Final post, or what do I know about anything really.

During the length of this course we have discussed several different research methods, but it still feels like we have only scraped the surface. There are still a thousand variants of the ones we know, and add to that the several methods I’m sure we haven’t even touched upon. Even such a simple thing as objectivity and truth turns out to be vastly complicated. There are arguments on whether there exists such a thing as truth, and if objectivity is ever possible or even desired. In fact, the question of objectivity is an interesting one. The first week was spent on whether we should strive to be as objective as possible (Plato), or to embrace the fact that we cannot be objective and work from there (Kant). I am of the opinion, and I believe that a lot of modern thinkers agree with me, that it is better to admit our faults in neutrality and instead spend time on analyzing how those faults affected our conclusions during research. This ties in to the choice of research method we use, since all methods have different ways for our preconceptions to influence our results.

Before you even get started on the actual research, it’s important to be sure of what you are studying. A lot of effort should be placed on defining the problems you are trying to solve or research, a part of the process often ignored or skimped on. In fact, if you define the same basic problem differently there will most likely be a world of difference in the solutions that someone would come up with.

Depending on the type of research question you want answered the method most appropriate will vary. A lot of research done in topics of social studies require a variety of qualitative research methods, for example, while many physics studies takes a quantitative approach. During this course I have discovered how many of my fellow student seem to be of the opinion that quantitative data is by its very nature objective and therefore more true and better all around. This is what is known as scientism, the belief that the empirical nature of the natural sciences means that they are always superior to all other kinds of science. Since quantitative research is more empirical in nature, it is easy to use the same logic on that to reach the conclusion that it is always better. However, that is not always the case.

So, what about qualitative methods? Well, while quantitatives are useful in, for example, measuring and analyzing things, qualitative methods are very useful in research where the results can’t be clearly measured. In the social sciences, and for that matter in a lot of research relating to our subjects such as interaction design, often you want to analyze things like people's opinion, or their preferences. These subjects can’t always be quantified and measured but must instead be reached through questions and other methods that fall under qualitative. Most of these methods, to my not all that complete knowledge, involve asking the subjects themselves to evaluate their reactions and responses to various objects and stimuli. This introduces the risk that the researcher will influence the subjects, or that their own bias will negatively affect the results. This bias can also be present in quantitative methods but there it takes other forms, such as confirmation bias, or ignoring and excusing data points that doesn’t fit the results desired.

We can from this draw the conclusion that there is no one superior research method. Well that sucks, things would be so much easier if there was. What method you should use is totally dependent on what question you are trying to answer. In turn, the questions you formulate are wholly dependant on the topic of your research.

If you are doing an exploratory study into a new area of research, a case study is often the most appropriate. Case studies allow for a more dynamic process, where you can gather data and formulate hypotheses and theory simultaneously. They are also, in my opinion, very useful for deep and focused research into a very specific case of something. Media technology research is often user centered, in fact the course we had earlier in human computer interaction was wholly focused on user centered research. When working with users you need to develop prototypes that they can test and evaluate, something which is easily done with design research where the changes done to the prototype during testing is the empirical data gathered.

So, in conclusion. Complex research questions can have very different requirements. In fact, research sometimes require a multitude of studies on the same topic to be complete. You might start with an exploratory case study, to generate enough theory that hypotheses can be constructed. After that, perhaps a small pilot study using quantitative data gathering to figure out the broader application of the initial findings. With that data from a broader group of people you can start building prototypes and evaluating them, in a design research process. After numerous iterations you can do a qualitative study on the impact your product had, or how it was received. This was just an example of how I imagine that a research process within media technology research could look, but it is an example of how the combination of various methods work together to make a fairly complete and adequate picture of the field you are investigating.

Compiled comments

I have done nothing to the text of the comments, exept correct some spelling and group the comments to make them readable.

Theme 1

I agree with you that things are meaningless without context. This is something I think that we often forget when we consider stuff created in a different time or place than what surrounds us.

My view, as far as it matters, is that you seem to have grasped the concepts of this week very well, and especially the whole "All I know is that I know nothing" thing that philosophy seems to have going for it.

I agree with most of your conclusions of this week. The baby thing is really interesting, since yes they are not influenced by their preconceptions about the world, but they are also not capable of (as far as we understand it) complex thought. I was in another seminar group that week, and while we also had the discussion about whether there exists such a thing as objective truth, our was more focused on if it actually mattered. With what we have learned since this theme would lead me to believe that you are a realist in the same way Plato was, since you believe there to be such a thing as an objective truth.

Group discussion seems to be the way to go to really understand what is going on in these texts.

I find what you said about human perception to be really interesting. Obviously there is no concept of bottle in the minds of people who have never encountered one, and therefore the thing doesn’t matter to them. I get a little curious as to what a thing would be if we had no concept of it, and how that would change if we were to suddenly get one. If I, let’s say, used a towel for a scarf and you told me that it was supposed to be for drying my hands, would that really alter my view of the thing or would I consider you crazy? I don’t really have an answer, I just thought it a really interesting point of view that I hadn’t considered.

Nice allegory with the radio! I find your discussion on Kant to be very interesting, and your presentation of your own questions you had to be helpful to me as a reader. But I lack an idea of your thoughts during the seminar. All of your post is really good, but it seems to be just your own reflections after reading the texts. I would have liked to see something about how your views changed during the week, or something along those lines.

Do you really believe Kant doesn’t care where knowledge comes from? That is not at all my understanding of him, instead I think him to be almost exclusively concerned with where it comes from. Most of his text is about how we know things, a priori of a posteriori. Other than that I liked you text. It was well balanced between recapping and your own thoughts.

This was an interesting read. I liked your explanation of the paradox of things having extensions but only being proved to exist by perception. Would that mean that the world only exists to us because we see it, and if we didn’t it would only exist to the creatures that could? I don’t know, but it’s interesting to think about.

Now, about the other part. I realize that it was a thought experiment, but there exists cases of children growing up without human contact. These cases seem to hint at (since I’m not an expert I won’t say anything more definitive than that) that for intelligence as we know it to occur children must be interacted with. Most cases lead to what we would call developmentally disabled humans. However, your discussion leads me to consider whether they just have a different perception of the world. I’m not sure, But I would recommend you to look at some of these cases, as they are fascinating. (And gross, since a lot involve extreme child abuse)

Theme 2:

I think it's true what you said about how showing things can make them happen. Seeing things can make them true in one's mind. Just look at how CSI and similar shows have influenced how people think crime solving goes on. Also, isn't it a thing that sci fi on TV has affected technology? We want to have what we see on television, so we build it.

I appreciate your grasp and opinions on nominalism, and agree with you on most of your points, however I would have appreciated a little more on how it contrasted realism.

Great write up. You really explain the concepts well, and your pre-post (as the commenter above me said) is excellent. However, I feel like this post is only a summary of the texts of this week. I'm not seeing any of your own thoughts, anything regarding the lecture or seminar, or any of your own contributions. What is is great, but it would have benefitted from a little more depth and opinion.

I like your explanation of nominalism, and the results if it was to be widely implemented. That would not be pleasant world to live in if you weren't born wealthy and healthy.

What you said about the production of culture affecting the culture I find interesting. Is production in itself a revolutionary act? If culture is revolutionary, and we produce culture, what does that lead to? Also, I'm interested on whether you believe all culture has the power to change things.

I agree that to understand nominalism we need to understand realism. They do seem connected, or rather nominalism is dependent on realsim to make sense. Your connection between nominalism and fascism was spot on, and helped me grasp it.

I wouldn't mind reading some of your thoughts on the subjects, because you seem (from what I can gather) to have interesting ideas. It'd be great if you could elaborate on what you think about the stuff discussed.

Ooh, I like your thoughts about myth. In a way maybe science has become a little like myth for a lot of people today? We do kind of just trust that it works, and I know I'm not above begging my computer to do what I want when it's misbehaving... What you said about people fearing unknown things must still be true today, and would perhaps be the reason some people don't believe in vaccines, for example. Maybe it's because, as I said, science has become sort of myth-light today.

I would have liked to know more about the article you mentioned reading for next theme. In what ways does it relate to the superstructure? Otherwise, good concise write up, and I like what you said about aura.

Theme 3:

I like your discussion about the connection between theory and knowledge. It's neat when we can connect back to the things we learned earlier.

I both agree and disagree with your conclusion that theory makes us unable to consider anything fact. Yes, there is always a risk that will be proven wrong,but that is not a reason to not consider things true right now. As you say, we perceive things from our senses. Since that is our reality it's all we can conceive. So I don't think theory is not true, but rather that credibility is all that we have.

I was also confused about the difference between strong and weak theory. I think your explanation was good, and it helped me remember what differences there were. I agree that it can be hard to tell the difference, and I wonder what you think the different values are. Perhaps weak theory is better than no theory at all, in fact it probably is. It can maybe be used as a base for things we haven't discovered yet.

I like your post! You manage to summarize your thoughts very well, and your differentiating between scientific and philosophical theory is great.

I agree with most of your points, for example that theory should be able to be confirmed. However, I wonder if I agree that data collection is the most important part about research. As you say, data isn't objective. With that in mind, shouldn't the focus be on analysing the data you have gathered to make sure that it is not influencing your results?

Good recap of the material from the week! It's concise and clear, but I'm missing a little about your own thoughts about it. I also thought it would be easier to read the texts this week, but like you found that was not true. Paradigms is an important concept that it is good you talked about, since it's easy to forget to mention.

Theme 4:

I agree that qualitative data is more useful when you want a clear, simple answer, but I also think you touched on something interesting when you spoke of subjectivity. It's hard to be objective about oneself, and since quantitative data is reliant on what people say about themselves and their reasons for living it's hard if not impossible to know that they are answering honestly. It was good that you mentioned this, because it's easily forgotten.

It was interesting to look at this week's theme through the glasses of having recently done a bachelor, agreed on that. In fact, it might have been useful to have had this course before that one... Anyways, nice write up. I agree with above, that the core seems to be that different questions require different methods.

Interesting that you landed on the methods being compatible, because that was not my takeaway at all. In fact, I'd take the opposite approach and say that they are used for altogether different questions. Sure, maybe you could use one as a precursor to the other, but not always. Qualitative methods are in my understanding used in more complex questions where there aren't one simple answer. Often in cases where the answer is subjective.

You seem to have a good grasp of the material, and I think your points about developing questionnaires are good. The bit on objectivity is interesting, since as you say there is no way of actually knowing if data is ever objective.

In your focus on questionnaires, don't forget that there are other ways of gathering quantitative data. For example, Ilias drum study had quantitative data, but was without questionnaires. Otherwise I really like your write up, is clear and easy to follow.

Theme 5:

This post reads mainly as a list of things the lecturers said. It's a good write up, and what thought you have is good and interesting, but there are few bits that read like your own reflections. The second lecture, to me, was about how to use and analyze data gathered from prototype testing, and some about how to do that testing in an effective way.

Nice reflection, I like that you had your own thoughts and examples about Haibo's lecture. However, as some above me said, there is nothing on the other lecture of the week, nor anything concerning the papers we read or something like that.

I agree with you on Haibo's focus on mathematics. I fail to see how that part was relevant to us, since at least parts of our research will be in "softer" areas such as interaction design. In fact, it goes a little against what he said himself, since he talked about the importance of thinking outside the box. Anyway, our write up was good. You didn't talk anything about the other lecture however, something I missed a little.

I think your understanding of the lecture you attended is very good. Something that came to mind when reading your final point was that Haibo's lecture seemed rather focused on research for a financial reason, and not so much as an academic endeavour. The market gain, financial plan, that is not really something you need to have as your main focus if the research is just in the pursuit of knowledge, do you agree?

Theme 6:

Your point about the convenience of quantitative v.s. the engagement of qualitative data is really interesting, and I had a similar thought back during the quantitative methods theme. This is in a way a problem in that it makes the current state of research unavailable to the uninitiated. A lot of research papers include significant amounts of qualitative data, and they can be hard to grasp for a novice.

I'm not sure I agree with you on the fact that a case study can never be used to confirm theory, only create it. Perhaps I'm reacting to your language, but I'm sure there are some cases where case studies can indeed be used on pre existing theories. In general I agree that it's preferable to use on new topics, as the example with purple and displays.

I'm interested in what you said about the longitudinal study. To me it sounds like that approach could be used with either qualitative or quantitative studies. Perhaps there is something I'm missing? Even if your paper was about a qualitative longitudinal study, couldn't the data gathered easily be quantitative?

I like what you said about when a case study is finished. That is something I never thought about, so it was good to get that point of view. I would like to add that perhaps the study could also be finished when the researcher feels it is completed.

Your thoughts on case studies and experiments brought up a thought in my mind, on how much a researcher is allowed to take part in what they are studying during a case study. To use your example of ethnic groups, which is a great example, isn't the very action of coming from the outside and trying to take part interfering?

Anyways, I liked that you used examples from other fields than ours to make your point, it made the post easy to follow and understand.

Your post is very short, so it's actually hard for me to know what you thought about the things discussed during the week. I'm glad that the seminar helped you understand case studies, but perhaps you could have elaborated on what your conclusions were?

Theme 6 comments

1. http://reb2572.blogspot.se/2015/10/post-theme-6.html?showComment=1445858360489#c4509563385638112871
2. http://alexisdm2572.blogspot.se/2015/10/theme-6-post-seminar.html?showComment=1445870828165#c7246741719012926028 
3. http://dm2572byen.blogspot.se/2015/10/theme-6-qualitative-and-case-study_16.html?showComment=1445871212090#c2806423250997472165 
4. http://mediatechmishmash.blogspot.se/2015/10/theme-6-afterthoughts.html?showComment=1445871492354#c5766749111874347133 
5. https://tmmkappa.wordpress.com/2015/10/19/theme-6-post-reflection/comment-page-1/#comment-38 

Comments on Theme 5

1. http://cscmediatechnologyassignment.blogspot.se/2015/10/theme-5-reflection.html?showComment=1445261116441#c6473375563174848517

2. http://gklo.blogspot.se/2015/10/theme-5-design-research-post-reflection.html?showComment=1445261370721#c5577706637627489897

3. http://pargman420.blogspot.se/2015/10/post-seminar-reflection-5.html?showComment=1445261865651#c4087801198572999063

4. http://fromplatotocasestudies.blogspot.se/2015/10/theme-5-reflections.html?showComment=1445262291231#c2507758370909360916

Post Qualitative Research, or It's all in the title.

Final reflection. Here we go.

I felt a little adrift this week. Without the lecture, which was cancelled, there was little to connect what we had read to what we were supposed to have gotten from it until the seminar. That helped a lot, but I still missed the lecture.

The discussion had a lot in common with the one that occurred during the quantitative research seminar. What makes qualitative research as valid as quantitative (the ghost of scientism rears it’s ugly head), how do you analyze the data, and so on. What really helped on establishing the differences was when Ilias explained about how it’s not the number of participants in a study that determines if it’s qualitative or quantitative, but rather the type of data collected. I think it’s easy to stare oneself blind on the assumption that “a lot of data means quantitative, while few sources means qualitative”. This line of thought represents a lack of understanding of how the methods work and differ, but is still one I occasionally find myself risking drifting into.

During the seminar, we mostly discussed what made a case study. There were some difficulty in my group to agree on the specifics that differentiated a case study from other research.The paper I had read, that clearly had the words case study in the title, turned out to be a good example of a case study. It concerned one specific thing, and only looked at that thing in order to reach its conclusions. However, as I discussed with Ilias, the lines between a case study and certain types of qualitative research can be murky at times, and basically the best lead you have on whether the paper you’re reading is a case study is whether it has the words in the title.

A case study is often used to come up with new theory. It’s a good way to start exploring a new area of interest where not much work has been done before. Since it looks a just one or maybe a few cases, there is not much need to spend a lot of time proving that your research selection is unbiased or representative of the whole, and you can get started on the actual research faster. It can give you a basis on which to build further research, even though it might not give a wholly complete picture on it’s own.

For this reason I like case studies. It can be a way to look at something you as a researcher finds interesting, without perhaps having to have a complete idea formed in you mind.

Theme 4 comments

1. http://theoatmeth.blogspot.se/2015/10/theme-4-post-seminar.html?showComment=1444656912400#c5631622502255850783

2. http://alexisdm2572.blogspot.se/2015/10/theme-4-post-seminar.html?showComment=1444657190247#c1040097354683633936

3. http://dm2572byen.blogspot.se/2015/10/theme-4-quantitative-research.html?showComment=1444657467790

4. http://literaturestuffm.blogspot.se/2015/10/normal-0-false-false-false-el-x-none-x.html?showComment=1444657898584#c8143349452592760359

5. http://ninopmedia.blogspot.se/2015/10/theme-4-reflection-0-false-18-pt-18-pt.html?showComment=1444658173714#c3838164377793259386

Post Design Research, or how to define a problem.

This week differed from the previous in that it had two lectures, instead of one lecture and one seminar. Design research turned out to be a bit more complicated than I expected, or at least my relationship to it did. I thought I had a fairly clear view of the topic, but that might have changed.

The first lecture was by Haibo Li. He talked about how to go from idea to prototype, with a focus on how to develop ideas from start to finish. It had a focus on the practical, and did not touch on when design research was appropriate, or in my opinion even on what design research actually is. He talked a lot about how we need to work on defining the problem that we are trying to solve way more than we’re probably doing. In fact, he said that most of the time should be spent on a proper problem definition, since a different definition can lead to you seeing a different solution. His lecture also seemed focused on development in a business environment more than a research one, since he talked about how you should focus on business potential when filtering ideas.

The second lecture was done by Andres Lundström. He had an unprepared and unstructured set up, since he was a last minute replacement. This did unfortunately make his lecture a bit hard to follow for me, but what I grasped was this:

Research is done to test theory and to gain knowledge, which we already knew. Prototyping can be used to that effect with the help of a design process that gives answers to questions. The process is important since in some cases, like in papers we read this week, the process in itself is the empirical data of that study. The different prototypes developed during the design process and the changes done to them can also be data, since that is what is tested. This analysis of the changes can be thing that separates design research from regular design, since the end goal is not a perfect product but rather to, as I said, gain knowledge. The focus of this lecture seemed more research based than Haibo’s, which I actually preferred.

I found myself missing the seminar. The chance to talk about the things we have learned was more important for my understanding than I thought, and therefore I feel like my reflections are shallower this week. I don’t feel like I contributed, since all I did was read the papers and answer the questions. It feels like there was less room for consideration and reflection.

Pre Qualitative and case study research, or the Arab Spring was really interesting from a journalistic standpoint.

“What is, Becomes What is Right”: A Conceptual Framework of Newcomer Legitimacy for Online Discussion Communities by Silvia Elena Gallagher and Timothy Savage

http://onlinelibrary.wiley.com/doi/10.1111/jcc4.12122/epdf

The paper uses using what is referred to as Qualitative directed content analysis. Content analysis is used to find commonalities within communication, be it written or verbal. It can be used to describe phenomena within the context of that, for example, specific communication platform. A directed approach is based on previous theory and research, and is therefore used to confirm or add to preexisting theory.  In this paper they are using it to find what textual codes newcomers to online communities use and what makes these codings stand out. This was done through using literature to establish a base a coding framework on, and then by viewing four different online, active communities and analyzing posts made by newcomers to these communities. They then looked at what strategies these posters used to gain legitimacy within the community and managed to establish common themes and way to do this.

Talking about “codes” like this might make the method seem quantitative, but this is not the case. The authors did not look at amount of times a word was used or anything like that, instead they looked at the whole context of the post. They look for commonalities that might not be explicit, but can still be determined from the text and subtext of the post.

I think this a good approach for this kind of study. It requires going through a lot of written material at a rather fast pace, and so the “simplifying” if using a predetermined code system speeds up the process significantly. The use of four different communities helped avoid findings that would not be useable in a general context, as it meant that local behaviours were accounted for. They established a framework that can be used in future studies, but one that as they say is not a static tool and could be adapted to a new context.

Sourcing the Arab Spring: A Case Study of Andy Carvin’s Sources on Twitter During the Tunisian and Egyptian Revolutions by Alfred Hermida, Seth C. Lewis, Rodrigo Zamith

http://onlinelibrary.wiley.com/doi/10.1111/jcc4.12074/pdf

A case study is the process of looking at a specific case to develop and prove a hypothesis. When doing a case study you start out with a basic idea of the topic you want to research, and then go and find a person, a place, or an organization of interest to this topic. It differs from other research methods in that you don’t start out with a well developed hypothesis, but instead create one during the study itself, based on what you find. You also do data collection and analysis at similar times during the course of the study, instead of the traditional approach to first gather all the data and then analyze it all. A case study also usually looks a limited number of cases, although the amount varies. It can be a single case as in the paper I chose for this week, or it can be up to eight, as in the Harris and Sutton (1986) study referred to in the Eisenhardt paper.

The paper I chose seems to be, based on the criteria from Eisenhardt, to be fairly solid. It seems the case was chosen early on, since the research questions as presented in the paper are very specific to the single case in question. It is however possible that they have been reworked in the process of doing the study, I have no way of knowing that.

The fact that the study is done on past events makes it harder for me to analyze their data collection process, since the study is based on stuff that is readily available online, as archived twitter posts. However, I can discern that the process seems to have been made with consideration to avoid bias and errors. The literature comparisons are perhaps a little limited in scope, since it seems to focus on the one viewpoint about “old media” as the gatekeepers of information, and the paper wants to prove that this barrier is being torn down in this case. However there are numerous sources on relevant material, and it helps prove their hypothesis. The conclusion is clear and easily understandable, but the conclusion of the case is not decided by the researchers as much as by the context.

Comments on Theme 3

1. http://reb2572.blogspot.se/2015/09/post-theme-3.html?showComment=1444044585929#c4813827715750899941

2. http://theoatmeth.blogspot.se/2015/09/theme-3-post-seminar.html?showComment=1444046422059#c5626692335877499347

3. http://dm2572byen.blogspot.se/2015/09/theme-3-research-and-theory_27.html?showComment=1444046871971

4. http://mediatechmishmash.blogspot.se/2015/09/theme-3-research-and-theory_23.html?showComment=1444047665285#c3974568342210831241

5. http://literaturestuffm.blogspot.se/2015/09/theme-3-reflections-after-lecture-and.html?showComment=1444048741918#c5235664867968827082

Post Quantitative research, or there is no such thing as objectivity

I think it’s easy to believe that if you just collect enough quantitative data you can get the answer to any question, and to view that data as being objective. However, there will always be questions that can’t be answered through quantitative means, and data needs to be regarded as dependant upon a context. I talked about this in my pre-seminar text, and nothing we’ve learned during the week has changed my mind.

People who are used to natural science seems to have a real problem grasping issues that can’t be quantified. This is what is called scientism. Since some fields deals with questions that often have fairly easy answers (Did it change, how many did, what was the cause) it’s easy to apply the same logic on other field that doesn’t deal in those easy answers. While a biological study on frogs can have a conclusion of about a paragraph, an anthropological study might have an entire book as the answer, and even that is the short version. That was the main thing I learned during the seminar. In our group we spent a lot of time discussing when to use quantitative and qualitative methods, and it felt like that question dominated the whole seminar.

An example of the different questioned that can be answered was one I posed during the seminar, about tastes in food. If we, in the classroom, want to learn which food is the most popular, that is easily answered by a poll. Simple, quantitative data. However, if we want to know why that food is the most popular, we need to ask about people's opinions, As soon as you get into an area where opinions are interesting you need to use a qualitative method and analysis.

So how about the drum study? Ilias explained that they wanted to know if people moved differently, but you can’t ask that type of question and get a usable answer. The asking of the question to the subject would probably make them change their behaviour, and therefore affect the end result. However using quantitative data that can be gathered without the subject being aware of the data gathered removes the risk of unconscious influence. Here it wouldn’t have worked with qualitative data.

Challenges when working with quantitative research can lie in analyzing your data. It’s important to remember that data isn’t necessarily objective or true in all contexts, and to keep that in mind when you look at it.