Theme 5: Reflection

                This week’s seminar and lecture provided plenty of room for discussion concerning design research. Dr. Li’s presentation went beyond a mere description of his opinion of design research and his experiences as a researcher and designer, but he focused not only on the basic work of testing but also on more intangible ideas that accompany such design. I enjoyed several of his points and learned a few tips for the inventor or designer that could easily be utilized in a business sense as well: like the filtering and selection of ideas. This is an important topic in both design and business as everyone has ideas but which are the ones to use?

                In my opinion this filtering of ideas is part of the foundation of design research because, as I mentioned in the first Theme 5 post, I imagine design research as a very creative field. But creativity must be channeled and a selection must take place to judge which ideas are more feasible than others, be it for scientific testing, development or business ventures. I was very amused that Dr. Li presented a scale on which to base our judgment and naming of ideas. Quickly, in his words: an innovative idea is worth $250000, where a big idea is worth $1M. However, the rare “great idea,” should be thought of as one worth over $1B! When one considers this, several products and discoveries come to mind such as the great idea of the microprocessor; the kind of idea that everyone knows about and started just as so many other technologies do, in the research design phase.  I wonder when the researchers working on ideas like these realize what they are doing; it must be quite exciting.

                I must now consider my journal article and whether the idea of a “soft multigait” robot could hold one of these lofty classifications. The researchers writing the article certainly thought it was at least a big idea, and the possibility remains to be seen in the future whether this could be great someday or not. Currently the idea needs more development, but I could see exciting potential in it. Which I think speaks to the power of a good proof of concept prototype. To be perfectly realistic, studies such as the one I found require funding, and typically those who are willing to fund something have an interest in its success. Therefore universities and industry/business world are constantly on the search for these innovative/big/great ideas, and, may I venture to say, design research is the top field for risk investments and possible future payoffs. What I can’t say is to what degree these investment politics play a role in the design research world. Certainly I have not considered public grants and foundation works as funding methods, but if there is one thing that any institution can understand it is value. Whether or not it can be identified early or not is one thing, but when, let’s say, the touch screen interface has become a standard, it is clear to everyone what a great idea that was, and no investor would want to be forgotten for their contribution, whether it is a university or a private group.

                Perhaps I am reading too far into a subject we only meant to understand as a research method, but when Dr. Li brought up the issue of business and success, it was a very important addition to what we had already learned. This, I would say, was a very practical addition, and certainly could be used as future advice as well as helping us to understand his particular field. Besides, doesn’t every kid go through a phase of wanting to be an “inventor?” I know I did!

Theme 5: Pre-Seminar

A further study into design research, this week's two articles further aided my understanding of this topic. Dr. Li's paper concerning his team's prototype experimental vibration-experience entertainment was a fine example of design research as well as my chosen paper, "Multigait Soft Robot" by Shepherd et al of Harvard University. These two papers shared common features, including the use and study of prototype systems. Dr. Shepherd's team designed and created a "soft robot" capable of dynamic locomotion.
The notion of prototypes in research is a fascinating one due to their potential influence of innovation and progress in technological fields. My paper focused on robotic progress through soft robots; those designed without any hard, "rigid skeleton to provide mechanical strength." The role played by this prototype as well as Dr. Li's are universally important in this field of research by providing the foundation of further study of previously theoretical ideas enacted through the prototype. This also highlights the importance of a proof of concept prototype to illustrate the potential success of a concept. A simple proof of concept prototype may be a much scaled down, or even an incomplete, version of a real prototype, and exists to prove quickly that the theories underlying the experiment are quantifiable and sound, or at least worthy of further investigation.
Theory was very important in the design process of Dr. Shepherd's soft robot. Without delving into our previous etymological discussions of truth, the theory behind such a practical prototype as this soft robot is what defines and gives the prototype its nature. Theory in this case can be understood as a basis of physical facts already known which give rise to new ideas, such as creating a robot out of soft polymer based upon the movements of starfish and worms found in nature. Theoretically it seems possible to create a polymer in a certain shape and, when certain chambers are pneumatically filled with air, it would create movement, and that movement, if properly channeled could be controlled to create planned and efficient movements commanded by humans. This is the theory behind the robot, as well as all the scientific principles which helped the research team to enact this concept successfully to amazing result, thus creating a completely new species of robot.
It is very clear in this paper that proper understanding of theoretical and scientific principles are required for success, as well as very accurate design and implementation of the prototype. This kind of research requires a large degree of skill and ingenuity to create what has never been created before, and thus typically is the reason innovation can move slowly as well as being quite expensive. These steps must also be meticulously recorded and shared to create credibility for the study.
The work done in design research differs greatly from qualitative and quantitative research for these reasons (but I'm sure these studies can be mixed and do overlap), as researchers are typically observing and recording data about something of their own creation, instead of something in the world at large.

Theme 4: Reflection

I will begin this week's reflection with a very simplistic observation I hope you'll forgive me for: I think it may be possible that design researchers get to have more fun than other researchers. What I mean to say is that while these scientists are testing and developing new technologies and concepts, it seems like they may have a lot more room for creativity and progress than standard qualitative or quantitative research. Perhaps I don't know what I'm talking about, but the title of this week's article helps my point:  "Comics, Robots, Fashion and Programming: outlining the concept of actDresses." Any team that can fir the words comics, robots and fashion into its title, must have had a little more enjoyment than the typical study.
I am going somewhere with this. My seemingly shallow observation made me wonder why this could be, and considering what we have learned this week about qualitative analysis and design research, I think there may be some truth to this idea where theory is concerned. Design research seems to be designed to create knowledge of a different sort from qualitative analysis, which typically is used as a form of observation of observable concepts, frequently in behavioral science. Where a qualitative analysis may yield truths of interactions and behaviors, design research captures the imagination in a different way by using theoretically designed ideas, translated into physical procedures or products. Not to get too ahead this week, Dr. Li's paper is a good example of a very creative idea engineered to become a physical reality, and then tested. Certainly not all design research happens at the prototype level, but I think the theory is similar. When the Kista team who wrote our article designed their study I get the impression they had a lot of creative effort to imagine the somewhat abstract theories of semiology they created.
My journal article,  "The psychology behind QR codes: User experience perspective" was a qualitative analysis of the user interaction behind the growth of this technology, but first there had to be QR codes to relate to. If we were to look back at those original experiments, where the Toyota engineers thought to themselves, "how can we make a better barcode to quickly categorize our car parts," they began research into the design of what would become those little square codes we now see more and more. It is the theory behind the imagination required to create completely new knowledge leading to creative innovation that I think is very interesting in this design method.

Theme 4: Retraction!

Well, anyone who read my pre-seminar report for Theme 4 this week may have questioned my ability to read. I say this because I must print this retraction for the multiple mistakes I made during my written report: it was a rough week! The attentive reader may have noticed I not once used the word "qualitative" in my response, and considering the assignment focused on this kind of research I must admit that is an oversight. I made two serious mistakes that I can now correct: I read our instructions too carefully, and, thinking it was a follow-up to last week, went ahead and wrote about quantitative analysis instead. Mistake number two: I selected an article which used qualitative analysis methods thinking it was the opposite! Imagine my surprise this morning when I prepared for our seminar. I had done everything completely backward! I had to wonder who this fellow was who wrote that posting last week. But I must say, my choice of article was quite convenient since it displayed some good examples of well executed qualitative work.
As I mentioned in my first response, the Korean team used highly precise in-depth interviews, selection of tested individuals by committee, a professional focus group created the survey questionnaires, and the survey was administered by professional marketers. I was fooled the first time around by the design of the questions to eliminate as much interference, bias and ambiguity as possible by creating yes and no answers. Considering today's discussion I now understand why I was wrong, as well as identifying another serious benefit to this method other than creating easily entered data for computation and formulation: An incredibly decreased amount of data collected. Instead of rivers of paper noting the subject's thoughts and opinion responses, the yes no approach greatly reduces workload.
For this reason I must thank Simon who commented on my embarrassing earlier post noting that 370 individuals for a study like this was not small in any way, as I had claimed, but would create a very large amount of interview data. I agree Simon, you are right! Hopefully any others who read or have read my post won't think I'm completely out of my mind. Apologies to readers for the mix-up! I'll try and make the next one a little more accurate, and begin by reading the instructions properly...

Theme 4 pre-seminar

The research study I selected focused on an experiment in which South Korean researchers attempted to learn more about how to improve public opinion of QR codes and discover ways of ensuring increased usage in the future. This was a well written and organized article and focused on a very interesting concept I haven't before encountered: QR codes are designed for mobile phone users, who have the appropriate software, to quickly scan for information coded within the image. This represents a communication-limited interaction based upon permission-based marketing. Such a relationship actually "...eliminates the methodology of broadcast media..." 

            This study utilized a methodological approach in an experimental design. Because this study was designed an a purely experimental way, the results could be victim to the faults and errors of a randomized testing scenario, one which much be monitored as closely as possible to generate accuracy. However, I learned a few things about quantitative testing through this article. The chief among these principles are thoroughness and oversight. Because this study sought to explore and discover new relationships the study design of this experiment was multileveled  and complex with four levels: Individual in-depth interviews, expert input from industry sources helped for groups of subjects, following focus groups a final questionnaire was developed with multiple inputs including industry experts and university professors, and finally this survey was administered by a professional marketing design group. The amount of input and oversight by knowledgeable professionals was huge. For a quantitative analysis like this one it is important to note that each question asked of the subjects in the survey was conceptualized in a "yes" or "no" format which creates the ability to place numerical value on the responses.

            Several weakness do become evident, however: first, the number of responses only totaled 370. In a study of widespread social importance this would be a serious problem, but in this study the research does focus on a specific technology not everyone has access to. I believe that in this case the small sample number may be adequate, but it can be open to criticism if future claims are made based upon this work.  Another problem is a technological one; such a study of emerging technology can only remain relevant for so long. QR codes are a new and rapidly evolving technology, and public opinion and use could shift rapidly at any time in the future.

            Another methodological problem is described in the study itself, that the sample input came only from the Korean market,

"...more research with samples from other countries is needed to validate the current results and provide pivotal implications for future convergence services. Customers’ value perceptions and their influence on commitment and behavior may differ from culture to culture, and results indicating the weights of the influence of different value dimensions should be interpreted with caution, at least with regard to the Asian markets, where the social influence of the group tends to be higher than in individualistic Western societies." (Shin, Jung and Chang, 2012)

Theme 3 Reflections

           Now that we're on the other side of Dr. Cleveland-Innes' lecture I must say that my first reaction to her lecture was a reconsideration of my comments about her article, Emotional Presence, Learning and the Online Environment. In my comments I accused her article of being heavily quantitative, and slightly qualitative, but to hear her speak about this topic, I had to think twice.

            My first indication was the simple fact that she believes strongly in mixed method research. This should be good evidence to imagine someone who espouses these beliefs must certainly practice them! And so, I must therefore have a limited understanding of what can be considered qualitative and what can be considered quantitative. I believe it was her team's method of numbering and categorizing responses which lead me to term it more quantitative, but the very nature of the study focusing on human emotion precludes any total qualitative overview. Does this mean I didn't give Dr. Cleveland-Innes her due credit? Perhaps at first I jumped to conclusions! Of course there would have to be some kind of subjectivity, but what lead me to believe her team relied more on quantitative analysis I have come to understand was their attempt to eliminate subjectivity to create reliable data!

            Dr. Cleveland-Innes described how many times they tested and re-tested, and painstakingly evaluated their data. I can only imagine the effort. This was similar to the process she described in her lecture of logic: a continuous process that must begin from either a deduction or an inductive argument. Deduction leads to specific instances which must then be interpreted to create general principles. The cycle continues as we take these principles and deduce from them. In her study their team had to be sure and thus set up very distinct parameters in the data collection and analyzation. 

            A very good point that I did not gain from the article is the systematical selection of subjects and randomization of data through random selection and random assignment. This will hopefully lead to no systematic effect. I can only hope that when it is time for me to perform research I can think back to this and recall the specific details!

Theme 3: qualitative and quantitative pre-seminar

Our two reviewed articles are no doubt linked; the first describing methods and designs for qualitative research, quantitative research and blends of the two in P. Lowenthal's Mixed Research and Online Learning. Our second article, M. Cleveland-Innes' Emotional Prescence, Learning and the Online Environment focused on one such study, the style of which Lowenthal attempts to describe in his article. It appears one bears reflection on the other and so I will attempt here to reflect on what I learned through these two pieces, and to analyze the form of the papers.
First, a good idea of qualitative and quantitative research methods needs to be developed; Lowenthal helps with this. In my simplistic words, quantitative research describes that which is mathematical and non-subjective systems based, while qualitative research is deeper in its abstraction and reflects the subjective how and why of a premise; certainly why it is used predominantly in the social sciences which requires such interpretations of scientifically ambiguous data. Lowenthal proceeds quickly to his point: suggesting a special mixed research is necessary and beneficial for online learning research, combining qualitative and quantitative methods into an elevated language of research. He recommends this path for several reasons. In his words, "One common purpose of using a mixed approach is to facilitate the richness of data and to expand the interpretation of the findings," as well as, "...quantitative and qualitative research questions can lead to very different samples, data, and analyses." This is a very important distinction as the purpose of research is to define acceptable and provable theories, and if different methods of research can produce different findings from the same data, something is amiss. "By relying on only one type of analysis, these researchers are possibly making interpretative errors," he suggests, and it is a very reasonable analysis, therefore leading to a model of mixed methods between the two.
The question now is how Dr. Cleveland-Innes designed her research into online learning based upon emotional activity through "communities of inquiry." My understanding posits that what appears to be predominantly qualitative research does bear the indications of a kind of mix in the final measure. Lowenthal does describe the difficulty in mixing these methods, as it requires the research team to be masters of both, as well as developing new skills of analyzing the interactive data between the two, which is a relatively new concept.
Cleveland-Innes' design of her experiments are rigorously scientific and based upon simple-answer quantitative questions which can be mathematically categorized and understood and formulated into the test design. However, this team certainly understood that in a social science experiment like this one, dealing with such unmeasurable input as human emotions, qualitative analysis was a necessity. As the article states, "Knowledge about the impact of emotion on learning broadly (Brookfield, 2006; Lipman, 2003) is starting to emerge, but we are at early stages of discerning appropriate actions by students and teachers online, let alone being able to explain how emotion impacts online learning." To discern these "appropriate actions" requires an understanding of the subjects and their interior lives and feelings. At this time I must argue that there is no quantitative way to accurately measure this broadly from individual to individual.