Final reflection

This course has taken us a long way through the theories and methods in the media technology field. From the definitions of what knowledge is in the first place to means and methods for how we can empirically produce new knowledge. Even though I had a quite broad experience with research methods and their actual execution beforehand, I gained a lot of new insights and some deeper understanding of the research methods I was familiar with and even new ones, such as design research. I personally felt that the format of this course succeeded in supporting the learning experience by making us first deal with topics on our own, then get external input from a lecturer and then let us discuss it with our fellow students. The learnings I took away from the course will be for the long term, I think. 

The first research method we dealt with was quantitative research. Quantitative research is guided by pre-existing assumptions which the researcher wants to quantify through research. This is opposed to qualitative research, which is much broader and less assuming and instead based on interpretation because it "allows you to examine people's experience in detail" (cf. Hennink, Hutter & Bailey, Qualitative Research Methods). This also means that a researcher using qualitative methods needs to be more understanding and flexible when he or she conducts a study with, for example, interviews, focus groups or content analysis. Execution of qualitative methods is extremely important, otherwise results turn out poorly (cf. Methodology Matters: Qualitative Research Methods). Quantitative research, on the other hand, requires a more detailed preparation beforehand and, even though the execution still has to follow the rules, it is not as crucial. As we have encountered in our seminars on both quantitative and qualitative research methods and as I have also started my reflection here, the definition of one of the research methods usually ends in juxtaposing it with the other one. However, as I have argued several times in earlier blog posts, the best research results come out of studies which combine different methods. 

Mixing research methods opens up entirely new possibilities to generate new knowledge (cf. A Momentous Development in Mixed Methods Research). Let us take an example. In my bachelor's thesis, I wanted to make predictions about how the role of a Chief Marketing Officer will develop in the future. For this, I conducted empirical qualitative research in the form of personal in-depth interviews with some CMOs. Although this helped me to generate relevant data and insights, in a bigger study it would have been a reasonable and helpful next step to quantify the insights with standardised questionnaires with a larger sample of CMOs. Also other researches I have conducted could have profited from the model of beginning with qualitative research and following it up with quantitative research. Nonetheless, there are studies in which this order is inverted. In Ilias' example of "Drumming in Immersive Reality", they, for example, first conducted a quantitative experiment and followed it up with qualitative interviews to ensure the validity of their study. This research, however, also merely aimed at an existence prove, which is actually quite common with experiments. They are mainly implemented to test specific hypotheses (cf. Social Research Methods). 

Another research approach which I had no experience with before the course is design research. The design process itself with its continuous iterations which include adjustments and improvements can be seen as a research in itself. However, this is also often combined with other research methods. In Anders Lundström's example of the electric car dashboard, for example, he first conducted qualitative interviews with users and some sort of content analysis in online forums in his state of the art research. A next logical step after this design process leading to a prototype could have been a qualitative user study of people actually testing the new dashboard, followed by a larger quantitative study to ensure its usability. To me personally, it seems that finalising a research with a quantification of the data in order to validate them in a larger scale, seems to be a very valuable approach. Another example would be the case study about Occupy Wall Street which I wrote about in an earlier blog post. In this study, the researches established a Twitter user typology of participants of the protest by conducting qualitative interviews. This, however, only generates an assumption or theory about a typology which is not validated to be generalisable. A quantitative follow-up study could have helped to establish a certified user typology. Combining research methods is relevant throughout different formats of research (cf. Integrating Case Study and Survey Research Methods: An Example in Information Systems).

Tu sum it up, different research methods complement and complete each other. When planning and executing a study, the researcher should not be too focused on deciding which path of research to follow, but which pieces of each path to combine with each other. This will help to discover the relevant results that were aimed for. Or as Sandelowski put it, the "complexity of human phenomena mandates more complex research designs" than just sticking to one particular method (cf. Combining Qualitative and Quantitative Sampling, Data Collection, and Analysis Techniques in Mixed-Method Studies). 
This has also been my major learning from this Theory and Method for Media Technology course. We have to be flexible with our research approaches if we really want to find the true result to our research question.