A learning curve may be a correlation between a learner's performance on a task and therefore the number of attempts or time required to finish the task; this will be represented as an immediate proportion on a graph.
The learning curve theory proposes that a learner’s efficiency during a task improves over time the more the learner performs the task.
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How to Apply the Terms "Learning Curve"
Two applications of the term “learning curve” are often found:
General
The “learning curve” is usually utilized in colloquial speech to explain the time and energy required when learning something challenging.
The application are often broad and generalized, like describing the training curve involved in learning to read. In these scenarios, a graphical representation using mathematics isn't being applied to elucidate learning progression. The term is therefore used as a qualitative description of learning progression over time.
Measured
The other application of “learning curve” is quantitative, where mathematical models are created to represent the speed of proficiency or mastery of a task.
This learning curve model is merely applicable when wont to measure the important rate of progress for completing a selected task against the clock . The task must be repeatable, measurable, and contains just one variable within a procedure; it cannot measure a whole procedure on its own.
Where to Use the Learning Curve
There are many variables in learning that impact the speed of progression and can't be accurately reflected within the learning curve model.
In the example of learning to read, the variables could include phonetics, vocabulary, sort of reading , teaching methods, motivation, previous knowledge or experience, quality of practice, and far more.
The learning curve model requires that one variable is tracked over time, is repeatable and measurable. Individual motivation, for instance , would be difficult to live . As an entire , learning to read may be a complex procedure involving many variables and isn't ideal for a learning curve.
An example of where a learning curve are often applied might be a measurable task sort of a mill-hand learning to work a replacement machine that needs specific, repeatable steps. because the worker learns to work the machine following the procedural steps, he becomes faster and better at using it. A learning curve would measure this rate of progression and mastery.
The learning curve model is employed most ordinarily in organizational or industrial engineering to enhance output by way of improving the performance of the human workforce.
The model was widely applied during war II (WWII) when it had been realized that the value of aircraft decreased with the rise in production performance. it had been later haunted by the economic and business for a spread of performance improvement applications.
The learning curve is understood by different names partly thanks to its big variety of application.
Terms wont to describe the training curve include:
experience curve,
cost curves,
efficiency curves,
productivity curves.
The model are often wont to determine how long it takes for one person to master a skill or how long it takes a gaggle of individuals to manufacture a product. In most applications, the “learning” within the curve is really mentioned as process improvement.
Let’s take a glance at some different samples of where the training curve is being applied today.
Industry
Manufacturing costs as associated with workforce performance are often tracked by using the training curve. rather than performance and number of attempts, the values might be cost or unit labor hours and cumulative production in units. As workers produce more product, the per-unit cost will often decrease.
The learning curve are often wont to predict potential costs when production tasks change. for instance , when the pricing of a replacement product is being determined, labor costs are factored in.
If a product takes two hours to supply , the merchandise is released to the marketplace for sale at a price that reflects the two-hour production period plus other associated costs and markups.
But what if the assembly time was supported the primary few attempts? What if by the 100th time the merchandise was produced, production time is reduced to at least one hour? the merchandise would get on the market at a price that's much too high, leading to potentially lower sales. Using the training curve can provide additional insight for planning purposes.
Business
Learning curves also can be applied to organizational performance using either the generalized approach or by conducting a measured analysis. Determining which approach to require depends on whether the specified performance are often directly measured.
For example, employees learning a difficult task, like learning to use a posh software program, may have poor performance at the start thanks to the inherent difficulty of the task. If the goal is that employees got to skills to use the software in their day to day tasks, this might be difficult to live because it involves many variables. By applying the training curve theory as a framework, organizations can still benefit.
The learning curve as a framework can help organizations to know during this scenario what's required to become proficient within the software. If training support and time to practice are identified as important factors, then it are often seen that employees who are given support and time to practice with the software will over time have better performance than employees who aren't given support or time to practice.
If the software is vital for productivity, then employee performance could decrease over time if employees cannot effectively use the software. Organizations can then provide additional support or resources needed.
To utilize a measured learning curve, organizations would wish to spot a selected variable to research . for instance , a corporation seeking to enhance the performance of customer service could decide that the implementation of a replacement initiative (# of attempts) would end in a decrease in customer complaints (performance). The organization could track and analyze the repetitive practice of this initiative over time to work out if indeed customer complaints decreased over time.
How to Apply the Terms "Learning Curve" Theory?
The learning curve theory states that the trouble to finish a task should take less time and energy the more the task is completed over time.
If one were to plot the repeated attempts of a learner against the time taken to finish the attempt, a pattern are often identified indicating that the task takes less time because the learner gains more experience via repeated attempts. the idea also can be expressed as a function which will be used as a prediction tool.
This is the idea for the training curve formula, the “Cumulative Average Model” (or “Wright’s Model”), which was described by T.P. Wright in 1936 in his work "Factors Affecting the value of Airplanes", after realizing that the value of aircraft production decreased with the rise in production performance. There are currently different variations of the first formula used today in specialized applications, but the thought remains familiar to the first formula:
Learning Curve Formula
The original model uses the formula: Y = aXbWhere:
Y is that the average time over the measured duration
a represents the time to finish the task the primary time
X represents the entire amount of attempts completed
b represents the slope of the function
The formula are often used as a prediction tool to forecast future performance.
The formula stipulates that the more attempts that are included, the more the general time will decrease. The formula are often wont to predict a learner’s rate of learning of an easy task or maybe help businesses to predict the assembly rate of a product.
Example and Learning Curve Model
Although the idea states that more attempts = a decrease in time, it doesn't always compute that way. Many factors can impact the end-results, leading to a spread of various learning curve shapes.
Here are four common sorts of a learning curve and what they mean:
1. Diminishing-Returns Learning Curve
The rate of progression increases rapidly at the start then decreases over time.
This describes a situation where the task could also be easy to find out and progression of learning is initially fast and rapid.
Progression levels off because the learner obtain full proficiency. this might be described as a plateau, where the individual is not any longer progressing. It could signal that the learner has reached a limit in their ability or that a transition could also be occurring. It could also mean that the individual has lost motivation or is fatigued.
2. Progressive(Increasing)-Returns Learning Curve
Progression levels off because the learner obtain full proficiency. this might be described as a plateau, where the individual is not any longer progressing. It could signal that the learner has reached a limit in their ability or that a transition could also be occurring. It could also mean that the individual has lost motivation or is fatigued.
3. Increasing-Decreasing Return Learning Curve (the S-curve)
This model is that the most ordinarily cited learning curve and is understood because the “S-curve” model.
It measures a private who is new a task. rock bottom of the curve indicates slow learning because the learner works to master the talents required and takes longer to try to to so.
The latter half the curve indicates that the learner now takes less time to finish the task as they need become proficient within the skills required. Often the top of the curve begins to level , indicating a plateau or new challenges.
4. Complex Learning Curve
This model represents a more complex pattern of learning and reflects more extensive tracking.
The beginning of the curve indicates that learning is initially slow.
The second stage of the curve shows a rise , which indicates that the learner is becoming proficient within the skill.
The third stage of the curve indicates that the learner is plateauing in his proficiency once the learner feels he has mastered the skill.
The fourth stage of the curve represents that the learner is really still improving the skill.
The last stage of the curve represents the purpose at which the skill becomes automatic, motor memory for the learner, often termed “over learning”.
Pros and cons of the learning curve theory
Pro of the learning curve theory
Using a learning curve can help a business to enhance the performance and productivity of their workforce and reduce costs.
When wont to track or predict performance, it can provide psychological motivation and strategic planning:
(OK) Performance improvement cannot happen on its own and is connected with learning. By incorporating a learning culture within the organization where employees are encouraged and supported to stay learning, performance levels are often expected to extend on the curve.(OK)The rate of learning is additionally considered to be consistent enough that trends are often established using the training curve, enabling better forecasting and business decisions.Cons of the learning curve theory
As a con, a learning curve is extremely hooked in to assumptions made about performance. As mentioned earlier, many variables can impact learning and future performance:
(X) Using a learning curve to predict overall performance of larger groups or processes means many assumptions are made on variables like motivation, sociological factors, workplace dynamics, training resources, and former knowledge or experience.(X) A learning curve which will not show expected results would wish further analysis to work out the underlying variables impacting its shape, because the curve doesn't tell the entire story.I hope this article will helpful for you.
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