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In grad school it seems obvious what you want to retain, after that it can become a bit trickier to make the choice. General question for everyone using this ap
by t_mann 4y ago
In grad school it seems obvious what you want to retain, after that it can become a bit trickier to make the choice. General question for everyone using this approach: how do you go about selecting topics to put into your SR schedule?
I mean there are so many things that would be good to remember: math problems and leetcode are actually continuously relevant if you're in employment and ever thinking about moving jobs, software engineering tools that are important for daily work (those are changing so fast in some cases that I'm wondering again how much is worth committing to long-term memory), maybe there are some academic fields where you want to stay up-to-date on the research, all sorts of life hacks in the household / cooking / DIY space, literally everything about your family life, maybe some strategies in hobbies (just recently got into speedcubing, which is a lot about algorithm memorization),...
Maybe the problem is just that I have too much of a "finite memory" mindset and we can easily remember all of those, lol.
- borroka 4y agoThe problem is quickly solved, and it is important not to fall into " paralysis by analysis." Sometimes, while writing a card, we tell ourselves that it is not so important to remember that information and discard it, other times we discard it when during the review process we sense or realize that we are not interested in remembering that information . Assuming that there is some sort of logic behind the decisions made, I recommend using the same strategy that Napoleon is said to have used in his campaigns: first we start, then we will see.
- t_mann 4y agoYeah, the whole thing is probably easy to overoptimize. Any recommendations wrt to the software? My preference for these sort of things are maximally compatible/portable solutions based on simplistic file formats (I keep a lot of personal tracking data in csv, eg). Here I'm thinking something along the lines of local markdown files for the cards, a database for the sampling info and a web app that does the sampling.
- borroka 4y agoI use Anki in a "straightforward" way. In the sense that I write the card using Anki's interface without using excel or markdown files. For example, if I want to memorize a word I found while reading, I highlight it in blue in Apple's books, it goes to readwise, then I take it from readwise by copying and pasting from Apple's dictionary the translation or definition. I am for the simplest things possible, the point is to learn/memorize and not to find the best pipeline. You may think that the optimal pipeline leads to optimal learning, but (1) what kind of difference are we talking about compared to the simplest method of building cards?, (2) if setting up the pipeline means having the pipeline as the goal (as in ML the platform and not the predictions become the goal) or abandoning the study because the whole process becomes too cumbersome, is that something we should aspire to? One of my favorite novelists, Arturo Pérez-Reverte, when asked what software he uses to write his novels, replied: "I only use Word, but it's true that I don't know any other [software]".