A learning curve is a hypothetical graph of how much time and energy must be invested before a tool can be used productively by the average user. If a tool has a high learning curve, it requires substantial study and experimentation before it will actually be useful. If a tool has an extremely low learning curve, the average user will be able to pick it up and intuitively know how to use it.

A lower learning curve is generally prefered, but sometimes a higher learning curve is acceptable if it results in a more powerful and flexible tool.

As an example, the Macintosh is generally considered to have a smaller learning curve than Unix.

From the day that we are born until the day that we finally sail off on that great tax-free holiday in the sky we are constantly on a learning curve.
Whether it be learning to sit without our mom's having to hold our heads up or learning to play by the rules or even learning to do a writeup. It never stops.
Of course nobody's learning curve is identical to anyone else's. Nor is there ever only one learning curve to life. It's more like a roller coaster without the loops (or perhaps not).

But there are certain milestones along the way on each learning curve which can help you to orientate yourself on the curve.

  1. euphoria - 'Hey! this is easy'
  2. on the up - 'uhm, okaaay.. who put this bump here?'
  3. climbing - 'sheesh! Are you kidding me? Perhaps I should've stayed at home.'
  4. doubt - 'nope, can't do it - sorry, goodbye'
  5. perseverance - now this is where it gets hard...
  6. success - it speaks for itself doesn't it?
  7. euphoria - 'sure, no problem'

In the end there probably isn't a fool-proof approach to learning curves, but it all comes together in the perseverance bit.

Interestingly, the common use of this term is completely, unutterably, WRONG! Wherever I look (particularly in rigourous, exact disciplines such as computing, but also one of the softlinks below does this) I see "steep learning curve" meaning hard to learn.

Really? As explained by Agthorr above, the learning curve is a (hypothetical, mythical, nonexistent) graph of how much one knows of something after spending X effort+time. Steep curves are the one which go up faster (we assume the learning curve is the graph of a monotone function here...). Would you rather (assuming -- incorrectly -- that you could do both and end up with the same amount of knowledge) Teach Yourself C++ In 21 Hours or Teach Yourself C++ In 21 Years?

Thought so. Yet many insist on claiming that the necessarily steeper learning curve of Teach Yourself C++ in 4 Hours is worse!

A probable source for this confusion is the intuitive expectation that steep ascents are "harder". This is true -- trying to learn C++ in 7 days wastes time rather than saving it, as you waste the first 7 days "learning" C++, the next 28 days discovering that you need to learn in properly, and only then can start studying C++. But all this shows is that the "2.4 days strategy" is ineffective. And the reason it is ineffective is that it gives a very shallow learning curve: you spend the first 14 days learning nothing.

Learning curves typically also factor in effort. So there really is no excuse.

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