什么是学习曲线？为什么陡峭而不困难？
- 学习曲线到底是什么？
- 为什么用“陡峭的学习曲线”这个词来形容那些进入门槛很高、需要相当长的时间才能进入的东西是错误的呢？
至于这个问题的原因：
- 这些术语在 Stack Overflow 上经常被使用，而且不一致，
- 我自己也被它弄糊涂了，
- 大多数新手在问“什么是最好的 php 开发框架”之类的问题时都会遇到这些术语。
- What exactly is a learning curve?
- And why is it wrong to use the term "steep learning curve" for something which has high entry barriers and takes quite some time to get into?
As to the why-ness of this question:
- The terms are used often and inconsistently on Stack Overflow
- I myself have been confused by it
- Mostly the newbies are confronted with these terms when they for example ask questions like "what's the best php development framework"
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评论（11）
这是时间与熟练程度的曲线。
陡峭为难是错误的，因为这意味着你在很短的时间内变得非常熟练
proficiency | __ | | | | Proficient in little time (steep = easy) | | |_/____________ time proficiency | | Proficient in lots of time (gentle = hard) | __ | / |__________/___ timeIt's a curve of time versus proficiency.
Steep for hard is wrong because it'd mean that you get very proficient in very little time
proficiency | __ | | | | Proficient in little time (steep = easy) | | |_/____________ time proficiency | | Proficient in lots of time (gentle = hard) | __ | / |__________/___ time请参阅维基百科。
“陡峭的学习曲线”是一个流行语，没有任何实际意义。 它曾经意味着你会取得快速进步。 “随着时间的推移，出现了一种误解，认为“陡峭”的学习曲线意味着某件事需要付出很大的努力才能学习......”
结论：使用该短语的人并不知道它不清楚。 你应该从他们那里了解哪些具体的东西很难学，并克服那些流行语和陈词滥调。
See wikipedia.
"steep learning curve" is a buzz-phrase that doesn't have any actual meaning. It used to mean that you'd make quick progress. "Over time, the misapprehension has emerged that a "steep" learning curve means that something requires a great deal of effort to learn..."
Conclusion: people who use the phrase don't know that it's unclear. You should get details from them on what specific things are hard to learn and get past the buzz-phrases and platitudes.
（来自
unix.rulez.org/~calver）（来源：rulez.org）
这个（非常不严肃）图表赞同陡峭==“难以攀登”的解释，对于任何记分的人来说。 Emacs。 如此真实。 ;-)
(from
unix.rulez.org/~calver)(source: rulez.org)
This (very unserious) diagram subscribes to the steep == "hard to climb" interpretation, for anyone keeping score. Emacs. So true. ;-)
我通常认为这与分配给学习的时间以及在那段时间必须学习的内容有更多关系。 如果你只有很短的时间来学习某些东西，那么你的学习曲线会比你有更长的时间来学习相同数量的材料要陡峭得多。 因此，陡峭的学习曲线是很困难的，因为这意味着你试图将六个月的学习时间塞进三周或其他什么时间。
在相同的时间内使用更多的材料会产生相同的曲线。
I've generally understood it to have more to do with the amount of time allotted to learning, and what you have to learn in that period of time. If you have only a short amount of time in which to learn something, your learning curve is going to be much steeper than if you had a longer amount of time to learn the same amount of material. So a steep learning curve IS difficult because it means you're trying to cram six months worth of learning into three weeks, or whatever.
More material in the same amount of time would produce the same curve.
来自维迪百科：
“陡峭的学习曲线”这个词经常被错误用来形容那些需要一些时间来消化的事情。 同样在 Stack Overflow 上，我多次看到它被错误地使用，因此这个问题和我自己的答案。
事实上，给出了一条陡峭的学习曲线，当相对容易开始新技能/技术/...时，
这意味着“学习进度（y）”和“时间”之间的关系投资 (x)" 大于 1。
from Widipedia:
The term "steep learning curve" is often wrongly used for things which need some time to wrap ones mind around. Also here on Stack Overflow I've seen it used wrongly many times and hence this Question and my own answer to it.
In fact a steep learning curve is given, when it is relatively easy to start of with a new skill/technique/...
it means that the relationship between "learning progress (y)" and "time invested (x)" is greater than 1.
这是一场直觉之战。 一方面，你有“陡峭=难以攀登”的联想，另一方面，你有“水平轴上的时间”约定（但“水平轴上的熟练程度”并不是“错误”，只是“更少”）受欢迎的”）。 因此，恕我直言，这不是“正确”与“错误”的问题，而是“直观”与“更直观”的问题。
我认为“陡峭=难以攀登”会获胜，因为它对任何在一生中任何时候爬过楼梯的人都有吸引力，而不是xy曲线，即使是受过数学训练的人有时也会混淆。
It's a battle of intuitiveness. On one hand, you've got "steep=hard to climb" association, on the other hand you have "time on the horizontal axis" convention (but "proficiency on the horizontal axis" isn't "wrong", just "less popular"). So, IMHO it's not a matter of "right" vs "wrong" but rather "intuitive" vs "more intuitive".
I think that "steep=hard to climb" will win, because it appeals to anyone who at any point in their life has climbed a stair, as opposed to the x-y curve which even people trained in mathematics sometimes mix up.
“学习曲线”有几种可能的解释，但一种相当自然的解释是 X 轴上是“经过的时间”，Y 轴上是“获得的知识”。 在该映射中，陡峭的曲线意味着您可以快速获得大量知识。
我能想到的“陡峭”与“困难”相同的唯一解释是，在 X 轴上映射“获得的知识”，在 Y 轴上映射“付出的努力”，这不是一个非常自然的映射。
There are a few possible interpretation of "learning curve", but a fairly natural one would be "time elapsed" on the X axis and "knowledge gained" on the Y axis. A steep curve, in that mapping, would imply that you gain a lot of knowledge, fast.
The only interpretation I can think of where "steep" is the same as "hard" is where you map "knowledge gained" on the X axis and "effort expended" on the Y axis and that is not a very natural mapping.
“学习曲线”最初在 X 轴上具有总经过时间[或制造/学习的总累积单元]，在 y 轴上具有生产/学习单个单元所需的时间。 你的第一个单元总是比第 100 个或第 1000 个单元花费更多的时间。 曲线的“陡度”取决于你擅长生产/学习某件事的速度。 学得快，你就有了“陡峭”的曲线； 慢慢地，你就会得到一条平坦的曲线。
我同意无知者已经改变了这个术语的原始含义，但准确地说陡峭很容易。 人们之所以感到不安，是因为我们这些在学校里注意正确使用语言的人很少参与这种类型的演变。
A "learning curve" originally had total elapsed time [or total cumulative units manufactured/learned] on the X axis and the time required to produce/learn a single unit on the y axis. Your first unit always takes more time than the 100th or 1,000th. The "steepness" of the curve depends on how fast you get good at producing/learning a thing. Learn quickly and you have a "steep" curve; slowly and you have a flat curve.
I agree that the uninformed have morphed the original meaning of the term, but to be accurate steep is easy. People get upset because those of us who paid attention to using language correctly in school rarely get to take part in this type of evolution.
学习曲线是获取知识的速度。 复杂系统上的新开发人员可能会经历陡峭的学习曲线，因为他们在提高生产力之前需要学习很多东西。 这意味着，如果经验丰富的开发人员熟悉系统，他们可能会经历浅层学习曲线。
获得知识并不总是意味着理解。 在某些情况下，开发人员可能不需要吸收大量系统细节，但可能需要了解底层设计才能高效工作。 这可能需要时间，但并不意味着学习曲线陡峭。
在实践中，理解和知识是齐头并进的。 大多数开发人员总是处于某种学习曲线上，但也会使用新知识来更深入地了解他们正在使用的系统以及他们正在使用的工具和实践。
Learning curve is the rate at which knowledge can can acquired. A new developer on a complex system will likely experience a steep learning curve as they will have a lot to learn before they can become productive. By implication an experienced developer may experience a shallow learning curve if they are familiar with a system.
The acquisition of knowledge does not always imply understanding. In some cases a developer may not need to absorb a lot of system detail but may need to understand underlying designs before they can be productive. This can take time but does not imply a steep learning curve.
In practise understanding and knowledge go hand in hand. Most developers will always be on a learning curve of some sort but will also be using new knowledge to forge a deeper understanding of the systems they are working as well as the tools and practises they are using.
确实，“陡峭的学习曲线”应该意味着“简单”，因为学习曲线的起源是测量性能随时间变化的图表，并且正确的难以学习的任务的表达应该是“渐进学习曲线”。 但是，“陡峭的学习曲线”应该意味着“困难”，这是完全自然的，因为a）大多数人从未看过实际的学习曲线，b）“陡峭”意味着“困难”，而“渐进”意味着“容易” ”。
这就是语言的演变方式，现在尝试改变这个术语的一般用法是完全徒劳的。 而且，无论如何，我可以不太关心整个问题（看看你怎么仍然确切地知道我的意思？）。
It's true that "steep learning curve" should mean "easy" given the origin of the learning curve as a graph of measured performance as a function of time, and that the proper expression for a hard-to-learn-task should be "gradual learning curve". But it's perfectly natural that "steep learning curve" should have come to mean "hard" given that a) most people have never looked at an actual learning curve, and b) "steep" implies "difficult" whereas "gradual" implies "easy".
This is how languages evolve, and it would be utterly futile to try and change the general usage of this term now. And, in any event, I could care less about the whole issue (see how you still knew exactly what I meant?).
难度级别不是一个因素。 学习曲线描述了获得熟练技能或高水平理解的时间长度。 描述将根据曲线所应用的测试对象而有所不同。 虽然可以肯定地说，获得诸如 MS 记事本之类的应用程序的熟练程度的学习曲线将是陡峭的，但该曲线的另一种应用是单个测试对象获得这种熟练程度所需的时间长度。 熟练使用 MS 记事本的学习曲线通常很陡，但玛丽的学习曲线可能比约翰更陡。
我认为关键是首先了解曲线的应用范围
Level of difficulty is not a factor. A learning curve depicts the length of time to acquire a proficient skill set or high level of comprehension. The description will vary based on the test subject that the curve is applied to. While one can certainly say that the learning curve for acquiring proficiency of an application such as MS Notepad would be steep, another application for the curve would be the length of time individual test subject take to acquire such proficiency. The learning curve for acquiring proficiency of MS Notepad is generally steep, but it may be steeper for Mary than it is for John.
I think the key is to first understand what the curve is being applied to