The Social Brain and Education

Pieter Rossouw


doi: 10.12744/tnpt(5)092-100

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There is a growing interest in the link between the developing brain and maximising outcomes in schools.  Recent research indicates that students in many western countries tend to fall behind in ranking on global scales.  Every three years, since 2000, the Organization for Economic Co-Operation and Development (OECD) has provided a comparative report on the rankings of the knowledge of 15 year-olds in mathematics, reading, and science.  The 5th report, the 2012 Programme for International Student Assessment (PISA), was released late last year (OECD-PISA 2012).  This report is based on results from 510,000 students in 65 countries, aged between 15.3 and 16.2 years, and is representative of 28 million students in this age group, globally, and 80% of the world economy.  Demographic information was collected through questionnaires to students and school principals regarding the student’s background, the school, the learning environment, and school systems.  Some of the findings were:


Shanghai-China has the highest scores in mathematics, with a mean score of 613 points—119 points, or the equivalent of nearly three years of schooling, above the OECD average.  Singapore, Hong Kong-China, Chinese Taipei, Korea, Macao-China, Japan, Liechtenstein, Switzerland, and the Netherlands, in descending order, round out the top ten performers in mathematics.

Of the 64 countries and economies with trend data for the years 2003–2012, 25 countries improved in mathematics performance.

Across the OECD countries, an average of 13% of students are top performers in mathematics, achieving Levels 5 or 6; they can develop and work with models for complex situations, and work strategically using broad, well-developed thinking and reasoning skills.  The partner economy Shanghai-China has the largest proportion of students performing at these levels (55%), followed by Singapore (40%), Chinese Taipei (37%) and Hong Kong-China (34%).  At the same time, however, 23% of students in OECD countries, and 32% of students in all participating countries and economies, did not reach the baseline Level 2 in the PISA mathematics assessment.  At this level, students can extract relevant information from a single source and use basic algorithms, formulae, procedures, or conventions to solve problems involving whole numbers.

Between 2003 and 2012, Italy, Poland, and Portugal increased their share of top performers and simultaneously reduced their share of low performers in mathematics.

Boys perform better than girls in mathematics in only 38 out of the 65 countries and economies that participated in PISA 2012, and girls outperform boys in 5 countries.


Shanghai-China, Hong Kong-China, Singapore, Japan and Korea are the five highest-performing countries and economies in reading in PISA 2012.

Of the 64 countries and economies with comparable data throughout their participation in PISA, 32 improved their reading performance.

Across the OECD countries, 8% of students are top performers in reading, achieving Levels 5 or 6.  These students can handle texts that are unfamiliar in either form or content and conduct fine-grained analyses.  Shanghai-China has the largest proportion of top performers (25%) among all participating countries and economies.  More than 15% of students in Hong Kong-China, Japan, and Singapore are top performers in reading, as are more than 10% of students in Australia, Belgium, Canada, Finland, France, Ireland, Korea, Liechtenstein, New Zealand, Norway, Poland, and Chinese Taipei.

Between the 2000 and 2012 PISA assessments, Albania, Israel, and Poland increased their share of top performers and simultaneously reduced their share of low performers in reading.

Between 2000 and 2012 the gender gap in reading performance—favouring girls—widened in 11 countries.


Shanghai-China, Hong Kong-China, Singapore, Japan, and Finland are the top five performers in science in PISA 2012.

Between 2006 and 2012, Italy, Poland, and Qatar increased their share of top performers and simultaneously reduced their shares of low performers in science; and between 2009 and 2012, Estonia, Israel, and Singapore similarly increased their share of top performers, and simultaneously reduced their shares of low performers.

Across the OECD countries, 8% of students are top performers in science, achieving Levels 5 or 6.  These students can identify, explain and apply scientific knowledge (and knowledge about science) in a variety of complex life situations. (OECD-PISA 2012). Although the report is not without significant levels of criticism—for reasons such as the small scope of the study, types of questioning, philosophical changes in reading, reasoning, and the understanding of “utilizing” skills—its impact for policy makers, educators, and government systems is significant, both positively and negatively. For a country like Australia (to use one example), the PISA results are unwelcome news.  Compared to previous results, it seems Australian school rankings have slipped further behind in reading skills (equal 12th position), science (equal 17th position) and mathematics (19th position).  The best performers in terms of percentage change from earlier reports were Qatar, Romania, Shanghai-China, and Israel.  Overall, the five top performing countries are China, Singapore, Chinese Taipei, Korea, and Japan.

An analysis of annualised change in performance between 2003 and 2012 (mathematics scores) provides an important snapshot of a country’s global position and direction in terms of its education system on a larger platform.  The report divided the group into two subgroups: (a) countries that performed below the OECD average, and (b) countries that performed above the OECD average.

Of the countries below the OECD average, the best-performing were Brazil, Tunisia, Mexico, and Turkey, with the United States and Spain demonstrating no change.  Countries below the OECD average, and slipping even further behind, were Uruguay, Hungary, the Slovak Republic, Norway, and Luxemburg.

Of the countries above the OECD average, the best-performing countries (increasing their performance even further), were Germany, Macao-China, Hong Kong-China, Korea, and Japan. Countries above the OECD average that deteriorated in performance are Sweden, Finland, Czech Republic, New Zealand, Australia, Iceland, Denmark, Netherlands, Canada, France, and Belgium (OECD, 2013).

The chapter on Australia, written by Dr Sue Thomson, director of educational monitoring and research at the Australian Council for Educational Research (ACER), identifies unique variables within the country (Thomson, De Bortoli, & Buckley, 2013).  Students in city centres like Canberra, Sydney, and Melbourne performed much better than students from rural areas like the Northern Territory.  Students from wealthy backgrounds were five times more likely to perform well in comparison to students from lower socio-economic groups.  Students in independent schools performed significantly higher than students from public or Catholic schools; moreover, students from Catholic schools demonstrated the largest drop in performance for the reporting period (OECD-PISA 2012). The OECD report highlights important aspects of performance without addressing solutions. It is up to every economy and every country to consider the implications for its educational system. Sadly, the global outcry in terms of a solution is simple rhetoric: more money.  For Australia, Thomson argues that more taxpayer dollars need to be allocated to disadvantaged schools.  Although it is a clear reality that education demands a commitment—commitment in terms of resources, energy, hardware, and time—it is also the case that education is a science and an art: a science that needs to be well understood, constructed and executed, and an art in terms of student-teacher relationships, the nurturing school, and the socio-economic environment (or lack thereof).  Thus, the purpose of education needs to well formulated, its essence clearly grasped, and its outcome identified.

If the purpose of education is to be the best in mathematics and the best in reading or science, then an obvious question is: “How does one define being the best in a discipline?” followed by the equally challenging—and obvious—questions: “How do you measure these disciplines?” and “What are we measuring?  Static knowledge?  Skills?  Ability to apply?”

On top of this, there are the even more pressing questions: “What do we know about the learner?” and “Is the student an eager learner, keen to apply and explore his or her world with an open attitude to questioning, and progressing further than us, or is the student a reproducer who may become unstuck when strict support networks discontinue, or who becomes anxious in the wake of challenging environments?”

Reports like PISA 2012 are the result of an education philosophy based on an industrial model.  The industrial model was (and still is in many respects) a commercially-driven enterprise based on output.  Although the model is commercially successful, it operates on production output—like building Model T Fords and washing machines, or making chicken nuggets.  Thus, when the industrial model is applied to the education system, we develop a benchmark of the product (a “gold standard”) and measure the results against this standard, then we write a report stating who produces output above or below the standard, or who performs best and worst in terms of the group.  The subtitle of the PISA report: What 15-year-olds know and what they can do with what they know (OECD-PISA 2012), is its Achilles heel.  It implies that by asking questions solely with regard to three disciplines—mathematics, reading, and science—it is possible to predict outcomes based on what these 15-year-old students know.  There are no questions about an individual student’s approach to life, support systems and sense of self and safety, or their happiness and social interactions—or, indeed, the absence of any of these variables.  In this report, rating responses are measures as to whether a country, or economy, performs well or badly in terms of its education, and the students’ personal qualities are ignored.  The suggested solution—to enhance outcomes with more money—is an even greater cause for concern.

Neuroscience, the social brain and education.

The brain is much more than an organ pre-scripted by its genetic code.  The spectacular failures of evil doctrines like Hitler’s “Uberrasse” (Aryan race), or the generic “care” approach to rearing orphans in Romania after World War II, demonstrated beyond doubt that the brain needs more than just a genetic pool.  Neuroscientists like Eric Kandel (cf., Kandel, 1998, 2005, 2006; Kandel, Schwartz & Jessell, 2013); Rizolatti (Rizolatti & Craighero 2004), Joseph LeDoux (LeDoux, 2005), Marco Iacoboni (Iacoboni, 2008), and many others have clearly demonstrated the role of the environment in shaping and moulding the brain.  This process does not stop at any given point—the brain continues to grow and change as a result of daily interactions with its environment.  These daily interactions form the basis of what drives a human being to learn, integrate, explore, and thrive.  Trauma, fear, and risk of survival change these motivations—they do not stop development, but they do change it (Rossouw, 2013).  This crucial point is often missed—that compromised environments (as opposed to enriched environments) alter the course of neural development and trigger changes in memory systems.  This does not indicate the absence of memory systems but it does indicate a different direction for them.  When performance is measured, therefore, the results may seem comparable but the sources—what drive the system—could be vastly different, especially in terms of long-term outcomes.

The Primitive Neural Complex

The brain develops from the bottom to the top, and from the inside out.  The well-known model of neural development by neurologist Paul MacLean, the “triune brain” (MacLean, 1990), showed that the first areas of the brain to develop after conception are the very primitive systems, specifically the systems that are responsible for survival (breathing, heart rate, the ability to procreate), which  he refers to as the reptilian brain—the brain stem, pons, medulla, and part of the cerebellum.  We share this with all living organisms.  This part of the brain is fully developed at birth.  It is also fully functional.  If any of these systems are compromised the entire living unit is in grave danger of not surviving.

The Paleomammalian Brain/Cortex

The second part of the brain that develops is the mid-brain, the structures below the corpus callosum.  These structures—the thalamus, amygdala, hypothalamus, hippocampus (often referred to as the limbic system) and the basal ganglia—are jointly responsible for the activation of patterns of sensory responses to external cues, and set the trajectory of protection—the stress response.  This neural section is fully developed but not fully operational at birth.  The implications are significant, and are closely linked to genetic expression—the interplay between genetic make-up and environmental impact.  When the external environment provides safe, secure, and manageable cues, the stress response is limited, and neural activation develops open neural pathways to frontal cortical areas.  Conversely, compromised environmental cues enhance the risk of neural patterns of avoidance to facilitate patterns of neural protection (MacLean, 1990).

The result is decreased social development, which compromises frontal cortical activation.  In both situations—enriched environments and compromised environments—memory systems are activated.  The nature of these networks are unique in nature.  On the one hand, to enhance survival, memory systems linked to threat (due to threatening cues), lead to fear-based (closed) reactions.  On the other hand, memory systems linked to enriched environments lead to open neural patterns, increased cortical blood flow to frontal cortical areas, and enhanced, ongoing problem-solving capacities.

Fear-based learning is learning that focuses on limbic activation.  The response—increased blood flow to limbic areas and reduction of cortical blood flow—is nearly immediate, due to the nature of the threat, and learning is quick.  The downside is that it remains a survival response, therefore, as soon as a threat occurs, it will happen.  This is protective/survival learning.  Consider a student who learns mathematics through a fear-based system: the student may perform well in the subject due to fear, however, as soon as they are able to choose, they drop the subject in accordance with the pattern of avoidance.  On the other hand, learning that is facilitated from higher cortical regions when primitive (survival) regions are down-regulated (controlled), will flourish (Allison & Rossouw, 2013).

Fear-based learning (memory systems) is much more powerful than open neural activation, due to the basic human need to survive, but the downside is a neurochemical detriment to the system—due to ongoing release of stress chemicals—and long-term performance deterioration, even apoptosis in some cases.  Measures of performance (memory networks) that do not include neural patterns (limbic-based or frontal cortical-based activation), neurochemical activations (increased serotonin flow, norepinephrine, corticotrophin releasing factor, adrenocorticotrophin hormone, cortisol level), and long-term performance and neural integration, lack key variables to provide effective comparisons.

The Neomammalian Brain/Cortex

The cortical regions of the brain are the last to develop.  This is the largest part of the cortical mass, and most connections occur after birth.  The brain then continues to organise and re-organise itself as a result of information processing—both from the external environment and later from the complex interplay between environmental stimuli and frontal cortical processing (right and left prefrontal cortex, anterior cingulate, and orbitofrontal areas).  Processing of neural pathways to the cortical regions—especially the frontal cortical regions—happens in close collaboration with the more primitive regions (Grawe, 2007).

When primitive, fear-based, survival patterns are activated, the memory systems respond according to fear-based patterns.  For example, when a soldier is trained to take cover as soon as he or she hears the sound of a gun, then it is a survival memory system that kicks in automatically without activating the frontal cortical regions.  This is a perfectly acceptable action for survival.  However, if the same soldier is sitting in a shopping mall, and a cleaner drops a bucket of water close by, and the soldier dives for cover, people will understandably be surprised by the behaviour.  Clearly, instinctive, survival-based responses are not especially helpful in enriched environments—consider people with phobias for lifts or the inability to cross a road because of a panic attack.  A pedagogical system that is based on fear may produce good outcomes in the short term, reflecting immediate responses that are deeply ingrained; nevertheless, effective applications are compromised because the response is fear based (Grawe, 2007).

Enriched environments are environments where stress can be tolerated—the concept of “controllable incongruence”.  Memory systems are formed when a pattern of neural activation is stimulated.  New memory systems are formed when new stimuli activate new pathways.  When these new pathways are stimulated, they establish incongruence to existing systems—that is, the onset of the stress response, when stress chemicals are released.  The main stress chemicals are: corticotrophin releasing factor, norepinephrine, adrenocorticotrophin hormone, adrenalin, and cortisol (Barnes, 2010).  When the stressor is manageable, it leads to cortical activation and the formation of memory networks towards the frontal cortical systems (especially the prefrontal cortex).  This process is referred to as controllable incongruence (Allison & Rossouw, 2013).  When the stressor impact is significant, shifting cortical blood flow towards the limbic areas and down-regulating  activation to frontal areas, memory systems are enhanced in fear-based regions, and patterns of survival and avoidance present.  This is the result of uncontrollable incongruence.  Learning takes place in both cases but the processes and long-term outcomes are very different.


The developing brain points towards important variables that need to be taken into account in terms of the provision and planning of effective education systems.  In this view, the fundamental variables are not the outcomes but the basics—a fundamental approach that facilitates a trajectory in neural development.  A measurement of performance at a specific point in time, such as the knowledge of 15-year-olds in mathematics, reading, and science bears no relation to an individual’s or, for that matter, a group’s performance over time, and provides even less information about the system—whether it is fear-based or open-approach—in which the performance is achieved.

The table above, which shows averaged scores in one subject from three countries (dubbed Country A, Country B, and Country C), describes the difficulty with single-point analysis.  The average can be correlated to the previous survey three years before, providing information on whether the average is up or down, and has some specific value.  However, in terms of the individual learner the score has no relevance; besides, the trajectory of performance can go in any direction—up, down or sideways—because no data is available, as the arbitrary lines indicate.  More importantly, there is no data as to the driver or motivator of the performance—either it is fear based, driven by limbic activation and stress chemicals, or it is exploratory based, driven by open neural activation in the prefrontal cortex.  Although the PISA reports have specific merit, they can by no means be a guide to addressing apparent defects in the education system.  The principles of learning and memory formation, the developing brain, and basic human needs for neural proliferation and wellness are both more fundamental and better able to provide a much clearer picture in the quest to enhance wellness and maximise capacity.

Indicators for Wellness and Capacity Maximisation

The key indicators for wellness and capacity maximization in education from a neuroscientific perspective are:

  • The need for a supportive teacher-student relationship.  This is the essential hallmark of effective education.  Without the facilitation of an effective relationship (addressing the basic need for attachment in the educational environment) primitive fear based systems are not effectively down-regulated and cortical sprouting inhibited (Schenk, 2011).
  • The need to increase latency periods when engaging with students.  Latency is described as the period of time that elapses between a student being given an opportunity to respond and when that opportunity is discontinued or interrupted.  This is a well-known phenomenon that has been around for decades: the research indicates that smarter or more popular students are given longer latency periods than less smart or less well-liked students (Schenck, 2011).
  • Ask open questions rather than direct questions.  Direct questions up-regulate a sense of distress.  Even when a teacher asks a particular student a question, and the teacher is quite certain that that student can effectively address the question, the fear response increases for other students less comfortable with the answer.  On the other hand, open questions with hints and clues increase interest, collaboration, and safety (Allison & Rossouw, 2013).
  • Encouragement.  Encouragement has significant neurobiological effects.  It enhances the student teacher relationship (down-regulating the primitive responses and up-regulating cortical sprouting); it increases motivation which leads to more neural activation (rather than to give up and discontinue neural firing); motivation also increases the release of endorphins and dopamine (key neurotransmitters) to assist with completion of tasks and enhance plasticity through ongoing engagement, thus strengthening neural patterns (Rossouw, 2013).
  • Respect.  A demonstration of respect has significant neural effects.  In particular, it enhances a sense of survival (being accepted) and inhibits fear.  It also encourages patterns of engagement and, as a result, facilitates neural activation to the frontal cortical areas—the key to social and cognitive development (Allison & Rossouw, 2013).
  • Enthusiasm and passion.  Studies on mirror neurons have demonstrated that humans learn many skills by observation.  This can be helpful or detrimental, depending on the environment, and in education settings the role of the teacher is pivotal in facilitating the learning environment.  Consequently, a teacher who demonstrates enthusiasm, and teaches with passion, facilitates similar responses in students and enhances learning outcomes (Rizolatti & Craighero, 2004).  Conversely, the opposite is also true.
  • Provide an enriched environment.  The ultimate goal of enhanced learning environments is to provide an enriched environment.  This is much more than a physical environment that provides access to all possible (electronic) media.  On both physical and emotional levels, an enriched environment means that safety needs to be present (Cozolino, 2013).  This means, first and foremost, the need for a trustworthy environment—that is, the absence of fear, bullying and violence, and the presence of emotional warmth, acceptance, and a sense of belonging (Tokuhama-Espinoza , 2011).  An enriched environment is an environment where the child can develop, laugh, play, and thrive.  It is an environment where there is a seamless collaboration between home and school (Grawe, 2007).



The PISA report has significant benefits.  It provides:

  1. a snapshot of what 15-year-olds know in terms of a fixed subset of items for reading, mathematics, and science;
  2. a snapshot of what 15-year-olds know in terms of this fixed subset of items in comparison to each other, both within countries and economies and between countries and economies; anda snapshot of what 15-year-olds know in terms of this fixed subset of items in comparison to another fixed subset of items every three years (within and between economies and countries).

However, the report fails to address:

  1. how this information will translate to applications of the current information basis (“knowledge”);
  2. whether the learner has obtained the information through fear-based activation or an enriched environment; and
  3. the wellness factor of neural development.


What students know, and what they can do with it, is more than a measure of information retention.  The development of the brain is a socially and environmentally-driven interaction that requires a close, holistic look at the social system in order to be able to make predictions like “what they can do” (Cozolino, 2013).  This is most likely the reason why simple solutions (such as recommending more money) are doomed to fail, if they are not driven by a socially responsible agenda with a clear understanding of both the challenges and the potential of the interactive developing brain.



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Rossouw, P. J. (2013, July). The effects of bullying on the developing brain: Strategies for effective interventions. Proceedings of Conference, No 2 Bullying: Workplace, school and cyberbullying. Retrieved from Schenck, J. (2011). Teaching and the adolescent brain. New York, NY: W. W. Norton.

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Tokuhama-Espinoza, T. (2011). Mind, brain, and education science: A comprehensive guide to  the new brain-based teaching. New York, NY: W. W. Norton.

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