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This past term[1] I had an illumination regarding how I work best academically.
I have long struggled with working effectively in a class when I don't really have interest in a subject, when I don't find the subject fun (Tews et al., 2016), or when I feel like the lessons being taught are ones I already know. This generally causes me to fall behind in my work, and results in me needing to make a mad dash to the finish line at the end of a term in order to not fail--if that is even an option that the teacher/professor/school gives me.
However, I think I've finally discovered a way in which I work well, even if I don't necessarily care about a subject. It requires some setup time, but once that time has been spent it allows me to work very efficiently thereafter. And best of all, it doesn't make me feel like I am wasting my time.
[1]: I've just finished my fifth term back at school, working towards a Bachelor's of Science in Computer Science. I'll likely make another informal reflection on that sometime soon, but suffice it to say I have learned about about how I learn.
For now, I'm referring to this as working "as a student of the subject".
Basically, I work best when I am passively familiar with a subject, can take my time to think--really think, as referenced by Hickey (2010) when talking about software design, for instance (01:08)--about how different references relate to one another, and can rely on a set of notes I've taken in the past.
If approaching something I am unfamiliar with, breaking it into smaller topics[2] and researching those first--recursively, if necessary--allows me to address the topic in a comprehensive and comfortable way. This process of partitoning complex concepts into simple, relatable components is recognized as a method that helps people learn any complex concept (Ortmann et al., 2016, p. 4).
I'll contrast this with some of the approaches I've tried in the past first, and then I'll try to explain what about this methodology works well with my brain.
[2]: This is not unlike the process in which a program or data model or algorithm is designed, and the congruence between the two is not lost on me
Working "the right way"[3]--where I only write about what I'm interested in and have thought a lot about, supporting that topic using my experience, research, and thoughts--is not productive and doesn't lead to learning.
Working "for the assignment"--where I view the prompt, do research, form a response, and then edit and submit all in one go before moving on to the next assignment--feels so disjointed and pointless to me. This is doubly true when I'm not interested in the subject; Ennui sets in very quickly. Knowing that grades are not necessarily accurate reflections of proficiency (Bockmon & Cooper, 2022, p. 31), I think it's likely that this dissonance contributes to that inaccuracy.
Working "to get a good grade"--by doing exactly what is required by a rubric, and nothing more--makes me feel like a fraud and think I am wasting my time, even if I care about the subject.
These were the big three I was oscillating between, because when the topic of finding the workflow difficult (as opposed to the workload; meaning the process of study, not the topic of study) these are the ones that are generally mentioned. And none of them really worked for me.
[3]: That is, "The Right Way" in my own, fictional world
Doing things "as a student of the subject" makes me feel like I am gaining something--something I can quantify, in notes taken[4] and papers/articles/books read--and lets me focus on an activity I enjoy doing regardless of the topic--namely, research.
I /love/ doing research, especially when I'm able to take two disparate ideas and connect them to one another through reference and citation. Synthesizing new ideas or concepts by combining others is what drew me to Computer Science in the first place--after all, what is a computation but the complex transformation of the representation of a datum or set thereof (Erwig, 2017, fig. 1.1)?--and it is something I hope to do as part of my career within the next decade or so.
[4]: This is why the concept of a Zettelkasten originally appealed to me; It helped me to really see my progress through my collection of notes growing.
I think this was one of the bigger hurdles for me, to be honest: If I enjoy research so much, why did it take me 5 weeks to write a review of this case study? And this is a simple, 3 page case study! Why was I finding it so difficult?
Well, I had no foundation from which to review it, and felt as though doing so through solely my own thoughts--or those of my textbook and lecturer--was not actually reviewing the case study. Furthermore, the brevity of the case study at 3 pages made it difficult for me to discover what I didn't know[5]--this is where the illumination came in, as this has happened more than a few times over the last year.
So, going forward, my process is going to be to work as a student of the subjct: Break new or unfamiliar concepts down into ones I can research, tackle those individually before even trying to address the actual topic, and then return to the topic--with a passing familiarity, a foundation of thoughts surrounding it, and a collection of notes related to the topic that I can use to support my ideas.
[5]: Indeed, this is the crux of the issue for me. Finding out the questions I need to ask is something I struggle with when considering things like Political Science or Public Health, mostly due to my lack of experience and interest in them