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The Science Behind How We Learn New Skills

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Posted By Sherwen Mohan

Learning new skills is one of the best ways to make yourself both marketable and happy, but actually doing so isn’t as easy as it sounds. The science behind how we learn is the foundation for teaching yourself new skills. Here’s what we know about learning a new skill.

Our brains are still a bit of a mystery. We’ll likely be learning about how our brain works for years to come, but we are starting to get a better idea of how we learn new things. To that end, let’s start by talking about what happens in your brain as you take on a new skillset before moving onto some of the scientifically effective ways to learn.

Every time you learn something new, your brain changes in a pretty substantial way. In turn, this makes other parts of your life easier because the benefits of learning stretch further than just being good at something. As The New Yorker points out, learning a new skill has all kinds of unexpected benefits, including improving working memory, better verbal intelligence, and increased language skills.

Likewise, as you learn a new skill, the skill actually gets easier to do. Cornell University explains what’s going on:

Specifically, training resulted in decreased activity in brain regions involved in effortful control and attention that closely overlap with the frontoparietal control and dorsal attention networks. Increased activity was found after training, however, in the default network that is involved in self-reflective activities, including future planning or even day dreaming. Thus, skill mastery is associated with increased activity in areas not engaged in skill performance, and this shift can be detected in the large-scale networks of the brain.

Essentially, the more adept you become at a skill, the less work your brain has to do. Over time, a skill becomes automatic and you don’t need to think about what you’re doing. This is because your brain is actually strengthening itself over time as you learn that skill. Scientific American breaks it all down like so:

Many different events can increase a synapse’s strength when we learn new skills. The process that we understand best is called long-term potentiation, in which repeatedly stimulating two neurons at the same time fortifies the link between them. After a strong connection is established between these neurons, stimulating the first neuron will more likely excite the second.
 

In addition to making existing synapses more robust, learning causes the brain to grow larger. Optical imaging allows researchers to visualize this growth in animals. For instance, when a rat learns a difficult skill, such as reaching through a hole for a pellet of food, within minutes new protrusions, called dendritic spines, grow on the synapses in its motor cortex, the region that allows animals to plan and execute movements.

The more connections between neurons are formed, the more we learn, and the more information we retain. As those connection get stronger, the less we have to think about what we’re doing, which means we can get better at other facets of a set of skills.

We’re still learning about learning. So, while we can see how learning skills affects the brain, we’re still digging into exactly why it happens and all the benefits of doing so. As the old saying goes, practice makes perfect, but how we practice is just as important as if we’re practicing.

How You Can Use This Science to Learn Faster

Knowing how your brain adapts to new skills is just part of the process. That knowledge is worthless if you don’t know how to apply it. With that in mind, let’s dig into some of the tried and true methods of learning new skills as quickly as possible. It’s all about boosting your brainpower in one way or another. Thankfully, it’s surprisingly easy.

Force Yourself to Learn Without Guides or Help

When we’re learning a new skill it’s easy to rely on YouTube, tutorials, walkthroughs, and guides to help get the process started. That’s great for those beginning days, but if we keep doing that we won’t ever actually learn because we’re not solving problems on our own.

In order to learn, we need to fail. Science writer Annie Murphy Paul calls this productive failure:

We’ve heard a lot lately about the benefits of experiencing and overcoming failure. One way to get these benefits is to set things up so that you’re sure to fail—by tackling a difficult problem without any instruction or assistance. Manu Kapur, a researcher at the Learning Sciences Lab at the National Institute of Education of Singapore, has reported (in the Journal of the Learning Sciences) that people who try solving math problems in this way don’t come up with the right answer—but they do generate a lot of ideas about the nature of the problems and about what potential solutions would look like, leading them to perform better on such problems in the future. Kapur calls this “productive failure,” and you can implement it in your own learning by allowing yourself to struggle with a problem for a while before seeking help or information.

Take the example of learning the guitar. You can easily hunt down the tablature for “Paint it Black” online, but that’s not going to help you learn the actual sound of each chord you’re playing. Instead, try to figure it out on your own instead of seeking out the answer. This is essentially learning by trial-and-error, which is frustrating, but works really well. The same goes any number of other skills. Sure, sometimes you need to break down and search for a solution, but you’re going to be better off if you don’t.

Spread Out Learning Over Time

When we’re picking up a new skill or learning something entirely new, it’s easy to binge-learn and obsessively work on it over time. However, that’s not always the best idea. In fact, spreading out learning, also known as distributed practice, is thought to be a better way to learn. A review of studies in Psychological Science in the Public Interest found that spreading out learning is far more effective than cramming:

Dunlosky and colleagues report that spreading out your studying over time and quizzing yourself on material before the big test are highly effective learning strategies. Both techniques have been shown to boost students’ performance across many different kinds of tests, and their effectiveness has been repeatedly demonstrated for students of all ages.

“I was shocked that some strategies that students use a lot — such as rereading and highlighting — seem to provide minimal benefits to their learning and performance. By just replacing rereading with delayed retrieval practice, students would benefit,” says Dunlosky.

Distributed practice is an old technique, but it actually works really well for the busy lives most of us lead. Instead of sitting down for hours on end to learn a skill, distributed practice is all about shorter, smaller sessions where you’re stimulating the link between the neurons more often throughout time. So, instead of trying to learn a skill by taking an hour long class every night, give yourself a lot of time overall, and small chunks throughout the day. Heck, even 15 minutes a day to spend on projects is enough for many of us.

Choose Your Study Time Wisely

You wouldn’t think it, but when you study or practice is just as important as how. As we’ve seen before, the body’s internal clock is tuned to work better during certain points in the day, and that goes for learning as well. According to one study published in the journal PLOS One, we learn best when we do so before sleep.

The study found that subjects who went to sleep right after learning something did significantly better in a series of memory tests. We’ve seen this before with naps, and know that sleep has a big impact on memory retention in general. Basically, when you learn a new skill before bed, you’re helping fortify the link between the neurons in your brain. This means you retain information better.

Apply Your Skills Every Day

We’re big proponents of experiential learning here at Lifehacker, and that’s because it’s often the best way to learn the types of skills we talk about here. The more you can apply what you’re learning to your every day, the more it’ll stick in your head.

The reason is simple. When you’re learning by doing, you’re implementing everything that makes our memory work. When you’re able to connect what you’re learning with a real world task, that forms the bonds in your brain, and subsequently the skills you’re learning will stick around. This is especially true with learning a foreign language, where application is the key to learning quickly.

You can do this in a number of ways. For some skills, like music, deliberate practice is a way to be more mindful of what you’re doing so you can actually improve. Deliberate practice is all about tracking what you’re learning, focusing on short learning sessions, and practicing as smart, not hard.

Just like memory, we learn best when we have context, and that applies to new skills as much as it does random facts in school. That’s why something like the transfer of learning is helpful when your learning a new skill. This means you’re applying your new skills in your day to day life in a context that matters. For example, if you’re learning about mathematics, make sure you find a way to work that into your daily life, even if it’s as simple as figuring out your gas mileage every day. It’s simple, but it’s about forming connections in your brain that actually matter to you.

Everyone prefers to learn a little differently, so unfortunately you might need to experiment with different methods as you’re taking on a new skill. The above list certainly doesn’t inlucde everything, but it’s a starting point to learning more effectively. You’re bound to hit plenty of barriers along the way, and sticking with it isn’t always easy, but the benefits are worth it: a bigger, smarter brain that can process things easily.

 

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The Characteristics of a Highly Effective Learning Environment

Terry Heick, the driving force behind TeachThought, examines ten crucial characteristics of a highly effective learning environment in which students learn deeply. 

Posted by: Ryan Schaaf

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Written by: Terry Heick

Wherever we are, we’d all like to think our classrooms are “intellectually active” places. Progressive learning (like our 21st Century Model, for example) environments. Highly effective and conducive to student-centered learning. But what does that mean?

The reality is, there is no single answer because teaching and learning are awkward to consider as single events or individual “things.” This is all a bunch of rhetoric until we put on our white coats and study it under a microscope, at which point abstractions like curiosity, authenticity, self-knowledge, and affection will be hard to pin down.

So we put together one take on the characteristics of a highly effective classroom. They can act as a kind of criteria to measure your own against–see if you notice a pattern.

10 Characteristics Of A Highly Effective Learning Environment

1. The students ask the questions—good questions

This is not a feel-good implication, but really crucial for the whole learning process to work.

The role of curiosity has been studied (and perhaps under-studied and under-appreciated), but suffice to say that if a learner enters any learning activity with little to no natural curiosity, prospects for meaningful interaction with texts, media, and specific tasks are bleak. (Interested in how to kill learner curiosity in 12 easy steps?)

Many teachers force students (proverbial gun to head) to ask question at the outset of units or lessons, often to no avail. Cliché questions that reflect little understanding of the content can discourage teachers from “allowing” them. But the fact remains—if students can’t ask great questions—even as young as elementary school—something, somewhere is unplugged.

2. Questions are valued over answers

Questions are more important than answers. So it makes sense that if good questions should lead the learning, there would be value placed on these questions. And that means adding currency whenever possible—grades (questions as assessment!), credit (give them points—they love points), creative curation (writing as a kind of graffiti on large post-it pages on the classroom walls), or simply praise and honest respect. See if you don’t notice a change.

3. Ideas come from a divergent sources

Ideas for lessons, reading, tests, and projects—the fiber of formal learning—should come from a variety of sources. If they all come from narrow slivers of resources, you’re at risk of being pulled way off in one direction (that may or may not be good). An alternative? Consider sources like professional and cultural mentors, the community, content experts outside of education, and even the students themselves. Huge shift in credibility.

And when these sources disagree with one another, use that as an endlessly “teachable moment,” because that’s what the real world is like.

4. A variety of learning models are used

Inquiry-based learning, project-based learning, direct instruction, peer-to-peer learning, school-to-school, eLearning, Mobile learning, the flipped classroom, and on and on—the possibilities are endless. Chances are, none are incredible enough to suit every bit of content, curriculum, and learner diversity in your classroom. A characteristic of a highly-effective classroom, then, is diversity here, which also has the side-effect of improving your long-term capacity as an educator.

5. Classroom learning “empties” into a connected community

In a highly-effective learning environment, learning doesn’t need to be radically repackaged to make sense in the “real world,” but starts and ends there.

As great as it sounds for learners to reflect on Shakespeare to better understand their Uncle Eddie—and they might—depending on that kind of radical transfer to happen entirely in the minds of the learners by design may not be the best idea. Plan on this kind of transfer from the beginning.

It has to leave the classroom because they do.

6. Learning is personalized by a variety of criteria

Personalized learning is likely the future, but for now the onus for routing students is almost entirely on the shoulders of the classroom teacher. This makes personalization—and even consistent differentiation—a challenge. One response is to personalize learning—to whatever extent you plan for—by a variety of criteria—not just assessment results or reading level, but interest, readiness-for-content, and others as well.

Then, as you adjust pace, entry points, and rigor accordingly, you’ll have a better chance of having uncovered what the learners truly “need”.

7. Assessment is persistent, authentic, transparent, and never punitive

Assessment is just an (often ham-fisted) attempt to get at what a learner understands. The more infrequent, clinical, murky, or threatening it is, the more you’re going to separate the “good students” from the “good thinkers.” And the “clinical” idea has less to do with the format of the test, and more to do with the tone and emotion of the classroom in general. Why are students being tested? What’s in it for them, and their future opportunities to improve?

And feedback is quick even when the “grading” may not be.

8. Criteria for success is balanced and transparent.

Students should not have to guess what “success” in a highly-effective classroom looks like. It should also not be entirely weighted on “participation,” assessment results, attitude, or other individual factors, but rather meaningfully melted into a cohesive framework that makes sense—not to you, your colleagues, or the expert book on your shelf, but the students themselves.

9. Learning habits are constantly modeled

Cognitive, meta-cognitive, and behavioral “good stuff” is constantly modeled. Curiosity, persistence, flexibility, priority, creativity, collaboration, revision, and even the classic Habits of Mind are all great places to start. So often what students learn from those around them is less directly didactic, and more indirect and observational.

Monkey see, monkey do.

10. There are constant opportunities for practice

Old thinking is revisited. Old errors are reflected on. Complex ideas are re-approached from new angles. Divergent concepts are contrasted. Bloom’s taxonomy is constantly traveled up and down, from the simple to the complex in an effort to maximize a student’s opportunities to learn—and demonstrate understanding—of content.