MET:Brain-based Learning

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Created by Susie Gareau, June 2011 (66C)

An educational philosophy developed based on findings from research in neurology. The method is said to extrapolate current knowledge about the actual structure and function of the human brain at different developmental stages for designing educational techniques that are brain friendly. The theory is used to explain recurring learning behaviours, and has been used to try to remedy learning disabilities (Arrowsmith). Opponents of the notion of brain-based curricula view the ideas as based on misconceptions and overgeneralizations of what is known about the brain (Bruer, 1997).

Picture of the Brain © 2009 WebMD, LLC. All rights reserved


Very early on, scientists identified the left hemisphere (LH) of the brain as the primary biological locus for language and analytical thought. In 1861, Pierre Paul Broca found evidence to link speech to a specific brain site. Carl Wernicke, in 1874, found additional evidence linking language to the LH of the brain. In 1892, Jules Déjerine found that reading and writing deficits resulted from damage to the LH. These findings were extrapolated to mean that specific mental functions had precise locations in the brain – the localization theory, which dominated neuroscience research in the first half of the twentieth century. Vygotsky strayed somewhat from this dominant theory by proposing that functions such as language, although possibly having a primary focus in the LH, was more likely to involve neural processes distributed throughout the brain. He also proposed that neurological structures associated with mental functions were influenced and modified by the sociocultural environment. In the mid-20th century, Sperry and colleagues confirmed that the LH dominates language and analytical thought; provided a breakdown of psychological functions according to hemisphere; and showed that both hemispheres are involved in complex thinking (See Springer and Deutsch, 1993 for a detailed account of the relevant experiments). In 1967, Eric Lenneberg observed that loss of speech due to disorders in a language function became permanent after puberty. This suggested to Lenneberg that, at puberty, the brain lost its ability to tranfer language functions from the LH to the RH, and from there, he inferred that the critical period for language acquisition is before adolescence. In 1990, the neurobiologist Paul MacLean developed the Triune Brain theory, stating that we have three brains, each representing a separate evolutionary stratum and function, and controlling our emotions, thoughts and behaviours. According to his theory, survival learning would be located in the lower brain, emotions in the mid-brain, and higher order thinking would take place in the upper brain. In the last three decades, neuroscientists have obtained information on how the brain works from autopsies, experiments and different types of scans (MRIs, EEGs, PET, CAT). For example, PET brain scans provide images of mental activities such as language, or show how the neocortex is involved in producing various psychological functions and psychomotor movements (Arrowsmith and Danesi). Results of neuroscientific research are interpreted as having implications for improving teaching practices (See list of authors and books in this area).

The cerebral cortex

The cerebral cortex is the largest part of the brain. It is divided into four different lobes: the parietal lobe, temporal lobe, occipital lobe and the frontal lobe. Each of the four lobes is responsible for different functions.

Parietal lobe

  • Spatial processing
  • Sensory functioning

Temporal lobe

  • Formation of memory
  • Processing sound and language

Occipital Lobe

  • Visual perceptions

Frontal lobe

  • Reasoning
  • Executive function
  • Motor skills
  • Expressive Language

The reactive and reflective brain


Reactive brain

The reactive part of the brain is referred to as the amygdala. It is part of the limbic system and is located within the temporal lobe. It is the reactive part of the brain. The amygdala is responsible for processing emotions and motivations that are related to survival. The amygdala responds to dangers by creating a flight, fight, or fright response. Overstimulation of the amygdala can be caused by fear, anxiety, embarrassment, boredom, frustration. When the amygdala is overstimulated it enters a hyper metabolic state. Information cannot then be fully processed. (See website on fear and learning).

Teaching strategies that promote optimal functioning

In order to maximize learning opportunities students learning should be situated in environments that have positive emotional climates and are stress free. This can be established by:

  • Establishing daily classroom routines
  • Encouraging open dialogue
  • Constructing achievable challenges
  • Encouraging participation not perfection
  • Discover the barriers to learning and reducing or eliminating them

Reflective brain

The reflective part of the brain is located in the prefrontal cortex. It is responsible for several processes including executive functioning. Executive functioning allows for:

  • Problem solving
  • Organizing
  • Self-monitoring
  • Self-correcting
  • Making connections
  • Prioritizing
  • Focusing
  • Predicting
  • Abstract thinking

Teaching strategies that support executive functioning

There are a variety of useful and practical strategies that can be implemented with a classroom environment that supports optimal executive functioning. Some of which include:

  • Creating a learning environment that is student centered
  • Introducing material in ways that are physically and emotionally energizing
  • Cross curricular teaching
  • Differentiated Instruction
  • Engaging the senses (hearing, seeing, touching..)
  • Encouraging students to make personal connections
  • Activating prior knowledge
  • Utilizing graphic organizers.

Some themes in neuroscience of interest to brain-based educators:

Critical period in brain development

'The first years of life hold the most critical periods for brain development. When the child is born, these billions of brain cells, called neurons, begin to connect to help a child build a useful brain. These connections are called synapses. The number of synapses multiplies to make trillions of connections that form a “map” with increasingly more complex connections. The network of connections influences intellectual capacity, memory, problem solving, and language.'

A large body of research has shown that very rapid synaptic development occurs from birth to age 3, that synaptic pruning starts around age 10, and that the brain increases in volume until around age 14. In parallel, glucose metabolism in the brain increases from about age 4 to 10, after which it decreases to adult levels until around age 16 (See Alferink & Farmer-Douhan, 2010, for detailed discussion and references). Based on these observations, some authors (e.g. Sousa, 1998) suggest that early childhood is the critical period when learning is most important Most neuroscientists now view early childhood as a “sensitive”, rather than “critical” period, and believe that subtle changes are continually occurring in the human brain such that recovery and learning can occur even after periods of sensory deprivation. Some areas of the brain continue to develop into adolescence (See interesting Teenage Brain Clips at the following web site: There is some evidence that performance on executive function tasks improves linearly with age (Anderson et al., 2001). Based on neuroscientific findings of brain development during adolescence, Blakemore and Frith (2005) sustain that schooling is imperative in moulding and shaping the adolescent brain. The adult brain also changes as a result of a certain type of activity. Navigation skills of London taxi drivers have been shown to change the size of their hippocampus (Maguire et al., 2000). Neuroscientists believe that brain cells can change specific function depending on usage. Thomas Scovel (1988), after extensively reviewing research in the “critical period” wrote that there are no clear-cut findings to suggest biological constraints on learning.

Plasticity in the brain

Historically, the brain was thought to be equipped at birth with all the cells that it would ever have. Adulthood was seen as a period of loss of brain cells during which one’s ability to learn, one’s memory and performance decreased. Neuroscientists now know that the adult brain is flexible, and can grow new cells and make new connections. Modern thinking is that the brain is flexible, modifiable and reparable (See The Brain that Changes Itself). Cognitive scientists interpret this new knowledge as meaning that the brain is set up for life-long learning and that educational rehabilitation in adulthood is possible (Blakemore and Frith, 2005).


Learning causes growth of brain cells. Dendrites increase in size and number in response to learned skills, experience, and information. Once these dendrites are formed, the brain’s plasticity allows it to reshape and reorganize the networks. The restructuring of neural pathways occurs in part as a response to the “use it or lose it” phenomenon also known as pruning. This pruning process exists to allow the brain to function efficiently (Willis, 2006)

Application to learning

Teachers can have an impact on student learning by using a variety of strategies to introduce material to students. Multiple stimulation of different areas of the brain can result in the development of more dendritic pathways and thus better memory and future access to information. For example, offering information visually will stimulate connections in the occipital lobes. Subsequently, having a student hear information will affect dendrites in the temporal lobes. The more regions of the brain that store information on the same topic means a greater likelihood of accessing this information at a later date (Willis, 2006).

Developmental disorders

One important discovery about developmental disorders is how specific it can be, affecting only a certain aspect of intelligence, leading scientists to assume that there are neural structures that are specifically geared towards processing a particular type of stimulus. This belief, in conjunction with evidence that brain cells can be reassigned to different functions depending on how they are used, is the basis for the method of treatment for learning disorders that is promoted by Arrowsmith.

For example, Sally Shaywitz used fMRI scans to show that dyslexic readers have brain patterns different from non-readers and non-dylexic readers.

Some links between brain studies and learning

Visual Imagery:

Brain imaging has shown that much of the same brain activity is observed when objects and events are imagined as when they are experienced (Ganis et al., 2004). Based on this information, proponents of brain-based learning view visual imagery as a powerful method of learning.


Rizzolatti et al. (1996) have observed that people watching an action being performed experience activation of the same brain areas as they would by doing the action themselves. Based on these findings, proponents of brain-based learning view imitation as a powerful learning technique.

Physical activity:

On the basis of evidence by van Praag et al. (1999) that mice that exercised regularly became better at learning than sedentary mice, brain-based proponents advocate physical activity as a way to boost brain function and increase learning.


Research by Maquet et al. (2000) has shown that the brain regions that are activated in learning during the day are reactivated during sleep, and that a task is better performed after a night’s sleep, leading to the interpretation that sleep-time brain reactivations are beneficial to memory and learning. In an interview, Dr. Carskadon highlights the consequences of insufficient sleep in adolescents as well as concerns about early schoolstarting times.

Safe learning environment:

The emphasis of brain-based educators in providing a safe learning environment is rooted in the notion from neurological research (e.g. LeDoux, 1996) that if the amygdala perceives the environment as unsafe, it will shift the blood and oxygen in the brain into a “flight or flight” mode, such that brain functions will not be available for learning.

Video: Brain-based learning in Education

Watch this video to get a better overall understanding of brain-based learning in the classroom.

Core principles directing brain-based education

(Caine and Caine, 1994)

  • The brain is a parallel processor. It can perform several activities at once.
  • The brain perceives wholes and parts simultaneously.
  • Information is stored in multiple areas of the brain, and can be retrieved through multiple memory and neural pathways.
  • Learning engages the whole body. All learning is mind-body: movement, foods, attention cycles, and chemicals modulate learning.
  • Humans search for meaning is innate.
  • The search for meaning comes through patterning.
  • Emotions are critical to patterning, and drive our attention, meaning and memory.
  • Meaning is more important than just information.
  • Learning involves focused attention and peripheral perception.
  • We have two types of memory: spatial and rote.
  • We understand best when facts are embedded in natural spatial memory.
  • The brain is social. It develops better in concert with other brains.
  • Complex learning is enhanced by challenge and inhibited by stress.
  • Every brain in uniquely organized.
  • Learning is developmental.

Recommendations to brain-based teachers based on core principles and neurological knowledge

  • Create learning environments that immerse students in a learning experience (orchestrated immersion).
  • Attempt to eliminate fear and reduce stress while maintaining a highly challenging environment. This recommendation is based on the recognition that complex thought and memory storage occurs in the neocortex, a region of the brain that does not function properly when humans are stressed or afraid.
  • Attend to the learning environment to enhance sensory stimulation by such efforts as using music, changing lighting, and using scents to optimize the learning conditions. This is based on research that indicate that music can induce compatible brain wave patterns that enhance learning and retention.
  • Develop a culture of acceptance of learning styles, capabilities and disabilities. Provide instruction that meets different learner modalities (auditory, visual, kinesthetic/tactile) and create instructional bridges from one intelligence or learning style into another. Use a combination of cognitive, affective and physical teachniques to teach, and allow students to use movement to reinforce knowledge.
  • Introduce students to metacognition concepts. Encourage them to discover how they think and learn best. Support them in developing their own learning and study techniques.
  • Present information in small chunks as the human brain is said to hold approximately seven bites of information at a time.
  • Encourage students to actively process information, and connect it to prior knowledge. Show them how the information is relevant to them.
  • Use activities that combine right and left-brain hemispheres’ functions.
  • Provide many opportunities for students to rehearse learned material.
  • Combine experiences that involve reflection, experiential learning and concrete entry into abstractions.
  • Encourage risk-taking in learning, and provide an environment in which it is safe to make mistakes. Promote an attitude of learning from mistakes.
  • Give students time to be reflective and creative.

Stop Motion Animation Video discussing Brain-Based Learning and the benefits educators can achieve when they begin to consider it in their teaching.

Practical advice to brain-based educators

  • Use student created products to make a rich and stimulating environment;
  • Include places for group learning to stimulate social skills and cooperative group work;
  • Link indoor and outdoor spaces;
  • Reduce threat to student;
  • Make learning environment varied and provide different lighting;
  • Create stimulating situations for brain development;
  • Have multiple resources available;
  • Be flexible, capitalize on teachable moment;
  • Provide active and passive places;
  • Give students personal space;
  • Use the community at large for learning;
  • Provide challenging and complex experiences with appropriate feedback;
  • Use music and art to tap into students’ emotions as natural conduits for remembering and connecting information;
  • Use diverse forms of assessment.

Awareness of Neuromyths

Effective brain based education requires a well-founded understanding of how the brain functions. The misunderstanding, distortion, or oversimplification of mind/brain science has led to the development of neuromyths. The Brain and Learning project of the Organization for Economic Cooperation and Development (OECD) define neuromyths as “a misconception generated by a misunderstanding, a misreading, or a misquoting of facts scientifically established (by brain research) to make a case for use of brain research in education and other contexts” (Dekker et al., 2012). There are many examples of neuromyths that have been perpetuated throughout society and have influenced education practices. One example has been referred to as the Mozart Effect. This effect suggested that exposure to classical music could increase IQ scores in children. This belief laid the foundation for many educational products to be developed despite opposing scientific data that determined the Mozart Effect to be scientifically invalid (Pasquinelli, 2012). It is suggested that teacher training include critical thinking and examination of scientific literature as a means of reducing misconceptions that exist. As Ansari and Coch (2006) point out teachers need to have a basic understanding of neuroscience to be informed and critical consumers of brain based strategies and programs. Improved communication between teachers and scientists could go a long way toward avoiding misconceptions. Interdisciplinary connection would allow for collaborative efforts and improved neuroscience literacy among teachers. It is also suggested that teacher training include neuroscience courses to support an enhanced understanding of scientific research (Lilienfeld et al., as cited in Dekker et al., 2012).

 (Video on the Mozart Effect).

Opposition to brain-based educational theory

For opponents of brain-based education, results from neuroscientific research have been oversimplified and inappropriately interpreted (Alferink and Farmer-Dougan, 2010; Ansari, 2005). To them, educators should be better informed of the limitations of neuroscience applications for education. In addition, there is little evidence to evaluate the effects of different educational methods on the functional and structural organization of the learning brain.

Localization theory

They view the use of data on function controls of brain hemispheres for educational techniques targeting one hemisphere as too vast a leap, and warn educators that such data was obtained primarily from participants with severed corpus callosum, and therefore, with atypical brain functions. In the opinion of Alferink and Farmer Dougan (2010), “Instructional activities that emphasize only the left brain while ignoring the right brain are not possible.”

Critical period for brain development

In their opinion, there is little evidence to suggest that early childhood is the most critical period for learning, as the causal link between the number of synapses or glucose uptake, and the rate or quality of learning have not been shown. For them, early learning is important because it is the basis on which to build later learning, but the focus must remain on the whole educational career. They also point out that the studies providing a time course of 0 to 3 years on synaptic density increases were conducted mostly on rhesus monkeys, and limited studies on humans have found a longer time frame. Moreover, neuroscientific research provides no information between synaptic density, emergence of skills and capacities, and the relationship between those and school learning. “In short, experience-expectant brain plasticity does not depend on specific experiences in specific environments, and for this reason, does not provide much guidance in choosing toys, preschools or early child-care policies. The experiences children need to develop fundamental sensory-motor and language skills occur in any normal environment.” (Bruer,1997)


Alferink, L.A. & Farmer-Dougan, V. (2010). Brain-(not) Based Education: Dangers of Misunderstanding and Misapplication of Neuroscience Research. Exceptionality, 18, 42-52
Anderson, V., Anderson, P., Northam, E., Jacobs, R. & Catroppa, C. (2001). Development of executive functions through late childhood and adolescence in an Australian sample. Developmental Neuropsychology, 20, 385-406.
Ansari, D. (2005). Paving the way towards meaningful interactions between neuroscience and education: Commentary on Blakemore & Frith 2005. Developmental Science, 8, 466.
Ansari, D., & Coch, D. (2006). Bridges over troubled waters: Education and cognitive neuroscience. Trends in Cognitive Sciences, 10(4), 146-151.
Blakemore, S.-J., & Frith, U. (2005). The learning brain: Lessons for Education: a précis. Developmental Science, 8, 459-471.
Bruer, J.T. (1997). Education and the Brain: A Bridge Too Far. Educational Researcher, 26 (8), 4-16.
Caine, R., & Caine, N. (1994). Making Connections: Teaching and the Human Brain. Somerset, NJ: Addison Wesley.
Dekker, S., Lee, N., Howard-Jones, P., & Jolles, J. (2012). Neuromyths in education: Prevalence and predictors of misconceptions among teachers. Front Psychol., 3, 1-8.
Ganis, G., Thompson, W.L., & Kosslyn, S.M. (2004). Brains areas underlying visual mental imagery and visual perception: an fMRI study. Brain Research: Cognitive Brain Research, 20 (2), 226-241
LeDoux, J., (1996). The Emotional Brain: The Mysterious Underpinnings of Emotional Life. New York, NY: Touchtone.
Maguire, E.A., Gadian, D.G., Johnsrude, I.S., Good, C.D., Ashburner, J., Frackowiak, R.S. & Frith, C.D. (2000). Navigation-related structural change in the hippocampi of taxi drivers. Proceedings of the National Academy of Science, USA, 97 (8), 831-836.
Maquet, P., Laureys, S., Peigneux, P., Fuchs, S., Petiau, C., Phillips, C., Aerts, J., Del Fiore, G., Degueldre, C., Meulemans, T., Luxen, A., Franck, G., Van Der Linden, M., Smith, C., & Cleeremans, A. (2000). Experience-dependent changes in cerebral activation during human REM sleep. Nature Neuroscience, 3 (8), 831–836.
Pasquinelli, E. (2012). Neuromyths: Why do they exist and persist? Mind, Brain, and Education, 6(2), 89-96.
Rizzolatti, G., Fadiga, L., Gallese, V. & Fogassi, L. (1996). Premotor cortex and the recognition of motor actions. BrainResearch: Cognitive Brain Research, 3 (2), 131-141.
Scovel, T. (1988). A Time to Speak: A Psycholinguistic Inquiry Into the Critical Period for Human Speech. Rowley, Mass.: Newbury House.
Springer, S.P. & Deutsch, G. (1993). Left Brain, Right Brain. (4th ed.). New York, NY: W.H. Freeman.
Sousa, D.A. (1998). Is the fuss about brain research justified? Education Week, 18, 52.
van Praag, H., Christie, B.R., Sejnowski, T.J., & Gage, F.H. (1999). Running enhances neurogenesis, learning, and long-term potentiation in mice. Proceedings of the National Academy of Science, USA, 96 (23), 13427–13431.
Willis, J. (2006). Memory, learning and test taking success. In Researched-based strategies to ignight student learning. Insights from a neurologist and classroom teacher . Viginia, USA: Association For Supervision And Curriculum Development.

Some book titles on Brain-Based Learning

Jensen, E. (2008). Brain-based learning: The New Paradim of Teaching. (2nd ed.). Thousand Oaks, CA: Corwin Press.

Connell, J.D. (2005). Brain-Based Strategies to Reach Every Learner. New York, NY: Scholastic.

Sprenger, M. (2006). Becoming a “Wiz” at Brain-Based Teaching. (2nd ed.). Thousand Oaks, CA: Corwin Press.

Caine, R.N. & Caine, G. (2011). Natural Learning for a connected World: Education, Technology, and the Human Brain. New York, NY: Teachers College Press.

Jensen, W. (2005). Teaching with the Brain in Mind. Alexandria, VA: . Association for Supervision and Curriculum Development.

Gardner, H. (2011). Frames of Mind: The Theory of Multiple Intelligences. (3rd ed.). New York, NY: Basic Books.

Levine, M. (2002). A Mind at a Time. New York, NY: Basic Books.

Willis, J. (2006). Research based strategies to ignite student learning. Alexandria, Virginia: Association For Supervision And Curriculum Development