What should I understand from "steep learning curve"? When a computer program (for example a translation program) has a steep learning curve, does it mean that it is not good at learning or it's hard for it to learn?


In informal usage, a "steep learning curve" means something that is difficult (and takes much effort) to learn. It seems that people are thinking of something like climbing a steep curve (mountain) — it's difficult and takes effort.

As it is technically used, however, a learning curve is not anything to be climbed, and is simply a graph plotting learning versus time. Thus, a steep learning curve would look like this (excuse the poor drawing):

Steep learning curve

One natural interpretation of such a curve, which was the predominant early usage (according to Wikipedia) and still exists in some technical circles, is that the thing being learnt is easy — a great amount of learning happens in a small amount of time. This is the opposite of the popular usage. Now there is also apparently an interpretation of the same curve in the negative sense — probably something about a large amount of learning existing, or that one never stops learning and keeps learning, but I'm not sure I understand how that's negative.


The popular meaning of "steep learning curve" is "difficult to learn"; the technical meaning is "quick to learn".

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    +1 for information about actual meaning of this phrase and the way it is usually used. More about this: discuss.fogcreek.com/joelonsoftware/…, stackoverflow.com/q/277618/95. – Marek Grzenkowicz Dec 4 '10 at 16:38
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    The technical meaning isn't "quick to learn"; by a steep learning curve, what's meant is a curve with a "cliff" in it. That is, something where it takes a while to learn anything at all, and then one "suddenly gets it". It's not such a big jump from there to "difficult", although the original literal meaning was a particular kind of difficult. – Henry Dec 4 '10 at 20:31
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    From psywww.com/intropsych/ch07_cognition/learning_curve.html: "People often speak of a steep learning curve when they mean the opposite. A steep learning curve is one in which skill improves quickly, meaning something is easy to learn. However, what most people mean by "steep learning curve" is difficult learning experience. No doubt they are thinking of steep hills and steep mountains which make climbing difficult. In actuality, the steepest part of the learning curve is the portion where learning is fastest and easiest." – Alex Dec 5 '10 at 14:24
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    I mean a curve with a long, fairly flat region, followed by a big, sudden jump. In other words, consider two skills where expertise in either can be achieved in 100 hours of training. In one task, there is a steady gain in understanding and ability as time is put in. In the other task, one gains almost no ability until after 90 hours, at which point mastery steadily climbs. In one sense, both are equally difficult (it takes the same amount of time to master each), but in another sense, the second task is more difficult. – Henry Dec 5 '10 at 18:47
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    Why is the author using time and learning as x and y axis? A steep learning curve is used in the context of a pre-existing domain of knowledge and refers to the amount one needs to learn in order to be operating effectively within that domain of knowledge. In other words, if you have to know 3 facts about a domain, it doesn't have a steep learning curve; if you need to know 1000 facts it does. Time is irrelevant in this context. The correct axis should be "facts to know" and "effectiveness to reason / act in domain". Based upon this, steep learning curve is accurate. – timpone Dec 20 '13 at 14:04

I would agree with ShreevatsaR a bit, but I'd modify the axes:

enter image description here

So steep learning curve usually refers to how hard it is to acquire additional proficiency.

The first 1/4 of "proficiency" with the software might be kinda easy to acquire. But mastering the software is increasingly difficult in the diagram above.

A more realistic proficiency/difficulty curve might look like this:

enter image description here

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    These curves seems to agree better with the common use of "steep learning curve". Moreover having proficiency/difficulty relates better with a "learning" curve since proficiency is the ultimate result of learning whereas difficulty is the hurdle that needs to be overcome to obtain that proficiency (hence the hump in the second graph). However I feel that proficiency should be the dependent variable since it is the "outcome" of learning whereas effort (the inverse of difficulty) should be the independent variable. – adib Feb 18 '16 at 5:47

This phrase has a scientific basis (Wikipedia has information on its origin and scientific usage), but is most commonly used to indicate that something is difficult to learn. It refers to a person’s rate of progress in learning a new skill as it might be plotted on a graph. In this case it sounds like the computer program itself is difficult for beginners to use effectively, not that it is not good at learning. I have never heard the phrase used that way, though I suppose it could apply to a program that uses artificial intelligence.

protected by tchrist Aug 13 '14 at 14:48

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