Final Post

The course Method and Theory for Media Technology covered a lot of key concepts of the research in this scientific field. A deeper understanding has been developed by starting at the origins of the definition of knowledge and working towards research methods and strategies. At the end all themes fitted together and build a foundation for our own research we might conduct in the future. A motive which reoccured in many themes is the theory of mathematics, the theory of logic and numbers. Math is an abstract kind of knowledge, its concepts are completely made up by human beings. Kant categorizes math as analytical a priori knowledge. This knowledge never came to us by actively observing real world objects. It came to us by thinking about abstract concepts. I agree with Kant’s opinion that it is mandatory to develop such abstract a priori knowledge in order to make progress in science. As it can be seen today, math is the basis of many scientific theories. Most if not every theory is based on another one and math is nearly always one of the foundation theories. What is the reason for this? I guess math makes it easy to argue in a logical and therefore in a verifiable way. And verifiability is the most wanted feature of a theory. I do not think that it is provocative to say that a non-verifiable theory is a useless one. Moreover, math conveys objectivity. Numbers and logic seem like untouchable concepts. Of course, logical reasoning is maybe the only way to support a theory but one should not get lost in this comfortable construction of objectivity. I think that true objectivity is a unreachable goal. The reason for this is basically what Socrates has been arguing. He says that perception happens ‘through’ the eyes. What he emphasizes is that everything we perceive has been gone through some sort of interpretation. Therefore everything is always subjective which implies that no theory can be considered as truth - at least not without a given context. But we have to consider some knowledge as proven or otherwise there would be no reason for science at all. This is why the historical context has to be viewed as a set of preconditions. We can make logical statements based on this preconditions and in the frame of that context, statements - which is to say a theory -  can be considered true. But what is a theory? It is definitely not only diagrams, figures and numbers which are often accidentally confounded with it. Their only purpose is to represent empirical data and without further evaluation the data remains nothing more than data. But if used to argue logically the empirical data can be prove for a theory. But how to gain empirical data? The tools to accomplish this task are qualitative and quantitative research methods. Quantitative methods can be defined as methods which will result into measurable data. Advantages of this methods are that data can easily be collected and evaluated. Moreover, researches which make use of quantitative methods can be repeated effortlessly and therefore the results can be verified by other researchers. But there are some drawbacks as well. These can be best illustrated with an example. It is common in psychological researches to use an EEG to gain data of the participant’s brain activity and to draw conclusions by analyzing this data. One problem which this bears is that the majority of the data is useless because a lot of brain activity is irrelevant to answer the research question. Therefore this data has to be filtered out before the left over data can be evaluated. But the filtering is not an easy task and it is very likely that mistakes are made [1]. The reason for this is that researchers are biased by their hypothesis and might filter out relevant data as well. Moreover, it could be that the chosen quantitative methods was the not the optimal one and some relevant data could not have been collected with it. Maybe an fMRT could have been a better choice in that case [1]. This means that a qualitative method put some sort of restriction on the results and therefore they represent only a narrowed view. In order to gain broader results, qualitative methods can be used. But this advantage comes not without the loss of an easy collection and evaluation. These task can become very time-consuming while using qualitative methods. But the advantages and disadvantages are not the only criteria which helps to decide on which method to use. It is very often the case that only one method can be applied due to a certain field of research. For example it is nearly impossible to use a qualitative method in physics and the contrary applies for literature studies. But in general it can be said that both methods can be used to prove a theory even though the usefulness of each method varies from research to research. Moreover, the correct method is not always the most important part. If we take one step back we come to the starting point of a research - a research question or problem definition. And it is worth to spend a sufficient part of time on that stage of the research. Because the way to view a problem decides whether its solution is a hard or an easy one. And then again it might not even be possible to define a specific problem. If the research is conducted within an unexplored area then it might not be clear which questions are interesting enough to ask. In this situation is necessary to do a case study as a first step and to gain enough knowledge to be able to formulate a theory. 

As it can be seen there are a lot of different aspects which have to be taken into account when conducting research. But the reward for paying carful attention to it is probably a verifiable, useful and profitable theory -  and this should be the goal of every researcher.

[1] Heller, J. (2012). Experimentelle Psychologie: eine Einführung. Walter de Gruyter.