A learning curve is a graphical representation of how an increase in learning measured on the vertical axis comes from greater experience the horizontal axis ; or how the more someone or something performs a task, the better they get at it.
The term learning curve is used in two main ways: where the same task is repeated in a series of trials, or where a body of knowledge is learned over time.
Hermann Ebbinghaus first described the learning curve in in the field of the psychology of learning, although the name did not come into use until The familiar expression " a steep learning curve " means that the activity is difficult to learn, although a learning curve with a steep start actually represents rapid progress. The first person to describe the learning curve was Hermann Ebbinghaus in His tests involved memorizing series of nonsense syllables , and recording the success over a number of trials.
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The translation does not use the term learning curve —but he presents diagrams of learning against trial number. He also notes that the score can decrease, or even oscillate.
The first known use of the term learning curve is from "Bryan and Harter 6 found in their study of the acquisition of the telegraphic language a learning curve which had the rapid rise at the beginning followed by a period of retardation, and was thus convex to the vertical axis. Psychologist Arthur Bills gave a more detailed description of learning curves in He also discussed the properties of different types of learning curves, such as negative acceleration, positive acceleration, plateaus, and ogive curves.
Fig 1 . In , Theodore Paul Wright described the effect of learning on production costs in the aircraft industry and proposed a mathematical model of the learning curve.
He named this particular version the experience curve. The economic learning of productivity and efficiency generally follows the same kinds of experience curves and have interesting secondary effects.
Efficiency and productivity improvement can be considered as whole organization or industry or economy learning processes, as well as for individuals. The general pattern is of first speeding up and then slowing down, as the practically achievable level of methodology improvement is reached. The effect of reducing local effort and resource use by learning improved methods paradoxically often has the opposite latent effect on the next larger scale system, by facilitating its expansion, or economic growth , as discussed in the Jevons paradox in the s and updated in the Khazzoom-Brookes Postulate in the s.
A learning curve is a plot of proxy measures for implied learning proficiency or progression toward a limit with experience.
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For the performance of one person in a series of trials the curve can be erratic, with proficiency increasing, decreasing or leveling out in a plateau. Fig 1. When the results of a large number of individual trials are averaged then a smooth curve results, which can often be described with a mathematical function. Fig 2. Several main functions have been used:   . The page on " Experience curve effects " offers more discussion of the mathematical theory of representing them as deterministic processes, and provides a good group of empirical examples of how that technique has been applied.
Plots relating performance to experience are widely used in machine learning. Performance is the error rate or accuracy of the learning system, while experience may be the number of training examples used for learning or the number of iterations used in optimizing the system model parameters. Initially introduced in educational and behavioral psychology , the term has acquired a broader interpretation over time, and expressions such as "experience curve", "improvement curve", "cost improvement curve", "progress curve", "progress function", "startup curve", and "efficiency curve" are often used interchangeably.
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In economics the subject is rates of " development ", as development refers to a whole system learning process with varying rates of progression. Generally speaking all learning displays incremental change over time, but describes an "S" curve which has different appearances depending on the time scale of observation. It has now also become associated with the evolutionary theory of punctuated equilibrium and other kinds of revolutionary change in complex systems generally, relating to innovation , organizational behavior and the management of group learning, among other fields.
Learning curves , also called experience curves , relate to the much broader subject of natural limits for resources and technologies in general. Such limits generally present themselves as increasing complications that slow the learning of how to do things more efficiently, like the well-known limits of perfecting any process or product or to perfecting measurements.
Approaching limits of perfecting things to eliminate waste meets geometrically increasing effort to make progress, and provides an environmental measure of all factors seen and unseen changing the learning experience. Perfecting things becomes ever more difficult despite increasing effort despite continuing positive, if ever diminishing, results. The same kind of slowing progress due to complications in learning also appears in the limits of useful technologies and of profitable markets applying to product life cycle management and software development cycles.
Remaining market segments or remaining potential efficiencies or efficiencies are found in successively less convenient forms. Efficiency and development curves typically follow a two-phase process of first bigger steps corresponding to finding things easier, followed by smaller steps of finding things more difficult. It reflects bursts of learning following breakthroughs that make learning easier followed by meeting constraints that make learning ever harder, perhaps toward a point of cessation.
The expression steep learning curve is used with opposite meanings. Arguably, the common English use is due to metaphorical interpretation of the curve as a hill to climb. A steeper hill is initially hard, while a gentle slope is less strainful, though sometimes rather tedious.
Accordingly, the shape of the curve hill may not indicate the total amount of work required. Instead, it can be understood as a matter of preference related to ambition, personality and learning style. Product B has greater functionality but takes longer to learn. The term learning curve with meanings of easy and difficult can be described with adjectives like short and long rather than steep and shallow. Fig 9 On the other hand, if two products have different functionality, then one with a short curve a short time to learn and limited functionality may not be as good as one with a long curve a long time to learn and greater functionality.
Fig For example, the Windows program Notepad is extremely simple to learn, but offers little after this.
At the other extreme is the UNIX terminal editor vi or Vim , which is difficult to learn, but offers a wide array of features after the user has learned how to use it.
Ben Zimmer discusses the use of the term "ON a steep learning curve" in an article "A Steep Learning Curve" for Downton Abbey , concentrating mainly on whether it is an anachronism.
Unfortunately, people didn't start talking that way until the s. Zimmer also comments that the popular use of steep as difficult is a reversal of the technical meaning.
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He identifies the first use of steep learning curve as , and the arduous interpretation as From Wikipedia, the free encyclopedia. Redirected from Time to learn. For other uses, see Learning curve disambiguation. Further information: Learning curve machine learning.
Business Dictionary. Retrieved 8 December Graphical representation of the common sense principle that more one does something the better one gets at it. Learning curve shows the rate of improvement in performing a task as a function of time, or the rate of change in average cost in hours or dollars as a function of cumulative output.
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Smith's remark about the usage of the term "steep learning curve": "First, semantics. A steep learning curve is one where you gain proficiency over a short number of trials.
That means the curve is steep. I think semantically we are really talking about a prolonged or long learning curve. I know it is a subtle distinction, but I can't miss the opportunity to make that point. General experimental psychology. Longmans Psychology Series. October , "Competitive cost dynamics: the experience curve", Interfaces , 12 5 : 50—61, doi : The learning curve.
Archived from the original PDF on Retrieved Encyclopedia of Machine Learning 1st ed. Journal of Intelligent Systems.
Tutorial: Machine Learning for Astronomy with Scikit-learn. Journal of Machine Learning Research. Physics in a Technological World 88 : Bibcode : ptw.. Categories : Learning Cognitive science Curves.