Chapter 1. How the Brain Learns Best

As you build your knowledge of the strategies that promote optimal brain processing, you'll recognize that neuroscience research may well support strategies you've already found most successful in your experience as an educator. Our goal is to help you increase your understanding of why "best practice" strategies and tools work at the neurological level.

The RAS: The Brain's Attention Filter

All learning begins with sensory information. Our brains are constantly bombarded with information from the body's sensory receptors. Continuous data reports flow from specialized sensory systems (hearing, vision, taste, touch, smell) and from the sensory nerve endings in our muscles, joints, and internal organs. These receptors do not evaluate the data. They just transmit constant status reports. Of the millions of bits of sensory data available each second, only about 1 percent are admitted to the brain, whose various areas are associated with different functions, as shown in Figure 1.1. Once information enters the brain's processing systems, it is relayed by numerous "switching stations." Ultimately, conscious or higher-level processing takes place in the outer covering of the brain, called the cortex.

Figure 1.1. Functional Areas of the Brain

One reason for restricting the enormous amount of sensory input is that the brain is rather stingy with its mental effort because it needs to preserve its limited fuel. Unlike other organs, it has no stored nutrients or oxygen. The average brain weighs only about three pounds, but it is so dense and metabolically active that it requires over 20 percent of all the oxygen and nutrients the body consumes. From a survival standpoint, it makes good sense for the brain to be a couch potato!

Because it is impossible for the brain to consciously sort through all the sensory information that is available every second, it is programmed to prefer selected input. To deal with this selection, the brain has a sensory intake filter, called the reticular activating system (RAS), in the lower part of the posterior brain (see Figure 1.1). The RAS determines what the brain attends to and what information gets in. Its involuntary programming gives priority to sensory information that is most critical for mammals to survive in the unpredictable wild. Any change in the expected pattern can signal a threat of death or, alternatively, a source of nutrients that can help ensure survival. This "hard-wired" criterion of selection for entry is essentially the same for humans as for other mammals; the brain gives priority admission to sensory input about change in the expected pattern—what is new, different, changed, unexpected.

Students are often criticized for not paying attention, but we now know that failure to focus on a teacher's instruction does not mean the student's brain is inattentive. A student's RAS is always paying attention to (letting in) sensory input—but not necessarily the input being taught at that time.

The Amygdala: The Brain's Switching Station

Deep within the brain is the emotionally responsive limbic system, which includes two structures (one on each side of the brain) called the amygdalae, which direct communication between the lower brain and the upper brain (Figure 1.2). The lower brain is the more primitive control center that directs bodily functions that are largely automatic, such as breathing and digestion, as well as reactions that are largely involuntary, such as the fight-or-flight response. The upper brain, known as the prefrontal cortex (see Figure 1.1), is where memory is constructed and neural networks of executive functions guide voluntary behavior with reflective, rather than reactive, choices.

Figure 1.2. The Brain's Limbic System

The amygdala can be thought of as the switching station for traffic flow between these upper and lower structures in the brain. After sensory information is selected to enter through the RAS, the level of activity taking place in the amygdala determines whether the information will travel down to the lower, involuntary, reactive brain or up to the reflective and memory-storing "thinking brain" (the prefrontal cortex).

Information perceived as possibly threatening is directed through the amygdala to the reactive lower brain. Input passing through the amygdala to the prefrontal cortex finds the home of logical thought, judgment, emotional self-management, and other executive functions needed to generate more accurate predictions about new information and direct more considered responses.

When a mammal is in a state of actual or perceived stress, new information does not freely pass through the amygdala's filter to gain access to the prefrontal cortex. Instead, input is diverted to the lower, reactive brain, which has a limited set of behavioral responses that can be summarized as involuntary survival responses to a perceived threat. In fact, it is these primitive mammalian responses that we are likely to observe in students when they are highly stressed by fear, frustration (e.g., as a result of repeated failure to succeed in a task or subject), alienation, anxiety, or sustained boredom (e.g., when they are asked to do lessons or drills on topics they have already mastered or that they see as irrelevant). Here are some examples of specific school-related stressors that can trigger the amygdala to send input to the lower, reactive brain:

• Anxiety related to speaking in class, answering questions, or oral presentations
• Fear of being wrong
• Physical and language differences
• Test-taking anxiety
• Boredom as a result of prior mastery or absence of personal relevance to the material
• Frustration with material students believe exceeds their understanding
• Feeling overwhelmed by the demands of school assignments
• Inability to effectively organize time in response to the demands of academics, extracurricular activities, and out-of-school chores and jobs
• Feelings of isolation or lack of acceptance by peers or teachers

During these states of stress, students are likely to display involuntary lower-brain responses, manifested in acting-out or zoning-out behaviors.

The Brain and Mindset

Because the brain seeks to preserve its limited energy resources, it directs its behaviors based on the probability that the effort expended will result in success. Understanding this survival programming provides new perspective about students' choices and responses. It is now evident that low intelligence, lack of initiative, or laziness may not be the most likely reasons students don't always remain fully attentive, remember everything they are taught, persevere at tasks, or manage their emotions. A more fundamental explanation for nonproductive student behaviors is rooted in the brain's design, which focuses sensory intake, reacts to stress with survival responses, preserves its resources, and minimizes outputs of effort.

The brain's expenditure of voluntary effort is linked to the expectation of positive outcomes. If students fail after repeated efforts to achieve goals and academic challenges, their willingness to put forth effort will decline. These negative self-expectations can grow progressively year after year with repeated failures, further compromising the likelihood of academic success. Psychologist Carol Dweck (2007) has coined the phrase fixed mindset to characterize the conviction of those learners who do not believe that their effort can lead to achievement and is therefore fruitless. This contrasts with a growth mindset, which attributes success to effort, perseverance, and use of strategies.

In survival terms, withholding effort when past experiences predict failure is beneficial for animals in the wild. Consider a fox living in a region where prey is limited and whose den is surrounded by three hills. One of those hills is particularly steep and covered by dense underbrush where the prey hides. To repeatedly chase prey up that hill is to exert effort—in this case, energy—without the likelihood of achieving the goal of an energy-restoring meal. In the interest of survival, the fox's brain ultimately develops a mindset that deters it from chasing prey up that particular hill.

As students' efforts toward achieving a goal repeatedly fail, they might develop the fixed mindset that their intelligence and skills are predetermined, limited, and unchangeable. They become less likely to expend the effort necessary to persevere on challenging learning tasks, and they fall behind academically. Without the needed foundation of knowledge and skills to understand subsequent instruction, the gap widens further and they become even more susceptible to the stress-related blockades.

Seeking Patterns to Make Predictions

The brain's programming promotes survival of the animal and the species. This programming has guided mammalian development and adaptations for survival in the unpredictable and perilous environments in which most mammals live. The human brain continues to follow two prime survival directives: to seek patterns and pleasure. These directives drive the brain's memory, effort, and actions.

Patterning refers to the brain's meaningful categorization and organization of sensory data based on relationships or commonalities. The brain stores new information by linking it to patterns of related information already stored in neural circuits of existing memory. These clusters of related information stored together in memory are what psychologist Jean Piaget (1957) described as cognitive frameworks, or schemas.

It is through this pattern matching with previously constructed and related neural networks that our brains recognize and make meaning of the thousands of bits of sensory input received every second. By linking information newly stored in memory networks with relevant prior knowledge, the brain can sift through the barrage of ongoing input to make sense of the world. Storing information in memory by relationship patterning allows for easier, more efficient retrieval of information, which is essential to interpreting and predicting, and enacting the best response to something new.

All animals must make predictions to survive. For example, based on frequent links between cold temperatures and the behavior of the local rabbits in its hunting territory, a fox's brain might establish a memory pattern. The memory would result from frequent repetition of the pattern of cold temperatures linked to rabbits entering their dens earlier in the evening. Therefore, on a cold evening, the fox might predict that the time to catch its dinner is earlier than usual, perhaps just as the sun goes down.

When presented with novel sensory input, such as change, unfamiliar questions, or choices, our brains rapidly self-scan the related patterns for those that match the new information. Our brains activate these stored memories to relate to the new input and to make predictions and choose actions guided by those memory patterns.

Prediction is successful whenever the brain activates enough information from a patterned memory category to interpret the pattern of the new input. For example, if you see the number sequence 2, 4, 6, 8 …, you predict the next number will be 10 because you recognize the pattern of counting by twos. Depending on the result of the prediction, the existing patterns relied upon to make the prediction are extended, fortified, or revised.

Through observations, experiences, and feedback, the brain increasingly learns about the world and can make progressively more accurate predictions about what will come next and how to respond to new information, problems, or choices. This ability for prediction, guided by pattern recognition, is a foundation for successful literacy, numeracy, test taking, appropriate social-emotional behavior, and understanding.

Successful prediction is one of the brain's best problem-solving strategies. To ensure that we will repeat the actions arising from accurate predictions, the experience of making accurate predictions stimulates a pleasure response mediated through the release of the neurochemical dopamine.

Dopamine: The Brain's Pleasure Drug

If you know pleasure, you know dopamine. Seeking and experiencing pleasure are innate survival features of the brain. When dopamine is released throughout the brain, it promotes feelings of pleasure, a deep satisfaction, and a drive to continue or repeat the actions that triggered the pleasurable response.

You might already be familiar with dopamine in its other function as a neurotransmitter. Neurotransmission involves axons and dendrites, two kinds of extensions of neurons that act as senders and receivers, respectively, of neural electrical signals. Dopamine carries these signals from the axons of one neuron, across a liquid-filled gap called a synapse, to the dendrites of another neuron.

The action of dopamine that is relevant to the pleasure or reward response derives from triggers that stimulate its release from a holding center called the nucleus accumbens, found near the amygdala (see Figure 1.2). This increase in circulating dopamine is seen in all mammals and activates those feelings you experience as intrinsic pleasure and satisfaction.

Making correct predictions is one of the strongest dopamine elevators. The dopamine-reward response to making accurate predictions promotes survival in mammals because the intrinsic pleasure that comes from accurate predictions drives the brain to remember and use memory circuits that have guided previously successful predictions. Experiencing accurate predictions and the resulting satisfaction of goal achievement leads the brain to remember the related choices, behaviors, actions, decisions, and responses and to seek more opportunities to repeat them. Concomitant effects include enhanced attentive focus, motivation, curiosity, memory, persistence, and perseverance.

There are intrinsic impediments to optimally processing learning through the brain. As you've read, the RAS and the amygdala are filters programmed to determine what information gets through and where it is directed.

To further optimize students' success in school, you can engage the dopamine-reward response to motivate the brain to put forth the mental effort needed for new learning. This is true even for things that are not immediately recognized as relevant or pleasurable. Academic effort can be stimulated by tapping into the brain's programming to focus attention and apply effort when pleasure is the anticipated expectation.

By showing students that they have the power to improve and by providing opportunities for them to see progress toward goals, they'll come to understand that their own effort may control the outcome. In subsequent chapters we'll suggest strategies for enhancing student engagement; reducing stress; boosting memory, motivation, and perseverance; and promoting growth (versus fixed) mindsets designed with the dopamine-reward response in mind.

The Brain's Neuroplasticity

A long-held misconception asserted that brain growth stops with birth, only to be followed by a lifetime of brain-cell death. Now we know that although most of the neurons where information is stored are present at birth, there is lifelong growth and expansion of the abundant connections through which neurons communicate. Neuroplasticity refers to the brain's continuous capacity to generate new neural networks in response to stimuli.

The expression "neurons that fire together, wire together" refers to the process by which the brain constructs neural networks. The increased strength of the connections between neurons that sustain memory derives from the repeated activations of those networks. Every recalled memory or memory-directed pattern activates electrical signals (firing) from neuron to neuron to stimulate a constructive process that strengthens the memory circuit. This is an aspect of neuroplasticity—the enhancement or modification of memory networks through repeated activation. (See Figure 1.3.)

Figure 1.3. The Neuroplastic Response

The neuroplastic response includes the building of more neuronal connections as well as the thickening of the layers of insulation, called myelin, around existing connections. A greater number of connections among neurons in a circuit means faster and more durable communication efficiency, just as adding lanes to a highway improves traffic flow. The addition of layers of myelin around the axons increases the speed of information travel and protects the circuit from being easily eroded through disuse.

Through the neuroplastic response, the brain strengthens the circuits used most frequently, enhancing their speed. Strengthening and speeding neuron-to-neuron communication provides longer-term durability and access—that is, memories are accessed and retrieved more efficiently and they last longer. For example, when children are learning to tie their shoes, they repeatedly practice the steps. In so doing, the associated neurons repeatedly activate in sequence, strengthening the circuit of connected neurons each time. Practice results in the establishment of a "shoe-tying" network. The abundance of dendrites, enhanced by thick layers of insulating myelin around the axons, allows that behavior to become increasingly efficient and, eventually, automatic. Through neuroplasticity, the brain is molded by experience to reshape and reorganize itself so that we awake with a "new" brain each morning!

Another side of neuroplasticity, beyond building and strengthening myelinated connections, is known colloquially as the "use it or lose it" phenomenon. Without the stimulation of the electrical activity generated by use of a network, there is a gradual loss of connecting dendrites and thinning of the myelin, eventually leading to their dissolution, or pruning. Teachers are familiar with this mental pruning in a form that is often referred to as the "summer slump." Without regular use, students are likely to "forget" what had been previously taught and will require considerable review and even reteaching to reacquire their previous learning. Another example of pruning is experienced when we don't remember the foreign language we studied in high school if we don't use it regularly.

Although it may seem unproductive for the brain to prune things that have been learned, recall the brain's high metabolic demands. Without this pruning, the brain's limited resources would be spread too thin to support its efficient operation.

The major roadways of neuron-to-neuron connections are in the cerebral cortex, and there are not many branching connections between them. The pattern is comparable to a view of the major cross-country highways from five miles above Earth, without the side streets. The filling in of the brain's cognitive map takes place over time as students actively engage in mental manipulations of information. Key learning activities planned through the curriculum planning framework Understanding by Design (described in the next chapter), such as exploring essential questions and engaging in authentic tasks, build and expand the cognitive networks needed for conceptual understanding and transfer.

How the Brain Remembers

New memory construction takes place after new sensory information leaves the amygdala and enters a brain structure called the hippocampus (see Figure 1.2), whose name derives from the Greek word for seahorse, because of its resemblance to that creature. This structure is where new sensory intake connects to a bit of pre-existing memory and consolidates from immediate into short-term memory.

None of our memories are held in single neurons. It has been a momentous evolutionary extension that has enabled communication among hundreds and thousands of neurons, each holding tiny memory pieces, to recall even the simplest concept or perform the most basic tasks, such as clapping one's hands.

Memory is stored in separate hemispheres of the brain, based on the sensory modality (e.g., vision or hearing) in which it is experienced. These multiple storage areas are linked by dendrites and axons (see Figure 1.3). The brain develops stronger and extended memory circuits when new learning is connected to multiple circuits by recognizing the common threads among existing circuits or experiencing the learning through multiple sensory modalities, such as vision, hearing, and movement.

Here's an example: If students learn about the positive and negative charges of magnets and relate the information to other memory circuits that include the concepts of positive and negative (evident in things such as emotions, electricity, numbers, or economic influences), they will store and can retrieve what they learned about magnets through multiple pathways. If positive and negative magnetic forces are further related to a story in which opposites attract, thinking about that story can retrieve an even more detailed memory of facts related to magnets.

Storage of memory in neural networks based on patterns (relationships) has evolved into a very effective system in which the brain accesses prior knowledge to enable it to make connections to new information and situations. For example, memory based on patterns and relationships guides children to avoid objects designated as hot. It takes only one or two negative experiences of feeling the discomfort of touching a hot stove or campfire, along with hearing the word hot or seeing flames, for their brains to construct the relational memory cementing the notion that the word hot stands for things that should not be touched. In short, they learn.

Have you ever read aloud a familiar story or poem and left out a word or phrase that is often repeated or rhymed? If so, it is likely that children have jumped in to complete that sentence. Their action reflects the brain's use of patterning. In mathematics, pattern recognition is what allows students to predict the next number in a sequence or to recognize which procedure to apply when word problems use phrases such as all together, remaining, or left over.

Activating students' existing relevant prior knowledge takes place when they understand a framework into which the new learning belongs. This awareness guides the brain to recognize connections with existing memory networks in the hippocampus. Knowing how the brain makes connections can help teachers maximize learning in their classrooms, especially because students themselves do not always make connections between what they already know and new information being taught.

To ensure that there is related existing memory in the hippocampus to link with the new input, it is essential to help students become aware of their prior knowledge. When new information is presented with some foundational pattern recognized by the brain, memory networks incorporate it more efficiently. For example, when students are learning about triangles, you can start by reminding them about other shapes with which they are already familiar, such as squares and circles. Illustrating how a square can be cut or folded to create a triangle and how two equal triangles can be put together to create a square will promote the linking of the new (triangle) to the known (square). With a successful pattern match, the new information encodes into a short-term memory circuit. Strategies to ensure activation of prior knowledge include the use of pre-assessments, advance organizers, essential questions, concept maps, graphic organizers, and "hook" activities. (These and related strategies will be described in greater detail in later chapters.) Such strategies make it more likely that students will link the new information to their prior knowledge to both consolidate and expand memory circuits.

Long-Term and Concept Memory Construction

Not all activations of memory circuits stimulate the neuroplastic response equally. Less neuroplastic growth occurs if circuits are activated only by multiple repetitions of the same information in the same format—for example, writing a word 10 times or solving 30 equations using the same formula. Rote memorization produces isolated and somewhat feeble circuits unlinked to other networks. Such shallow memories only allow learners to "give back" what was taught, mirroring the way it was taught. This limits their ability to transfer—that is, to apply their learning to new situations beyond the original context in which it was learned.

Once encoded, short-term memory requires mental manipulation of the new information—it must be thought about or applied—to form richer and deeper connections and ensure its place in long-term memory storage. Without this mental manipulation, the short-term memory fades in less than a minute. Indeed, practice really does make permanent, as long as the practice involves active mental manipulation, construction of new ideas, and opportunities to apply the newly acquired knowledge and skills in different ways than they were originally learned—all tenets of the UbD framework.

The Video Game Model

What can we do to motivate sustained effort from a stingy brain and improve the mindset of students, especially those who have experienced failure and the erosion of their confidence in school? To answer this question, consider an activity that is popular among many young people and that leads them, despite repeated failures, to persevere—video games!

The video game experience models effective learning by the brain and thus offers a guide for effective teaching strategies. We have identified four elements of this model that educators can replicate to enhance the learning of their students: (1) establishing a desirable goal, (2) offering an achievable challenge, (3) providing constant assessment with specific feedback, and (4) acknowledging progress and achievement en route to a final goal.

Desirable Goals

Whether it is saving Earth from a devastating asteroid collision, slaying a dragon, or finding a lost treasure, a video game player knows the ultimate goal of the game. Players participate in the game because they enjoy the challenge or because friends or other people who are playing think it's cool. They buy into the goal of the game, even though it is merely fantasy.

Similarly, in the classroom, we need to make clear at the beginning of a new unit what the goals are and what it will take to achieve them. The brain's self-preservation programming means that it is most likely to apply its resources when it recognizes that effort will help to attain a desired goal. Accordingly, students will be more likely to engage and make an effort when they have clarity about the learning goal, evidence of its achievement, and an understanding of how a particular goal relates to them. In other words, goal buy-in is a critical component for all learning in order to motivate the brain to focus its attention, apply its energy resources, and persist when challenges arise. Like those that motivate avid video game players, goals need to be clear and relevant for students to have goal buy-in.

Achievable Challenges

Imagine the following scenarios:

• You are dropped off at the top of a ski resort's steepest run when you are only a beginner.
• You must spend your day on the bunny hill when you are an expert skier.
• You play a game of darts with the target 2 feet away.
• You play a game of darts with the target 20 feet away.
• You are a 3rd grade student trying to complete a crossword puzzle designed for adults.
• You are an adult trying to do a crossword puzzle designed for young children.

In each of these extremes, you would likely feel either frustrated or bored, depending on your level of mastery in relation to the challenge. Reflecting on those feelings helps us understand the stress students feel if they do not have the foundational knowledge to understand new topics or the skills required by a challenging task. Alternatively, consider how bored you feel when you are asked to spend time on a topic or skill that you have already mastered.

Engaging video games are designed around levels of difficulty (such as 1 to 10) and require progression through appropriate levels of challenge based on player mastery. When playing a game, players are usually working on a task at their appropriate challenge level and can progress only after achieving it. This same model of allowing game players to progress according to their individualized levels of achievable challenge is a key to reducing stress and sustaining motivated effort in the classroom.

Achievable challenge means that learning goals are clear and the learner embraces the expectation that success or mastery is within reach. Applying the video game model to classroom learning means planning goals that students accept as being within their range of potential. The famed Russian cognitive psychologist Lev Vygotsky (1978) coined the phrase zone of proximal development to characterize the importance of finding the balance point between learning tasks that are not at all challenging and those that are out of reach. When learners have opportunities to work toward desirable goals at their individualized levels of achievable challenge, their brains invest more effort in the task, remain more responsive to corrective feedback, and engage with the focus and perseverance akin to that of video gamers. As Goldilocks would say, the challenge needs to be "not too hard, not too easy, but just right!"

Constant Assessment with Specific Feedback

A central feature of video games is their feedback system. Players receive constant feedback as they play; they can then use that feedback to immediately make adjustments, alter their actions, and find out if these are successful. Gamers certainly make errors (incorrect predictions) on the way to mastery, but the most compelling games give feedback and unlimited chances to try again without pressure or the stress of boredom or hopeless frustration. When their choice or prediction is wrong, they know they will always have another chance. Solo players aren't receiving the negative message that they are alone in their confusion or experiencing the boredom of waiting for a class full of others playing the same game to catch up to their level before proceeding. Without those stressors, they remain comfortable trying other strategies or building skills needed for the designated task. Through experience, they find that despite frequent errors, if they act on feedback and persist, they will eventually improve and make incremental progress toward their goals. This cycle reinforces a growth mindset.

When the brain receives the feedback on progress that has been made, the associated memory, skill, or concept networks are reinforced. You can emulate the video game model in the classroom by providing your students with regular and timely feedback from formative assessments. The benefits of this practice have been conclusively documented (Black & Wiliam, 1998).

Acknowledgment of Progress and Achievement

It is interesting to note that video game players fail to achieve their goal as much as 80 percent of the time while playing. Why, then, do they persevere? Note that video games do not require mastery of all tasks at all levels; instead they highlight incremental progress. A player's advancement is noted via points, tokens, or graphics. Neurologically, each time a player's progress is acknowledged in the game, a small dopamine release occurs in the player's brain.

The motivation to persevere and pursue greater challenge at the next level stems from the brain seeking another surge of dopamine, which is the fuel of intrinsic reinforcement. This explains why players seek greater challenge at the next level. To keep the pleasure of intrinsic reinforcement going, the brain needs a higher level of challenge, because remaining at a level already mastered does not activate the necessary expectation of dopamine and its pleasure.

Much of what makes video games so compelling is the way they continuously give players evidence of the efficacy of their practice and continued efforts—essential ingredients for development of a growth mindset. The academic learning model can follow suit. When learners have opportunities to engage in learning tasks at their individualized, achievable levels of challenge and believe that their effort can achieve the goal, they are more likely to persist. When incremental progress is valued, they are more likely to recognize that specific feedback will help them improve toward goal achievement, rather than seeing the feedback as criticism or evidence of failure.

The video game model gets at the essence of building growth mindsets fueled by the belief that performance and achievement can improve by using feedback and exerting effort. Students build the self-confidence and experience the intrinsic satisfaction needed to persevere and confront successive challenges.

In subsequent chapters, we will explore the use of the UbD framework for planning curriculum, assessment, and instruction that support how the brain learns best.

Chapter Understandings

• The past two decades of brain research have provided insights that have profoundly extended our understanding of how to maximize the brain's development of the neural networks known as executive functions, the foundation for building skills. This research can be applied to optimize learning success.
• Because it is impossible for the brain to consciously sort through all the sensory information available every second, the brain has an attention filter that prioritizes what information gets in.
• The amygdalae are switching stations that direct communication between the lower brain and the upper brain.
• The brain seeks patterns. Pattern recognition enables predictions. Pattern linking builds short-term memory, and activation of prior knowledge promotes this memory linkage.
• Durable long-term memory and enduring understanding are promoted by active mental manipulations, construction of new ideas, and opportunities to apply newly acquired knowledge and skills in different ways than they were originally learned.
• Dopamine is a neurotransmitter that is released when a learner makes a successful prediction, reaches a goal, or makes progress toward a goal. When dopamine is released in the brain, it promotes feelings of pleasure, a deep satisfaction, and a drive to continue or repeat the actions that triggered the pleasurable response.
• Learners with a fixed mindset do not believe that their effort can lead to achievement and are unlikely to put forth effort when challenged to learn something new. Learners with a growth mindset attribute success to effort, perseverance, and strategy use.
• The video game model contains replicable elements—goal buy-in, achievable challenge, frequent assessment with specific feedback, and acknowledgment of progress—that can be applied in the classroom to promote engaged attention, sustained effort, and perseverance.
• Every class, assignment, and experience reshapes each student's brain through neuroplasticity. Understanding how the brain processes information and changes in response to experiences provides keys to best strategies and interventions for guiding learners to sound understanding and durable, transferrable, long-term memory.

Questions and Answers

Does using the video game model in the classroom mean that students should be playing video games to learn content?

Although there may be some value in having learning games matched to students' skill levels (e.g., for developing basic math skills or learning vocabulary in a new language), that is not our point. Instead, we propose that particular components of video game design can be emulated in the classroom (without actual video games). When these components are incorporated into an instruction and assessment system, they compel students to learn and sustain effort through challenge and setbacks, and they promote motivated effort and learning.

Is dopamine always a good thing? Can students get too much dopamine from learning experiences designed to promote the dopamine-reward response?

In some addictions and types of mental illness such as schizophrenia, an excess release of dopamine has a negative impact. However, in the amounts released by the dopamine boosters we suggest to promote learning and sustain effort, dopamine will not be elevated to the levels where the effects are negative.