CHAPTER 2

Our Brains and the
Science of Learning

The goal for learning professionals is to help people retain information in the best way possible. Although everyone learns differently and uniquely, there are basic principles that learning professionals should be aware of to maximize people’s potential. This chapter reviews those basic principles, structured in terms of how the brain works, learns, and applies.

Keeping these principles in mind during the analysis phase can advance learning. We do not claim these principles are exhaustive or comprehensive, but we do view them as guardrails that will keep you on track during the analysis phase. We present a deeper dive of these principles and how they relate to the CLICS model in subsequent chapters.

How the Brain Works

Tomorrow is the day. You spent weeks, perhaps months preparing for this workshop, where you will launch important training around inclusion and bias mitigation for the organization. You and your team have invested hours thinking, collaborating, and coordinating for this day. You have defined a series of objectives that this workshop aims to achieve. So, what can you do to ensure that valuable teaching doesn’t all go down the drain? How can you ensure that people not only engage in the material now, but also retain the information and actively apply it on the job?

To start, it’s helpful to know how people remember and retain information. How does the brain process events and record them as memories? In short, memory is an information-processing system that involves a set of processes used to encode, store, and retrieve information (Figure 2-1).

Figure 2-1. How the Brain Processes Events

Encoding involves actively inputting information into the memory system. The brain processes, labels, and codes information it has received, then organizes it with other similar or relevant information, thereby connecting this new information to already existing concepts.

Once information has been encoded, the brain puts it into storage, or a permanent state of retention (long-term memory, LTM). For memory to go into storage, it must pass through the stages of sensory memory and short-term memory. Sensory memory is the very brief storage (up to a couple of seconds) of sensory events, such as sights, sounds, and tastes. We are constantly bombarded with sensory information that we cannot absorb and, frankly, don’t need to. For example, what did you eat for lunch on Tuesday this week? If there was not anything unique about lunch outside of our daily rhythms and routines—for example, we didn’t go out to eat with a friend we haven’t seen in a while or we didn’t contract food poisoning—the brain does not encode every detail. It is selective. Only some information, contingent on many factors (necessity, value, meaningfulness, and so forth), will move into short-term memory.

Short-term memory (STM), or “working memory,” briefly stores incoming sensory memory. Exactly how much can be stored in STM? George Miller (1956) found that most people can retain about seven items in STM. Some remember five, some nine, so he claimed the capacity of STM as seven plus or minus two.

STM can be imagined as the information you just typed up on your computer—a document, a spreadsheet, or a webpage. Information at this stage can go in one of two ways: either to long-term memory (as if you saved it to your hard drive) or to trash (you deleted a document or closed a browser tab). For information to move from STM into LTM, it must be consciously and repeatedly practiced or rehearsed.

Otherwise, it will be forgotten.

Here is how quickly memory fades. Hermann Ebbinghaus analyzed how information is lost over time. He first memorized a bunch of nonsense syllables (for example, “WID” and “ZOF”), then measured how much of these he learned over different periods of time, 20 minutes to a month later. He then plotted his results on a graph, which became known as the “forgetting curve” (Figure 2-2). He found that an average person will lose about half of the memorized information after 20 minutes and 70 percent of the information after 24 hours when there are no attempts or strategies to retain it (Ebbinghaus 1885/1964). He determined that the speed of forgetting depends on several factors: the complexity of the material and psychological factors (such as sleep and stress). The best way to increase the strength of memory is through mnemonic techniques and spaced repetition.

Figure 2-2. The Ebbinghaus Forgetting Curve

The Ebbinghaus forgetting curve depicts how quickly retention of new information declines over time (Ebbinghaus 1885/1964).

 

Finally, after doing the hard work to encode and store information, the brain must be able to retrieve it at relevant moments. Retrieval is getting the information out of memory and back into awareness. There are three ways you can retrieve information out of long-term memory storage:

•  Recall is what we most often think about when referring to the retrieval process: it is when you can access information without cues, such as on an essay test.

•  Recognition is when you identify information that you have previously learned after encountering it
again. For example, you primarily rely on recognition for a multiple-choice test to help you choose the
right answer.

•  Relearning is exactly what it sounds like; it is learning information that you have previously learned. Imagine you learned French in high school but post–high school, you never really had the opportunity to practice it. Fast-forward many years later, and you are offered an opportunity to work in your company’s Paris branch. Just for fun, you enroll in a French course online and are surprised by the speed at which you can pick up the language even after many years of not practicing it. This is relearning.

How the Brain Learns

Now that we know how the brain works to encode, process, and retrieve information, how does the brain then piece everything together? First, let’s define what learning is:

Learning is different from behaviors that are reflexes or instinctual (such as how birds build nests and migrate as winter approaches and how infants will naturally suck when their mouth is gently touched); these behaviors involve more primitive centers of the brain, like the spinal cord and the medulla. Learning, on the other hand, involves the higher-order structured parts of the brain like the cerebellum and the cerebral cortex.

In its most basic form, learning occurs when our mind automatically associates two events. That is, when two events occur closely together or in sequence, the brain learns if and how these events are connected through classical conditioning or operant conditioning.

You may have heard about classical conditioning before (also known as Pavlovian conditioning; a ringing bell causes a dog to salivate because it knows it’s getting delicious food). Classical conditioning is when the dog links two events that repeatedly occur together. Classical conditioning is not just limited to how animals learn; we experience this associative process in our daily lives. For example, during a storm, your toddler might see lightning flash in the sky, then hear a loud boom of thunder that closely follows. She quickly learns to pair these two events, as lightning reliably predicts the impending boom of thunder, which causes her fear. So, by classical conditioning, every time she sees lightning, she will react in fear knowing that the booming sound of thunder will closely follow.

In operant conditioning, the association is made between a behavior and its consequence, either through reinforcement or punishment. A reinforcement consequence encourages more of that behavior, whereas a punishment deters a given behavior. For example, imagine you are potty-training a toddler. You verbally encourage and reward her with M&Ms every time she successfully uses the toilet. After repeated experiences, your toddler begins to associate the successful use of the toilet with receiving praise and chocolate treats. On the other hand, if your toddler is punished when exhibiting a certain behavior, she becomes conditioned to avoid such behavior (such as receiving a time-out every time she yells at her younger sibling).

Finally, observational learning (also called vicarious learning) adds a social layer to associative learning. We learn by watching others. What exactly are we watching? We watch how people act and speak and see how others respond to these actions and words, then eventually we imitate those behaviors and speech. Think of how a chimpanzee imitates gestures such as hand clapping or knocking on windows, or how an infant imitates their mother’s speech and language. We tend to follow both positive and negative role models—or people who model both good and bad behaviors.

How the Brain Applies

How does the brain socialize the information it has registered, processed, retained, and learned? It highly depends on how (the degree to which and way in which) the brain is motivated. Motivation is defined as needs or wants that direct our behavior toward a goal. Although these needs and wants can be based on purely biological motives (such as hunger and thirst), motivation can also be driven by our psychological needs (for example, intrinsic versus extrinsic). Intrinsic motivation arises from internal factors that drive us to perform because of the sense of enjoyment and personal satisfaction we gain when we engage in those behaviors. On the other hand, extrinsic motivation arises from external factors that drive us to perform for the sake of gaining something else. It’s a means to an end versus an end in itself (Figure 2-3).

Figure 2-3. Intrinsic Motivation versus Extrinsic Motivation

Think about why you’re reading this book right now. Are you reading because you enjoy learning from it and want to use it to improve your approach to learning? If so, you’re intrinsically motivated to engage here. But, if you’re reading because your supervisor told you to or it’s a necessary assignment, then your motivation is extrinsic. In reality, our motivation is a mixture of both these types, depending on context and situation; but, unsurprisingly, intrinsic motivation is linked to deeper and effective learning.

Whether individuals are motivated by intrinsic or extrinsic reasons, social norms can also be highly effective in reinforcing learning patterns. A social norm is a group’s standard or expectation of what is considered appropriate or acceptable behavior—how a person should think, behave, and speak when in the group’s presence (Deutsch and Gerard 1955; Berkowitz 2004). Social norms are powerful in their ability to shape and motivate behavior as clear roles, rules, and scripts are defined by the group.

Looking Ahead

In the next chapter, we begin a more detailed look into each of the CLICS domains, starting with Capacity. The subsequent five chapters follow a common structure of defining and presenting examples and support for the purpose behind the domain. Additionally, you will learn what the key considerations for the domain include, followed by a view of CLICS in practice in three real-world examples that span each of the five domains.