Before the lecture I thought it was a bit tricky to classify a paper as quantitative research since papers almost always include some sort of analysis or interpretation in the discussion. I would argue that this would make the paper a combination of quantitative and qualitative research. However, one should probably disregard the discussion section and just focus on the methodology when categorizing papers.
Quantitative research should gather data in an objective manner and it should be quantifiable. There are different ways of doing this and some might be better and more suitable depending on what’s being researched. The second part of quantitative research is processing or analysis of the data. The tools for doing this come from mathematics, statistics etc.. What’s good about these tools is that they’re often well established and widely used. A thing that’s not as good is that it’s sometimes difficult to understand why they work. I can think of one example which is Word Embeddings. Word embeddings is a method used in Natural Language Processing. It has proven to be very useful for finding concepts and relationships between words yet it’s not very clear why it works, it just does. A big problem with quantitative research is that it’s not straightforward how to map complicated things in life such as human behavior to a limited number of quantifiables.
In qualitative research, the methodology is a bit more liberal. Take for example a survey: the users may be allowed to freely right down sentences or even paragraphs to answer a question. In a quantitative study this would most likely be replaced by let’s say a question with a numerical answer in the range from 1-10. The latter is much more restrictive in terms of content. It’s quite a challenge to understand what the test person meant by answering a 7, compared to an elaborate explanation in plain words. Furthermore, it’s also unclear to the test person what a number in the scale represents. People can have different interpretations of the scales. This was a big problem in a paper I read for Theme 3 where scientists tried to interpret users’ movie ratings on Netflix. On the other hand answers in a qualitative study may be varied and it can be hard to find patterns and draw any general conclusions from them. Even though quantitative methods have their drawbacks, scalability is a major advantage. One numerical answer might not give you a lot of insight but combining a lot of data might actually do that. There are many techniques for extracting information from big data sets and that is in itself a hot field of research.
There are obviously both benefits and drawbacks by using quantitative methods. A solution could be to combine quantitative with qualitative methods. For example, a numerical answer combined with a few sentences could give more insight into what the test persons are thinking. This can also serve as good feedback to see if your questions are well designed.
I’ve been focusing mostly on surveys in this post but there are of course other ways to conduct studies. The main thing for quantitative research is that it needs measurables. Sometimes, depending on the setting it can be harder to find that or it just doesn’t make any sense to quantify some thing.
An important advantage of quantitative studies is that it relies a lot on mathematical and logical tools. Since mathematics is often considered a pure form of knowledge, quantitative methods should be less subjective than qualitative.
I like you definition of the problem of users' misinterpretation in questionnaires and the way you suggest to solve it - adding the text under the numerical evaluation. Whenever I was taking tests where I had to rank my attitude etc. often that was quite hard to put the certain number - that's a huge disadvantage, unfortunately, of the quantitative methods. Word Embeddings is a bright example as well although I would also have doubts which method it belongs to.
SvaraRaderaOverall, good job!
Thank you for your really personal feedback on quantitative and qualitative research methods. It’s true that a disadvantage of quantitative methods is that every individual might interpret scales different than others. Researchers are aware of that and try to solve this problem. Because of this constructs are sometime not just investigated in single questions, but as a group of variables, that are summed up to an index. The statistical analysis is made with this value. A different interpretation of one question by the participants is not that strong valued anymore. In general, it can not be said that one of the methods is better than the other. It always depends on the field, the previous researches in that field, and the research intention. We need both methods (1) to be able to identify new constructs and theories and (2) to be able to generalize theories and verify or falsify them. I agree with you that a mixture of both methods in one research can be really suitable depending on the intention, but if that’s possible is often a financial question.
SvaraRaderaAllo,
SvaraRaderaThis is a very good reflection you brought here.
But i think this is the point of qualitative research, is that they don't procure an overall understanding of thing through pattern of data but more an answer to the why and how. This is focused on why this instead of that.
I think using both method may end up to a wider understanding of the situation therefore a better result and a better research.
I agree that quantitative are less subjective than qualitative but doesn't mean that qualitative are totally subjective, they have their part of Objectivity otherwise the result would change everytime we realise the study. But since we are dealing with numbers most of the time in quantitative it appears that this is way more objective.
Thank you for the reflexion
Thanks for your reflections. It is not uncommon that studies combine different method (especially in case studies) so your selected paper might use a mixture of quantitative and qualitative approach. To combine different methods can expand the scope and offset the weaknesses of either method. In order to describe an unexpected relationship additional qualitative information would benefit the research and might give key insight. Of course there are disadvantages with mixing methods as well. Anyway good job with your blog post!
SvaraRaderaI think you make an interesting point regarding ratings. It's definitely a big issue within quantitative research as it is meant to rely completely on objective hard data. It shows how even hard data is an subject for interpretation. I think that this proves how important it is to try the method of choice a couple of times in order to validate it before actually using it in the study.
SvaraRaderaThe purpose of discussion sections is to link the findings of the qualitative or quantitative method/s to the theoretical framework that has informed the theory or hypothesis that is being tested. In that sense it’s an essential part of any paper, but is in no way per se qualitative research. One of the “louder” claims about quantitative methods indeed has to do with its objectivity compared to qualitative methods. However, I think it’s very important to always ask ourselves how objective can a quantitative approach be, given that the researcher/s behind the study is/are (a) human beings with their own biases and flaws. Pleasure to read your blog post!
SvaraRadera