the researchers decide to
approach a problem and a data source. If researchers were to put an entire
paper into context and be completely objective, it might need an entire book
just to describe every single aspect of the context – which is absolutely
impossible to achieve. So, as a reader of different papers it is always
important to have your own critique of what is written and try to do your own
analysis to find which “pit falls” might have been present when conducting the
research.
I also think that the above highlights the
fact that it is always important to use qualitative methods as well as
quantitative – to try to reach one step closer to an objective answer.
Hi!
SvaraRaderaI agree with you that this week was a bit more tangible than previous themes, and with previous experience from the bachelor's it was easier to work with. I also agree that quantitative data can be very difficult to work with objectively, although numbers and statistics may seem more objective than interviews and opinions, like you pointed out, it all depends on how researchers decide to approach a problem and a data source. Somethings might have been left out, if research subjects fill out a form, it all depends on the questions and how people interpret them, and it can also be difficult to know how serious the research subjects were when filling out the answers etc. Like you wrote, it's very important that the readers of the research have a critical thinking, and analyses the answers best they can, and are aware of the different "pit falls". It's also important that the researchers are aware of their own "pit falls". I think it's a good idea as you said, to both use qualitative and quantitative methods, to get as close as possible to an objective answer.
Hi you there! I totally agree that it was really hard to reflect upon this theme without the seminar, however, I think most of us already have at least a little bit experience dealing with quantitative data. Also I think by saying that there might never be a completely objective approach to the problem. However, I think that quantitative research leaves less space for researchers own opinion and even if a scientists uses some of his assumptions or interpretations it can be simply taken as his own contribution of knowledge to the research. Lastly, I agree with you that research is strong when it contains both qualitative and quantitative data as it has explanatory fields as well as evident one.
SvaraRaderaThanks for interesting thoughts!
Hi! Nice reflection. I agree with you about the difficulties researchers (and the over all academic field) face regarding objectivity and "true knowledge". Quantitative methods might have a reputation of being more objective, but at the end of the day even quantitative papers are written by a subjective being. So how do we minimze the risk of skewed results? Just like you write, I believe it is an impossible mission to set out on. I think your conclusion of criticism being key is very valid!
SvaraRaderaHi! Thanks for your reflection I really enjoyed reading it. I agree with you on that gaining objective data is almost not possible. I also agree with you on combining both qualitative and quantitative method as both can enhance the each other’s strength and weaknesses. This also influences the reliability of the data as more of the limitations have already been taken away by choosing two methods. By using both methods to complement each other, you can also get a more complete and detailed picture of certain situations.
SvaraRaderaHi! Thanks for the insightful reflection, I really enjoy reading it. The concepts of quantitative and qualitative methods are not easy to understand without having a seminar. Also, you made a clear point here : quantitative method might be objective to collect the data. I would like to know how researchers solve the problem of quantitative methods up to now.
SvaraRaderaHi,
SvaraRaderaI think you make a good point in discussion whether data can be entirely objective or not. Although I believe a researcher can reach a fairly objective result thanks to hard data, I agree with you that it is probably impossible to make it all the way. After all, quantitative data (numbers, statistics etc) won't convey any meaning unless any theory, e.g. cultural studies, is added to it. But as soon as you add theory you have already put it in a certain context instead of another. This is followed by an analysis which is interpreted by the researcher - based on his perceptions.
It is interesting to see that during this course, according to some peoples’ blog posts this is the first time they encounter and get familiar with the qualitative research method. For me, having several methods courses as part of my bachelor, I feel that this is a bit strange. The distinction between quantitative and qualitative research is according to me one of the most basic concepts.
SvaraRaderaIt is an interesting idea to discuss the concept with people who read the course last year, I wish I had that opportunity! I agree that it is hard to be completely objective about data. Data has derived from some where, they do not exist in themselves. I also like the examples of categorizing data into Positive/Negative/Neutral. How do you determine that something is positive? What is it positive towards? The paradox of creating something that describes something in a thorough way, yet, has to be short enough for a great mass of people to actually take the time to read and reflect upon it, is interesting. I think one of the implications of internet and digital communication is that we want answer to the questions of why, quickly. I think infographics for example could be one way to adapt data to a modern context, making it quickly apprehensible for a great mass.
Your discussion on objectivity reminded me about our week one reading from Kant. You state that there might never be a completely objective approach to a problem, which fits in with Kant’s theories that we all apply our own “lens” when obtaining new knowledge and that it is not possible to avoid this. As research and empirical evidence can be classified as “a posteriori” knowledge, I agree with you that it is not possible to be completely subjective, especially when you must initially formulate a specific hypothesis. Therefore, I found it interesting that in this theme’s lecture we were told that subjectivity is not necessarily a bad thing when completing a research paper. Perhaps this is because subjectivity is unavoidable.
SvaraRadera