Want to see how the learning curve is affecting your learning strategy and application of knowledge? We dig deeper.
Understanding learning curves is essential in both personal development and professional growth.
Whether you’re picking up a new skill, adapting to a new role, or navigating the complexities of a project, learning curves provide insight into the time and effort required to achieve proficiency.
In this blog, we’ll explore what learning curves are, how they impact our progress, and why acknowledging them can lead to more effective strategies for success.
Let’s delve into how understanding this concept can make your journey to mastery more efficient and rewarding.
We’ll learn:
- What a learning curve is
- What a learning curve usually looks like
- How to calculate the learning curve
- Plus, benefits to using the learning curve
Let’s get started.
💡 Pro Tip
An LMS directly impacts the learning curve by streamlining content delivery, personalising learning experiences, and providing real-time feedback. It helps flatten the learning curve by offering structured courses, adaptive learning paths, and on-demand resources, making complex topics easier to grasp.
Learn more about our LMS
What is the learning curve?
The learning curve is a graphical representation of the rate at which someone learns a new skill over time.
It was first created by Dr Hermann Ebbinghaus, who in 1885, tested his own memory and knowledge retention.
He posited that 60% of information would be retained after just 20 minutes.
This concept is vital in various domains, including education, business, and psychology, to gauge the efficiency of learning processes.
Typically, the horizontal axis of the curve denotes time or experience, while the vertical axis represents proficiency or performance.
Initially, the curve often shows a steep incline, reflecting rapid skill acquisition, followed by a plateau where progress slows as the learner reaches a higher level of competence.
Understanding the learning curve can help you to develop more effective teaching strategies and optimise training programmes to ensure continuous improvement and mastery.
A learning curve is often expressed as a percentage indicating the rate of improvement.
Visually, a steeper slope on a learning curve signifies rapid initial learning, leading to significant cost savings.
As learning progresses, the slope becomes less steep, reflecting that further improvements are slower and achieving additional cost savings becomes more challenging.
Understanding the learning curve
Understanding the learning curve in a practical sense involves recognising how quickly skills are acquired and how this impacts performance and efficiency over time.
In real-world applications, such as in the workplace or during personal development, the learning curve helps identify how much time and effort is needed to reach a certain level of proficiency.
Initially, as new tasks or skills are learned, progress is typically swift, leading to noticeable improvements in productivity or quality.
However, as one becomes more skilled, the rate of improvement slows, and further gains require more deliberate practice or innovative approaches.
By grasping this concept, individuals and organisations can better manage expectations, allocate resources effectively, and plan for the gradual nature of mastery.
Phases of a learning curve
A learning curve typically comprises three key phases: the initial learning phase, the plateau, and the mastery phase.
In the initial learning phase, learners experience rapid progress as they acquire basic skills and become familiar with the task at hand.
This is often depicted by a steep upward slope on the curve.
Following this, the plateau phase occurs, where the rate of improvement slows down significantly, indicating that the learner is consolidating their skills and knowledge.
Finally, in the mastery phase, performance levels off as the learner achieves a high level of proficiency, with only marginal gains from further practice.
The phases of the learning curve can also be broken down as follows:
- Unconsciously incompetent: A learner has no idea what they’re doing or how to do it
- Consciously incompetent: A learner is aware where they’re going wrong and what they need to work on
- Consciously competent: A learner has grasped the basics but it’s not natural to them
- Unconsciously competent: A learner has mastered knowledge and can apply it without effort or thought
How to calculate the learning curve
The learning curve formula is used to model how the time required to complete a task decreases as a worker gains experience with that task.
A commonly used form of this formula is:
Y=A×Xb
Where:
Y: Time required to produce the \( X \)-th unit (or the cost, or another metric of interest).
A: Time (or cost) required to produce the first unit.
X: Cumulative number of units produced.
b: The learning rate exponent, calculated as \( \log(r) / \log(2) \).
r: The learning rate, often expressed as a percentage (e.g., 80%, 90%).
If the learning rate is 80% and the time to produce the first unit is 100 hours, then after doubling the production from 1 to 2 units, the time to produce the second unit would be \( 100 \times 0.8 = 80 \) hours.
This formula is particularly useful in manufacturing, project management, and any context where repetitive tasks lead to efficiency gains over time.
But it’s handy to be aware of in the L&D space across all businesses too.
Benefits and disadvantages of using the learning curve
The learning curve model can help you monitor lots of different aspects of company performance. It has pros and cons, so let’s look at them:
Pros of using the learning curve
- Reduced costs through increased efficiency As employees and processes gain experience, tasks are completed more quickly and with greater precision, leading to lower labour costs. With time, teams also learn how to better manage resources and minimise waste, resulting in overall reductions in production expenses.
- Enhanced quality of output Experience leads to a deeper understanding of tasks and workflows, which reduces errors and defects. As techniques are refined over time, the quality of products or services improves, driven by both increased skill and process optimisation.
- Continuous skill growth The learning curve emphasizes ongoing development and learning. As employees improve their skills, they become more valuable to the organisation. This model supports continuous training and ensures staff stay current with evolving tools, methods, and technologies.
- Consistent and measurable performance The learning curve provides a framework for predicting how performance improves over time. This allows learning and development teams to track training effectiveness and forecast how long it will take for employees to reach proficiency or for new processes to be fully integrated.
- Reduced risk through experience With accumulated experience, organisations become better at identifying and managing potential risks. Lessons learned from past initiatives inform future decisions, enabling more effective risk mitigation strategies when launching new projects or implementing unfamiliar processes.
Cons of using the learning curve
- Initial inefficiency and higher costs At the beginning of the learning curve, productivity is often low, and error rates are higher. This can lead to increased costs and slower output as employees or teams get up to speed, which may impact deadlines and profitability in the short term.
- Dependence on time and repetition The benefits of the learning curve rely heavily on time and repeated practice. In fast-paced environments where immediate results are expected, there may not be enough time to realize significant improvements, limiting its practical value.
- Resistance to change As teams become comfortable with learned processes, they may develop resistance to adopting new tools, methods, or innovations. This can hinder organizational agility and slow down the adoption of more efficient or modern solutions
- Uneven progress across individuals or teams Not everyone learns at the same pace. Some employees may quickly become proficient, while others may struggle, leading to inconsistent performance and uneven quality. This variability can be difficult to manage, especially in large or diverse teams.
- Overreliance on past experience Relying too heavily on the learning curve can cause organizations to favour existing methods over experimentation or innovation. This may result in missed opportunities to improve or to pivot in response to changing market demands or technological advances.
Wrapping up
Usually, people get better at doing something the more they do it.
Time and resources spent on doing something once is going to be higher than the time and resources spent repeating that activity.
This idea of continual improvement through repeated learning should underpin your learning strategy.
While you might convey an idea once within your learning content, you actually need to reference important information multiple times, offer refreshers, and test frequently.
That way, you can be sure that your learners are getting, and staying, in the loop with particular job-related tasks.
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FAQs
What do you mean by a learning curve?
A learning curve is a graphical representation of the rate at which someone learns a new skill over time. It was first created by Dr Hermann Ebbinghaus, who in 1885, tested his own memory and knowledge retention.
What does it mean when someone says steep learning curve?
A steep learning curve is an expression that is used colloquially to describe the initial difficulty of learning something. It applies back to the learning curve principle, where it is overfacing to begin with.
What does the learning curve tell you?
The learning curve is the correlation between a learner’s performance on a task or activity and the number of attempts or time required to complete the activity.