Effective learning (part 1)

“Practice doesn't make perfect. Perfect practice makes perfect.” It is totally obvious to anyone that to master a skill we need to practice. However, there are many ways to practice, some of which are more effective than others. But when it comes to learning, most people are usually relying on their intuition alone, which can often lead them to devastating failures. It usually happens because learners lose all their motivation and just give up. They simply come to believe that they can’t become good at it, saying things like: “It’s just not my thing”, or “I’m not too smart enough” and etc. But in reality the thing they might be lacking is not the cognitive ability, but rather understanding of how to efficiently learn and develop new skills. And the main reason is, that the most effective learning strategies are not intuitive at all. The purpose of this article is to give you all the necessary information needed to become an efficient learner. It is a compilation from several dozen sources, so having it in one place has proven to be quite handy. I’m a learner myself, so as part of my learning I’ve decided to share my finding with others. I hope it will be helpful.

I. What is learning?

Learning is acquiring knowledge or behavioral responses from experience. The “from experience” part is very important. Learning might come from studying, or from being taught, or just from living life, but it has to come from experience. Behavioral responses that are genetically programmed, such as instincts and reflexes, don’t count as being learned. The result of learning is memory. It is the record of learning that is stored in your mind. Learning involves making physical changes in the brain that allow information to be retrieved later on. And those changes constitute the physical basis of memory. Many people think of learning as a single, unitary process, but in the past few decades, scientists have discovered that human beings are equipped with a variety of very different mechanisms that are tailored for learning different kinds of information. For example, our short-term working memory is very different from long-term memory. In fact, it have been discovered that we even use different mechanisms for storing different kinds of information within working memory and long-term memory.

Sensory memory

Sensory memory is a very brief memory that allows people to retain impressions of sensory information after the original stimulus has ceased. It is often thought of as the first stage of memory that involves registering a tremendous amount of information about the environment, but only for a very brief period. The purpose of sensory memory is to retain information long enough for it to be recognized. Key characteristics:

Duration: very short.
Capacity: all sensory experience.
Encoding: sense specific (different stores for each sense).

Short-term memory

Short-term memory, also known as primary or active memory, is the information we are currently aware of or thinking about. The information found in short-term memory comes from paying attention to sensory memories. It is limited in terms of both duration and capacity.Short-term memory is often used synonymously with working memory, but some theorists consider the two forms of memory distinct, assuming that working memory allows for the manipulation of stored information, whereas short-term memory only refers to the short-term storage of information. Key characteristics:

Duration: short.
Capacity: 7 +/- 2 items.
Encoding: mainly auditory.

Long-term memory

Long-term memory refers to the storage of information over an extended period. Through the process of association and rehearsal, the content of short-term memory can become long-term memory. Long-term memories can last for a matter of days to as long as many decades. Key characteristics:

Duration: unlimited.
Capacity: unlimited.
Encoding: mainly semantic (but can also be visual and auditory).

There are two types of long-term memory: explicit (conscious) memory and implicit (unconscious) memory.

Explicit memories

Are memories that you can consciously bring to mind and describe verbally. When most people think of learning and memory, they’re thinking of explicit learning and memory, such as remembering what you ate for breakfast.
1. 1.1 Semantic memory
  Semantic memory refers to memory that is consciously accessible and verbalizable. You know that in Java an int is a primitive data type. This is an example of verbalizable, conscious, explicit memory.
2. 1.2 Episodic memory
  Episodic memories are a type of explicit memory that refers to memories for personal episodes in your life. Your memory of eating breakfast today is an episodic memory.
Implicit memories

Are memories that you can’t consciously recall but that nevertheless influence your subsequent behavior. For example, your memory for how to ride a bike is an automatic, implicit memory.
1. 2.2 Procedural memory
  Procedural memories are accessed and used without the need for conscious control or attention. Knowing how to read, how to speak a language, how to play a music instrument, and how to type using a keyboard are examples of procedural memory.
  
  Procedural memory is created through procedural learning, or repeating a complex activity over and over again until all of the relevant neural systems work together to automatically produce the activity. Implicit procedural learning is essential for the development of any motor skill or cognitive activity.
2. 2.2 Priming
  Priming occurs when previous exposure to a stimulus makes you faster, or more efficient, at processing similar stimuli in the future. For example, suppose you are asked to repeatedly say a few relatively difficult to pronounce words out loud. The more you say the words, you’ll probably get a little faster and more fluid. Saying them the first few times “primes the pump” and makes the words come out more fluidly and efficiently the next time.

Summary

This should give you a general idea on how our memory is arranged. It is a very complex and difficult topic in itself, but having some basic picture should help you understand how we learn and why some strategies are better than others. For example, if you want to target your long-term learning, it can be significantly improved by introducing changes that actually make short-term performance more difficult rather than easier. These are called desirable difficulties. But sometimes you might want to do the opposite and focus on temporary performance effects instead.

II. How do we learn?

Human beings use multiple different learning systems, depending on what they’re learning. In particular, learning unconscious information is fundamentally different than learning conscious information and even depends on different parts of the brain. For example, amnesia clearly shows that brain damage that dramatically impairs conscious memories can leave unconscious memories intact. Again, it is very important to understand, that we don’t have a single, unitary system in our mind that is responsible for learning. Instead, we have multiple brain systems for learning different kinds of information.

Main types of learning

Nonassociative learning

Nonassociative learning refers to changes in behavior related to a stimulus that do not involve associating that stimulus with another stimulus or event. When repeated exposure to a stimulus by itself changes your reaction to that stimulus, that’s nonassociative learning.
1. 1.1 Habituation
  A type of nonassociative implicit learning is habituation. We habituate to stimuli all the time, and we’re typically unaware of it. For example, you get habituated to the sound of a computer fan blowing. Over time, your response to the sound gets smaller and smaller until finally you don’t notice it at all. This is a very simple kind of learning, yet it’s still learning. Your behavior is changing as a result of your previous experience—in this case, your experience of being repeatedly exposed to a stimulus. Essentially, you’re learning to ignore it.
2. 1.2 Sensitization
  The opposite can also happen; that is, rather than learning to ignore a stimulus, you can learn to become more sensitive to it. This is called sensitization, and it’s also a form of nonassociative learning. Imagine that you’re trying to solve a dofficult programming task, but someone near by is constantly talking on the phone. Rather than getting used to the sound and habituating to it, you might actually become more and more sensitive as time goes by. This is an example of sensitization. Previous experience makes you more and more sensitive to it.
Associative learning

Associative learning is the process by which a person or animal learns an association between two stimuli or events. It includes both classical conditioning and operant (instrumental), conditioning.
1. 2.1 Classical conditioning
  Classical conditioning involves placing a neutral signal before a naturally occurring reflex. In Pavlov's classic experiment with dogs, the neutral signal was the sound of a tone and the naturally occurring reflex was salivating in response to food. By associating the neutral stimulus with the environmental stimulus (food), the sound of the tone alone could produce the salivation response.
2. 2.2 Operant conditioning
  Operant conditioning, sometimes referred to as instrumental conditioning, is a method of learning that employs rewards and punishments for behavior. Through operant conditioning, an association is made between a behavior and a consequence (whether negative or positive) for that behavior. Operant conditioning has also been used to explain, and potentially treat, many psychological and social problems, including clinical depression, addiction and etc.
  
  In this context it is also crucial to understand what a learned helplessness is. Especially when in comes to learning some very chellenging skills (f. e. programming or foreign language) you should know how to protect yourself against it. One way to do it is to use growth mindset, instead of fixed mindset. We will discuss this in more details later in this article.
Observational learning

Observational learning describes the process of learning through watching others, retaining the information, and then later replicating the behaviors that were observed. This is not the same as pure imitation of another behavior. Observational learning occurs as a result of witnessing another person, but is performed later and cannot be explained as having been taught in any other way. This type of learning also encompasses the concept of behavior avoidance as a result of seeing another person behave in a certain way and receive a negative consequence.

Observational learning can be a powerful learning tool. When we think about the concept of learning, we often talk about direct instruction or methods that rely on reinforcement and punishment. But a great deal of learning takes place much more subtly and relies on watching the people around us and modeling their actions.

Skill acquisition

Any behavior that needs to be learned and that is improved by practice can be considered to be a skill. A standard way that scientists think about skill acquisition is as converting explicit, declarative knowledge into an implicit, procedural skill. How do we go from knowing that to knowing how? Explicit, declarative knowledge is knowledge about a skill that you can verbalize and talk about—declare. It’s the book knowledge and verbalized instructions about how to perform a skill. But actually doing a skill requires implicit, procedural memory. Just because you can talk about how to do a skill, that doesn’t mean that you can actually do it. Somehow you need to convert the declarative knowledge into a procedural skill that you can actually execute. And that takes practice and time.

Stages of skill acquisition

Paul Fitts and Michael Posner came up with a very influential theory that proposes that we go through 3 major stages over the course of skill acquisition: the cognitive stage, the associative stage, and the autonomous stage.

The cognitive stage is dominated by cognition—that is, by thinking, or by explicit, declarative knowledge.
The associative stage involves tweaking the skill, associating it with different responses, and hopefully improving. It involves figuring out what works and what doesn’t and using that feedback to slowly get rid of actions that lead to errors.
The autonomous stage is the point at which the skill can be performed really well with little or no need for conscious oversight.

How skill acquisition happens

One of the most influential answers to this question was developed by John Anderson, who proposed that the nature of our representation of procedural skills is very different from our representation of declarative knowledge. Anderson refers to the conversion process as knowledge compilation, in which you compile declarative knowledge and turn it into procedural knowledge. In computer science, a compiler takes a high-level description of the program you want to run and transforms it into an executable form. In this case, the high-level description is in natural language rather than a programming language, and the executable form is a set of production rules rather than a computer’s machine code—but the basic idea is the same. According to Anderson, as we’re learning a skill, we’re taking a high-level declarative description of what we want to do and converting it into a form that our motor system can actually execute.

III. Myths and facts about learning

There are many factors that can contribute to our cognitive performance. Therefore, it is obvious that for maximizing your learning potential you have to control as many of these factors as possible. However, there are also many popular myths which might negatively affect your decisions in regard to how you learn. We will start by debunking some of the most important misconceptions.

Myth №1. People have different learning styles.

One popular theory proposes that people tend to be more auditory, visual, or kinesthetic learners. In other words, some people learn best by hearing, seeing or doing. Current evidence shows that humans don’t have specific learning styles that work better for each individual. Different people do have different preferences, but it doesn’t translate to being the most effective way to study for them. So, to be more efficient, we should be ready to tailor our habits and switch to strategies that are scientifically proven to work better for everyone.

Myth №2. Left-brained people are rational, right-brained people are creative.

It is undeniably true that humans have two brain hemispheres. Also, there is scientific evidence (from brain-damaged patients as well as more modern neuroimaging techniques) to suggest that some types of tasks might use more resources from one hemisphere than the other. A good example of this is language, which tends to use more resources from the left hemisphere than the right. However, what is NOT true is that individuals can be “right-brained” or “left-brained,” or that the former is “creative” while the latter is “rational.” This is a misunderstanding of how the brain works: just because some tasks require more resources from one hemisphere, does not mean individuals differ in terms of their brains. In fact, we tend to do better at tasks when the entire brain is utilized, even for things that are typically associated with a certain area of the brain.

Myth №3. We only use 10% of our brain.

Researchers suggest that this popular urban legend has existed since at least the early 1900s. Brain imaging scans clearly show that almost all regions of the brain are active during even fairly routine tasks such as talking, walking, and listening to music. Also, if the 10% myth was true, people who suffer brain damage as the result of an accident or stroke would probably not notice any real effect. In reality, there isn't a single area of the brain that can be damaged without resulting in some sort of consequence.

Myth №4. Brain-training apps will make you smarter.

There has been a huge increase of interest in “brain training” over the recent years. The idea is that with practice, we can change our working memory capacity, processing speed, and/or attentional control. Based on early results suggesting this might be possible, commercial companies created brain training products and promoted them with unsubstantiated claims. Unfortunately, all the users of these games can really expect is an improvement in their performance on the games themselves. Transfer from the games to real-life tasks involving attention and working memory has not been found consistently in the research.

Myth №5. Male brains are biologically better suited for math and science, female brains for empathy.

There are small anatomical differences between male and female brains. The hippocampus, involved in memory, is usually larger in women, while the amygdala, involved in emotion, is larger in men, which is quite contrary to the myth. Because of this many gender disparities might exist due to cultural expectations instead of biology.

Important facts

Scientists have been unable to find any kind of capacity limit on how much we can store in our memory.
We remember visual information significantly better than verbal information.
We remember vivid, striking pictures better than we do ordinary pictures.
Connecting the information that you’re trying to learn with information you already know is much more efficient than trying to learn something completely new and unrelated to anything.

Interestingly, the method of loci, a powerful memory enhancing technique, utilizes these four above-mentioned facts.
Evidence suggests that various sleep stages are involved in the consolidation of different types of memories and that being sleep deprived reduces one’s ability to learn. Adequate sleep each day is very important for learning and memory! You can also learn and remember information better before a good night’s rest. This effect applies to both explicit, declarative memory as well as implicit, procedural learning.
Attention is often defined as a limited-capacity resource. An important feature of attention is the ability to selectively focus on just one stimulus at a time. The data point strongly to the conclusion that it is almost impossible to pay attention to more than one thing at the exact same time. When you feel like you’re multi-tasking, or paying attention to two things at once, you’re actually switching back and forth between the two things you’re trying to pay attention to, which diminishes efficiency for both of the tasks. It is very similar to how single core processors run multiple tasks at once. As a result, the easiest and most obvious way we can help to focus our attention is by reducing the amount of distractions in our environment.
While short-term stress often strengthens memory (via narrowing of attention), long-term, chronic stress seems to undermine it. Surprisingly, but even confusion can sometimes be beneficial to learning. Research has shown that being confused about new ideas or a situation can spur us to work harder to understand, leading to a deeper grasp and better retention of what we have learned.
Nutrition and brain function are crucially interlinked. What you eat and when you eat it can drastically impact the way your brain functions. Therefore, it affects how productive and efficient your studying time can be. Sticking to a mediterranean diet have many benefits for brain health and memory. Staying properly hydrated is also equally important for your cognitive performance.
Smoking or alcohol consumption can do a lot of harm to your brain, but when combined they are even more destructive. It is in your best interest to avoid these drugs.
Regular physical activity, especially aerobic, have a positive effect on memory and thinking skills, while also improving mood, sleep, and reducing stress and anxiety.
Aging has dramatically different effects on fluid intelligence compared to crystallized intelligence. Research suggests that while fluid intelligence begins to decrease after adolescence, crystallized intelligence continues to increase throughout adulthood. Semantic memory seems to get better, while episodic memory worsens. Procedural memory doesn’t normally decline as we get older.
Despite being popular, re-reading materials, cramming, highlighting and underlining are highly inefficient learning habits and should be replaced with a much more efficient ones as soon as possible!