Learning to Learn — Why and How It’s Possible to Become More Efficient at Learning Everything
Live as if you were to die tomorrow. Learn as if you were to live forever (Mahatma Gandhi)
The is no better way to start talking about learning than this quote by Gandhi.
The act of learning should be a constant and endless process, it makes us grow, discover new horizons, becoming more complete as human beings.
But I realized, through the years, facing new learning challenges for fun and working necessities, that be able to learn in a better way is something that can be improved and this is possible only when there is complete awareness of the pursued process and the used tools.
We can be great learners, taming the most difficult concepts but, having this mindset, I’m sure we’d love to know how and why we’re able to learn.
After all, athletes follow a training course, adapting to their achievements and conditions. It’s possible to do the same about the learning process.
But let’s start by setting a baseline, made a recap to assess how much the concept of learning is present in our lives.
The learning path in our lives
With a little simplification we can distinguish three major learning phases in our lives:
- Pre-scholar: allow us to develop primary abilities and skills — walking, talking and so on. It’s a complete DIY (Do It Yourself) approach. One interesting thing to notice is being failure-free: everyone, with his/her own time, achieves them
- Scholar: learning becomes organized, with less or more prolonged and variegated cycle studies, allowing us first to achieve a set of generic skills (reading, writing, math, etc.), acting as a foundation to acquire new specific ones. We learn almost through standard and specific didactic methodologies. In the meantime, we learn other things with a DIY approach or extending didactic (private lessons, etc.)
- Post-scholar: this is the less standard phase: we can start using actively the acquired skills or learning some specialized new ones, maybe with a “by doing approach”, very common in a working environment or, maybe, continue on a more organized learning path (doing research, etc.) or mixing approaches.
And, concurrently, in all these phases, we learn new stuff, constantly, by direct experience, casually or by intent.
But when we learn to learn? The simpler answer is “by doing it”, meaning without a specific awareness but developing probably a pragmatic approach due to experience. It’s cool and it works, but it seems too much outside our control.
In other, more “rigorous” words, our pedagogical life is heavily oriented and exposed to didactic, the science of teaching, but less or none to the mathetic, the science of learning, both necessary for a successful education.
This article will try to enlighten a bit this part, based on both bottom-up parts— my experience — and top-down theory and practical approaches, to gain awareness about this process that we're performing every day.
My learning experience
To start, I can share my learning experience and doing some considerations about it. In the last years, besides working skills, I’ve approached several disciplines and topics, divided into four “clusters”:
- kinetic/physical oriented: running, skiing, mountain bike, Krav Maga, Calisthenics
- creativity oriented: photography, piano, violin, music composition, orchestration, writing
- “inner work”: Yoga, personal development, meditation, learning improvement
- technical/practical oriented: machine learning, flight simulation, market analysis, barbecuing
But, clearly, it’s a simplification and there is a lot in common between all of them, like the presence of theory and practice working together.
Different learning needs and goals
An important aspect is each of them was triggered by different needs, with different goals, something making a huge difference between failure and success.
Every learning path on a specific subject, that can embrace dozens of skills, needing countless hours of practice, should have a goal and specific, realistic set of objectives, based on the available learning constraints (time, resources, etc.)
For example, I started skiing to be able to follow my son on the ski slopes (the goal) in the shortest amount of time (the objective).
Having only a few days per year of practice (learning constraint), my approach had to be very pragmatic. I took lessons for the basics, made a lot of practice by myself in the kinder zone, took other lessons to gain more confidence on real slopes and, after countless falls, I was able to do it.
I’m a terrible skier but I reached my learning goal.
Moreover, sometimes you can “sample” a subject with simpler goals and then go deeper, setting more challenging ones.
For instance, I can cook a spectacular t-bone steak without knowing anything about the Maillard reaction (a chemical reaction happening during cooking) and this is perfectly fine when my objective is to serve a great dish.
Topics seeming very distant such as barbequing and playing an instrument can share a similar approach that can be improved over time, consciously, even because every discipline is composed of just two different skill types: hard and soft.
Different skills type
Daniel Coyle, the author of “The Little Book of Talent”, explain what they look like and how to deal with them:
- Hard skill means repeatable precision — playing a note on an instrument for instance. Consistency is the key: there is just one correct and optimal way to perform and this is what we should achieve.
- Soft skills, instead, may have different outcomes, so recognize a situation and reacting accordingly is what to learn and practice. An example is improvising while playing that instrument.
They are off course highly dependent, generally the hard ones being the foundation for the soft ones.
We will see practical approaches more in detail later but, first, look at some learning theories.
Modern learning theories
Going top-down, let’s do a panoramic about what was theorized, gaining some more knowledge about modern learning theories.
It’s not exhaustive and very brief, so don’t worry!
Behaviorism (1900+)
In this theory, learning is a change of behavior, due to a specific response to a stimulus.
Generally, the environment is an input processed by the brain in a passive and deterministic way.
The most notable theorists are:
- Pavlov, with his famous dog’s experiment
- Skinner, introducing positive and negative reinforcements to program learning
- Bandura, who added the concept of social behavior imitation
Cognitivism (1960+)
Unlike behaviorism, for this theory, a human being is taking an active role, through internal elaboration, building a model.
The act of learning is changing the model structure.
Notable theorists are:
- Ausubel, distinguish between mechanic and significant learning
- Gagné, theorizing a learning topology with a hierarchical model, where learning new things is a composition of something learned on lower levels
- Merril, introducing learning principles (problem, activation, demonstration, application, integration) to describe the process of learning
Constructivism (1950+)
In Constructivism, learning becomes building a personal experience, based on previous subjective experiences.
So the process and the model are personal and different for everyone.
It’s really interesting how things changed and became more subjective and complex.
Main theorists are:
- Dewey, who rejected classic methods and proposed a “directed living” approach
- Piaget, theorizing a dynamic learning process, passing through different stages of adaption to reality (assimilation, accommodation, equilibration)
- Bruner, who emphasized the role of the teacher and the Socratic tradition of learning through dialogue and discoveries
- Vygotsky, who developer social constructivism, where the social context is not separable from the learning process
But, theories apart, a huge changing factor happened in the last decades that affected everything: entering the Information Era!
The modern technology factor and recent theories
The rise of information technology had a major impact on learning theories.
In 1967 Papert created the LOGO language, with the specific objective to use computers as support to education.
In 2005, George Siemens introduced the concept of Connectivism, considering learning as a network of interconnected specialized nodes and information sources (even “not human”).
In fact, in the Internet era, the immense amount of available learning resources is an awesome opportunity to access all kinds of information but the negative sides are “information overload” or “paralysis analysis”, simply because there is too much to choose from.
Now, more than ever, having tons of inputs mixed with noise, is paramount to develop a learning awareness, learning how to (effectively) learn.
To do so, the most important step is going to “meta”!
Metacognition
Until now we saw the “know” and the “apply” element, the results of learning something.
With metacognition — literally “above cognition” — we became aware of our thinking process and, by doing so, we can monitor, change and improve it.
This means we can adopt a structured approach, adapting it to the subject and learning goals and, in the meantime, learning how to be more effective.
It’s a huge win-win situation, where learning something increases the learning skill itself, allowing us to learn even better every time.
Motivation, emotions, learning habits, mindset come into play too, becoming a success — or impediment — factors.
Let’s try to analyze how we learn and break it down into simpler components.
I like to think about three different axes.
1 — Model
Is there a model describing learning styles?
Of course, there are many of them: one of the most interesting is the Kolb’s Model, where experience is a major key player
“Learning is the process whereby knowledge is created through the transformation of experience”
Kolb theorizes a cycle connecting experience, reflection, conceptualization and testing.
It’s possible to enter the learning process starting from any phase and four different learning styles are possible:
- Accommodating: relies on others analysis with a more “gut” feeling approach
- Diverging: sees things with multiple points of view, very effective in brainstorming and working in groups
- Converging: attracted to technical tasks, with a likeness to experiment
- Assimilating: interested more in concepts than practice and people
It’s interesting how different approaches are feasible to gain knowledge instead of just a “one-for-all” method.
2 — Tools and techniques
The second major point is using tools and techniques to improve the learning process. It’s a huge part and should need a dedicated article only about it but let’s see some examples.
To be successful in acquiring and retaining concepts, a mix of tools and techniques should be used, according to subject, goals and constraints.
If there is a need to memorize a lot of concepts, using spacing effect — repeating concepts over time, augmenting the interval length with a spaced approach — can be very effective, especially for long term retention, maybe in conjunction with flashcards.
When practice is needed, the available time is few and is important to avoid doing execution mistakes, hiring a coach could be the best solution instead of figuring it out.
Sometimes, there is no need to learn everything from the ground but just use a just-in-time approach, meaning learning a concept only when is needed.
Other times this is not possible, because a more or less explicit concept hierarchy is present and so an ordered approach is necessary: taking a course could be the best option in this case, instead of wandering through endless, sparse resources.
When be sure to have acquired knowledge on a subject is paramount, the Feynman technique — basically teach it to others in simple terms — is the tool to pick.
And we can continue, but the point is finding the right solution for every learning problem we face. How to do it? Experience, gained by learning how to learn!
There are frameworks too, meaning a more guided approach to the whole learning process. The best I found is “Ultralearning” by Scott Young: I’ve already written shortly about it but my advice is to read the book, especially if actively interested in this topic.
3 — Motivation
The third factor is, partially, more personal but fuels the whole process.
Motivation is driven by the answer to: “why I would like to learn …” and should be specific, because can be determinant to choose a particular learning approach and, consequently, a path.
I can summarize my experience about it in these points:
The more learning motivation is rooted, the more can be sustained for long: if we are determined and fully aware of the deep whys, we can exploit them in the “low” moments that inevitably will come, and overcome them.
Willpower can be trained: the armed arm of motivation is willpower and it can be trained. Building new habits is an example of how to lower the cognitive load necessary to do something, like decide to start a practice session.
Achieving progress is a major boost: making progress — real ones — gives confidence, feeding willpower. To do this, it’s important to pick SMART (Specific, Measurable, Achievable, Relevant, Time-limited) objectives and pile them up. Learning is a multi steps process.
Put in practice what learned, almost from day one: if knowing something is good for motivation, when able to put it into practice and, even better, having some feedback, not only can give a more correct assessment of the progress but skyrockets confidence and sense of achievement.
Failure is not a lack of progress: not achieving results or not fast enough is not a failure, but just a signal something should be changed in the learning plan. It’s perfectly fine. We fail only when we quit.
Be kind: having objectives and goals is necessary but, sometimes, we have to just give up for a bit, to avoid overlearning stress. Skip something or relaxing is not only ok but necessary.
Have fun: be joyful while learning is very important to keep going. Personally, when I’m able to grasp a difficult concept, connect the dots or perform something I was incapable of before, I feel awesome. Sometimes we can’t particularly like the subject but we should at least appreciate the learning aspect itself, enjoying the ride.
Conclusions
We saw different aspects around learning concepts and theories, intending to turn on the spotlights on the process we’re constantly performing.
The “meta” approach is essential to gain awareness of how we learn, as seeing it from the “outside” is the best way to evaluate and improve.
Several approaches can be followed, depending on goals, needs and constraints. With practice, gaining a learning experience, their choice will become almost automatic, resulting in great results improvement, in a shorter period.
So, next time, on approaching learning a new subject:
- be perfectly conscious of the reasons to do it
- set goals and incremental objectives towards them
- choose approaches and techniques, based on needs and constraints
- evaluate periodically how it’s going and be prepared to change if things are not working as expected
- practice what you learned and learn how to practice
- have fun
Do it consistently and a world of possibilities will be unlocked!
