Learning Curve Theory: Types, Formula, Examples 2024

A learning curve is a plot of proxy measures for implied learning (proficiency or progression toward a limit) with experience. The model was widely applied during World War II (WWII) when it was realized that the cost of aircraft decreased with the increase in production performance. It was later taken up by the industrial and business sector for a variety of performance improvement applications.

The rate of progress is thus slow at the beginning but picks up, and the final learning rate shows a noticeable increase. The learning curve helps the employees to become more efficient, and this increases production. Now it is used in planning for materials needed to become necessary because ultimately the inventory turnover and rate of work in progress will also increase. The third stage of the complex learning curve tends to demonstrate that learner knowledge is plateauing. The learning curve theory shouldn’t only be applied during times of change or when training difficulties arise; instead, monitor the learning curve year-round. Continuous monitoring uncovers problems as soon as they appear, allowing you to easily correct and modify your approach as required.

That the price of technology declines when more of that technology is produced is a classic case of learning by doing. Increasing production gives the engineers the chance to learn how to improve the process. This means that with each doubling of the installed cumulative capacity, the price of solar panels declined by 20%. What is exceptional about what is learning curve technologies that follow a learning curve is that this effect persists, and the rate at which the price declines stays roughly constant. The learning curve is used in cost projection and forecasting future costs or the rate at which the assumed costs may fall in the likelihood of commissioning new plants. The two important things required in this endeavor are getting hold of the necessary workforce and materials in a timely fashion.

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 learning curve as a framework can help organizations to understand in this scenario what is required to become proficient in the software. A learning curve is important because it can be used as a planning tool to understand when operational efficiencies may occur. The learning curve identifies how quickly a task can be performed over time as the performer of that task gains proficiency.

Using a learning curve can help a business to improve the performance and productivity of their workforce and reduce costs. The formula stipulates that the more attempts that are included, the more the overall time will decrease. The formula can be used to predict a learner’s rate of learning of a simple task or even help businesses to predict the production rate of a product. This is the basis for the learning 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 Cost of Airplanes“, after realizing that the cost of aircraft production decreased with the increase in production performance.

Complex Learning Curve

At those lower prices, the technology becomes cost-effective in new applications, which in turn means that demand increases. In this positive feedback loop, these technologies power themselves forward to lower and lower prices. As the cumulative installed capacity increased, the price of solar declined exponentially. For more than four decades, the price of solar panels declined by 20% with each doubling of global cumulative capacity. Technologies that follow Wright’s Law get cheaper at a consistent rate, as the cumulative production of that technology increases.

The rate of progression increases rapidly at the beginning and then decreases over time. The experience curve theory states that the effort to complete a task should take less time and effort the more the task is done over time. Note that the cumulative quantity must double between rows—to continue the table, the next row must be calculated using a quantity of eight. In addition, note that the incremental time is a cumulation of more and more units as the table is extended.

First described by Dr Hermann Ebbinghaus in 1885 who, after evaluating his own memory over time, formulated a graph to demonstrate the rate of lost information. He posited that after a mere 20 minutes, just 60% of the information would be retained. The shift to remote work has forced many people to adapt to new tools and methods quickly.

What is the Learning Curve Theory?

1. Perfecting things becomes ever more difficult despite increasing effort despite continuing positive, if ever diminishing, results.
2. The economic learning of productivity and efficiency generally follows the same kinds of experience curves and have interesting secondary effects.
3. This model represents a more complex pattern of learning and reflects more extensive tracking.

Over time, as they become more familiar with the technology, their proficiency improves, leading to increased productivity, innovation, and often a competitive advantage. The complex learning curve model looks different for each activity, individual, or group. When learning tasks with complex learning curves, learners often encounter multiple peaks and plateaus. Wright developed the basis for the modern learning curve formula, which he termed the “Cumulative Average Model” (also known as “Wright’s Model”) in his paper Factors Affecting the Cost of Airplanes.

What are the Benefits of Understanding Learning Curves?

As the chart above showed, the price declined from $106 to $0.38 per watt in these four decades. The application of new ideas will improve his skills until it reaches peak inefficiency. The fourth stage shows him once again enhancing his skills and the last stage where it becomes a routine habit. Now at this stage, it becomes a habit and as the learning becomes automatic and is also known as over-learning. Here the learner is slow at the beginning and slowly increases his knowledge until he reaches full potential. Thus it is also known by the names of productivity curve, efficiency curve, cost curves, and experience curve.

In the example of a 90% learning curve, this means there is a corresponding 10% improvement every time the number of repetitions doubles. The third stage of the Complex Learning Curve shows that the learner feels he has mastered his skill and thus reached a plateau. Sometimes this plateau is false because the learner might be developing new skills and ideas to improve his efficiency and productivity. The concept of the learning curve is meant to show the learnability or the learning ability of a subject. It is presented in graph form so that an individual can relate his relative progress visually throughout the process and the estimated difficulty in learning the subject over a specific time.

Models

At the onset, the curve depends on the nature of the learner and later depicts from zero to mastery. Especially medical technology, in-face AI is now being integrated into MRI machines for more accurate diagnoses and patient care treatment. The more experience colleagues have, the better understanding they have of the processes.

As the worker learns to operate the machine following the procedural steps, he becomes faster and more proficient at using it. The learning curve model requires that one variable is tracked over time, is repeatable and measurable. As a whole, learning to read is a complex procedure involving many variables and is not ideal for a learning curve. There are many variables in learning that impact the rate of progression and cannot be accurately reflected in the learning curve model.