An end of the quarter reflection

I've completed my first quarter, and I want to take some time to reflect on my experience.

What I learned from my classes

I was looking for a simple or easy thread to pull through all three classes I took, but I don't think there is one; I can force it, but for now, I'll just focus on takeaways from Social Computing; many of these are Rodrick-isms that really resonate with me.

• "As a scholar, you are under no obligations not to make anyone mad." As social science moved away from an attempt to catalog and describe, and into a space of interpretation, the field became positional and it became appropriate for a researcher to actively bring an informed opinion to their work (of course, this was always the case—it just became legitimized.) This demarcates a stance, and that will likely piss some people off. That's fine; scholarly work (at least in social sciences, and I'll wrap design in there) can be overtly positional.
• "Scholarly value isn't about popularity." This was said both in the context of mass-popularity (Malcolm Gladwell), as well as in the context of academic popularity. It's okay to generate knowledge and publish it for an audience of one, ten, or a hundred. Popularity shouldn't be part of a research goal. But what about citation count...
• "A book does not owe you legibility." I had such a hard time with Barad, primarily because the writing is garbage. It's entirely illegible, and as we discussed in class, she's generous with neologisms of 6 or more syllables. Rodrick feels that a scholarly book does not promise more than scholarly content, and writing ability is not part of that promise. I still disagree with this one. If you conduct scholarly research and publish it in a way that no one else can understand it, it's art. That's fine, but then it can't be considered on equal footing to real research. And, as Rodrick described, this is a book that everyone cites but no one reads....
• "You can publish without collecting any data." This stood out to me: it legitimized interpretation and qualities of abductive reasoning as an end, not as a means to an end. This is the "the answer isn't in the data, it's what you do with it," and the data in this case is other scholarly content. But there has to be an argument, so you have to have something interesting to say.
• "The basic job of a scholar is to connect one thing to another." I don't know if I agree with this, mostly because I haven't given it enough thought and consideration, but I love the sentiment of it, because one of the basic jobs of a designer is to do just that—to find relationships between things that aren't overtly related and connected them.
• "Every field has a structural centerpiece." This is wonderful, and is maybe one of the larger conceptual ideas I walked away with. I imagine it as a set of concentric circles away from a grounding, and the grounding is built over time, little by little. We explored this in the context of "a turn," where the field at large decided to go in a different direction or to question something fundamental, and I liked the idea that I can "use" a turn in my writing. It's a warrant to start a story, acting like a sign indicator, and is a way to summarize a lot of research. For example, it can characterize decades of anthropology quickly. It acts as a reference point, and I can locate myself and my argument in or around it.

In terms of method, I learned a structural style for writing that can be used broadly (and at the very least in contexts of "publishing without collecting any data.") This is a three part "formula" of historicize, denaturalize, and synthesize.

• Historicizing is to explain why things look the way they do: to treat a particular subject as historical. The source for this could be literal archival work ("I went into a building and looked at old scrolls") but is more likely to treat a thing, anything, as a historical artifact. This means viewing it as contingent, with multiple explanations. An approach here is to find a historical force that no one else has thought about; the "formula" for this is "I’m thinking of [x] in terms of [y]."
• Denaturalizing is to bring something into the forefront that has typically been taken for granted as factual, unquestionable, and backgrounded as a result. There's a givenness to things, and to denaturalize is to question the giverness. The questioning can focus on what people do with things, and what things do to people.
• To synthesize is to recombine the denaturalized output into the context of the current, creating something new—creating a "new object of study" which can then act as a bundle or container for the entire exploration.

I also picked up on even more jargon, which is both useful and ridiculous; this includes Project, Unpack, Problematize, Curatorial, Performative, and so-on.

What I learned about my process

I feel pretty solid about my literature review working process, which largely follows these steps:

• Establish and work a backlog of things to read
• Read them online (as pdf), and highlight while reading
• Write a brief critical analysis of what I read, primarily focusing on highlighted elements, and including a view of the relevance of the content for my own research
• Add the analysis into my source control and highlight elements digitally
• Add the content to my running literature list
• Publish, pushing content automatically into Miro
• Organize in Miro
• Grab, copy, paste, edit into Word

Since the output of all of this is eventually some sort of written document, I've learned to write the critical analysis in a chunked format; each paragraph can, with little effort, be dropped into a larger paragraph or piece of content. This means including quotes that substantiate an argument, avoiding editorial commentary, and more or less avoiding "the author" in the body of the content because I'll end up citing the work and better threading the author's arguments into more of their content later.

I’ve worked ChatGPT into a few parts of this with mixed success. I have a rule for grammar and syntax checking, which it operates moderately well, and a rule for converting to clean and simple markup, which it does very well. I have found it very good at formatting my citations into Chicago format, but really bad at actually creating the citations from memory; if it has seen the citation before it still seems to change the author name to whatever it wants. I’ve tried a few times to integrate AI into my writing process itself. It’s moderately useful in summarizing my arguments back to me, and extraordinarily bad in authoring any new content or even working an editing process with me.

There are some overlaps and inefficiencies in here, but I don't mind them, because they force me to review the content many times rather than once and done. People have recommended other tools, like Zotero, but I haven't had a lot of success with them; I like the control I have over the Next environment here.

What I learned about the machine of academia

• In class, Rodrick once said "graduate school itself is a psychological stressor." I don't see it for myself, although I can see potential for that in my younger peers. I think it's because of how much is new for them at once. There's not a lot of scaffolding going on, and there's a bunch of threads intertwining: the course content itself, the freeform nature of the degree, the push to define a research topic quickly, and the machinations and operations of working, generally. It's the last part that younger students seem to struggle with the most, and it's basic project management that you learn in industry (at least in consulting)—getting shit done.
• I'm surprised/not surprised by the seat of pants way that some administrative work happens here. Even though there's not a lot of unexpectedness to the broad planning in academia (things are figured out 5-10 years in advance), there's a lot of scrambling around for basic things. I can work with that; it’s just interesting to see parallels to the corporate mess I'm used to.
• There's so much unused space. For all I hear in my research about design schools not having room for studio space, as I wandered around various parts of the campus, I probably saw at least six large, usable spaces for semi-permanent creative work that were entirely unused, and with no future plans to use them. I’m talking thousands of square feet of unused space. Related: so many classes are so large as to be meaningless. A writing class with 100 students? Intro to HCI with 200? It's insane. The students know it. The faculty know it. The administration knows it...... But $
• I really like being on campus. I knew this because of my SCAD teaching, but forgot it. It's calming, and I find myself contemplative and focused when I'm there.

What I accomplished

I'm pretty proud of what I've produced so far:

• Submitted a CHI paper, which was accepted to the second round, whatever that means
• Submitted a paper to Design Issues, which was accepted
• Submitted a paper to Art, Design & Communication in Higher Education, which was rejected
• Submitted a paper to International Journal of Technology and Design Education, which will probably be rejected
• Kicked off and completed my first research study, focused on Hiring for Creativity
• Kicked off and am mid-way through my second research study, investigating the way faculty think about and leverage studio in their teaching
• Submitted my third study to IRB, which will be a deep examination of the student studio experience
• Applied for a small Center for Craft research grant, which is pending
• Worked through about 140 papers for comps, and summarized them comprehensively
• Focused my studies and research on design studio culture

Oh, and we bought a condo.

Future schedule

Next quarter, I'm taking Qualitative Research Methods in Information Systems and Research in HCI. This is the end of my coursework (except for one elective), and the rest of my work will be focused on research.