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Retrieval practice, elaboration, and concept mapping help students make richer, more meaningful connections between ideas.

With uncertainty hovering over fall plans, teaching and learning continue to look different from district to district than ever before. While administrators juggle with tough choices, almost every teacher is back to reading, reflecting, and restructuring their lesson plans to keep their learners engaged and learning-and as equitable as possible given the constraints. In this post, I share three strategies, informed by the learning sciences, that teachers can use online or face-to-face to deepen student learning: retrieval practice, elaboration, and concept mapping.

Strategy 1: Retrieval Practice

1. Create a version of your study guide that has only the questions. Ask students to practice answering them without additional support. Once they're done, they can share their answers; they can also look up the correct answers, either alone or in groups.

2. Use a brain dump. Ask students to write down everything they remember relevant to your question (or the topic) on a piece of paper. You can stop here, or have students compare their work to find gaps, similarities, and differences.

Retrieval practice, or the practice of remembering, is a robust learning strategy as summarized in a meta-analysis of more than 200 studies published by my colleagues and me. Retrieval practice is when you push yourself to write, tell, or draw what you've already learned, and it can be especially helpful for concepts you may not remember as clearly-the process of remembering will help strengthen your memory. Plus, you have the added benefit of identifying what you know and don't know. Some teachers use this strategy in their classrooms already-maybe you do too. If not, here are two ways to start:

Strategy 2: Elaboration

1. Ask learners to compare two examples of the same concept or share specific examples. For example, when covering concepts of reusable energy, ask questions such as, "What are three similarities and differences between wind and solar energy?" Use these questions in a discussion board, in a short answer prompt, or to jazz up the thinking quotient of your worksheet.

2. Learners can explain the topic out loud to themselves, friends, a sibling, or a parent. You can also incorporate it into group activities-like a jigsaw-or have students role-play as the teacher and explain the topic to the class. For virtual classrooms, Flipgrid is an excellent tool: Students can record themselves reading about a topic and then answering questions like "How do I apply this topic in my life?" For younger students who may need more scaffolding, you can ask a more targeted prompt, like "How do I consume energy every day?"

Elaboration -also known as elaborative interrogation-refers to expanding a concept to be more detailed, allowing our brain to connect multiple concepts to one central idea. The more connections we make, the more likely we are to remember relevant information. Think of the icebreaker "Tell me one fun thing about yourself." Not only does it help you remember something interesting about a person-they like rocky road ice cream, for example-but you may also think of that person every time you see the flavor. In a learning context, elaboration can often be done by asking questions that require engaging deeply with content. So instead of asking learners to simply memorize information, they can compare and contrast right and wrong answers. This approach is so simple, you likely use it in your class already. Here are two ways to start:

Putting It All Together: Concept Mapping

Concept mapping combines retrieval practice and elaboration through the process of drawing one's understanding of relationships between concepts. A map usually contains at least two concepts (nouns), a relationship (verb or concise description), and a directional arrow connecting the concepts. When reading the map, we create mini sentences (excusing poor grammar, of course). For example, a student learning about bacteria can create a concept map that includes any relevant ideas-such as specific types of bacteria (" Helicobacter pylori") or ways to describe them ("single-celled organism"). This layout allows learners to identify what they know and where the gaps are, in addition to the relationships between concepts. A review of more than 140 experiments suggests that this strategy is superior to rote memorization because it encourages students to make richer, more meaningful connections within a topic.

1. Focusing stage: Learners are given or are asked to identify a guiding question-such as "How is ice formed?"-relevant to the current topic.

2. Brainstorming stage (making use of retrieval practice): Learners do a brain dump in response to the guiding question, writing down any concepts and ideas that come to mind.

3. Organizing stage (elaboration): Learners review their brain dump and pick out concepts that are central to the guiding question, followed by asking themselves, "How are these concepts connected?"

4. Layout stage: Learners build their map connecting the concepts with directional arrows showcasing their understanding. At the top of the map, they can start by writing down the main ideas of the topic, and then start connecting words together.

5. Linking stage: They complete the first draft of the concept map by labeling the arrows with these descriptions. For example, if they start with the words "ice" and "cold," they can connect the two with "is." This encourages learners to think about the relationships between different ideas.

6. Revising stage: There is no perfect concept map. Give learners the opportunity to redo and update based on their understanding.

There are six stages in concept mapping, starting with the instructor providing learners with a specific guiding question.

In the past, I've done concept mapping with kindergarteners, replacing words with pictures, and it's so much fun to have them form sentences using images. The goal is to help them retrieve, elaborate, and share their understanding. (I also recommend looking into Dual Coding for Teachers and other resources by Oliver Caviglioli.)

A final tip: You don't have to do all of these strategies for every topic. Pick and choose, mix and match. Start small and build up. These strategies work because they engage the learner's attention and encourage them to think more deeply about the content.

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3 Brain-Based Strategies That Encourage Deeper Thinking

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Retrieval practice, elaboration, and concept mapping help students make richer, more meaningful connections between ideas. With uncertainty hovering over fall plans, teaching and learning continue to look different from district to district than ever before.

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Read “How People Learn II: Learners, Contexts, and Cultures” at NAP.edu

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Read chapter 6 Motivation to Learn: There are many reasons to be curious about the way people learn, and the past several decades have seen an explosion o…

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Putting Neuroscience in the Classroom: How the Brain Changes As We Learn

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The more we know about how the developing brain changes as we learn, the better we can support young learners.

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Reviews recent neurophysiological studies of learning under 2 major research categories: (a) correlational measures of neural processes during the course of learning in relatively intact animals, and (b) simplified model biological systems to study mechanisms underlying animal learning. Emphasis is placed on electrophysiological studies. Discussion of correlational measures includes neural activity in the brainstem and diencephalon during classical and instrumental conditioning. Biological studies include habituation of sympathetic ganglia and classical spinal conditioning. Recent methods for investigating the relationship between synaptic action and memory are also discussed. (249 ref.) (PsycInfo Database Record (c) 2022 APA, all rights reserved)

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Abstract

The past few years have been marked by a large number of discoveries about the learning brain. Those insights have the potential to support teachers in designing even better classroom environments to help you learn better. While understanding the brain can be helpful for teachers, this knowledge can also be beneficial for you as a student. For instance, it can encourage you to believe in your capacity to improve your own skills. Such beliefs make it more likely for you to make an effort and to make better use of supportive learning strategies []. In this article, we briefly present some core principles of the learning brain and suggest learning strategies inspired by neuroscience for you to try at school or at home.

What Happens in My Brain When I Am Learning?

Your brain is primarily composed of about 85 billion neurons, which is more than the number of stars you can see with the naked eye in the night sky. A neuron is a cell which acts as a messenger, sending information in the form of nerve impulses (like electrical signals) to other neurons (see Figure 1). For example, when you are writing, some neurons in your brain send the "move fingers" message to other neurons and this message then travels through the nerves (like cables) all the way to your fingers. The electrical signals that are communicated from one neuron to another are therefore what allows you to do everything you do: write, think, see, jump, talk, compute, and so on. Each neuron can be connected with up to 10,000 other neurons, leading to a large number of connections in your brain [], which looks like a very dense spider web (see Figure 2).

Figure 1 - Figure illustrating two neurons that are connected.

Figure 2 - Figure illustrating the very large number of connections between neurons.

When you are learning, important changes take place in your brain, including the creation of new connections between your neurons. This phenomenon is called . The more you practice, the stronger these connections become. As your connections strengthen, the messages (nerve impulses) are transmitted increasingly faster, making them more efficient []. That is how you become better at anything you learn whether it is playing football, reading, drawing, etc. We can compare the connections between your neurons to trails in a forest (see Figure 3). Walking through a forest without a trail is difficult, because you have to compact and push the vegetation and branches out of the way to carve your way through. But the more you use the same trail, the easier and more practicable it becomes. Conversely, when you stop using the trail, the vegetation grows back, and the trail slowly disappears. This is very similar to what happens in your brain-when you stop practicing something, the connections between your neurons weaken and can ultimately be dismantled or pruned. That is why it may seem so difficult to start reading again when school starts if you have not read all summer. However, it is possible for some neural networks to become so strong that the trails or connections never completely disappear.

Figure 3 - Figure illustrating the analogy of the trail in the forest.

The fact that learning rewires your neurons shows how dynamic (plastic) your brain is-that the brain changes and does not remain fixed. Practicing or rehearsing repeatedly activates your neurons and makes you learn. These changes happen as early as when a baby is in their mother's womb and continues throughout a person's life. So, the question is, how can you help your neurons to create and strengthen their connections? Here, we present two strategies that appear to be more compatible with how your brain works and could help you learn better.

Which Learning Strategies Are More Compatible With Your Brain?

Because the connections between your neurons need to be activated multiple times to become stronger and more efficient, a first and crucial strategy is to repeatedly activate them. This means that to learn arithmetic tables for instance, you have to practice it repeatedly, to establish the "trail" between your neurons. As a baby, you were not able to speak and walk within 1 day: you practiced a lot. However, it is important to note that only reading or glancing at your arithmetic tables will not be that helpful in connecting your neurons. You might also find it quite disengaging and boring. To create the connections between your neurons, you need to retrieve the arithmetic tables from your memory. In other words, you have to try recall the answer yourself to activate your connections. We are not saying that this is easy to do! However, scientists think that this "struggle" improves learning because the challenge is an indication that you are building new connections. Remember, learning something new is like hiking in a bush with no designated trail, you will probably walk slowly at first, but if you keep hiking, trails will start forming and eventually you will be walking on well-beaten tracks. Besides, when you do try to recall what you have learned and make a mistake, it can help you identify gaps in your learning and give you an indication of which trail still needs to be worked on.

Scientists have also noted that performing tests or exams can help you remember information better than studying alone []. For example, if you study your arithmetic tables interspersed with test periods, you will probably perform better on your final test than if you had only studied. Why? The tests require that you retrieve the information from the neurons in which the information is stored, thus activating your connections and contributing to their strengthening. The point is thus to practice retrieval in an engaging way. There are different strategies that you could try at home, for example answering practice questions or using flashcards. These should improve learning more than re-reading or listening to lectures (as long as you do not flip the flashcard over before recalling the answer!). Other strategies include preparing questions to ask to a classmate or a parent as well as redoing tests or exercises. Use your imagination! What you need to remember is that first, for your neurons to strengthen their connections, you need to retrieve the information and avoid just reading or listening to the answer. Second, you should plan a way to get feedback to know whether you got something correct or incorrect. Do not be discouraged if you face challenges, this is a natural step of the learning process taking place in your brain!

Now that you know that neurons need to be activated repeatedly for learning to occur (and that it means retrieving information), you probably wonder how often you should practice. Scientists who study the learning brain observed that breaks and sleep between learning periods enhance learning and minimize forgetting []. It therefore seems better to retrieve often within spaced practice sessions, as opposed to a massed practice (practicing a task continuously without rest). For instance, instead of studying or doing homework for 3 h, after which you would probably feel exhausted anyway, you could separate this learning period into three 1-h periods or even into six half-an-hour periods. In short, when spacing your retrieval practice, you allow your brain to make the connections that you strengthened during your practice sessions more efficient. When you take a quick break from practicing, let us say a 20 min recess, you allow for the maintenance or replacement of the receptors on the surface of the neurons. The receptors are like electric outlets that receive the nerve impulse (electrical signals) from other neurons. Taking a break helps them work better: your neurons can thus transmit their nerve impulses more easily to other neurons. Finally, when you get a night of sleep between practice sessions, you actually benefit from a free retrieval practice session because while you sleep, your brain reactivates the connections between the neurons that you activated during the day. You could also get similar benefits from a nap. Next time you find yourself sleepy in class, you could tell your teacher that you are in fact trying to do retrieval practice! In brief, when spacing out learning, and especially retrieval practice, your brain is more activated than when you mass learn in one long session.

At this point, you are probably asking yourself how to space out learning in your day-to-day life. The good news is that there are a number of ways to do it and it can be easily adapted to different skills, such as solving mathematical problems or memorizing definitions. The most obvious change you can make to your study schedule is to break up sessions into smaller sessions. You could also ask your teacher to set daily or weekly review quizzes and other assignments. Finally, spacing can be done by doing interleaved practice. This consists of a set of problems arranged so that consecutive problems cannot be solved by the same strategy. For example, you could mix your math problems so that geometry questions, algebra, or inequality problems are randomly sequenced. The added benefit of interleaving is that you engage in different activities in-between two sessions, making good use of your time. In brief, one thing to keep in mind is that information that was previously learned will require less effort to re-learn because the spacing gives your brain time to consolidate-meaning your brain produces the building blocks required for the connections between your neurons.

Conclusion

Your brain is where learning occurs and you therefore need to keep your neurons active to optimize the use of class or study time. The two learning strategies proposed in this article have the potential to help you learn better by creating optimal conditions to strengthen and consolidate the connections between your neurons. You now know that you can get better by repeatedly using the "trails" in your brain and by spacing out your practice. This greater understanding of how your brain learns and the use of supportive learning strategies can now allow you to help your brain learn better!

Glossary

Neuroplasticity: ↑ The ability of your brain to change, that is to create, strenghten, weaken or dismantle connections between your neurons.

Repeatedly Activating Your Neurons: ↑ Practicing a lot, trying to retrieve information from your memory, for example by explaining a concept to a friend or answering quiz questions.

Spacing the Activation of Neurons: ↑ Practicing more often but for a shorter period. For example, instead of studying for 2 h in a row, studying 4 periods of 30 min over a few days allows your brain to take breaks and sleep which helps you remember better in the long run.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to wholeheartedly thank those who assisted in the translation of the articles in this Collection to make them more accessible to kids outside English-speaking countries, and for the Jacobs Foundation for providing the funds necessary to translate the articles. For this article, we would especially like to thank Nienke van Atteveldt and Sabine Peters for the Dutch translation.

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Understanding Your Brain to Help You Learn Better

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The past few years have been marked by a large number of discoveries about the learning brain. Those insights have the potential to support teachers in designing even better classroom environments to help you learn better. While understanding the brain can be helpful for teachers, this knowledge can also be beneficial for you as a student.

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In the past two decades, neuroscience research has proven the traditional classroom isn't as stimulating for student learning as it could be. Enter brain-based learning, an innovative approach to education based on scientific research. It involves a teaching method that limits lectures and encourages exercise breaks, team learning, and peer teaching. Brain-based learning centers around neuroplasticity, or the remapping of the brain's connections when learning new concepts.

Brain-Based Learning: Definition, History, and Principles

Brain-based learning uses neuroscience to create an informed curriculum and lesson design. The goal? Speedy and efficient learning. The research that informs this method centers around the brain's ability to change, remap, and reorganize itself while someone is learning new information, according to Education Reform. This ability is influenced by things like exercise, diet, and stress level. A person's emotional state also impacts their learning ability.

When information is presented in effective ways, the brain is able to function better, its resilience is increased, and its overall working intelligence is improved. Research has also shown that the brain physically changes while learning. Thus, the more new skills are practiced, the easier learning becomes.

Using this research as a springboard, teachers implement brain-based learning principles in the classroom. They specifically focus on reducing stress, effectively delivering material, increasing students' movement, and building in opportunities to practice. While the principles remain the same no matter the age of a student, people do begin to learn differently as they mature. So, the delivery methods of these principles adapt accordingly.

History of Brain-Based Learning

Neurological research gained momentum in the 1990s. Up until this point little was known about neural pathways, and the left and right brain theory, introduced in the 1960s, was decades old. From the 1990s up to the present day, scientists have discovered more about the brain than in all other centuries combined, according to the Global Digital Citizen Foundation.

In 1994, Geoffrey Caine and Renate Nummela Caine's research concluded that students had increased retention and understanding of topics when in a brain-based teaching environment. Since then, brain-based learning has become a more common practice in schools.

Principles

The core principles of brain-based learning follow. Each principle lays out a formula for better retention and learning among students.

Health and Exercise

The more active and engaged students are physically, the better their learning outcomes. This requires more than a midday recess or a walk between classes. Allowing students to take walking breaks during lessons and throughout the day, for example, revitalizes students, increases their attention span, and better prepares them to retain information.

Positive Emotions

The happier students are, the more they are willing to learn and think effectively. Affirmations from the teacher are one way to raise student self-esteem.

Group Work

Working in teams with classmates allows students to learn from one another. This helps them retain information they may not have accepted or understood from the teacher.

Peer Teaching

When students teach materials to their peers, it helps them retain that same information. This can be done in small groups or through presentations.

Practice

Learning through repetition and trial and error is more effective than simple memorization. Students will gain a better understanding of the subject through practice, rather than just memorizing the details.

Limited Lectures

Only 5 to 10 percent of information is retained during a lecture, according to Classcraft. Making lessons largely discussion-based promotes student learning.

Meaningful Information

Students are more likely to remember information if they are engaged with the lesson. By applying the material to their lives, students will find it meaningful. For example, a lesson on economics could be related to smartphone ownership.

Written and Verbal Information

Having students both write and verbalize information will help move it from their short-term memory to their long-term memory.

Stimulation

Catching students' attention through humor, movement, or games stimulates their brains' emotional center. In turn, this increases students' engagement and processing of information.

Less Stress

Stress chemically changes the brain. In a calm classroom environment, students have the opportunity to perform at higher levels.

Benefits of Brain-Based Learning

The benefits of brain-based learning follow the principles. These include:

Health. This approach promotes health and exercise, boosting the overall fitness and wellness of students.

Better psyches. Positive affirmations and limited criticism helps students feel good about themselves and view themselves in a positive manner.

Cooperation. The more group work students do, the more they learn how to cooperate and compromise.

Improved memory. Overall, brain-based learning helps students build their memories and retention. The peer-teaching principle, in particular, leads to increased memorization and understanding of information.

Teachers experience another major benefit from this approach: more than one strategy works. This teaching and learning style isn't a one-size-fits-all experience. Teachers can apply multiple strategies following the principles, making it likely they will experience results with their students.

Classroom Application

As it has multiple strategies, brain-based learning also has many classroom applications. For example, both verbal and written information can be included in lessons, which boosts retention. Hands-on activities can also be created, such as providing students with physical clocks to learn time.

Another application is modeling assignments on real-world challenges students experience. For example, when teaching about percentages, a shopping activity can be set up. Each item could be on sale and the student challenged to calculate the sale price before they can be rewarded with it. This activity can also be done in groups where they have a budget to follow. This helps them learn problem solving and critical thinking all in one activity, moving outside the lecture and into practical applications of the lesson.

It's important to note that not all strategies work for all students. Regularly trying new approaches and working through trial and error is the best way to begin implementing brain-based learning in the classroom.

Grow as a Teacher at American University

Brain-based learning is just one innovative approach teachers use today. To develop more techniques and grow as a teacher, American University's Online Master of Arts in Teaching program prepares students to be progressive minded and prepared. Through courses like Effective Teaching for Diverse Students, American University students cultivate skills to design cutting-edge curriculums. Grow your knowledge and passion for teaching at American University.

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What Is Brain-Based Learning? | American University

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Brain-based learning applies neuroscience to interaction, group work, exercise, and meaningful information. Discover how to apply this method in your classroom.

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Motivation, as the name suggests, is what 'moves' us. It is the reason we do anything at all. For teachers, a lack of motivation has long been one of the most frustrating obstacles to student learning. While the concept of motivation may intuitively seem fairly simple, a rich research literature has developed as researchers have defined this concept in a number of ways. Social scientists and psychologists have approached the problem of motivation from a variety of different angles, and education researchers have adapted many of these ideas into the school context. While there is a great deal of overlap between motivation theories, researchers differ in their identification of the underlying belief systems leading to motivational variation. Some theorists emphasise belief in oneself and one's competency, others prioritise goal orientation, and a third group argues that the difficulty of the task shapes individual motivation. This resource will provide an introduction to various theories of motivation, explain the importance of motivation for learning, and outline several practical strategies that teachers can use to support and promote student motivation.
Theories of motivation
Intrinsic vs. extrinsic
A common distinction made in the literature is between extrinsic and intrinsic forms of motivation. Intrinsic motivation is the act of doing an activity purely for the joy of doing it, and it is frankly very rare in school and work contexts. Extrinsic motivation, or the use of external rewards or punishments to encourage student work completion, is generally painted in education as the enemy of good instruction. This is true to a certain extent because, as learning is comparable to exploration, the use of rewards or punishments tends to outline a boundary around how much a student should explore.

However, there are actually many different forms of extrinsic motivation, and not all are equally likely to lead students down a path of apathy and dissociation from the joy of learning. For example, one extrinsically motivated student may work hard in school because they fear failure and the anger of their parents. Another may study hard because they see the value of the content in helping them work toward their dream of becoming a doctor. Neither student in these examples is intrinsically motivated - their goals lie outside the simple enjoyment of the activity. However, the second student is likely to be more independent and self-guided in their learning because they recognise the value of these extrinsic rewards. This form of motivation is much more sustainable because it does not require constant threats or prizes from teachers or parents. There is also some research to suggest that extrinsic motivation can lead to intrinsic motivation, in the sense that students may embark on a task for reasons associated with extrinsic motivation but become intrinsically motivated through the process of engaging with the task and learning to value it.
Achievement Goal Theory
Achievement Goal Theory argues that all motivation can be linked to one's orientation towards a goal. According to this theory, there are two forms of goal: performance goals and mastery goals. Performance goals are based on satisfying one's ego by appearing smart in front of one's peers or on achieving a sense of superiority. Mastery goals are, as they sound, motivated by a desire to fully master a skill or concept. Students with mastery goals will finish a project when they are proud of it rather than when it meets the minimum requirements. Even after they turn in the assignment to be assessed, they may continue to reflect on it and make refinements. Mastery goals largely align with intrinsic motivation in the former theory.

Some researchers in education have broken the concept of Achievement Goal Theory down further, borrowing the idea of approach and avoidant behavior from psychology. As the name suggests, students with approach performance goals actively seek to outperform others while those with avoidant performance goals actively work to avoid being seen as inferior. While less studied, approach and avoidant orientations also apply to mastery goals as well.
Expectancy Value Theory
Goal orientation has a strong impact on persistence through a rigorous task, as described in Expectancy Value Theory. According to this model, expectations and values influence performance and task choice directly. There are two main components to this theory. First, a student's effort, the level of challenge they choose and ultimately their performance will follow their expectation of success or failure. Second, the extent to which a student values learning a skill or concept directly impacts their effort and mastery of that skill or concept. Expectations and values themselves are influenced by beliefs about one's competence (otherwise known as self-efficacy) and by beliefs about the difficulty of the task. If the student remembers doing well or feeling satisfied when completing a similar task in the past, they are more likely to push themselves to work hard on the current task. However, if the student remembers that the activity was too difficult to be completed and they became frustrated, or not difficult enough and they became bored, they are unlikely to engage with it.

These beliefs, goals, and memories are also affected by a student's beliefs of other people's attitudes towards and expectations for them, and by their own interpretations of their previous achievement outcomes. Children's perceptions and interpretations are influenced by a broad array of social and cultural factors, and especially by parents and teachers.
Flow Theory
Flow is described as a psychological state in which an individual is purely intrinsically motivated and in which their sense of time is muted. Students experience flow during mastery-oriented tasks. This state is accompanied by a lessening of self-conscious thoughts and feelings. While there are many different psychological states that a student can experience throughout the learning process, such as wonder, confusion, worry and helplessness, flow is the most effective state of learning. Not only do students learn a great deal while experiencing flow because their learning is internally motivated, but they will continue without constant teacher prodding. These students will continue the learning process beyond the minimum requirements, or even outside the confines of the school context. Flow is said to occur within 'Goldilocks' conditions: tasks that are too difficult for the student will engender frustration and helplessness, while tasks that are too easy will cause the student to feel bored, and both these states of mind lead to disengagement from the activity. When possible, differentiation for individual student ability allows students to practise skills and concepts that are just withintheir current ability.

Nature versus nurture

Each of these theories points to the malleability of motivation. While natural genetic variability will lead to differences in a student's innate drive, every student has the desire to reach their goals. Our task as teachers, then, is to apply what we know from social science research to create environments, instruction, and activities to cultivate student motivation.

Some theorists classify motivation as a stable trait of the person, while others consider it to be more task specific. Individual-specific motivation describes the orientation with which all activities are approached, while task-specific motivation is dependent upon the appeal of the activity. Both forms can be improved through positive reinforcement, just-difficult-enough tasks, mastery-oriented goals and plenty of opportunities for success, as research indicates that even small initial successes are motivating for students. Individual-specific motivation is not the same as genetic predisposition to be a motivated person. Any individual can garner a more motivated outlook through specific supports and strategies. This resource focuses on motivation as an individual-specific trait because the research for this argument is fairly compelling, and because efforts to improve motivation of a person as a whole rather than towards one activity has greater potential impact.

Why is motivation important?

First and foremost, motivation is an orientation towards learning. Therefore, it impacts how likely a student is either to give up or push forward, and how thoughtful their reflection on their learning will be. The deeper the motivation for pursuing an activity, the more likely that the student will not accept easy answers to complex questions. In short, intrinsic motivation fosters strong and flexible critical thinking skills. On the other hand, amotivation and purely extrinsic motivation lead to low interest and academic persistence.
Motivation fosters creativity and critical thinking
Students who are intrinsically motivated treat learning like play. As a result, they are more likely to flip the learning on its head to see it from a new angle. Motivated students are not more intelligent than unmotivated students, but their need to find out the answer to a question or to master a concept pushes their thinking. Intrinsically motivated students will think about questions far beyond the confines of the classroom, because the presence of the teacher or the fear of a low grade are not the underlying drivers for their thinking. Therefore, motivated students, by virtue of thinking longer and harder and enjoying the challenge of being confused, will ask deeper, more thought-provoking questions. Motivated students are more able to adapt learned content to new situations because they tend to reflect on underlying causes or frameworks.
Motivation cultivates resilience and self-assurance
When a student is truly engrossed in a task, they have less cognitive and emotional energy to focus on social image. Individuals who engage in intrinsically motivating activities report that their self-consciousness and other stressors tends to fade for the period of the activity. Motivated students are also more able to emotionally 'bounce back' from a low grade on a test or a harsh criticism from a teacher or peer. Because intrinsically motivated students are not driven by fear of failure or criticism, they are less likely to disengage in such circumstances. With that said, every student does feel the demotivating effects of negative feedback, even if driven students experience them to a lesser extent.
Motivation and agency
Agency may be defined briefly as a sense of purpose and autonomy in striving after one's goals.Agency and motivation are inextricably linked concepts because, as a student becomes more driven to reach a goal, they consequently develop a stronger sense of purpose in directing their energy towards that goal. When it comes to educational attainment, highly motivated students find a way to forge their own path and tend to be skeptical of the limitations set by others. As professionals, motivated individuals also tend to be skeptical of established ideas or rules of the field, and instead constantly challenge themselves by experimenting with new ideas.

How do we cultivate motivation?

While the above theories may differ in emphasis, each can support student motivation through the following practical applications.

Students who feel like they will improve through hard work will exert more effort than those who believe that their success is based on intelligence. Teaching students to use the phrase 'yet' when explaining their gaps in knowledge helps to move them away from this deterministic orientation. For example, if a student says 'I can't do that', suggest that 'you can't do that, YET'. Making a conscious effort to provide wait time also removes the pressure of needing to be the first to find the answer. When students come to realise that their teacher will always wait 5 seconds or so before calling on a student rather than always calling on the first hand up, they will be more likely to engage with the struggle of thinking through the problem. Finally, by keeping the emphasis on progress rather than scores, growth mindset pushes students to continually challenge themselves and reflect on their improvement. Even small improvements and successes can help to spur a student's motivation.

Students who are paralysed by low academic self-confidence will struggle to drive their own motivation. A sense of competence is enhanced through optimal challenges. These are also referred to as 'just right' challenges because they are difficult enough to be just above the student's current ability to work independently but easy enough for the student to follow along with the teacher. As the student practises this new skill or concept, the teacher slowly removes their structured support, making it more and more difficult. This slow removal of support, paired with positive reinforcement and opportunities to receive support along the way, keeps students at this level of optimal challenge as they improve. Consistent small successes will further enhance motivation.

In addition, most of us can relate to the value of being reassured of one's own competence to learn a skill or concept. Students often base their view of their own competence on how they believe their teacher views them. Therefore, teacher observations of student effort encourage a sense of competence, as well as pointing out how far the student has come in their learning. When students have a firm sense that they are regarded as competent, they will be more likely to treat learning like play, making mistakes and taking risks. Threats and unyielding deadlines tend to diminish this orientation towards play-like learning.
Normalise the struggle
Students may give up because they falsely believe that, if they were going to succeed, it would be easy. Teachers can disentangle this misconception by providing examples of failures that well-known individuals overcame along their journey towards success. Emphasising the value of asking for help may catch students who are falling behind and becoming disengaged from the material. Finally, modeling the struggle through your own words and actions can be a powerful example to students. One phrase that may be useful when students seem to lose motivation for a difficult task is: 'This is new, this is hard, and if you get it wrong the first time then the challenge is simply to figure out why and to carry on.'
Minimise competition when there is one right answer
A pressure to compete tends to diminish motivation unless the two students are and perceive themselves to be equally competent: if a student at the top of the class is pitted against a student who is struggling, the latter student may feel that there is no reason to try. This is not to say that class or school-wide competitions should be avoided. When broader competitions are more open-ended, students can creatively self-guide their projects, and will feel a stronger sense of intrinsic motivation.
Develop optimally challenging, mastery-oriented goals
Differentiating tasks so they are appropriately challenging allows students to maintain optimal engagement. When students are working just within their current ability, they are drawn in by their curiosity to find the answer and spurred by the belief that they can find the answer. Teachers can also encourage students to set authentic learning goals rather than performance goals. Students can practise using mastery-orientation language when writing weekly, monthly, or long-term goals. Goals that begin 'to learn...', 'to understand...', or 'to master... [a particular skill]' support this orientation, while goals such as 'to get... grade', 'to earn more points than last quiz' or 'to meet my parent's goal of...' all express performance goals. Teachers can reinforce mastery-orientation by modeling it in their own goal setting.
Create quiet space
Despite the popular idea that fidgets or music support student focus, brains generally need quiet or ambient noise to stay engaged. Higher level brain functions such as creativity and critical thinking are inextricably linked to a state of flow, so students who are constantly interrupted will never be able to reach this level of highly motivated thinking. Therefore, independent and collaborative work should occur at separate times, or in separate spaces if they must occur simultaneously.
Avoid tangible rewards
Some learning is simply not particularly interesting, and no amount of differentiation can make every learning experience enjoyable for every student all of the time. External rewards such as long-term career goals and teacher approval are realistic external rewards that teachers can use. However, when deciding whether to use external motivation, it is important to keep certain principles in mind. Tangible rewards are often counterproductive, and the more external the reward, the less inherently valuable the student will find the activity. Even when students complete an activity for the inherent value they see in it, and are given an unexpected reward, they later regard their motivation for doing the activity as more extrinsically motivated than students who were not given a reward.
Acknowledge but don't dwell on potential hurdles
Students who believe that they can succeed are more likely to reach their goals. However, it is important that students consider what may go wrong in order to avoid being emotionally devastated when they encounter setbacks. In fact, letting students know that they will encounter setbacks, and that they are entirely normal, takes away some of their sting in the moment. In addition, students who consider hurdles before taking on a challenge are able to make a plan regarding how to continue moving forward. It is deeply valuable to emphasise to students that obstacles will always come up, but that what is important is to learn from these obstacles rather than to dwell on them.

Measuring motivation

Periodically evaluating students' social-emotional learning serves the dual purpose of informing the teacher of their students' progress and wellbeing, and prompting students to practise self-awareness. While formal school-wide social-emotional assessments are valuable for collecting comprehensive data, these measures are time-consuming and cannot practically be implemented more than once or twice each year. For these formal assessments, one reliable measure with strong evidence of validity is the Panorama Social-Emotional Learning Survey. However, on a fortnightly or monthly basis, teachers can informally gauge student motivation by asking the following questions:

How often do you do the following? Write a 1-10 next to each response (1=Not Often; 10=Very Often)

1. Choose to work above and beyond what is expected _____

2. Stick with a task until it is completed _____

3. Attempt to solve problems that others have difficulty with _____

4. Hurry through assignments _____

5. Ask questions to better understand difficult concepts _____

6. Try to avoid competitive situations _____

7. Put forth minimum effort _____

8. Do something over again just to get it right _____

These questions are suitable for verbal or written check-ins. When scoring written check-ins, items 4, 6, and 7 should be reverse-scored.

It is also prudent to consider not only the level of motivation a student has but their form of motivation. Is the student more intrinsically or extrinsically motivated, or somewhere in between? With this knowledge, we can use the above strategies to nudge the students towards more internal motivation by developing their sense of competency and control over their learning, as well as doing what we can to draw students in with interesting content.

References

Anderman, E. M., & Patrick, H. (2012). Achievement goal theory, conceptualization of ability/intelligence, and classroom climate. In Handbook of research on student engagement (pp. 173-191). Springer: Boston, MA.

Deci, E. L., Vallerand, R. J., Pelletier, L. G., & Ryan, R. M. (1991). Motivation and education: The self-determination perspective. Educational psychologist, 26(3-4), 325-346.

Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary educational psychology, 25(1), 54-67.

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American psychologist, 55(1), 68.

Vansteenkiste, M., Lens, W., & Deci, E. L. (2006). Intrinsic versus extrinsic goal contents in self-determination theory: Another look at the quality of academic motivation. Educational psychologist, 41(1), 19-31.

Wigfield, A., & Eccles, J. S. (2000). Expectancy-value theory of achievement motivation. Contemporary educational psychology, 25(1), 68-81.

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Motivation, as the name suggests, is what 'moves' us. It is the reason we do anything at all. For teachers, a lack of motivation has long been one of the most frustrating obstacles to student learning. While the concept of motivation may intuitively seem fairly simple, a rich research literature has developed as researchers have defined this concept in a number of ways.

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Cite this

Semrud-Clikeman, M. (2015, March 9). Research in brain function and learning. American Psychological Association. https://www.apa.org/education-career/k12/brain-function

The importance of matching instruction to a child's maturity level

The brain begins to mature even before birth. Although it continues to mature throughout most of life, the brain does not mature at the same rate in each individual.

This should not be surprising. After all, our bodies grow at different rates - we reach puberty at different ages and our emotional maturity at different times as well. Why should our brains be any different?

Just because you have a classroom full of students who are about the same age doesn't mean they are equally ready to learn a particular topic, concept, skill, or idea. It is important for teachers and parents to understand that maturation of the brain influences learning readiness. For teachers, this is especially important when designing lessons and selecting which strategies to use.

As a teacher, all children need to be challenged and nurtured in order to profit from your instruction. Instruction that is above or below the maturity level of a child's brain is not only inappropriate; it can also lead to behavior problems in your classroom. Inappropriate behaviors - such as avoidance, challenging authority and aggression towards other students - can be explained by a failure to match instruction to the brain maturity of your students.

You should also know that all brain functions do not mature at the same rate. A young child with highly advanced verbal skills may develop gross and fine motor control more slowly and have trouble learning to write clearly. Another child may be advanced physically but not know how to manage his/her social skills. Others may be cognitively advanced but show emotional immaturity.

For all of these reasons, it is important to understand how our brains mature as well as the differences that may be present at each stage of "normal" development.

The recommendations below are supported by evidence.

Do:

Be aware of developmental differences among your students. These differences have implications for behaviors that students display in your classroom.

Understand that normal development varies widely within the same age and the same grade. Our educational system is set up for the convenience of teaching large numbers of children in a grade-level classroom. The age for entrance into a particular grade is not necessarily linked to brain maturity for all children. Although you do not determine which children are in your class, you should be sensitive to the variety of developmental levels presented in your classroom.

Be aware that children who are born prematurely may not be at the same developmental level as others of their chronological age. Children who are born more than 8 weeks early may not catch up to their peers until they are 3 or 4 years old. Although premature children over the age of 4 are often indistinguishable from children who were not premature, there may be prematurely born children who continue to show delays. Be aware of this possibility when discussing a child's progress with his/her parents.

Be aware that childhood illnesses - such as ear infections, asthma, severe allergies, frequent hospitalizations, etc. - or family disruption caused by death or divorce may impact a child's development. A child with a history of these difficulties may benefit from specific accommodations, including:

- Sitting at the front of the class.
- Adjusting his/her pace of school work.
- Receiving a more overt display of understanding and encouragement by his/her teacher.

In addition, it is often helpful to provide children who have chronic illnesses and/or physical limitations alternate activities and to help their peers to understand the reason for offering these different activities.

Be aware that a healthy brain likes to learn, and children learn best when they are exposed to a variety of ideas, experiences, skills and materials. In the early years, children like to explore and learn using several senses or multiple skills at the same time.

Activities that pair motor and auditory skills can encourage the development of both pathways.

A child who has difficulty with writing and other fine motor skills benefits from lacing cards, mazes and tracing. These activities actually help students develop the visual-motor areas of their brains.

When a child talks through a difficult visual problem, it can help him/her learn. In other cases, a child whose language skills are delayed may benefit from tasks that don't require language.

Be aware that brain systems do not all develop at the same time or at the same rate. A child may show advanced development in one area and be delayed in another. For example, a child may read early but be physically clumsy.

Brain development also does not occur in a straight line. Some skills may develop earlier than other skills. Also, precocious ability does not necessarily last. It is possible for a child to be accelerated in reading or verbal skills in kindergarten but show average ability by third or fourth grade.

Don't:

Don't assume that a child has a disability just because his/her learning is delayed. Be aware that the development of cognitive and other skills is often uneven.

Don't assume that delays a child is showing today will get better over time. If a child does not improve his/her progress, it is important to gather more information and then refer the child for further evaluation if indicated.

Don't adopt a one-size-fits-all approach. Experienced teachers vary skills and activities for different students within a grade. Some of this variability works because of the different life experiences of children and some works because of differences in brain maturity. But, for either reason, variety is a good thing.

Don't place children in groups based solely on age. For some children, learning to read is a struggle. Many are not ready to learn to read until they are seven years old, while others are ready at age four. (This may be particularly true for boys.) Social maturity does not correlate with other learning skills. Both social and learning characteristics need to be addressed separately to determine appropriate placement.

Don't judge ability based on physical appearance. It's very important not to judge children based on their physical appearance. Children who are taller and/or more physically mature may not be cognitively advanced. And children with cerebral palsy often have average to above average ability despite significant problems with motor and speech production.

What do we know about brain maturation?

Children learn in different ways. And although the maturity of the brain is an important factor when it comes to learning differences, the real story is more complicated than that. The way children learn depends on age, level of development and brain maturity. Learning differences are also related to genetics, temperament and environment, but in this module we will focus on how and when the brain matures.

Different brain structures mature at different rates and follow different paths, but maturation begins long before birth. As a fetus grows, nerve cells (neurons) travel to their eventual locations within the brain. The survival of any one neuron is not guaranteed. There is competition among neurons for limited space and those that do not find a home - a place where they can live and thrive - are pruned back and destroyed. It is not yet known why some neurons find a home and others do not, but after a neuron settles down it continues to grow and develop within its region of the brain.

When pruning does not happen or is incomplete, disorders in learning and/or behavior can be the result.

Development of the brain from 25 days to 9 months:

At birth, both motor and sensory systems of the brain are already up and running. A newborn infant has enough motor control to feed and to move away from painful or other unpleasant stimuli. Although visual and auditory systems are present at birth, they continue to develop in the first few months of life as the brain reacts to the environment (Carlson, 2014).

In healthy children, motor and sensory systems continue to develop during toddlerhood and the preschool years. Auditory and visual skills improve during this time too. Since brain development after birth is influenced by inputs from the environment, and because those inputs are unique to each child, every human brain is unique.

Note: Inputs from the environment are not always a good thing. Children born prematurely are thought to associate the initial noise and clatter around them as painful. Research indicates that a quiet environment allows these children to catch up as their neurons make connections (Rothbart et al., 2003).

Although the age at which a child is ready to learn a specific skill becomes hard-wired as the brain develops, learning itself is also environmentally determined. For example, a child is ready to learn to read when his or her auditory system is developmentally ready to distinguish one sound from another. But if reading instruction is not provided, or if the child's parents do not enrich the environment by reading to him or her, learning to read will be delayed.

Conversely, a child whose auditory system is not ready when reading instruction is provided will also be delayed in learning to read.

The ability to read is also enhanced by the development of the auditory cortex and the development of skills involved in remembering what is taught and applying that knowledge to real problems.

Note: A key predictor of reading readiness is a child's ability to understand rhyming (Semrud-Clikeman, 2006). This ability translates into skills in understanding how sounds differ and in turn predicts a child's success with phonics instruction.

At every stage of development, it is important to give children age-appropriate tasks. But, be careful when you combine tasks. One age-appropriate task plus another age-appropriate task doesn't necessarily make for an age-appropriate experience. For example:

In the early grades, children learn how to coordinate fine motor skills and visual skills. They are able to copy letters and figures they see. Although this simple task is automatic for you, it takes a lot of concentration for them. Therefore, a child should not be asked to copy items from the blackboard and solve problems at the same time unless the act of copying has become automatic.

During the early elementary years, fibers continue to grow between neurons and the white matter of the brain (also called myelin). The growing neural networks of connected neurons and fibers are essential to the transmission of information throughout the brain. As the brain matures, more and more fibers grow and the brain becomes increasingly interconnected. These interconnected networks of neurons are very important to the formation of memories and the connection of new learning to previous learning.

As neural networks form, the child learns both academically and socially. At first, this learning is mostly rote in nature. As skills become more automatic, the child does not have to think as hard about what he or she is learning or doing, and brain resources are freed up to be used for complex tasks that require more and more attention and processing. Skills in reading, mathematics and writing become more specialized and developed.

Late elementary to middle school years

The late elementary and middle school years

From late elementary school into middle school, inferential thinking becomes more emphasized in schools, while rote learning is de-emphasized. This shift in focus is supported by the increased connectivity in the brain and by chemical changes in the neuronal pathways that support both short and long term memory. These chemical changes can continue for hours, days and even weeks after the initial learning takes place (Gazzaniga, & Magnun, 2014). Learning becomes more consolidated, as it is stored in long-term memory.

Where does learning occur?

During the early elementary years, the child develops motor skills, visual-motor coordination, reasoning, language, social understanding and memory. As learning is consolidated into neural networks, concepts combine into meaningful units that are available for later use. An ability to generalize and abstract begins at this stage and continues into adulthood. Also during this time, the child learns about perspective-taking and social interaction. The ability to understand one's social place is crucial for the development of appropriate relationships with other people. These skills are closely tied to development of the tracts of the right hemisphere as well as in the areas of the brain that are tied to emotional processing (also called the limbic system) (Semrud-Clikeman, 2007). (A tract is a pathway that connects one part of the brain with another, usually consisting of myelin-insulated axons. Tracts are known collectively as white matter.)

During the later elementary years and early middle school years, the child's brain activity is mostly in the posterior regions where the areas for auditory, visual and tactile functioning intersect. This intersection is called the association area of the brain and generally contains information that has been learned and is now stored. This is the information that is commonly measured on achievement tests and verbally based ability tests.

The frontal lobes begin to mature more fully in middle school. The maturation continues through high school and adulthood (Semrud-Clikeman & Ellison, 2009). The frontal lobes are a more recent evolutionary development in brains and allow humans to evaluate and adapt their behavior based on past experience. The frontal lobes are also thought to be where social understanding and empathy reside (Damasio, 2008).

The refined development of the frontal white matter tracts begins around age 12 and continues into the twenties. This region of the brain is crucial for higher cognitive functions, appropriate social behaviors and the development of formal operations. These tracts develop in an orderly fashion and experience appears to contribute to further development.

If you are teaching adolescents, you should emphasize inferential thinking as well as metacognition. For some adolescents, brain development matches our educational expectations. For others, the two do not coincide and there is a mismatch between biology and education. In this case, the adolescent is unable to obtain the maximum benefit from instruction and is often unable to understand more advanced ideas. Although learning problems may be due to immaturity, they may indicate more serious learning or attentional problems.

As connecting tracts in the frontal lobes become more refined, adolescents are expected to "think" about their behaviors and to change these behaviors. Unfortunately, this is the time when adolescents are more risk-prone and impulsive than adults. Some of this tendency is linked to changes in hormonal development as well as in brain changes.

The figure below shows the white matter tracts in a mature brain. Notice the colored areas that reveal the tracts from front to back of the brain, allowing for good communication both from front to back as well as from right to left.

Brain changes in the frontal lobe continue at a fast pace during adolescence and the healthy individual becomes better able to control more primitive methods of reacting (such as fighting or being verbally aggressive) in favor of behaviors that are adaptive. Adolescents and young adults start to see the world through the eyes of others and they become better at relating to other people.

Their progress toward more independence can be an exciting but also daunting task. When the transition to more adult behavior is problematic, the difficulty may be due to brain maturation. That's where a teacher can help.

Some adolescents need more structure; others need more freedom. A teacher is in a unique place to help parents and adolescents to understand these boundaries and to tailor their guidance to each situation. Schools are also beginning to recognize that smaller groupings and more contact with adults helps, too. These changes are very appropriate and in tune with the social and emotional needs of adolescents - as well as brain maturation - that are occurring at this crucial time.

In each stage of development, it is important for teachers to understand the relationship between neurological development and learning. This understanding is particularly important when there is a mismatch between development and educational expectations. The mismatch may be due to brain maturational differences or it can be due to a developmental disability. Research has found differences in brain structure, activation and development in children with learning disabilities (Aylward, E. H., et al., 2003; Maisog et al., 2008; Shaywitz, 2004), attention deficit hyperactivity disorder (Siedman et al., 2006; Swanson, et al., 2007) and in mood disorders (Konarski, et al., 2008; Pliszka, 2005). Further research is needed in all of these areas.

Myths about brain development and learning

Myth: You can train certain parts of the brain to improve their functioning.

Fact: This has been an attractive and sometimes lucrative idea for many entrepreneurs. However, it is not possible to target a specific brain region and teach just to that part of the brain. The brain is highly connected. Neurons in the brain learn remember and forget, but they do not do so in isolation. Skills need to be broken down into their component parts and these parts can be taught. However, we do not totally understand how this learning takes place nor do we know exactly "where" in the brain that learning is stored. Evidence from victims of stroke and head injury show that injury to the brain of one individual may not result in the same loss in the brain of another person (Goeggel, 2012). Brains are like fingerprints - although there are commonalities, there are differences that make each brain unique.

Myth: You are born with certain abilities and these do not change over time.

Fact: At one time, people believed that the brain developed into its full form by the age of three, and that what developed afterwards was just a matter of refinement. In fact, we now know that the brain is plastic - it changes with experience and development. Evidence shows that rather than ending development at the age of 5, or even 12, brain development continues into one's twenties. For some adolescents, the maturation of the frontal lobes may not end until age 25. For others, frontal-lobe maturity may be reached by the age of 18 or 19. For this reason, some adolescents may require additional time before they are ready for college, while others are ready at an earlier age.

Facts about brain development and learning

A child with a learning disability will always have the disability.

While a child with a learning disability, or with attention deficit hyperactivity disorder (ADHD), may show continuing problems in these areas, there are treatments that may help the child compensate for the problems. (These interventions are discussed in other parts of this module.) The brain changes with experience and the direct teaching of appropriate skills is the most important aspect of learning for children with special needs. Shaywitz (2004) reports success in teaching compensation skills to children with severe dyslexia beginning at an early age and continuing throughout school. Gross-Glenn (1989) found that adults with an early history of dyslexia, who had learned to read, had developed different pathways compared to those without such a history. The evidence from this research indicates that new pathways can be formed with intervention. Although these pathways are not as efficient as those generally utilized for these tasks, they can function adequately. Response To Intervention is a method that can help tailor an intervention to a child's needs (Fiorello, Hale, & Snyder, 2006).

The environment can improve a child's ability.

The environment can increase ability or it can lower it. A child with average ability in an enriched environment may well accomplish more than a bright child in an impoverished environment. Although it is heartening to believe that enrichment can be effective at any point, recent research indicates that early enrichment is more beneficial than later enrichment. The brain grows in spurts, particularly in the 24th to 26th week of gestation, and between the ages of one and two, two and four, middle childhood (roughly ages 8 to 9) and adolescence (Semrud-Clikeman & Ellison, 2009). These brain growth spurts are roughly commensurate with Piaget's stages of development. They coincide with periods of fast learning of language and motor skills in the one to four year old child; concrete operations in middle childhood; and formal operations in adolescents. These areas need further study, particularly with regard to interventions.

Skills such as working memory, planning, organization and attention develop over time with brain maturation and with practice.

Working memory is the ability to keep information in mind while solving a problem. For young children, teachers need to give directions one at a time. For late elementary school children, directions can be given in a limited series of steps. For children with difficulty in this area, it is helpful to have them repeat the directions to make sure they recall what is asked of them. Listing steps on the blackboard can also be helpful. Problems in working memory can be linked to difficulties with distractibility and/or attention.

Executive functions are those skills that allow a person to evaluate what has happened, to review what was done, and to change course to an alternative or different response (Diamond, 2006). Executive function skills allow children to understand what has happened previously and to change their behavior to fit new situations. Teachers can help with executive function development by including exercises that ask "what do you think may happen next in the story?" or they can provide story maps.

Planning and organization is the ability to plan and organize is a skill that develops along with the brain's ability to consolidate information. These skills develop slowly and with experience and development. Teachers can assist in developing these abilities by initially asking the child to think about the steps needed to complete a project. Teaching the child how to analyze a problem is also helpful - what do you need to do first? What do you need to do next? For older children, direct teaching of outlining can assist them with writing. The use of day planners and calendars can also help students plan for the completion of longer assignments.

Working memory

Do you ever go to a telephone book to look up a number and remember it just long enough to dial it? That's an example of working memory. If you get distracted between looking up the number and dialing the number, you will forget it. In order for something in working memory to be stored, it must be rehearsed and practiced. For a young child, this is particularly difficult because attention and distractibility significantly impact working memory. In addition, working memory is generally a frontal lobe function and for younger children the frontal lobe is not as well developed as in older children. Therefore, asking a young child to do more than one, or at the most two things at a time will not be successful - their brains are simply not ready. For elementary school children, working memory improves as the brain matures. Most children in elementary school are able to follow up to four directions at one time. For those who are younger, it is possible to practice one direction at a time or to have the child repeat the directions - practicing these skills improves performance. For adolescents, working memory may fail due to distractions. To improve the functioning of working memory it is helpful to make sure the person is listening to you. In addition, even for a fully developed working memory, the memory buffer is sensitive to overload. If a student is asked to do (or remember) too many things at once, he/she will not be able to process this information. Similarly, in a lecture format, information needs to be provided both visually and orally in order for sufficient material to make it into the working memory buffer. The use of lists, rehearsals and day planners have all been found to be helpful in remembering information that would otherwise overload working memory (Diamond, & Lee, 2011).

Executive functions

Evidence suggests that these skills primarily reside in the frontal lobes and develop over time. Although young children have some ability to improve their executive functioning skills based on feedback from teachers and parents, executive functions improve with age. Older children become more adept with these skills and use them more flexibly. It is interesting to note that executive functions are negatively affected by lack of focus, and children with ADHD frequently have difficulty with executive functions.

Recent research also indicates that when material is emotionally charged in a negative way (such as the pressure to learn something for a test, or the pressure of being called on by the teacher and made to answer a question), executive functioning decreases. This happens to some degree in every child, but it is particularly true for children with ADHD (Castellanos, Songua-Barke, & Milham, 2006).

When you are asking any child to perform a task that requires concentration and planning, it is important to provide as much scaffolding as possible for the child in order for him/her to profit from instruction. With maturity, executive functioning is related to appropriate behavior in a variety of situations.

Posner's model

In Posner's model of attention, both posterior and anterior regions of the brain form a complex network that includes subcortical structures such as the caudate nucleus for processing attention-related activities (Posner, & Rothbart, 2007). In this model, there are three networks believed to be involved: alerting, orienting and executive.

The alerting network lets a person know that something different is occurring. The orienting network orients the person to an event - where the event is, what the event is, etc. The executive network coordinates input of information and determines appropriate actions and reactions. Right frontal lobe dysfunctions are related to deficits in the alerting network, bilateral posterior dysfunctions are consistent with deficits in the orienting network, and left caudate nucleus dysfunctions correspond to deficits in the executive network.

Similar to Posner's theory, Corbetta and Shulman (2002) suggest that networks in various parts of the brain are involved in attentional functions. They say that the anterior of the brain is involved in selecting or detecting items to be attended to and preparing goal-driven behavior. The second system is in the temporal-parietal region and the lower frontal regions of the right hemisphere. It is this system that is specialized for the selection of relevant stimuli particularly when an event is unexpected. This second network pays attention to environmental events that are important because they are either rare or surprising. As such, this system would be a protective system to channel attention to particularly threatening or rewarding stimuli.

For further recommendations for skills also see Lynn Meltzer's "Executive Function in Education: From Theory to Practice" (Meltzer, 2011).

1. Reward good behaviors quickly and as frequently as possible. Please refer to the module on giving praise.

2. Follow through with consequences. When a child breaks the established rules, warn once. If the behavior continues, follow through with the promised consequence immediately.

3. For excessive activity:

1. Use activity as a reward. Alternate a seat-based activity with a more physical activity. For example, send the child to the office with a note for the secretary or give an activity that removes the child from the situation.

2. Solicit active responses. Examples include talking, moving or organizing responses.

3. Do not try to reduce physical activity.

4. Encourage non-disruptive movement.

5. Allow students to stand while doing seatwork.

4. Positively reinforce effort as well as success. For example, tell the child how well he/she is working.

5. Give clear, concise instructions.

6. Have a child repeat directions to you aloud.

7. Reinforce directions with a visual reminder when appropriate. For example, provide a list on the blackboard of what is expected and the approximate amount of time that each step should take.

8. Allow limited choice of tasks, topics and activities.

9. Use a child's interest whenever possible in designing activities or introducing material.

10. Match a child's learning ability and preferred method of response.

11. Allow alternate response modes (computer, taped assignments) with every assignment.

12. Provide a predictable routine in your class.

13. Encourage the use of color coded folders or other forms of personal organizers.

14. Make tasks as interesting as possible.

15. Allow children to work with partners.

16. Alternate high and low interest tasks.

17. Give targeted children priority seating close to the teacher.

18. Increase or provide novelty at later stages of the task to keep the child motivated.

19. Decrease the length of the tasks you assign.

20. Break up tasks into smaller parts.

21. Have tasks arranged so that children complete smaller parts after longer parts.

22. For every task students tend not to prefer, engage in two preferred tasks. Let students know that this will happen.

23. Give fewer math or spelling problems. For example, have the child do only the odd or even problems. Or put fewer problems (words on one page).

24. Use distributed (rather than mass) practice for problems beginning a task.

25. Increase structure and/or add emphasis to relevant parts of a task or assignment.

26. Ask a child to repeat directions.

27. Use written directions.

28. Set realistic standards for acceptable work.

29. Point out topic sentences, headings, etc. to improve task completion.

30. Use lists and assignment organizers.

31. Substitute verbal or motor responses for written responses.

32. Have a child work on easier parts of a task before tackling the more difficult ones.

33. Underline key words in directions.

34. Allow quiet play.

35. Encourage note taking for older children in high school.

36. Reward short intervals of patient waiting.

37. Don't assume that impulsive behaviors are aggressive.

38. Cue the child to upcoming difficult times when extra control is needed.

39. Bring distracters or toys that are quiet and absorbing.

40. Encourage after school activities.

41. Develop the child's sense of confidence and responsibility.

42. Encourage targeted children to play with children who can serve as positive role models.

43. Model good behavior.

44. Reward good behavior.

There are few direct studies of differences in brain development between girls and boys, and few to none on ethnicity. However, there are a number of studies looking at differences in brain structure and functioning in children with learning disabilities (LDs), autistic spectrum disorder or ADHD. Findings shed light on the difficulties that can arise when brain development does not go according to plan.

The next paragraphs briefly review the literature on gender differences, learning disabilities and ADHD. The review is not exhaustive, as research in this area is ongoing. It continues to contribute to our understanding of how the brain matures and give us ideas about interventions that can be used to alleviate problems.

Although there are few studies looking at gender differences in young girls and boys, it has been found that adult women have a larger corpus callosum (a bundle of myelinated fibers connecting the two hemispheres) than men (Semrud-Clikeman, Fine, & Bledsoe, 2009). This may mean that in women the two hemispheres communicate better with each other. In addition, there are indications that women have their skills spread throughout the brain, while males tend to have their skills in specific regions of the brain. It is not clear whether these differences are universally present. As a result, much more research is needed.

More and more we are learning that children with learning disabilities have brains that are different. Using magnetic resonance imaging (MRI), many studies have found that the brain area involved in matching sounds and letters is compromised in children with dyslexia (Maisog, Einbinder, Flowers, Turkeltaub, & Eden, 2008). These smaller brain areas correlate with poorer performance on tests of reading achievement, word attack and rapid naming ability of letters, numbers and objects (Gabrieli, 2009). The corpus callosum has also been found to differ in children with dyslexia. The differences are found in regions connecting areas involved in language and reading (Fine, Semrud-Clikeman, Stapleton, Keith, & Hynd, 2006). These differences appear to be due to decreased rates of pruning during the fifth and seventh month of gestation (Paul, 2011).

Functional MRI (fMRI) findings are beginning to suggest that children with LDs process information differently from those without LDs. Frontal brain regions are more efficient in fluent adult readers compared to children who are beginning to read (Schlaggar, 2003). As a child develops, the left frontal region becomes more active. But, fluent reading appears to be related to this region too. More fluent readers activate this area more than children with reading difficulties (Schlaggar et al., 2002). Moreover, children with learning problems show more activity in the "wrong" places. For example, their parietal and occipital areas are more active, and they show more activity in the right hemisphere than the left. In contrast, children without learning problems activate the frontal regions and the left hemisphere with less activation in the right hemisphere.

Activation of the brain is more diffuse when children are beginning to learn to read. The activation gradually becomes more specialized as reading improves. Similarly, when asked to read single words, normal readers show left hemispheric activation, whereas those with dyslexia show more right hemispheric activation (Breier, et al., 2002; Papincolaou, 2003).

Brain regions in the left hemisphere and temporal region have been found to be more active in good readers compared to those who had compensated for their dyslexia and were able to read adequately (Raizada, Tsao, Liu, Holloway, Ansari, & Kuhl, 2010). In addition, Gabrieli (2003) found that improvements were found in activation following remediation of auditory processing ability. It is not yet clear whether these changes continue over time; further study is needed to understand possible brain response to remediation. This finding is important because activation of the left hemisphere, a region specialized for language functions, plays an important role in reading while the right hemisphere has generally been implicated for processing of novel stimuli. Since children with learning disabilities activate the right hemisphere when they read, this seems to indicate that they find reading to be a more novel task than a learned task.

Early reading uses visual-perceptual processes generally located in the posterior portion of the brain. As the reading process becomes more automatized, the frontal systems become more active. Thus, the progression from simple letter and word calling to actual reading comprehension requires a maturation of neural pathways linking the back of the brain to the front (Shaywitz, 2004). Changes from right hemispheric processing to left hemispheric processing have also been found to occur with improvement in reading skills and improvement in language functioning. Such changes are not found for children with dyslexia, and their reading skill does not become automatic and effortless. Additional research is progressing in learning disabilities in older students.

Attention deficit hyperactivity disorder

There have been several studies of the possible structural differences between children with and without attention deficit hyperactivity disorder (ADHD) (Bledsoe, Semrud-Clikeman, Pliszka, 2009; Castellanos, Sonuga-Barke, Milham, & Tannock, 2006; Cherkasova, & Hechtman, 2009; Shaw, Eckstrand, Sharp, Blumenthal, Lerch, Greenstein, ... & Rapoport, 2007). A study of total brain volume found a five percent smaller volume in the brains of the group with ADHD compared to a control group. This difference in volume was not related to age, height, weight, or IQ. Another structure of interest has been the caudate nucleus. The caudate nucleus is located in the center of the brain and is associated with the neurotransmitter dopamine. The caudate has been found to be smaller in children with ADHD, possibly indicating less availability of dopamine - the neurotransmitter that assists with focusing of attention and impulse control (Semrud-Clikeman et al., 2006). Volumetric studies have also found smaller frontal lobe volumes in children with ADHD particularly the white matter volume of the frontal lobe. Differences have also been noted in the white matter in the posterior regions of the brain particularly for those children who did not respond to stimulant medication such as Ritalin (Hale, Reddy, Semrud-Clikeman, Hain, Whitaker, Morley, ... & Jones, 2011).

The finding of reduced white matter volume in the right frontal and posterior regions of the brain, as well as caudate asymmetry differences, suggests that systems commonly associated with sustained attention are different for children with ADHD. This finding may help to explain the difficulty children with ADHD have in more advanced attentional functions, such as self-regulation and executive function. Reduced white-matter volume leads to less communication between the frontal and posterior areas. The posterior region of the brain is responsible for accessing information from previous situations while the frontal region of the brain applies this knowledge to the current situation at hand. When there is not enough communication between these two centers, the child will have difficulty either accessing previously learned information or applying it correctly to the new situation. This corresponds to the finding that a child with ADHD has difficulty applying knowledge (or rules) even though he/she may be able to tell you the rule.

A fairly new avenue of investigation is the gene X environment interaction to help understand the etiology and course of ADHD. Nigg et al. (2010) reviewed the literature and found that psychosocial factors contribute to attentional difficulty. For example, a child may do adequately if family stresses are lower. However, if family disruptions (divorce, contentious parenting) occur, significant impairment may ensue. ADHD has a relatively high heritability meaning that it tends to run in families. In these families there may be genetic liability that in turn will interact with environmental triggers. Thus, when working with families with a history of ADHD, it is important for educators to provide information as appropriate and to be aware of these vulnerabilities.

The development of fewer connections between brain areas may well impact the efficiency of these connections - resulting in a poorer level of functioning but not a total loss of function (Fair, Nagel, Bathula, Dias, Mills, ... & Nigg, 2010; Makris, Buka, Biederman, Papadimitriou, Hodge, Valera, ... & Seidman, 2008; Nigg, 2006). Functional neuroimaging, which allows one to view what the brain is doing when the person is completing a task, showed lowered activation in the regions of the frontal lobe and caudate nucleus when the child is asked to inhibit a response. (Not respond when he/she would like to respond) (Pliszka et al., 2006). Less activation may well indicate fewer connections being made between neural networks and poorer attention to detail. Additional study is needed in this area to more fully understand differences that may be present in children with ADHD and those without.

Autistic spectrum disorders

Children with autism have been found to have larger heads than the general population (Verhoeven, De Cock, Lagae, & Sunaert, 2010). It has been found that the brains of toddlers with autism are 10 percent larger than same-aged peers, with the largeness of the head decreasing with age. They continue, however, to be larger than matched aged peers throughout life (Anagnostou, & Taylor, 2011). Interestingly, there is no difference in head size at birth (Keller, Kana, & Just, 2007) and the brain growth that later occurs may be due to early overgrowth of neurons, glial cells and a lack of synaptic pruning. Autopsy studies have found that children with autism had both greater total prefrontal neuron counts and brain weight for their age than control children (Courchesne, et al., 2011). Findings have suggested that the extra tissue that causes the increase in size is not well utilized or organized - thus resulting in poorer skill development (Aylward et al., 2002). Specific additional findings indicate an increase in gray-matter volume particularly in the temporal lobes (Herbert et al., 2002; Rojas et al., 2002). Using structural MRI analyses, Courchesne et al. (2003) found smaller amounts of white matter compared to gray matter in toddlers and adolescents. Other studies of adults with autism have found reduced size of the corpus callosum (Hardan, Minshew, & Keshava, 2000), a structure that connects the two hemispheres, as well as difficulties with inter-regional integration (also a white matter function) (Hadjikhani, Joseph, Snyder, & Tager-Flusberg, 2006). Some studies have suggested that the larger brain, higher white matter volume and disrupted gray matter cellular columns may contribute difficulty that a person with autism has in integrating information and generalizing this information to new situations (Schultz et al., 2000). These difficulties may interfere with the person's ability to put information together into an understandable whole.

The amygdala, anterior cingulate and hippocampus are part of the limbic system - the emotional part of the brain. The amygdala is important in emotional arousal, as well as processing social information. The hippocampus allows for the short-term and eventual long-term storage of information while the anterior cingulate works as a type of central executive, directing attention where it is most required.

Autopsies of autistic individuals have revealed abnormalities of both the hippocampus and the amygdala including fewer connections and smaller hippocampi. This finding could lead to difficulties in forming new memories or associating emotions with past memories (Carlson, 2014), and may contribute to difficulties seen in people with autism with respect to social reciprocity and social awareness. Structural neuroimaging studies of children with autism show the volume of the amygdala and hippocampus to be enlarged (Groen, Teluij, Buitelaar, & Tendolkar, 2010), although further research is needed in these areas. Some have suggested that the amygdala may be important for mediating physiological arousal and if it is not as active, the person may well not be as motivated for participating in social activities (Murphy, Deeley, Daly, Ecker, O'Brien, Hallahan, & Murphy, 2012).

More recent studies have begun evaluating discrete areas of the brain that may be disrupted in people with autism. An area of the temporal lobe that has been found to be important for recognizing faces has been studied in children with autism. This area has been found to be underactive in people with autism and the degree of under-activation is highly correlated with the degree of social impairment (Schultz et al., 2001). Of additional interest is that this area of the temporal lobe has also been implicated in successful solution of Theory of Mind tasks, skills that are also impaired in people with autism (Castelli et al., 2000; Martin & Weisberg, 2003).

Both the frontal lobes and the upper area of the temporal lobes are important for understanding and perception of social interactions as well as interpretation of facial expressions. The frontal lobes have also been implicated in the ability to take another's perspective - or in social cognition. These areas are intimately connected to the limbic system as well as the temporal lobe areas discussed earlier in this section. Studies of brain metabolism have found reduced activity in these regions of the brain in patients with autism particularly when asked to perform tasks that tap social cognition and perception (Harms, Martin, & Wallace, 2010).

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Abstract: Higher-level reasoning or understanding.

Amygdala: An almond-shaped cluster of neurons in the limbic system thought to be involved in processing emotions and memory.

Anterior cingulate: Anterior section of the cingulate cortex. Asymmetry: favoring one side or the other. Also called laterality.

Attention deficit hyperactivity disorder: Mental disorder that consists of behaviors such as impulsivity, hyperactivity and difficulties with inhibition and self-regulation

Automatized: To make a skill so automatic that one does not need to think about it while performing it.

Caudate nucleus: Part of the Basal-Ganglia, the Caudate nucleus is thought to be involved in regulation of movement, learning and memory.

Corpus Callosum: A white matter structure that connects the right and left hemispheres of the cerebral cortex. Thought to contain approximately 250 million axons that allow right and left hemisphere communication.

Dopamine (DA): Part of the catecholamine family of neurotransmitters (epinephrine and norepinephrine), Dopamine is naturally produced in the brain and is thought to be involved in reward-based cognitive functions.

Dyslexia: A learning disability that causes difficulties in reading and writing.

Empathy: The ability to recognize and vicariously experience another person's emotional state.

Executive function: Higher-order cognitive processes that allow one to control organization of thought, and apply context specific rules in order to execute a task successfully.

Formal operations: The skill to think systematically about all of the parts of a problem and to arrive at a reasonable solution.

Frontal lobes: Area of the brain made up by the front portions of right and left hemispheres of the cerebral cortex. These areas are involved in memory, planning, organization, language and impulse control. These areas also have been linked to personality.

Functional magnetic resonance imaging (fMRI): A technique in which neural activity is measured by changes in blood flow. Brighter areas on an fMRI images indicate higher amounts of blood flow and greater activity.

Generalize: To apply a conclusion beyond a specific example.

Glial cells: Cells of the nervous system that provide physical support and nutrition for neurons. Higher cognitive functions: See executive functions.

Hippocampus: Part of the limbic system involved in storing new knowledge.

Impulsive: Behaviors that are not thought out.

Inferential thinking: Reading between the lines, often involves meaning that is implied rather than explicit.

Inhibition: The ability to regulate behavior or impulses.

Inter-regional integration: Neural connections that are similar in location. Language: A system/group of symbols used in verbal and visual communication.

Learning disability: Difficulties in the development of language, reading, mathematical reasoning or other academic undertakings compared to expectations of one's ability. Believed to be neurological in nature.

Left hemisphere: The left side of the cerebral cortex, thought to mediate language and verbal communication.

Limbic system: A multistructural system involved in emotions, memory and physical regulation. Structures such as the amygdala, cingulate gyrus, hippocampus, hypothalamus, ammillary body, nucleus accumbens, orbitofrontal cortex, and thalamus are all structures of the limbic system.

Memory: Ability to store and recall conceptual, social, emotional and physical information.

Metacognition : Thinking about one's own learning, thinking or perception.

Myelinate: The white matter in the brain. It is made up of lipids (fat) that help impulses move more quickly along the nerve.

Myelination: Process during development by which Myelin is formed over the neurons.

Neuronal pathways: These are pathways through which nerve messages travel as they move among the various parts of the brain.

Neurons: Cells that make up the nervous system, they process and transmit signals electrically.

Neurotransmitter: Nervous system chemicals that relay, amplify and modulate electrical signals from one neuron to another neuron.

Perspective-taking: The ability to understand another person's point of view or beliefs. Processing of novel stimuli: Analyzing new information that the brain has not seen before.

Pruning: Process by which brain cells die off in order to make room for more efficient connections between neurons.

Reasoning: Mental process that deals with one's ability to perceive and respond to feelings, thoughts and emotions.

Right hemisphere: The right side of the cerebral cortex, thought to mediate spatial, social and emotional understanding.

Risk-prone: Susceptible to taking chances and making mistakes.

Rote: Learning by memorization.

Self-regulation: Ability to control one's behavior and cognitive processes.

Social understanding: Ability to manage and function in social settings such as peer relationships.

Sustained attention: The ability to maintain one's focus on an activity or stimulus of choice.

Synaptic pruning: When weaker neural connections are thinned and replaced by stronger connections.

Temporal region: The side region of the cerebrum thought to be involved in auditory processing.

Theory of Mind tasks: Tasks that evaluate whether one has the ability to consider another's personal beliefs, needs, desires and intentions.

Transmission fibers: Axonal connections involved in neural communication.

Visual-motor: Coordination of visual and motor processes, like tracing letters.

Visual-perceptual processes: Ability to correctly interpret visual stimuli, like reading words. White matter fibers: Myelinated axons.

White matter volume: Quantified amount of myelinated axons.

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It is important for teachers and parents to understand that maturation of the brain influences learning readiness. For teachers, this is especially important when designing lessons and selecting which strategies to use.

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Although there has been considerable discussion about neuroscience in relation to education, 1 there appear to be very few outcomes with respect to teaching practice. 2 It is logical to assume that further progress may require cross-disciplinary integration of research from psychology, neuroscience, machine learning, and education, 3 particularly because, at present, there is no clear consensus on the nature of learning. 4- 6 To facilitate such cross-disciplinary discussion, the use of technical terms has been limited and the current paper uses an education-centered approach focused on learning that involves conscious processes that require goals and the associated strategies required to achieve them. 7 Neuroscience studies have shown that the learning process involves both working memory (WM) and long-term memory (LTM) 8 and associated control processes in the prefrontal cortex (PFC) that select and manipulate goal-relevant information. As these PFC regions appear to play a crucial role in controlling learning processes, reference has been made specifically to both the dorsal and ventral lateral prefrontal cortices (DLPFC and VLPFC) and the anterior prefrontal cortex (APFC).

Working memory plays a critical role in the learning process because it has been shown to facilitate the formation, strengthening, and expansion of LTM. 9, 10 The control component of WM has been associated with the DLPFC, and this region appears to be involved in the selection, monitoring, and maintenance of goal-relevant information held temporarily in the posterior association cortex (PAC). 11, 12 The WM system is only capable of processing a limited subset (3-5) of items at any one time, but remains active until new information is selected. 13 From an educational perspective various strategies have been used to facilitate entry of relevant material into WM by, for example, adapting instructional design and by managing cognitive load (eg, by focussing on the main points of a task and by removing distractions). 14- 16 However, recent findings have increased our understanding of WM with respect to flexibility in goal pursuit and learning. This work has elucidated how DLPFC control may switch from maintaining current information to permitting WM to update with new, relevant, information. 17, 18 Consideration of these mechanisms may help to extend thinking about the role of WM in an educational context and help us understand educational research results where WM capacity and motivation can be used to identify different student learning profiles. 19

Working memory only stores information for a relatively short period, and LTM is thus essential. One type of LTM is semantic (factual/concept) memory (SM), which is both a result and a critical component of the learning process. 20 Learning appears to be not only concerned with the long-term storage of specific facts, but with the formation of associations between facts (concepts), and this stored information can be referred to as a semantic framework. 21 According to some authors, associations and associative processing may form the basis for thought and learning, 22 and neuroscience studies may provide useful directions for computational modeling studies of these processes. 23, 24 From an educational point of view, an understanding of these mechanisms may help to support the suggested use of analogical reasoning as a means to strengthen associations between facts. 25 The storage of SM involves the PAC, particularly the temporal pole, 26 and the control of SM selection and retrieval has been associated with the VLPFC, which shows stronger activity when a learning task includes concepts or facts that are only distantly related. 11, 27- 29 However, association of a common object with an unusual function (eg, a shoe used as a flower pot) also activates the APFC in addition to the previously mentioned regions. 30 The APFC is thought to represent the highest level within the control process hierarchy because it is activated during abstract reasoning and metacognition. 31- 33 Educators may benefit from an understanding of how facts and their relationships are processed by the brain, particularly when considering the use of graphical representations of concepts in the form of "concept maps" and the like. 34

One area of neurophysiology research that has only had a limited impact on teaching practice is that related to the default mode of brain activity (a default network of brain regions where processing may become suspended during task-related action). 35, 36 This default network is thought to include brain regions involved in self-referential processing (ie, thinking about oneself or how others relate to you) and memory retrieval. 37 Such a putative network is important to consider with respect to learning for two reasons. First, the common phenomenon of "mind wandering" may reduce the effectiveness of task performance and learning 38 and has been posited to be associated with engagement of the default network. 39 On the other hand the default network has also been associated with useful activities such as planning and autobiographical goal setting (imagining future personal experiences). 37 It has been proposed that both task-related and default networks may contribute to achieving a particular goal. 40 In summary these findings indicate that learning may involve not only the more established task-related networks, but may also require support from "internal" prospective mechanisms involving "self." "Switching" to the "default" network may, therefore, be important where students work with others in a group situation and where their estimation of self and that of others may impact on learning. 41 However the interaction between task performance and self-referential activities has yet to be established in a formal learning context.

It is clear that representations of personal brain function can be made (metacognition) 42 and that this ability plays an important role in reasoning and planning 43 and in communicating internal states to others. 44 Both the APFC and the DLPFC provide a major contribution to metacognition, and changes in APFC gray matter volume may reflect the effects of learning in individuals. 33, 45 Individual differences in metacognitive ability, established by neural and behavioral studies, suggest that metacognitive training should be considered (learning how to learn), and Mayer 46 proposed that improving metacognition should be a primary educational objective. Although metacognitive reporting usually mirrors task performance, the two can sometimes be dissociated. 45, 47 Therefore, one should be vigilant with respect to the value placed on verbal or written reports relating to "self," because educational research often depends on student self-reporting. 47

Finally, the lessons learned by consideration of neural representations and control hierarchies may aid the development of individualized intelligent tutoring systems. 48 Although human tutors can provide effective learning support, increasing class numbers make one-to-one tutoring much more difficult to achieve. Computer-based tutors may help to support individual student learning by selecting appropriate problems to be solved and by providing alternative solution strategies, feedback, and hints. 48- 50 An understanding of neuroscience and an interdisciplinary synthesis of research may lead to optimum outcomes for teaching practice.

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Neuroscience and Learning: Implications for Teaching Practice

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Although neuroscience studies have provided us with an increasingly detailed picture of the basis for learning and memory, very little of this information has been applied within the area of teaching practice. We suggest that a better understanding of ...

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Use chunking to organize information into manageable parts.

Incorporate movement and physical activities to boost cognitive performance.

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Use goal-setting to increase student motivation.

Create a positive learning environment to reduce anxiety and enhance focus.

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Scaffold learning based on students' cognitive development stages.

Use age-appropriate activities that align with brain development.

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Practice retrieval techniques to strengthen neural pathways.

Encourage spaced repetition to enhance long-term memory retention.

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How to use Brain-based learning in your class

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Milestones in Brain Development and Cognitive Growth: Curious Learners

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Instructional applications integrate brain research and learning theories to develop effective teaching strategies that align with how the brain learns best.

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Motivation and emotions play a pivotal role in learning by influencing attention, persistence, and memory. Positive emotions can enhance learning, while negative emotions may hinder it.

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Brain development is a critical factor in learning, with different stages of development impacting cognitive abilities, memory formation, and skill acquisition.

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Neurophysiology of learning involves understanding how neurons communicate, synaptic plasticity, and the biological processes that enable learning and memory consolidation.

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Learn about the parts of the brain and their functions. Get a diagram of human brain anatomy and key facts about this important organ.

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Use of graphic organizers to visualize complex ideas.

Integrating sensory activities in lessons to activate different brain regions.

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The Structure and Physiology of the Human Brain

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This section focuses on the brain’s organizational structure, including how different areas work together to process information, memory, and learning. It explores the neural connections that facilitate learning and cognition.