2 Fundamental Reasons Why People Don’t Like Change

fear of change

I grew up in a traditional environment that had a strong bias against change. For example, the main social changes of the last 50 years were rejected, technological change was often deemed suspicious, and the good old days were definitely preferred to the depressing modern times.

But since then, I’ve noticed that this bias in favor of the status quo is strong everywhere. Granted, our world is changing faster than ever, but truth be told, only a handful of change agents are responsible for that.

People resist change for political, sociological and psychological reasons. Today I’ll dwell on the latter and show that resistance to change runs really deep.

Here are the two culprits responsible for this situation:

  1. Fear: Humans are hardwired to initially dislike unfamiliar stimuli
  2. Laziness: Humans use System 1 (an automatic mode of thinking) by default

First, people unconsciously prefer things for no other reason than their being familiar with those. This phenomenon is called the mere-exposure effect and has been studied extensively.

Of course, for our ancestors, this made sense. As the psychologist Gary Marcus says, what great-great-great-grandma knew and didn’t kill her was probably a safer bet than what she didn’t know. Similarly, those who stuck to the well known tended to outlast those ventured too far into uncharted territories.

Fear of the unknown and attachment to the familiar might once have helped us adapt, but now we’re stuck with this unconscious bias. This explains why incumbents are typically favored in an election, and why people often accept and even defend systems that truly threaten their self-interest (slavery, communism, apartheid, etc.).

Second, people instinctively rely on a cognitive process, System 1 (see my post on the topic), that discourages change.

Yes, we’re lazy and often prefer using heuristics (mental shortcuts) rather than deliberate thinking. For example, instead of analyzing the costs and benefits of a change, we’ll apply this simple rule: “If it’s in place, it must be working.”

This reliance on System 1 explains why we’re creatures of habit, and why it’s so hard to break away from routines and comfort zones. It’s true that habits increase efficiency, but they also impede improvement and innovation.

You can always change for the better; so be on the look out for those improvement opportunities. More than anybody else, peak learners must avoid inertia and embrace change.

3 Things To Know About The Learning Curve

the learning curve

In my workplace, we’re fighting over our learning curve (of course, we don’t call it that).

It has to do with our pay scales and job categories. To make a long story short, if we can prove to our employer that it takes our rookies two years instead of just one to be fully autonomous, we’ll move up a category and get a 5% raise. Yes, there’s excitement in the air.

In any job or human activity, efficiency increases with repetition, and a learning curve is the best way to quantify and graphically show that improvement.

Here are three things you should know about this curve.

First, the learning curve can either go up or down. It goes down when it measures the decreasing time, energy or number of trials needed to perform a task (vertical axis) as experience increases (horizontal axis).

But usually, the first image that comes to mind is a curve that goes up. In this case, we measure the increasing scores or amount of learning (vertical axis) that result from increasing experience or study (horizontal axis).

By the way, when people speak of a steep learning curve, they actually say the opposite of what they think, because a steep curve really means rapid progress.

Second, the learning curve usually follows an S-shape (see image above). When you start something new, you typically struggle at first; after a while, you quickly improve; but as time goes on, your rate of improvement decreases and even levels off.

This last phase derives from the law of diminishing returns, which says that making progress becomes more and more difficult as you get closer to a high level of expertise. Each unit of input will produce less and less output.

The S-shape is especially true for skill learning. My daughter is currently learning to play the recorder, and I can testify to that.

Third, the learning curve is used in many industries, not only to assess the progress of workers but also that of the organization as a whole. Each time the production quantity is doubled, the rate of improvement can increase from 5% to 30% depending on the type of work.

Here are some industries’ average rates of learning.

  • Raw materials: 5%
  • Electronics manufacturing: 10%
  • Aerospace: 15%
  • Shipbuilding: 20%
  • Electrical operations: 25%

As my story above shows, my employer pays us according to some preset categories of difficulty rather than considering individual improvement. But variations exist not only among tasks, but obviously among people too.

Do you know how to recognize peak learners’ learning curves? Well, look for curves that are steep, straight and that seem to go on forever.

Economic growth is impossible without learning

cause of economic growth

If you think education is expensive, try ignorance,” as a former president of Harvard University famously said.

Whatever its primary purpose is (or should be), education has a huge effect on any country’s productivity and economic health.

When you look at the data, you see a clear correlation between the education level of a population (enrollment ratio) and its country’s GDP. Today, let’s go further and explore how learning is actually the main driving force behind current economic growth.

First off, how does an economy grow?

If you remember your economics class, you know growth usually depends on the increase of the four traditional production factors, namely

  1. Land
  2. Labor
  3. Capital
  4. Entrepreneurship

But in reality, these inputs are typically hard to change in developed economies. Instead, as some recent theories have proposed, economic growth comes down to two things:

  1. Working smarter (human capital)
  2. Using better tools (technology)

So, in knowledge economies, getting better beats getting more. Of course, working harder, using more machines, and extracting natural resources from more land will generate some growth. But that’s not where most of our productivity gains have come from in the last decades.

Rather, it has come from working smarter and using better machines. In other words, it’s been the result of a more efficient use of existing assets. Let’s look at the two ways of achieving that.

Human capital refers to the knowledge, skills and experience of a country’s workforce. By and large, the more trained and educated workers get, the more productive they become. The general principle behind this is the specialization and division of labor, which has been one of the most powerful economical force since the Industrial Revolution.

Technological innovation refers to the development and adoption of better processes and products. Even if they disagree on how much of the growth can be attributed to new technology, all economists agree it plays a major role. For example, Nobel Prize winner Robert Solow pegged it at more than 80%.

Now what drives the increase of knowledge and technology?

Effective learning, of course. In a world where change is ubiquitous, there no better way, sorry, there’s no other way to succeed.

Therefore, peak learners are really the core of economic growth.

Why I regularly test my students even if it’s not popular (and the takeaway for peak learners)

testing students

This may surprise you, but I get criticized for my way of teaching. More precisely, some of my colleagues think I give too many evaluations. I confess I love my quizzes, and I typically assess my students’ progress every week.

But “teachers should spend less time testing and more time teaching” as the Badass Teachers Association often reminds me on Facebook. Similarly, for some of my colleagues, my strategy just reeks of old-school thinking. They say frequent quizzes undermine learners’ sense of responsibility and intrinsic motivation.

But, to me, regular testing has always felt intuitively right, and a few years ago, this intuition was confirmed by the largest evidence-based research about what works best in education. John Hattie’s mega-study Visible Learning is a synthesis of 50,000 studies involving more than 80 million students; there’s a reason why it’s been called the holy grail of education.

Hattie has identified 138 influences on student achievement and ranked them by degree of effectiveness. Here’s his top ten.


As you clearly see, providing formative evaluation ranks third (formative means low or no point value). Let me repeat this: testing has the third most powerful effect on learning among hundreds of investigated variables.

The thing is, formative assessments do two main things.

  1. They measure learning
  2. They strengthen learning

First, progress monitoring provides a great window into where you’re at as well as what works and what doesn’t, which allows both the teacher and the student to adjust accordingly. And the more often they get this feedback, the faster they can course correct.

Second, many recent studies (most likely included in Hattie’s mega-study) have established that taking tests is one of the best ways to reinforce learning, and that it should be done sooner rather than later (even if you haven’t finished learning).

For example, one of the studies shows that giving short quizzes on a regular basis like I do increases performance by about half a letter grade as opposed to relying on four major exams. The most famous research has been done by Roediger, who has listed ten benefits of testing.

This is the takeaway for peak learners. You really have to stop seeing studying and testing as two different things.

Testing / self-testing is learning at its best.

2 Reasons Why Learning a Second Language Is So Hard

second language acquisition

In my studies abroad and within my language-related work, I’ve heard plenty of second-language speakers. Yet I’ve only met one person who spoke my language as a second language with native-like fluency. I actually couldn’t believe it was his second language.

Why does learning a language seem so gleefully easy for babies, but so cruelly hard for adults? Why is it that the better you get at learning in general, the worse you perform in learning a language?

Here are your two culprits.

  1. The brain
  2. The learning process

For babies, learning means choosing. A three-year-old has about twice as many neural connections (synapses) as an adult. When synaptic pruning kicks in, weak connections get deleted while those that are used get a boost. So, as the brain gains in efficiency, it must let go of some opportunities.

This operation is obvious when it comes to language learning. A study by Hyltenstam and Abrahamsson shows that, if you miss the boat and don’t get early exposure to a language (yes, the famous critical period), you’ll likely never reach native-like proficiency (sorry).

For example, babies at birth have the amazing capacity to distinguish the sounds of all human languages, but as they grow up, their brain cleans out the unused connections, and this sensitivity to other languages gets radically reduced.

Similarly, it seems impossible to perfectly re-acquire a gender-category system if you didn’t develop it as a kid (unlike English, most European languages attribute gender to nouns).

Now that the bad news is out of the way, let’s see what we can learn from the way babies master their native tongue.

Second language acquisition feels like climbing Mount Everest because we typically engage System 2 (see my post on this topic). When you study German in your living room or classroom, you emphasize that rational, deliberate and conscious learning process. You sit down and try to find ways to assimilate the material, right?

Children, on the other hand, master their native tongue exclusively through System 1, and don’t even need feedback about whether they’re getting it right. Unlike System 2, which takes place in the prefrontal cortex, System 1 uses the limbic system, where the learning process is implicit, instinctive and spontaneous.

That’s why immersion is so effective. Of course, sheer exposure plays a big role, but this method also enables System 1 to kick in and open up a whole new type of learning.

So what’s the lesson for those trying to pick up a foreign language?

First, relax. Feeling overwhelmed is normal. Your brain needs time to create new pathways. Also, bear in mind that some aspects of second-language learning have no critical period. Second, as peak learners now know, call upon the power of System 1 (stay tuned for more info on that).

People don’t naturally think like scientists (but peak learners should)

learners as scientists

One of my close friends definitely prefers “being right” than being accurate. He has lots of opinions and theories on everything, but if you show him evidence that contradicts one of them, he’ll put the full weight of his reasoning power to discount your evidence.

As it turns out, we’re all like him to a lesser or greater extent, and this flies in the face of the popular theory of discovery-based learning, which posits that students intuitively learn like scientists.

What does it mean to learn like a scientist?

It means you’re an active creator of your own learning, and you do this by

  1. exploring your environment,
  2. generating ideas about how things work,
  3. testing those ideas and
  4. changing your model accordingly.

In other words, scientific thinking is about coordinating evidence (things you observe) and theory (ideas about how those things work).

So, for people to think like scientists, they need at least to be able

  1. to distinguish theory and evidence and
  2. to update their theory in the light of new evidence.

As many studies have found, untrained people are bad at both.

After reading Researcher Deanna Kuhn’s study, you’ll indeed notice that people easily blur the difference between theory and evidence in everyday life.

Let me give you the simplest example. When you see people smile, you probably take this as evidence that they’re happy, right? But the thing is, you can’t see happy; happy is a theory. It may look like a safe theory, but it’s still a theory.

But even when theories don’t get confused with facts, shifting theories to match facts doesn’t come naturally for most people. As Lord, Ross and Lepper’s classic study showed, when they come across a fact that contradicts their theory, people will often ignore it or interpret it in a biased way (confirmation bias).

Of course, as evidence accumulates, people will eventually adjust their theory accordingly, but that process often occurs unconsciously; unlike scientists, people don’t actively review their models (Kuhn).

With information currently flowing from all directions, critical thinking is more needed than ever. But thinking like a scientist is an acquired skill, and a difficult one at that. And if you want to become a peak learner, you have no choice but to develop that skill.

The best first step you can take in that direction is to set your ego aside and ask yourself: “What would show me I’m wrong?”

4 Basic Strategies To Boost Learning Performance

how to be a top learner

Recently, one of my colleagues wanted to test my budding expertise and asked me to give him learning strategies you can’t live without, be it for improving dance moves, public speaking or language acquisition.

So here are four basic tricks given by Professor Monisha Pasupathi in How We Learn.

  1. Spread out your rehearsals
  2. Mix them up
  3. Draw the connections
  4. Sleep on it

Spacing out your rehearsals is the essential first step for anyone serious about learning. Leaving enough time between your practices or studying is like changing your Pentium computer for the latest iMac (sorry if you’re not into Macs). It just turbo-charges your performance. To know how much time is enough time, check my post on the topic.

Varying the way you learn is your second performance booster. Remember the old advice of sticking to a strict practice routine? Throw that out the window. You want to often change where, when and how you practice and study. For example, instead of always reviewing your Spanish with flashcards at the kitchen table, try finding the words in texts or talking about it to friends. Each change in your routine reinforces your learning by making it more independent from the context.

Using elaborative encoding in the third strategy applicable everywhere. This big word simply means that you need to connect your new material to what you already know, either deliberately by organizing it around past info and experience, or implicitly by using past movements to generate new ones. For more details, check my post on the topic.

Getting a good night’s sleep is your fourth power. Sleeping consolidates learning by helping the brain complete new neural connections forged through practice and study. Brain images show that the patterns of activities occurring while learning are reproduced during REM sleep (and it’s a good thing your body is paralyzed during that phase). Sleep is like an extra rehearsal at the brain level.

So that’s what I told my colleague. You want to reach peak learner status in your field? Start by making these habits part of your daily routine.