What Is Learning Curve Theory? (2024)

In his book Outliers, author Malcolm Gladwell succinctly distills decades of research on the topic of expertise, writing that “the closer psychologists look at the careers of the gifted, the smaller the role innate talent seems to play and the bigger the role preparation seems to play.”

The book, which popularized the ‘ten-thousand-hour rule,’ focused on understanding how ‘outliers’—Grandmasters in chess, titans of industry, or musical savants, to name a few—developed skills or expertise well beyond that of the average person. But the core takeaway is equally relevant whether our goal is to become an expert or simply to become a little bit better than we were yesterday: Mastering complex tasks requires more than aptitude alone; it requires lots and lots of practice.

This concept laid out by Gladwell fits into a learning theory known as Learning Curve Theory. The idea at the heart of this theory—that each time we repeat a task, we learn more and become slightly better at performing it—can help L&D professionals design more effective and efficient learning programs.

Learning Curve Theory is based on the concept that the more an individual repeats a process or activity, the more adept they become at that activity. This translates to lower input costs and higher overall output. Learning Curve Theory is used to track, model, and predict learners’ performance and improvement over time.

But, the relationship between the amount of time an individual spends learning and practicing an activity and their overall performance is not linear. There will be specific periods for each activity where a small amount of practice will yield massive improvement in output and others where even minor improvements will require many hours of hard work.

This variance in the relationship between practice and proficiency over time is called the ‘learning curve.’

Understanding the learning curve associated with a given activity gives L&D professionals a valuable framework for modeling output over time and designing training resources that achieve productivity goals. Not only do learning curves help identify where time and resources will have the most significant impact on output, but they also make it possible to make predictions about the likelihood, the timeframe, and—importantly—the cost required to meet potential output goals.

Not all learning curves are the same, of course. 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). For other tasks, learning the basics may be straightforward, but true mastery requires much more practice and effort (such as learning to play the guitar).

Four primary learning curves are used to describe the relationship between input (time invested in practicing) and output (productivity, efficiency, and performance).

Activities that follow a diminishing returns learning curve are the most straightforward when measuring and predicting how the performance and output of a workforce will change over time.

An L&D manager may use this curve when developing a training plan to teach their Quality Control team how to use a new reporting tool where the employee only needs to enter the ID number of was tested and the results of each test. Since this is a fairly straightforward activity with few steps, employee productivity with the tool can be expected to rise sharply at the beginning before leveling off as employees become proficient and approach the limits of how fast they can correctly type the numbers into the program.

These tasks are often made up of multiple complex actions or require learning many unfamiliar concepts. When the learner is first introduced to the task, they may need to learn each step and each concept before they are able to complete the task successfully. Once this initial learning period has been completed, performance will increase steadily as the learner becomes more comfortable with the task. At that point, the learner’s performance will level off, after which point they will likely see only slight increases over time.

An L&D manager might encounter this type of curve when a new productivity tool is introduced to employees in their office, for example. The first time employees see the tool, they will likely have no idea how to use it, and overall performance output with the tool will be near zero. The L&D manager may need to help the learners understand the essential functions of the tool, what each button and menu item is used for, or how to find help when they get stuck.

Once the employees have learned the basics of the platform, however, productivity with the tool will begin to increase rapidly over time before starting to level out once the majority of employees have become proficient with the tool.

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.

L&D managers should expect to encounter complex learning curves when a tech organization adopts a new programming language, for example. There may be an initial spike in programmers’ performance with the new programming language as the software developers get acquainted with the language, using previous programming knowledge to help them master the basics of the language.

Once they have learned enough to be proficient with the syntax and formatting of the new language, employees may reach a temporary plateau as they confront the unique aspects of the new language and begin familiarizing themselves with the language’s libraries and data structures.

As employees continue using the programming language, there will be periodic peaks and plateaus, which may be unique to each individual.

One of the most important tasks for any L&D professionals is to determine when and where to deploy resources to achieve the greatest possible effect. L&D managers can use Learning Curve Theory to track productivity and determine where employees need the most support and where L&D resources will have the biggest impact.

When used in conjunction with a Collaborative Learning platform like 360Learning, these benefits can be even greater. Not only are L&D managers able to identify common plateaus that hold back employee growth, but they also have a readily-available pool of experts who have already overcome these plateaus and understand exactly what new learners need to overcome each obstacle.