Theme 5 Post 2

I feel like I now have a clearer grasp on what empirical data is. It’s data which has been acquired directly through someone’s observations and experiences. It’s not just any data which has been previously collected. However, this got me thinking about what the opposite of empirical data is. Unfortunately I didn’t get to discuss this during the seminar but I spent some time thinking about it. Opposites to empirical data would then be speculations, hypotheses and basically anything which is unobserved and just analytically thought out. Since empirical data has once been observed it’s also possible to verify the data.

Design work is in itself knowledge contributing. One main thing that should be stressed is that this is almost the purpose of doing research through design. Design work is explorative. It can start out from common design principles but they can change along the way since the purpose is mainly to gain insight into the field where the research is taking place. The iterative nature of design work facilitates this since changes can be made according to observations made in the study. It’s quite a flexible approach as it can be tweaked during the study and not everything has to be thought out before beginning. Instead of having a lot of research questions in the onset of the study, the questions may emerge as it proceeds. Future research topics could actually be revealed as the result of design work. I think that the most important take away from this is that the intentions of design work is different from other research. In design work the intention is to gain insight while doing, and in other research the insight comes as the final results. I do also think that in design it’s not necessary to explain all observations or design choices. It provides a lot of freedom to try stuff out and see if they work. Basically it’s a bit like learning by doing.

I wasn’t exactly sure what was meant about whether design work was ever replicable. In some sense it is. You could use the exact same technology, given that it’s still available. And then from a technical point of view wouldn’t this mean that the study is constructed in the same way? Probably, but a thing that has changed is the setting and the context in which the study is conducted. This could lead to unwanted results even though the study was very much the same. So it’s not only a matter of what technology is used but it’s also about the context of use. One could also think of replication as the methodology of a study being used again. The study could still be a replicate even though the technology has been renewed but the core methodology and structure remains the same (like the sequel to the tangible programming paper). Another thing which I would argue is even more important to discuss than the replicability is if it’s really meaningful to do so. Surely this depends on a lot of factors but I would argue that in many cases, especially in the softer sciences it’s not worth replicating older studies, mainly because the social context has been significantly changed. In general, harder sciences are more meaningful to replicate because they are less dependent on the social environment in which they’re performed. Social life contexts incorporates many complex variables which will influence the scientific results.