Theme 5: Design Research - Reflection

This week we changed from having the usual seminars to two lectures, both conducted by a researcher that was involved with last week’s research papers. Since during this course we have mainly thought for ourselves, read, and discussed in groups what we think is a theory and so on, it was great to finally having scholars telling us what their opinion on these subjects were, in a more concrete way. Ylva Fernaeus’ presentation was a bit more casual, inviting us to discussion, which kind of failed due to no one in the lecture hall talking, but it was a good lecture in the sense that it was directly applicable to the research paper. Ylva said that she wasn’t involved in the subject of physical programming and robots anymore, and when asked she didn’t know if any further research has been done in the area which I think is a pity since it’s an interesting new field of research. 

Haibo Li's lecture was more “general” than Ylva’s, not going through so much of his research paper, but more the process from idea to prototype in a 5-step model from a technological perspective. Each step was broken down and he gave several examples, which I enjoy since just stating facts is kind of boring no matter what the topic is. A completely new thing for me was the ANOVA-system, which is an important part in using statistics and then forming a “real” conclusion. To use the conclusion to really formulate what is relevant and what is redundant data from the research that has nothing to do with the original problem. I liked the last part that was about what happens after your idea is basically done, that is, how you should present your idea to businesses and so on. Just stating technical facts might lead to people thinking that you’re just a tech-nerd that has no sense of the market and demand for such a product, and vice versa if you go on a more traditional sales pitch, selling words more than a product/idea. Instead of this, you should kind of merge them into an entrepreneur approach, telling companies why your idea could help their company (and clients) by using it while backed up by technological facts, kind of baked in to a sales pitch.

An interesting part than I’ve never thought about myself, is what differs “fame” from “greatness” in problem solving. That if fame is all you want you should put about 90% of your time into solving (existing) problems, and 10 % to statement of problem, yielding a lot of research papers being published. But if you want greatness you should have it the other way around, putting 90 % into defining and re-defining the original problem, causes and possible solutions. This thought really got me evaluate my own typical process. Most of the time I just go for a “good-enough” problem to solve and then never return to re-stating the problem, putting most efforts to getting done with the solution. Even though much of the material from the lectures served more as a refresher of things that I’ve learned before, there is much that I will try to carry with me in the future.