LEARNING TO LEARN
“Learning to learn” sounds almost absurd. Yet the competence of learning is becoming increasingly not merely important: fundamental.
Let’s start from the basics.
If training is a series of initiatives aimed at acquiring knowledge, skills and attitudes; if learning consists of sustainable behavioural and cognitive changes; and if learning transfer indicates how much learning derived from training is applied at work or influences performance, then the goal of training is a kind of learning that enables the acquisition of skills in the best possible way so they endure over time and are applied.
Learning to learn means precisely this: knowing how to shape training for oneself or for others that generates this kind of learning.
In this article you will find:
- Why learning to learn
- For whom learning to learn is important
- The false myths of training and learning (rote learning, VARK learning styles, Dale’s cone, Pop neuroscience)
- How to learn to learn
- Trainin methods (tech-driven, corporate, individual)
WHY LEARNING TO LEARN
Learning to learn is a fundamental competence, and we don’t need the European Commission to tell us; just look at what’s happening around us: the changes we are exposed to are so radical that they require continuous training simply to keep up.
And this means one very simple thing: the skills we must acquire to use tools are constantly new, and we must become ever faster at acquiring them.
We need to accelerate our ability to gather information, store it, and then forget it when it becomes irrelevant.
In other words, we must learn to learn.
FOR WHOM LEARNING TO LEARN IS IMPORTANT
Learning to learn is important, fine, but for whom exactly—apart from “everyone”?
In short, for three profiles: managers, HR, C-level executives and entrepreneurs.
It is important for HR, who must develop learning projects that meet the needs of people and the company—that famous learning design we often talk about.
It is important for C-level executives and entrepreneurs, if only for competitiveness. They say “train or fall behind,” and it is truer than ever right now.
It is important to know how to learn for managers, given the continual changes in the world of work and their need to stay up to date.
If it is true that thanks to artificial-intelligence and automation tools managers have had some workload taken off their shoulders (automation frees people from repetitive, automated tasks, and often much more), it is also true that managers themselves both need to train on these tools and have more time to devote to learning those non-replicable skills: emotional intelligence, communication, relationships, creativity.
The expectation is that managers will be able to acquire these skills rapidly, maintain them, and apply them.
Thus, in this context, the whole discussion about knowing how to learn a skill well and quickly becomes not merely fundamental.
It becomes a matter of survival.
THE FALSE MYTHS OF TRAINING AND LEARNING
So far, so good. We talk about learning, we talk about acquiring knowledge, and the most direct connection we probably have with the world of learning is school.
We all studied and learned in middle and high school.
We read, underlined, revised and repeated—then sat the exam.
The question few have asked, however, is “was that really the right way to work and study?”
Unfortunately, the answer is a resounding no.
The world of training is plagued, from the very start—indeed right from school—by the survival of certain false myths: inconsistent, unsuitable, at times harmful methods for the learning process, because they do not activate any of the learning processes whose functioning we are certain of (spacing, interleaving, active recall—see below).
The problem is that these false myths survive out of habit—and if our goal is truly to learn to learn, we must look at what they are, know them and identify them so we can avoid them. Here they are:
- Rote learning
- Learning styles (VARK)
- Dale’s cone / Glasser’s pyramid
- Pop neuroscience
ROTE LEARNING
Rote learning is nothing more than what we all did to prepare for a class test: read, underline, review, reread, repeat aloud—basically what our teachers advised.
And the practical effect?
We all know it: lots of concepts available in the short term but which vanish as soon as the oral exam or test is over.
If this is true, then the question we must necessarily ask ourselves is whether it is actually useful to study this way.
If our goal is to store a series of bits of information that we want on the tip of our tongue for a few days, then yes.
If instead we want to learn a new skill and be able to apply it over time, better avoid it.
LEARNING STYLES (VARK)
Learning styles are like weeds: they NEVER die.
We have all heard of them. The basic idea is that each of us has a better way to learn: some learn better by seeing images, others by reading, some by listening, others by doing.
There is no (recognised) test that can tell you what your learning style is. It is simply up to you to assess how you best store and retain information.
The immediate problem is that no one is capable of self-assessment.
Any self-assessment is a bias. In one study, for example, participants were asked whether they were better than average at driving a car—70 % believed they were better than average; clearly some bias is at work.
Far more serious, however, is that to date there is no scientific evidence for the effectiveness of learning styles, let alone for their existence.
In other words, it has never been proven that, on a large scale, people learn more with their preferred learning style and less with others. There is no reason to support their existence—so why believe in their effectiveness?
True, different, more or less effective ways of learning a skill can exist—you learn to repair a car better by getting your hands under the bonnet than by listening to a podcast.
But this depends on the skill being studied, not on the person and their preferences
DALE’S CONE / GLASSER’S PYRAMID
You know those posters that promise: “You remember 10 % of what you read, 20 % of what you hear, 90 % of what you do”?
Well, those figures come from neither Edgar Dale nor William Glasser.
Dale, in the 1940s, only wanted to show that the more concrete an experience is (for example, carrying out an experiment) the easier it is to understand; the percentages were added later by some training-marketing enthusiast.
Glasser, on the other hand, was talking about therapeutic education: the infamous “pyramid” does not appear in any of his official publications.
Dale’s Cone and Glasser’s Pyramid should be read as reminders—“the more you do, the more you understand”—not as natural laws with built-in decimals.
POP NEUROSCIENCE
Neuroscience is a science I respect tremendously, but it is, relatively speaking, recent—just a couple of decades or so.
Moreover, it is a complex science and at present only the scientists who work on it daily have—or should have—something to say.
The problem is that, like learning styles and leadership, neuroscience is fashionable.
For example, just open YouTube to see the latest self-styled genius talking about dopamine in training.
The rough message is that dopamine is a neurotransmitter that gives us a sense of joy and engagement when we achieve a result—and that when we work in training we must stimulate the release of dopamine in participants, so that they become almost addicted to training and want to train more and more.
No, or at least not necessarily.
It is true that dopamine also has this function, but it is also active in digestion—so what then?
Another example: when we talk about “motivation” in neuroscience, it refers to something quite different from “professional motivation”.
Motivation, in neuroscience, is an almost primordial instinct that pushes us to act for our survival.
And here too we see that the overlap is minimal.
So—maximum respect for neuroscience, but for all these reasons it might be better to leave it to the scientists.
HOW TO LEARN TO LEARN
At this point we know that learning to learn is a necessary and urgent competence and we also know what we must avoid at all costs in order to acquire it.
In this paragraph we will add the final piece: what we need to know to acquire new skills quickly and well, and to make sure they stay with us over time.
HOW MEMORY WORKS
If we want to learn to learn, we first have to understand exactly how competence acquisition works. That means talking about memory.
First, we don’t have just one memory: we have at least three, each with different characteristics and functions:
- sensory memory
- working memory
- long-term memory
Sensory memory has enormous capacity and a very short duration: it is all the information we receive through our senses. Through sensory memory we perceive this information for about half a second. Many of these inputs are discarded; some—the ones we paid attention to—pass into working memory.
Working memory can hold only between 5 and 9 elements and has a limited duration of about 20 seconds. It works rather like a computer’s RAM: it receives some information from sensory memory via attention, which can then be discarded and forgotten or encoded into long-term memory, which is what interests us.
Long-term memory, on the other hand, has potentially infinite capacity and duration.
So if we want to learn to learn, we need to focus on two transitions:
- through attention, move the information we care about from sensory memory to working memory
- through encoding, move the information from working memory to long-term memory
These two steps are the foundation of everything. In the next paragraphs we will explore both.
1 – TRANSITION FROM SENSORY MEMORY TO WORKING MEMORY
Attention is what ensures that the elements we care about reach working memory; it is the protagonist of the first step of learning and of learning to learn.
However, attention is far more complex than it may seem.
Watch this video for example:
This was originally a campaign to raise awareness about cyclists on London’s roads, but what does it tell us for our purposes?
A couple of things.
First, it tells us that our attention is single-focused: if we really want to focus on one thing, we cannot concentrate on anything else. In the video this means that if we follow the story, we lose sight of other important details, and vice versa. In individual study it means that while we are studying we cannot do anything else: phone notifications are a problem, pop-ups, emails, phone calls.
Second, it also tells us that if we develop training courses—if we are HR, EdTech companies, trainers, team leaders or CEOs—we must ensure that people’s attention is always directed where we want it. If it isn’t, learning will not take place.
Obvious?
Perhaps, but less obvious is that there isn’t just one type of attention—there are two: bottom-up and top-down.
BOTTOM-UP ATTENTION
Bottom-up attention is a reaction to an external stimulus. We are generally drawn to things that move, things with colour contrast, things that stand out.
What stood out in the video?
Obviously the detective leading the story and the various movements, and indeed we paid attention to him.
If someone had placed colourful arrows saying “pay attention to the detective’s coat changing colour”, we would have noticed that instead and not followed the story—it is deliberate, of course.
TOP-DOWN ATTENTION
Top-down attention, on the other hand, works differently: it is not a reaction to an external stimulus, but a conscious choice about where to direct it.
Practically speaking, in training, once we have attracted someone’s attention (bottom-up attention), we must be able to maintain it through exercises, discussions, engagement or similar activities.
This way we ensure that this person keeps attention on the course topics, and is not attracted elsewhere.
IN PRACTICE
The first step in training is to ensure that the information we care about moves from sensory memory to working memory.
We know it is possible through well-used attention. In practice, this means ensuring that:
Bottom-up attention is not attracted by other stimuli—and we can achieve this by removing external stimuli and, if possible, integrating movement, sound and contrast into the material we use.
Top-down attention is always stimulated—and we can achieve this by creating engagement, for example by answering questions or using tools such as Cornell Notes or gamification.
Having done this, we can move on to the second step: transferring the information we care about from working memory to long-term memory.
2 – TRANSITION FROM WORKING MEMORY TO LONG-TERM MEMORY
MEMORY AND SCHEMAS
The second aspect we need to work on is the transition from working memory to long-term memory through an encoding process of the elements we care about into what are called schemas.
A schema, in this definition, is a structure that encloses elements, experiences and knowledge related to a specific competence.
The more complex and interconnected the schema, the more competent we can claim to be in a subject.
Take driving, for example: when we start, we have to insert the first elements and connect them (steering wheel, gear lever, pedals…).
The more we go on, the better our familiarity with how all the elements interact—for example, downshifting before a curve—and the more complex and interconnected our schema becomes.
If we then look at a professional driver’s schema, we will see that theirs is even more complex and interconnected, precisely because of the greater number of experiences, elements and knowledge about it.
I’m obviously simplifying, but that’s the essence.
3 PILLARS OF LEARNING: HOW TO CREATE AND CONSOLIDATE MEMORY SCHEMAS
This is perhaps the most important step in learning to learn: knowing how the encoding of the skills we care about within these memory schemas works.
Encoding occurs in three ways:
- spacing
- interleaving
- active recall
Learning to learn means knowing these three elements and knowing how to apply them.
SPACING
Spacing is distributed repetition.
It means exposing ourselves or training participants to the same concept multiple times over time, over a more or less long period instead of concentrating all study in a single session (as happens with “cramming” or rote learning).
INTERLEAVING
Interleaving means working on different concepts at the same time.
For example, learning all four operations together instead of working first on addition, then subtraction and so on.
Interleaving works because it exposes the brain to a mix of different information, forcing it to make new connections.
It makes short-term learning more difficult, but leads to deeper understanding and greater adaptability of knowledge. It makes the learning process harder, but it is also this difficulty that allows the encoding of elements into schemas.
ACTIVE RECALL
Active recall consists of answering questions related to the competence in question.
It may seem similar to simple review, but it is quite different.
Reviewing means repeating aloud; recalling information means answering questions and using the question itself as a source of learning.
Of the three, this element is perhaps the least intuitive. The fact is that the mere act of recalling information is much more effective than simple review: it helps strengthen the neural connections associated with the learned information, making memory more solid and durable.
The interesting thing is that even when we don’t know the answer, or when the answer we give is wrong, active recall still works: the mere attempt to answer a question stimulates the reference schema and consolidates it, even if the answer is wrong.
WHY SPACING, INTERLEAVING AND ACTIVE RECALL WORK
Spacing, interleaving and active recall are what are called “desirable difficulties” in learning: processes that can make the learning process slower than other methods but are directly linked to the creation and consolidation of memory schemas and therefore lead to slower but more enduring learning
TRAINING METHODS
Learning to learn means understanding how memory works through attention and encoding, and knowing how to integrate spacing, interleaving and active recall within our study or training methodology.
We know that the “false myths” don’t work because they don’t activate any of these factors, so we can set them aside in practice.
We also know, however, that there are many codified training methods whose effectiveness is proven precisely because they already have spacing, interleaving and active recall integrated.
For simplicity, I have grouped them into three areas: tech-driven training methods, corporate training methods, individual training methods.
TECH-DRIVEN TRAINING METHODS
Technology is a fundamental piece of training, and thus of learning to learn—if only for its pervasiveness.
However, there is an interesting aspect: the presence or absence of a technological solution in training is totally irrelevant to the effectiveness of the training itself.
It becomes effective if and only if it manages to integrate spacing, interleaving and active recall—at which point it can truly make the difference.
Let’s look at two examples: microlearning / LMS and gamification.
MICROLEARNING + LMS
Microlearning and LMS (Learning Management System) often work in parallel.
Basically, microlearning is conceived as presenting learning nuggets (e.g. short videos) that make study lighter, integrating them within a platform—an LMS. The system itself isn’t wrong, but it can be applied ineffectively or effectively, depending on how well it respects the rules of learning.
INEFFECTIVE APPLICATION
A tech company posts a series of short videos, each 5–10 minutes long, covering various aspects of the product development process (e.g. code optimisation, testing strategies, UX design). All the videos are made available simultaneously on the corporate learning portal. Employees are invited to watch them when they have time, with instructions to complete everything within X days.
The expectation is that employees will self-regulate their study, but without further specifics there’s a risk they will watch all the material in one go. If there are no follow-up activities or structured reviews, employees will likely forget much of the content soon after watching the videos. This setup exploits neither spacing nor active recall and leaves interleaving to the user, making learning passive and completely ineffective in the long term.
EFFECTIVE APPLICATION
The same company reorganises the microlearning programme by releasing a 5–10-minute video each week for a month. After each video, employees receive a short quiz to verify key concepts (active recall) and are invited to review the previous week’s content through spaced review questions. In addition, the videos cover topics from different disciplines: the first week is coding, the second UX, and the third returns to coding from a different perspective, ensuring interleaving of competences.
This version respects the principles of distributed repetition, interleaving and active recall. By distributing content over time and integrating quizzes and reminders, employees are more likely to remember and apply the knowledge acquired, improving long-term learning outcomes.
GAMIFICATION
INEFFECTIVE APPLICATION
A company introduces a gamified learning app in which employees earn points and badges by completing various coding challenges. However, the challenges are all based on a single programming language and must be completed within a day. There is no possibility of distributed practice and the leaderboard drives employees to finish as many challenges as possible in a short time.
This approach focuses on quick wins rather than lasting learning. Because challenges are concentrated in a single day (no spacing) and focus on a single area (no interleaving), employees may feel pressured to complete tasks without truly assimilating the material. Moreover, there are no review mechanisms to strengthen learning (absence of active recall).
EFFECTIVE APPLICATION
The gamified platform offers coding challenges spread over several weeks, with tasks rotating among different programming languages and skills (interleaving). Employees are rewarded not only for completing challenges, but also for accuracy and consistency in recalling past lessons. After completing each challenge, they receive a quiz reviewing the key concepts from previous weeks, reinforcing memory (active recall). Leaderboards are updated weekly to encourage distributed engagement over time rather than cramming.
This approach respects the principles of spacing, interleaving and active recall. Attention shifts from speed to long-term learning, making gamification more effective for real skills development.
CORPORATE TRAINING METHODS
These methods are relevant for anyone involved in offering or organising training.
The trainer must learn to learn, and then integrate the basic concepts into their methods to allow those listening to better understand and store the most relevant concepts.
MENTORING / SHADOWING
INEFFECTIVE APPLICATION
An employee shadows a senior product manager for three consecutive days. The employee observes the manager leading meetings, creating product roadmaps and interacting with stakeholders. However, the shadowing is very passive, and there is no opportunity for the employee to participate actively or reflect on what they have observed.
This passive approach does not encourage active engagement or review. Without distributed repetition or interleaving of different skills, and without active recall activities (such as summaries or practical applications), the shadowing experience becomes less effective for knowledge retention.
EFFECTIVE APPLICATION
The shadowing is spread over several weeks, with the employee observing different aspects of product management on different days—strategic planning one week, stakeholder meetings the next and team coordination the following week (interleaving). After each day of shadowing, the employee is asked to write a reflection on the experience and discuss the main lessons with the manager during a follow-up session (active recall). This structured shadowing allows the employee to progressively deepen their understanding.
This approach uses spacing, interleaving and active recall, making shadowing much more effective. The mentee has time to assimilate information between sessions, while periodic review and practice ensure that knowledge is consolidated.
WORKSHOP
This method is close to my heart because something I am still often asked for is the “training day”.
I understand that there are budget and performance issues, but purely from a training standpoint, an eight-hour training day is of little use, especially if the organisation expects a frontal approach where people listen, receive, and are then left with a huge amount of information but have had no opportunity to implement it in everyday life.
To reconcile everything and ensure that the concepts covered stick, I always propose a preparatory invitation video, followed a week later by a highly practical workshop including questions and practical aspects, followed by materials and a debriefing session a month later—this way I touch all three pillars and guarantee greater retention of the concepts covered.
Let’s see another example.
INEFFECTIVE APPLICATION
A two-day bootcamp on cloud infrastructure is offered to employees, introducing them to AWS services such as S3, Lambda and EC2. The workshop is very intense and tries to cover as much information as possible in two days. Once the bootcamp is over, employees return to their daily activities without any structured follow-up.
Accumulating so much information in two days leaves no room for distributed practice, and without recall or review mechanisms, employees will probably forget much of what they learned by the end of the bootcamp.
EFFECTIVE APPLICATION
The bootcamp is redesigned to include distributed learning. After the two-day workshop, employees receive follow-up emails once a week for the next month, each containing a brief summary of the AWS services learned, accompanied by practical tasks to apply the concepts. Each task requires them to work on a different aspect of AWS (interleaving), and periodic quizzes ensure they remember what they learned during the bootcamp (active recall). Employees are also encouraged to discuss their progress in small working groups.
This version integrates distributed repetition, interleaving and active recall, making the bootcamp more effective for long-term learning. Follow-up activities ensure that employees not only retain the information, but can apply it in real contexts.
INDIVIDUAL TRAINING METHODS
Learning to learn is also an individual task: we ourselves control our learning when we understand how everything works.
Below are some methods that activate spacing, interleaving and active recall which you can use independently or incorporate into your use of workshops or mentoring to make the training process even more effective.
One caveat: these methods are not mutually exclusive; indeed, applying them in parallel can yield even better results.
FLASHCARDS
Flashcards are probably the best way for effective, scientific, long-term learning.
Each flashcard is a piece of card with a question written on one side, and the answer on the other.
We can write them while studying or listening, or develop them in parallel with Cornell Notes, then use them to study or revisit the concepts they refer to.
In their simplicity, flashcards are a powerful tool: we can review them multiple times over time (spacing), we can mix questions concerning different subjects (interleaving), and the mere fact that they consist of a question implies constant active recall.
CORNELL NOTES
Cornell Notes take their name from Cornell University in the United States and are simply a (much) more effective way of taking notes.
You start by dividing the page into three parts: two vertical columns (one-third on the left and two-thirds on the right) and one horizontal row at the bottom.
While listening or studying, you summarise key information and concepts in the right-hand column.
Then you add questions in the left column, questions whose answers are already contained in the right-hand column (these can later form the basis of flashcards).
Third step: summarise everything. In the space at the bottom of the page you write a summary of what you have understood.
Taking notes in this way is harder, certainly, but remember that learning to learn also means placing desirable obstacles in front of oneself—stimuli that help move key concepts into long-term memory and keep them there.
Cornell Notes meet this need excellently.
CONCEPT MAPS AND DIAGRAMS
A concept map is an excellent way to activate active recall because it forces the brain to “fish” from the mental archive not only individual concepts but also the relationships that bind them: while you draw nodes and arrows, you are retrieving information in a deliberate and generative way—the same mechanism that makes flashcards and free-response quizzes effective.
Simplifying, given a topic of study, we can map its structure visually by following three micro-steps:
- Brain dump: without reopening your notes, write the main theme in the centre and around it the first 5–7 concepts that come to mind.
- Connections: draw directional lines between one node and another and add a verb (“generates”, “depends”, “contrasts”) that makes the logical link explicit.
- Levels: for each key concept, insert sub-nodes of detail until you feel you have “downloaded” everything you remembered. Only at this point do you compare the map with the original material to fill any gaps: the interval between retrieval and verification is what strengthens memory.
For example: the concept map of this article would have “Learning to learn” at the centre; from here branches would go to “Memory and attention”, “False myths” (Dale’s cone, VARK styles…), “Spacing-Interleaving-Recall”, “Training methods” (tech-driven, corporate, individual).
Sketching it on the fly immediately after reading triggers active recall; then reviewing it a week later while adding details (e.g. examples of effective microlearning) acts as spacing: together, the two steps move concepts into long-term memory and increase their operational availability when needed at work.
CONCLUSION
In the context of accelerated change that characterises contemporary work, “learning to learn” is not an accessory advantage but an umbrella competence that governs all the others.
Debunking seductive myths—from Dale’s Cone to the Pyramid percentages—is the first step towards an evidence-based approach.
The second is to adopt tools that amplify proven cognitive-behavioural mechanisms: focused attention, distributed practice, interleaving and active recall. Concept maps, algorithmic flashcards and workshops structured in micro-cycles are not “gadgets”, but concrete vehicles of these processes.
For managers, HR and entrepreneurs, the challenge now is twofold: design learning ecosystems that incorporate these principles and, in parallel, create learning-transfer metrics that go beyond immediate satisfaction. Those who succeed will not only maintain their competitiveness, but will build organisations capable of adapting and thriving in increasingly dynamic markets.
