What is the knowledge curve (Dunning-Kruger effect)?
Have you ever heard of the knowledge curve? Also known as the learning curve, these two phenomena are actually linked to a very well-known psychological effect: the Dunning-Kruger effect.
It is, in fact, a well-known cognitive bias in psychology that explains why the least competent people in a field tend to overestimate their abilities, while those who are most experienced underestimate their expertise.
More commonly, this effect is represented by this curve:
As you can see, several stages can be observed:
- A phase of illusory incompetence;
- A phase of despair;
- A phase of growing competence.
In this article, we will explore together all the details about the Dunning-Kruger effect, how it influences the way we learn and perceive our skills, and why it is essential to understand it in order to evolve.
The Origins of the Dunning-Kruger Effect
It was in 1999 that David Dunning and Justin Kruger developed their study on this psychological bias. According to the latter, individuals who have little competence in a field are often unable to recognize their incompetence.
This leads them to overestimate their abilities and results in excessive confidence.
In other words, the least qualified people are often the most confident, while those who are more competent tend to be more critical of themselves. 😗
This phenomenon is often summarized by a quote attributed to the philosopher Charles Darwin: "Ignorance more frequently begets confidence than does knowledge."
The Stages of the Knowledge Curve
Often represented in the form of a curve, as we saw in the introduction of this article, this bias is often marked by three important stages.
The Phase of Illusory Incompetence
To start, the individual possesses overestimated confidence right from the beginning: when they start learning a subject, they quickly acquire some basic knowledge and think they already master the subject. This is called the illusion phase.
Confidence is at its highest level, while actual competence is still very low. Individuals feel they have understood everything when they only master a tiny part of the subject.
Example: Imagine a student who has just started learning programming. After a few trainings, they know how to code simple loops and conditions and feel empowered to develop an entire application.
They still ignore the complexity of algorithms and the necessary optimizations to make their site usable: this is the phase where most people fall. 😉
The Phase of Despair
Next, faced with evidence of their incompetence, the individual moves to another stage: the desillusion phase (also called the loss of confidence phase or despair). By delving deeper into the subject, they realize its full complexity.
It is in this stage that confidence plummets abruptly. It is also in this stage that most people give up, believing they will never succeed.
Example: The programming student begins to discover advanced concepts like data structures, databases, and object-oriented programming. They feel overwhelmed and doubt their abilities to truly master the subject one day.
The Phase of Growth
Finally, they enter the growing competence phase: thanks to their increasing strength, they gradually regain confidence in their abilities.
At this stage, individuals become aware of what they know and what they don't, allowing them to better assess their skills.
Example: After months (or years 🥲) of training, the programming student becomes capable of understanding advanced concepts and applying their knowledge effectively. They are confident but remain aware that there is always more to learn.
Examples of the Dunning-Kruger Effect
In addition to our example of the programming student, let's look at other everyday situations where this psychological bias is very present (perhaps you have even experienced it).
Example 1: When Learning to Drive
Do you remember your first hour of driving? Many people, before even touching the steering wheel, think they already know how to drive!
Obviously, thirty hours of driving later, many have gone through all the phases of the Dunning-Kruger effect: going from excessive confidence, to despair and the desire to quit, believing they will never be able to take the highway until obtaining their driver's license.
Example 2: When Learning a New Language
It's no wonder that apps that allow you to master a language are flourishing and do everything to keep us hooked at the beginning: because the Dunning-Kruger effect is very present.
At the beginning, a well-made app can give the impression that "it's easy".
It's not the case.
It's only after several lessons that the majority of learners give up in the face of the immensity of knowledge to acquire.
Finally, it's after months of sticking with it that they manage to speak a language fluently while being aware of things they don't know.
How to Avoid the Dunning-Kruger Effect?
It's not very easy to avoid this cognitive bias. In fact, the key is to stay humble and to continue to learn actively (without getting distracted).
Generally, our learners manage to combat this effect with these little tips:
- Be aware of your limits: accept that you can't know everything and be willing to listen to those who have more experience than you;
- Take a step back: make sure to always test and validate your knowledge through external feedback (like mentors or experts) before believing you are fully competent;
- Adopt a continuous learning mentality: even the greatest experts never stop learning. There's never a moment when you "will know everything you need to know".
Conclusion
The Dunning-Kruger effect reminds us of the importance of humility in our everyday learning.
This knowledge curve, which shows how our confidence varies with our actual skills, is an excellent illustration of the path we must take when learning something new.
Being aware of this effect, recognizing your own limits, and persevering through moments of doubt is essential to evolve, whether in the professional field or in daily life.
The next time you feel too confident in a domain or too overwhelmed, remember the Dunning-Kruger curve and keep learning! 😬
