A learning curve describes the degree of success achieved during learning over time. It is a diagram in which the horizontal axis represents the time elapsed and the vertical axis the number of successes achieved in that time.[1].
Many mistakes are often made when starting a new task. In the later phases, errors decrease, but so do new subjects learned, until reaching a plain.
It is also possible that the outcome of the learning process is random, such that the learner only thinks he learns or forgets something (nondeterministic experiment).
In economics, the learning curve represents increases in productivity (understood as the relationship between the amount of input per unit of output) as a consequence of a better way of doing things, that is, the “know-how” of workers and managers in the exploitation of a technology. Know-how takes shape in processes, skills and abilities. Broadly speaking, learning is done through experience and applied research. Experience is a learning vehicle that improves skills through the continued repetition of tasks and techniques performed by individuals or groups over time. Research and development increases "know-how" through discovering new techniques, procedures or products, taking advantage of the base of scientific and technical knowledge accumulated in one or more branches of knowledge. The learning curve has been applied to a wide range of problems ranging from the study of the performance of a machine (Zangwill & Kantor, 1998)[2] to growth in the productivity of a production plant (Adler and Clark, 1991;[3] Sáenz and Salas, 2013[4]).
Definition and Calculation Method
The learning curve in economics has been quantified based on empirical evidence in a wide variety of industries and products. Initially the phenomenon is associated with the reduction in the number of direct labor hours needed to manufacture a product, as the number of products manufactured increases. Subsequently, it is verified that the improvement in productivity achieved with the repetition of tasks and the accumulation of units produced can be extended to all tasks and processes, direct and indirect, that intervene in production.
The steeper the curve, the greater the learning efficiency. The slope of the curve depends on several counterbalancing factors:
Learning Curve Analysis
Introduction
A learning curve describes the degree of success achieved during learning over time. It is a diagram in which the horizontal axis represents the time elapsed and the vertical axis the number of successes achieved in that time.[1].
Many mistakes are often made when starting a new task. In the later phases, errors decrease, but so do new subjects learned, until reaching a plain.
It is also possible that the outcome of the learning process is random, such that the learner only thinks he learns or forgets something (nondeterministic experiment).
In economics, the learning curve represents increases in productivity (understood as the relationship between the amount of input per unit of output) as a consequence of a better way of doing things, that is, the “know-how” of workers and managers in the exploitation of a technology. Know-how takes shape in processes, skills and abilities. Broadly speaking, learning is done through experience and applied research. Experience is a learning vehicle that improves skills through the continued repetition of tasks and techniques performed by individuals or groups over time. Research and development increases "know-how" through discovering new techniques, procedures or products, taking advantage of the base of scientific and technical knowledge accumulated in one or more branches of knowledge. The learning curve has been applied to a wide range of problems ranging from the study of the performance of a machine (Zangwill & Kantor, 1998)[2] to growth in the productivity of a production plant (Adler and Clark, 1991;[3] Sáenz and Salas, 2013[4]).
Definition and Calculation Method
The learning curve in economics has been quantified based on empirical evidence in a wide variety of industries and products. Initially the phenomenon is associated with the reduction in the number of direct labor hours needed to manufacture a product, as the number of products manufactured increases. Subsequently, it is verified that the improvement in productivity achieved with the repetition of tasks and the accumulation of units produced can be extended to all tasks and processes, direct and indirect, that intervene in production.
Several psychological factors influence the learning curve:
The learning curve is often used simply to describe the difficulty of a learning task, for example when saying:.
This means that at the beginning great progress is made, but after a while acquiring new knowledge is more difficult.
This means that the unknown producer will have different ways of accomplishing the same task.
In addition, you can see in a learning curve the time in which there are still ignored topics.
The learning curve is a logarithmic curve and, although there are several calculation formulas, the most common responds to the following form:
where.
This is a decreasing function and does not resemble the increasing function shown in the learning curve graph, in which the variable Y is "learning capacity",[5] or what is the same, the value of each point on the curve is equal to the number of the execution raised to the exponent that results from the division of the decimal logarithm of the slope of the curve expressed as x 1 by the decimal logarithm of 2.
If a job is subject to a 90% curve and the first execution takes 140 hours, how long would execution 30 take?
History
Historically, the concept of learning curve comes from Hermann Ebbinghaus, who in 1885 used the term for the first time in his monograph "Über das Gedächtnis" ("On Memory").
In psychology it is also used without a strict definition of the x and y coordinates in such a way that the issue of the steepness of the curve is appreciated in the special case considered. The first definition for use in business management was made by Theodore Paul Wright" in 1936.
Alternative definitions
Contenido
Junto a la definición académica existe en el lenguaje coloquial un uso diametralmente diferente del término. Especialmente en el mercadeo de software y en la rama de herramientas se dice que una curva de aprendizaje es empinada cuando el aprendizaje del uso de una nueva herramienta o programa es difícil y largo. Visto así, una curva de aprendizaje plana significa un aprendizaje fácil y eficiente. En tal diagrama estarían representados en el eje horizontal la acumulación de lo aprendido y en el eje vertical la acumulación del tiempo gastado. La pendiente de la curva es en ese caso la razón de tiempo a avance (tiempo/avance) y es como lo define Wright.
La diferencia entre ambas consiste en que la definición académica representa al aprendizaje como el éxito obtenido y la definición coloquial lo representa por el esfuerzo invertido.
Reviews
Some authors claim that in most organizations it is impossible to quantify the effects. They claim that experience effects are so closely intertwined with economies of scale that it is impossible to separate them.[6] In theory, we can say that economies of scale are those efficiencies that arise from a larger scale of production, and that experience effects are those efficiencies that arise from learning and experience gained from repeated activities, but in practice the two mirror each other: the growth of experience coincides with the increase in production. Economies of scale should be considered one of the reasons why experience effects exist. Likewise, experience effects are one of the reasons why economies of scale exist. This makes it difficult to assign a numerical value to any of them.
[2] ↑ Zangwill, W. I., & Kantor, P. B. (1998). Toward a theory of continuous improvement and the learning curve. Management Science, 44(7), 910-920.
[3] ↑ Adler, P. S., & Clark, K. B. (1991). Behind the learning curve: A sketch of the learning process. Management Science, 37(3), 267-281.
[4] ↑ Sáenz-Royo, C., & Salas-Fumás, V. (2013). Learning to learn and productivity growth: Evidence from a new car-assembly plant. Omega, 41(2), 336-344.
The steeper the curve, the greater the learning efficiency. The slope of the curve depends on several counterbalancing factors:
Several psychological factors influence the learning curve:
The learning curve is often used simply to describe the difficulty of a learning task, for example when saying:.
This means that at the beginning great progress is made, but after a while acquiring new knowledge is more difficult.
This means that the unknown producer will have different ways of accomplishing the same task.
In addition, you can see in a learning curve the time in which there are still ignored topics.
The learning curve is a logarithmic curve and, although there are several calculation formulas, the most common responds to the following form:
where.
This is a decreasing function and does not resemble the increasing function shown in the learning curve graph, in which the variable Y is "learning capacity",[5] or what is the same, the value of each point on the curve is equal to the number of the execution raised to the exponent that results from the division of the decimal logarithm of the slope of the curve expressed as x 1 by the decimal logarithm of 2.
If a job is subject to a 90% curve and the first execution takes 140 hours, how long would execution 30 take?
History
Historically, the concept of learning curve comes from Hermann Ebbinghaus, who in 1885 used the term for the first time in his monograph "Über das Gedächtnis" ("On Memory").
In psychology it is also used without a strict definition of the x and y coordinates in such a way that the issue of the steepness of the curve is appreciated in the special case considered. The first definition for use in business management was made by Theodore Paul Wright" in 1936.
Alternative definitions
Contenido
Junto a la definición académica existe en el lenguaje coloquial un uso diametralmente diferente del término. Especialmente en el mercadeo de software y en la rama de herramientas se dice que una curva de aprendizaje es empinada cuando el aprendizaje del uso de una nueva herramienta o programa es difícil y largo. Visto así, una curva de aprendizaje plana significa un aprendizaje fácil y eficiente. En tal diagrama estarían representados en el eje horizontal la acumulación de lo aprendido y en el eje vertical la acumulación del tiempo gastado. La pendiente de la curva es en ese caso la razón de tiempo a avance (tiempo/avance) y es como lo define Wright.
La diferencia entre ambas consiste en que la definición académica representa al aprendizaje como el éxito obtenido y la definición coloquial lo representa por el esfuerzo invertido.
Reviews
Some authors claim that in most organizations it is impossible to quantify the effects. They claim that experience effects are so closely intertwined with economies of scale that it is impossible to separate them.[6] In theory, we can say that economies of scale are those efficiencies that arise from a larger scale of production, and that experience effects are those efficiencies that arise from learning and experience gained from repeated activities, but in practice the two mirror each other: the growth of experience coincides with the increase in production. Economies of scale should be considered one of the reasons why experience effects exist. Likewise, experience effects are one of the reasons why economies of scale exist. This makes it difficult to assign a numerical value to any of them.
[2] ↑ Zangwill, W. I., & Kantor, P. B. (1998). Toward a theory of continuous improvement and the learning curve. Management Science, 44(7), 910-920.
[3] ↑ Adler, P. S., & Clark, K. B. (1991). Behind the learning curve: A sketch of the learning process. Management Science, 37(3), 267-281.
[4] ↑ Sáenz-Royo, C., & Salas-Fumás, V. (2013). Learning to learn and productivity growth: Evidence from a new car-assembly plant. Omega, 41(2), 336-344.