I was fortunate enough to be selected to attend the Centre Researches Interdisciplinaries (CRI) Workshop on Teaching through Research with additional funding from ExCiteS to allow me to do so. For those who may be unfamiliar with my research, I’m interested in teaching Map Making Concepts to graduate researchers interested in using it in Interdisciplinary Research who are coming from disciplines that may not be familiar with said concepts/tools (for more information, check out my personal blog).
My goals for this workshop were to engage with various researchers to potentially enable collaborations with ExCiteS, but most importantly, establish the structure of the experiments I plan on running as part of my PhD. My aim was figure out what, specifically, to teach, the best way to teach it (including projected time scales), and then how to assess if what I taught stuck. In the end, I’d say I was largely successful in pulling most of what I needed together, but there’s still more to do.
With that said, though, the workshop made me think about interdisciplinarity from a broader perspective. When I went to the Association for Interdisciplinary Studies’ conference, I felt like people focused too much on interdisciplinarity and forgot about their own disciplines and how those knowledge domains can enrich other studies. On the other hand, from this workshop, which was mainly made up of Biology, Chemistry, and Physics people, they talked about the interdisciplinary understandings they achieved between Biology and Chemistry, but seemed to mostly stick in their own disciplines. To me, it also seemed different in comparison to my own research unit, in that as an outsider to their disciplines, I would consider Biology and Chemistry to be relatively similar, in comparison to, say, Anthropology and Computer Science. But beyond that, as someone coming from an outside discipline (Geographic Information Science), if we are being interdisciplinary, then there’s certain understandings that we’d need to achieve between our disciplines, which I don’t entirely felt happened. I know no more about a protein or an enzyme today than I knew before the workshop, and I’m sure the participants aren’t even aware of any of the common map projection types. Perhaps people weren’t bothered about bridging those gaps as my domain may not have been of interest to them.
To clarify, using the image at the top of the post, I’d like to propose the following concepts on interdisciplinarity:
- Two disciplines (e.g. Biology and Chemistry) can be perceived to be more similar than two other disciplines (e.g. Psychology and Painting), and therefore a bigger gap of common knowledge. Therefore, perhaps we can refer to the former as “small scale” interdisciplinarity and the latter as “large scale” interdisciplinarity.
- Researchers from two different disciplines may share an interest in doing interdisciplinary research together (e.g. a Biologist and a Chemist to increase the effectiveness of the biochemical agents of washing powder OR a Biologist and a Psychologist working together to understand how the body’s systems are effected by mental disorders), but that interest in other disciplines is limited to what the researchers want to do (e.g. a Chemist may see no way Painting could be infused in their work, whereas a Psychologist could use Painting as a medium of expression for those with mental disorders). Therefore, perhaps we can say that one’s sphere of interdisciplinary interest can be as inclusive/exclusive as they see fit.
From this, we can start to see that “interdisciplinarity” doesn’t have a one-size-fits-all definition. It could be suggested that we can more effectively work in an interdisciplinary way by thinking “large scale” and expanding one’s sphere of interests, to be as inclusive as possible. On the other hand, “small scale” may be necessary to tackle fundamental disciplinary difficulties that may need to be handled to progress with research, and it’s unlikely that someone can be interested in EVERYTHING.
Bearing this in mind, perhaps we can start to be more effective in interdisciplinary research by understanding what it means to those involved and then working from there.