Throughout this course we have explored and traveled, from the philosophical mindsets of Kant, Plato and more to the practicalities of theory itself and the research around it. We have touched upon many different methods and strategies regarding the search for knowledge, how they are used, for what purpose and what they kind of knowledge they can produce. Delving into all this while also acknowledging the methods limitations and benefits has made it clear that they all have a special place and purpose, that however does not entail that they should be the end all be all. Throughout history these methods and strategies have barely been used, they are actually quite new in the scope of man, in fact the oldest way of gaining new knowledge was simply by observing the world through our own senses, empirically. And all though the people of old most certainly tried to keep an objective outlook, but there was certainly some form of bias regarding their own situation in time and place much like historically determined perception. Even though we now have access to proper methods and strategies for gaining knowledge we are still biased creatures and should keep that in mind when exploring new territories. Plato said it himself, it is through the eyes that we see, not with them - ergo our mind is interprets things differently from others, we do not see raw empirical data.
What I have come to understand through this course is the fact that nothing is absolute, even though we as students are drilled that the things we learn are a part of the “absolute truth”. Because of my earlier statement it is nigh impossible to reach an absolute truth, we can only reach a conclusion that the probability of the statement is high enough to accept it. Therefore we still need to keep a critical and open mind towards the things we learn in school, questioning and analysing them. There has to be a balance though, through the concepts of nominalism and classic realism I have learned that the end of both sides on the spectrum is detrimental to progress forward. On the one hand we have taking everything at face value and denying the conceptualization of our observations, never creating new ideas. Or on the other hand we insist that nothing in the world is real and it is only the conceptuality of our thinking that can reach the true heights of proper knowledge. The balance between these two ways of thinking will allow us to continue to progress forward.
I find it thoroughly interesting that we have built most of our current theories upon old ones, which we regard as true. But the fact that there can only be “strong” theory and not absolute theory means that the theories branching out from it can easily crumble if the main foundation is falsified. One example of this was Copernicus new theory about the way celestial bodies orbit on another. Because all previous theory was built upon the fact that Earth was in the center of the universe to challenge such a deep ground rule was preposterous, after the paradigm shift when the new theory was accepted all of the old theories were falsified.
Now I shall reflect about different ways that we can combine methods to answer complex research questions. To begin with I think we should focus on the research question itself. It is one of the most fundamental things when dealing with knowledge creation. From Haibo Li’s lecture we learned the importance of defining a problem before going about to solve it. He even stated that you should spend ninety percent of the effort on defining and the rest on solving. The merit with this approach as I see it is the fact that you know what you are after and can therefore choose the most appropriate method(s) to apply. We have two fundamental methods when gathering data and those are quantitative and qualitative methods which roughly translates to numerical or non numerical data. Because we have defined the problem properly we can assess if one is better than the other or if a combination is required. They both have their own benefits and can often times be combined to increase the validity and reliability of the research. Quantitative data can provide you with a general overview of the situation while qualitative data might give you something more in depth.
While on the subject of data I have learnt that it is often times not enough to create new knowledge. According to Anders Lundström it is the analysing thoughts that create the knowledge generation, with only pure raw data you cannot get anywhere, someone has to connect the dots and reach a conclusion. This enforces that you know how to handle this data and can comprehend its meaning, thusly one should not just throw in every scientific method for data gathering lest they know what they are looking for. If the problem or question is clearly defined you might only need one of these methods, as other data could just be considered irrelevant noise.
When looking at strategies such as a case study or design research the goal might not be in the finale but the journey itself. They are both working with an iterative process which could in itself be considered knowledge contribution, as long as the different stages of progress are analysed. I find this thrilling as it allows the researchers to continue and perfect their craft as the chances are otherwise slim that a single probing of a subject might provide the whole picture. The case study in particular is a very peculiar strategy in how it does not heavily rely on previous knowledge (because there rarely is some), it focuses on exploring something new, an event that few might have a full grasp on. It more or less forces one to stay open minded when dealing with this new subject. I wonder if Copernicus himself was conducting a “case study” on some specified region within astronomy and therefore freeing himself of bias when he noticed that the main theory of celestial bodies might be wrong.
