I do not like “steep learning curve” the way people use it. It raises my probability estimate that person using it has done no study of learning. This reduces my probability estimate that they have sound insight about learning.
Sometimes I work with learning curves for machine learning or human learning. These curves are plots of a measure of learning (say, correct score, or number of mistakes) versus time or number of trials or number of training examples or number of iterations. When topic is hard, curve is shallow! It takes more learning to improve score or reduce mistakes. Steep learning curve means topic is easy. Mastery comes with very few repeats or little time or little data.
Does anyone know why so many use it wrong, to mean topic is hard and progress is slow? I believe Wikipedia article is right and “learning curves” must come from scientific study. How did meaning get reversed? Wikipedia article says “Arguably, the common English use is due to metaphorical interpretation of the curve as a hill to climb.” but has no citation.
The first post didn’t use it only to mean progress is slow. Version control software is no subject that takes much time to learn. The problem is that if you want to use it for the first time, it takes time to wrap your head around it before you can use it productively.
I don’t think the progress on learning R is much slower than the progress on learning Excel but learning R is harder. You can use Excel while have relatively little skill at using Excel.
Climbing a steep mountain takes more effort than climbing a mountain that isn’t step. It doesn’t necessarily take more time.
That’s what I understand by a “learning curve” too. I would tend to agree with the wikipedia proposed explanation: “steep” is, in some contexts, synonymous with “difficult”. Saying “you have to climb a shallow learning curve” would certainly be interpreted wrongly by most people.
Concerning the OP question, I wish I had learnt something interesting at school, instead of the thoroughly irrelevant, utterly boring, mindboggingly wrong pseudoknowledge.
To zedzed and D_Malik: I think what you have in mind is learning to play an instrument as a profession. I that case I agree that the rewards are probably not commensurate to the effort, unless you are exceedingly talented and lucky. But for everybody else it’s probably a good idea. If done for its entertainment value it’s surely worth it, and it helps you understand and enjoy music at a deeper level. On the minus side, it also makes you realize that most popular music sucks. Really really sucks, to the point of irritating me.
I understand the “steep learning curve” to be a curve on the plot where the X axis is the measure of progress, how far into the subject did you make it, and the Y axis is the measure of difficulty.
I do not like “steep learning curve” the way people use it. It raises my probability estimate that person using it has done no study of learning. This reduces my probability estimate that they have sound insight about learning.
Sometimes I work with learning curves for machine learning or human learning. These curves are plots of a measure of learning (say, correct score, or number of mistakes) versus time or number of trials or number of training examples or number of iterations. When topic is hard, curve is shallow! It takes more learning to improve score or reduce mistakes. Steep learning curve means topic is easy. Mastery comes with very few repeats or little time or little data.
Does anyone know why so many use it wrong, to mean topic is hard and progress is slow? I believe Wikipedia article is right and “learning curves” must come from scientific study. How did meaning get reversed? Wikipedia article says “Arguably, the common English use is due to metaphorical interpretation of the curve as a hill to climb.” but has no citation.
The first post didn’t use it only to mean progress is slow. Version control software is no subject that takes much time to learn. The problem is that if you want to use it for the first time, it takes time to wrap your head around it before you can use it productively.
I don’t think the progress on learning R is much slower than the progress on learning Excel but learning R is harder. You can use Excel while have relatively little skill at using Excel.
Climbing a steep mountain takes more effort than climbing a mountain that isn’t step. It doesn’t necessarily take more time.
That’s what I understand by a “learning curve” too. I would tend to agree with the wikipedia proposed explanation: “steep” is, in some contexts, synonymous with “difficult”. Saying “you have to climb a shallow learning curve” would certainly be interpreted wrongly by most people.
Concerning the OP question, I wish I had learnt something interesting at school, instead of the thoroughly irrelevant, utterly boring, mindboggingly wrong pseudoknowledge.
To zedzed and D_Malik: I think what you have in mind is learning to play an instrument as a profession. I that case I agree that the rewards are probably not commensurate to the effort, unless you are exceedingly talented and lucky. But for everybody else it’s probably a good idea. If done for its entertainment value it’s surely worth it, and it helps you understand and enjoy music at a deeper level. On the minus side, it also makes you realize that most popular music sucks. Really really sucks, to the point of irritating me.
I understand the “steep learning curve” to be a curve on the plot where the X axis is the measure of progress, how far into the subject did you make it, and the Y axis is the measure of difficulty.