Theme 5: Design research

What is the 'empirical data' in these two papers?

The empirical data in Anders Lundströms paper is gathered using three different methods. Firstly, using a "state-of-the-art analysis" while driving all available electric cars and comparing the different methods of displaying the remaining range. This analysis further involved online researches for the user interfaces being used in the cars by looking at information from manufacturers as well as reviewers of the cars. The empirical data they found in this case is, that most manufacturers display the range as a single number. Some (BMW/Nissan) also display it in a map-based interface. Secondly, they gather data from online platforms and forums, specifically those topics that came up, when searching for the term "guess-o-meter" on Google. The data they found there was mostly, that there is a big need for understanding how the range is being calculated and what influences that range. Many online users seem to be frustrated with the sudden jumps in range depending on their style of driving or use of additional features like climate control and so on. Users of the Nissan Leaf even came up with a spreadsheet that cross referenced battery status with driving speeds and thus gave a better range estimation as the build in feature. Thirdly they conducted several interviews, leaving them with a set of data from which they concluded that drivers have come up with their own range estimation either based upon experience, or based upon the battery level gauge. The latter ones seemed to have had a better understanding on how different styles of driving as well as the use of additional features influenced the range of the car. So to summarize: their empirical data is the outcome of a state-of-the-art analysis, the findings of the analysis of online discourses and the answers to the interviews conducted.

In Ylva Fernaeus & Jakob Tholanders paper, the empirical data is gathered studying (qualitative) how children are using their tangible programming system that they build up as a workshop activity in an art gallery. They iterate this process with a low fidelity and a high fidelity prototype to gather their empirical data. This data lead them to "shift their focus from a focus on persistent representation and readability of tangible code structures, to instead focus on achieving reusability of programming resources".

- Can practical design work in itself be considered a 'knowledge contribution'?

While one can argue about the style of research and the quality of the outcome, it is from these two papers very clear, that they can be considered knowledge contribution. By trying to come up with a good practical design both of the researchers where able to pinpoint problems that exist and then come up with an improved way of tackling the problem, even if it might be a rudimentary solution at first, it can lead to further analyzing, testing and designing of the problem at hand.

- Are there any differences in design intentions within a research project, compared to design in general?

It is safe to assume that there are differences in the design intentions. In research projects one usually aims for a scientific explanation of a problem which then leads to a better understanding of it and therefore to an improved design. In general design this scientific problem (or reason for the design needing an improvement) is often not of a higher interest to the designer.

In research, the focus is on the scientific problem, whereas in general design, the focus is simply on the design itself.

- Is research in tech domains such as these ever replicable? How may we account for aspects such as time/historical setting, skills of the designers, available tools, etc?

It is highly debatable whether research in tech domains are really replicable. They evidently are replicable to some extend when done shortly after the original research. However as time progresses it becomes harder and harder to replicate the same situation as in the original research due to progress of the technology at hand. If for example one was studying Augmented reality some 20 years ago, one would have needed expensive high-tech equipment to even get the simplest representation of mixed reality whereas today smartphones come with gyroscopes, GPS, cameras, display and even the computational power necessary to process all of that input in one single device.
That being said the early studies usually are what lead to the improved technology in the first place and therefore are of utmost importance for later research.

- Are there any important differences with design driven research compared to other research practices?

The most important difference with design driven research seems to be the iteration process that always happens during design research. One never just comes up with a good design. The design has to be first tested, then refined, then tested again, then refined yet again et cetera. Other research fields usually "just" research and (re-)define the problem, do experiments on it and draw conclusions from the findings and then stop.