Thanks. That’s a really nice list.I have not seen a lot of these ideas previously.Especially general purpose tool-idea and stock of problems-idea is very good.These ideas are really nice to ensure in-built spaced repetition.
But can you give me some ideas about the second question I asked.I cant do this because I am still undergrad.So pick a topic that you learned about say 4-5 years ago(or any time-frame for that matter),make sure that you haven’t used that particular knowledge for the past 4-5 years,try to get back to the same knowledge-level that you had acquired when you first learned the topic(or some % of it) and measure the amount of effort/time that you took.Then calculate the ratio of (this time or effort)/(time or effort when you first read that particular topic).
I graduated 7 years ago. During that time, I’ve actually used most of the subjects I studied in college—partly at work (as a data scientist), partly in my own research, and partly just when they happen to come up in conversation or day-to-day life. On the occasions when I’ve needed to return to a topic I haven’t used in a while, it’s typically been very fast.
But the question “how long does it take to get back up to speed on something I learned a while ago?” kind of misses the point. Most of the value doesn’t come from being able to quickly get back up to speed on fluid mechanics or materials science or inorganic chemistry. Rather, the value comes knowing which pieces I actually need to get back up to speed on. What matters is remembering what questions to ask, how to formulate them, and what the important pieces usually are. Details are easy to find on wikipedia or in papers if you’re familiar with the high-level structure.
To put it differently: you want to already have an idea of what kinds of things are usually important for problems in some field, and what kinds of things usually aren’t important. If you have that, then it’s fast and easy to look up the parts which are important for any particular problem, and double-check that you’re not missing anything crucial.
Thanks. That’s a really nice list.I have not seen a lot of these ideas previously.Especially general purpose tool-idea and stock of problems-idea is very good.These ideas are really nice to ensure in-built spaced repetition.
But can you give me some ideas about the second question I asked.I cant do this because I am still undergrad.So pick a topic that you learned about say 4-5 years ago(or any time-frame for that matter),make sure that you haven’t used that particular knowledge for the past 4-5 years,try to get back to the same knowledge-level that you had acquired when you first learned the topic(or some % of it) and measure the amount of effort/time that you took.Then calculate the ratio of (this time or effort)/(time or effort when you first read that particular topic).
I graduated 7 years ago. During that time, I’ve actually used most of the subjects I studied in college—partly at work (as a data scientist), partly in my own research, and partly just when they happen to come up in conversation or day-to-day life. On the occasions when I’ve needed to return to a topic I haven’t used in a while, it’s typically been very fast.
But the question “how long does it take to get back up to speed on something I learned a while ago?” kind of misses the point. Most of the value doesn’t come from being able to quickly get back up to speed on fluid mechanics or materials science or inorganic chemistry. Rather, the value comes knowing which pieces I actually need to get back up to speed on. What matters is remembering what questions to ask, how to formulate them, and what the important pieces usually are. Details are easy to find on wikipedia or in papers if you’re familiar with the high-level structure.
To put it differently: you want to already have an idea of what kinds of things are usually important for problems in some field, and what kinds of things usually aren’t important. If you have that, then it’s fast and easy to look up the parts which are important for any particular problem, and double-check that you’re not missing anything crucial.