taxonomy What’s a learning curve and why is steep not hard?

A learning curve measures the rate at which a person learns a new skill. A famous example is learning how to drive, where you need to know all sorts of things. About driving, such as steering, stopping and starting, turning corners, etc. 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. 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.

These are often highly complex tasks or require higher degrees of creative or strategic thought. Performance may increase steadily at the beginning before reaching a plateau once learners have mastered the basics. This productivity plateau may lead to additional performance increases as they learn more advanced concepts.

How Can You Flatten The Learning Curve For Effective Employee Training

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. 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. 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.

“On a steep learning curve”

Also here on Stack Overflow I’ve seen it used wrongly many times and hence this Question and my own answer to it. “steep learning curve” is a buzz-phrase that doesn’t have any actual meaning. “Over time, the misapprehension has emerged that a “steep” learning curve means that something requires a great deal of effort to learn…” Microlearning makes sure that topics that learners find difficult are repeated more often.

1. It shows that for every doubling of a company’s output, the cost of the new output is 80% of the prior output.
2. In the example of a 90% learning curve, this means there is a corresponding 10% improvement every time the number of repetitions doubles.
3. In general, there are four types of learning curves that you should look out for as a business.
4. In 1885, Ebbinghaus discovered the phenomenon we now know as the learning curve.
5. This is usually because employees need to become familiar with the interface and features.

Products

Your instructor would probably tell you that it takes many hours of practice before anyone becomes good enough at driving stick-shift cars what is learning curve to pass their driver’s test. 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?). Find centralized, trusted content and collaborate around the technologies you use most.

Learning curves are present all around modern businesses – whether you realise it or not! Here are a few examples of learning curves in digital learning and organisational development spaces. 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.

However, one thing that’s remained constant in all these pursuits is the concept of the learning curve. In 1885, Ebbinghaus discovered the phenomenon we now know as the learning curve. The simplest explanation of Ebbinghaus’s findings is that practice really does make perfect. At the center of the story is German psychologist Hermann Ebbinghaus, who discovered fundamental learning principles like the learning curve, the forgetting curve, the spacing effect, and many others.

1. Simplify your employee training with a Training Management System (TMS).
2. As the employee becomes more proficient at their job, they will be able to manufacture more goods in a smaller amount of time (all else being equal).
3. So, as a business, it’s important to enforce measured learning curves if you want to optimise your learning and development experiences for your employees.
4. A comprehensive understanding of the application of learning curve on managerial economics would provide plenty of benefits on strategic level.
5. Learning curves are a natural part of learning any new skill or knowledge.
6. As learning increases, it decreases the cost per unit of output initially before flattening out, as it becomes harder to increase the efficiencies gained through learning.
7. From the start I knew this wasn’t just about picking up a new hobby; it was about diving into a whole new world of logic, creativity, and problem-solving.

This is usually because employees need to become familiar with the interface and features. With continued use, their proficiency will grow, making it easier to navigate and complete training modules. The term “steep learning curve” is often used to describe situations where the learning process is challenging or complex. In this context, “steep” implies that a significant effort and time frame are needed to make real progress.

Shapes/Types of Learning Curves

Some tasks take a lot of effort initially but are easy to master once the basics have been learned (such as learning to ride a bike). However, the graph above fails to demonstrate how the process is becoming more efficient. Because of the graph’s upward slowing curve, it appears it takes incrementally more time to perform more tasks.

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 theory is a way to explain how we learn new things, and it has been around since the 1950s.

For example, suppose you keep practicing regularly and challenge yourself by taking on complex material or listening carefully for musical subtleties in songs that catch your interest. Daniel Brown is a senior technical editor and writer that has worked in the education and technology sectors for two decades. Their background experience includes curriculum development and course book creation. 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. The data produced by third parties and made available by Our World in Data is subject to the license terms from the original third-party authors.

The S-curve model is used to illustrate activities that combine aspects of both the increasing-returns and diminishing-returns learning curves. These activities require a significant amount of effort early on to understand, followed by a rapid increase in performance as the learner becomes more proficient (similar to what we see in the increasing returns learning curve). However, once the learner has attained a certain level of mastery, they reach a performance plateau (similar to what we see in the diminishing returns learning curve). The slope of the learning curve represents the rate in which learning translates into cost savings for a company. It shows that for every doubling of a company’s output, the cost of the new output is 80% of the prior output. As output increases, it becomes harder and harder to double a company’s previous output, depicted using the slope of the curve, which means cost savings slow over time.

However, due to the nature of the learning curve, the x-axis is doubling and incrementally taking less time per unit. For example, consider the graph below that demonstrates the approximate average time needed to perform a given number of tasks. 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”. A high or steep learning curve indicates that it takes a substantial amount of resources to perform an initial task. However, it also signifies that subsequent performance of the same task will take less time due to the task being relatively easier to learn. A high learning curve indicates to a business that something might require intensive training, but that an employee will quickly become more proficient over time.