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Crystalizing Potential
“Learning is what most adults will do for a living in the
21st century”
– Alfred Edward Perlman
You were born, and it began.

The acquisition of knowledge and information, feelings and
behaviors that would combine over years to shape who you are
right now. Were you to look at your progress through those
newborn eyes, the feat would surely have appeared
insurmountable: the fine motor skills that allow you to
write and eat, the ability to speak and comprehend language,
the development of complex social relationships, education,
professional skills and so on.

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So, in the beginning was life and then there was learning
and, for the duration of our existence, there is life-long

In this paper, we explore the neuro-scientific underpinnings
of the learning process, factors that hinder or limit our
learning ability, including ways to optimise this most
fundamental attribute of being human.

Part One: How we learn
Neural networks and neuroplasticity
Use it or lose it
Motivation, failure and learning
Conditions for learning
Part Two: Limitations to learning
Prefrontal cortex limitations
Learning barriers
Part Three: Implications for best practices
Learning today
A model for learning
– Attention
– Generation
– Emotion
– Spacing
Stress and learning
Informal & collaborative learning
Technology and learning

Continual stimulation of neural pathways keeps them healthy and active
Part One: How we learn
Neural networks and neuroplasticity
The human infant is born with approximately 100 billion brain cells, or
neurons. That number remains relatively stable throughout life, a fact that
has contributed to the long-held belief that the brain is fixed, or hard-
wired, particularly post-adolescence. However, what is far from formed at
birth and continues and changes throughout life, are the tens of thousands
of connections that form between each one of these 100 billion neurons. The
creation of these connections form neural networks and their continual
restructuring and change is known as neuroplasticity.

A neuron is a single cell, with a cell body, or soma, that houses the DNA
and proteins that guide its functioning. Each neuron has one axon that
sends messages and many thousands of dendrites that receive messages.

Dendrites appear like the branches of a tree, with more branches
representative of more connections. These connections represent learning.

On its own, a single neuron can achieve nothing – it takes many thousands
combined to generate every action, thought or memory we have. Neurons,
therefore, need to relate to other neurons. They achieve this by sending
electrical signals along their axon, which, upon reaching a threshold,
release neuro-chemicals into the gap, or synapse, between two neurons. If
the dendrites of the receiving neuron have the appropriate chemical
receptors, a connection will be formed that results in the receiving neuron
firing its own electrical charge, which will be received by yet another
neuron and, so, on goes the flow. One of the founders of modern
neuroscience, Donald Hebb, showed that neurons that continued to activate
one another in this way strengthened their connections, like a path through
a forest. “Neurons that fire together, wire together” became Hebb’s Law and
is a fundamental principle to how we learn1.

In this way, our brains develop neural networks that embed and store our
learning. You have neural networks for every conceivable object, person,
animal and situation you have ever encountered. The neural network for your
perception of an orange will involve cells in different areas of your brain
that code for the type, shape, feel, size, smell and taste of an orange,
along with whether or not you like oranges, when and where you last had
one, ways to use them, as well as abstract variants, like the colour
orange. It takes thousands of connected neurons in a neural network for
‘orange’ to create this representation each time you see, think about or
just hear the word, ‘orange’. And that’s just an orange.

Your perceptions change over time. You acquire new information that adds to
or changes what you know about things and people in your world, or how you
feel about them. For example, a colleague may, surprisingly, disappoint you
in their response to an issue and this gives you a new insight into their
motivation or agenda. This new information requires your own neural network
of this colleague to change – literally, physiologically change – in order
for you to process it. This change shows the plasticity, or adaptability,
of your neural connections and occurs thousands of times each day as you
experience your world – at both conscious and subconscious levels.

Neural networks will be formed for everything to which we pay attention and
nothing that we don’t. Due to the vast amounts of information we encounter
each day, we have evolved to selectively place our attention on only
stimuli that are interesting or meaningful to us. Attention is the filter
through which we see the world and accounts for why two people, observing
the same situation, may have quite differing recollections of it: we
literally see differently, based on what we attend to.

Attention requires focused concentration and is a prerequisite for neurons
to be activated and neural networks to be forged. Forging new networks is
energy-intensive and our brains are not designed to remain attentive for
long periods of time. The brain needs down-time at regular intervals to
rest and re-focus. During this time, it is also strengthening the newly-
formed connections. When we push ourselves to focus beyond our natural
limits, our concentration wanes, which is our brain’s way of forcing a
break – and we catch ourselves daydreaming.

When we pay attention, memories are formed, stored and recalled in a
complex process that engages numerous regions of the brain. Without memory,
there is no learning. Studies of patients with hippocampal damage (the
brain region most strongly associated with the formation of new memories)
show severe impairment of memory function. Such is the case of ‘H.M.’, who
lost all declarative memory following the removal of his hippocampus as
part of surgery to alleviate severe and chronic epilepsy2. As a result,
H.M. could learn nothing new, including who he had just met, or the
conversation he had just had, because information held in his short term
memory was never transferred to long term memory.

Memory is typically described as a three-part process of encoding, storage
and retrieval. Incoming data is held in short term, or working, memory and
will be quickly lost if not consolidated. How well we encode a memory is
critical to how effectively we will be able to recall it at a future point.

Failure to learn can be a function of shortcomings at any of the three
stages in the memory process.

Recent functional magnetic resonance imaging (fMRI) studies show the
important role of the neurotransmitter, dopamine, in the learning process.

Dopamine is the brain’s chemical reward and is triggered in response to
positive feedback during the learning process. So, when we eat in response
to hunger, feel the warmth of the sun, or receive a smile for an action
taken, the brain releases
a short dopamine burst to signal its pleasure and give us a quick reward
for gaining it. This dopamine reward mechanism serves to reinforce the
neural connections in the associated network, strengthening it with each
repetition of the thought or behaviour that caused it3. This is the
biological process that embeds learning.

Use it or lose it
The good (even great) news about neurons is that there is now clear
evidence of the birth of new cells replacing old ones, particularly in the
memory centers of our brain, even into late adulthood4.

This is the process of ‘neurogenesis’ and counters the previous belief that
we only lose brain cells and never grow new ones. This is one of the
profound findings of recent neuroscience and carries very positive
implications for our learning and development over time. Neurogenesis in
the hippocampus means that we are capable not only of continually extending
the connections between neurons as we learn, but even adding additional
ones, which has been shown to occur as a result of both physical and mental

The not so good news is, like the muscles in our body, the ‘use it or lose
it’ principle also applies to our brain cells. Continual stimulation of
neural pathways keeps them healthy and active, but connections weaken and
recede through lack of activation. This cell atrophy is observed as we age
and is accelerated by a sedentary and unstimulating lifestyle. So,
neuroplasticity has a ‘reverse’ function. To guard against this, continual
mental stimulation, or learning, is essential.

Short Term Memory
(working memory)
Long Term Memory
|Declarative |Non-Declarati|
|Memory|ve Memory|
|(explicit| |
|memory)| |
|| |
| |Episodic || |
| |Memory|| |
|c||l Memory |
|Memory |||
| |(experienc||
| |es, ||
| |events,||
|(facts/|locations)|(learned |
|ge)||skills, |
| ||habits, |
| ||abilities|
| ||) |

Our learning environment must address the physical, cognitive and emotional
elements in that environment
Motivation, failure and learning
Learning is not isolated to positive reinforcement: much of our learning
comes from trial and error. As infants, we are learning the basics of how
to live and we make numerous mistakes along the way. Being able to fail and
learn from failure is an essential component of constructive learning.

Harvard psychologist, Tal Ben Shahar, cites fear of failure, resulting from
often unrealistic and perfectionist demands, as being one of the key
detractors from learning, leading to lack of creativity and

Conditions for learning
Under what conditions are learning outcomes optimised? Current approaches
recognise that the dichotomy of mind and body is unnatural and, instead,
emphasise the integration of the whole. In this context, learning at this
level of cognition must be supported by the environmental, physiological
and emotional conditions conducive to its uptake.

Imagine two individuals in two different learning contexts, where the goal
in both is the acquisition of a new skill; learning to read Braille. Both
students come to the task with equivalent cognitive profiles. Student A is
provided with a complex manual, a passage in Braille, seated in a cold
classroom with no support, no intrinsic motivation for learning this task
and approaches it with anxiety and apprehension. Student B is provided the
same materials, a supportive teacher, a comfortable and familiar setting
and is motivated and enthusiastic about assisting his vision-impaired
sister to learn to read. Who is more likely to master this task? The answer
will not be determined by the cognitive ability of the two students alone,
their learning occurs in a broader context.

Holistic learning recognises that the brain not only interacts with
incoming information, but with the entire context in which it is presented.

To this end, our learning environment must address the physical, cognitive
and emotional elements in that environment.

Many studies have highlighted the importance of nutrition in healthy
physical and mental development. The brain draws approximately 20% of the
body’s available energy and increased mental demands draw more oxygenated
blood into the brain as neurons need fuel to fire. Dehydration and low
glucose levels drain the body and the brain of its functional necessities
and, in turn, inhibit the learning process.

Recent neuroscientific research points to the role of sleep in memory
consolidation. Studies have shown that hippocampal neurons activated during
learning tasks are reactivated during slow wave sleep, reinforcing the
neural network and consolidating the learning. In a study requiring
participants to learn routes through unfamiliar streets, performance, as
measured by error rates in the task, was significantly lower for those who
had benefited from sleep6. Other studies focusing on sleep loss provide
clear evidence for lower academic performance caused by reductions in both
declarative and procedural memory, suggesting that the prefrontal cortex is
highly sensitive to sleep deprivation7. So, regular good quality sleep is a
precursor for memory and learning.

Learning is a resource-hungry brain activity and there are limits to our
capacity to digest and store new material. There is a cost that comes with
learning something: it takes the resources required for something else.

Adult learning, in particular, requires that we channel our available
resources to meet all the learning demands in our environment. We have any
number of concurrent projects: related to family, work or career, leisure
activities and
Emotions are integral to thinking and learning. The amygdala, a small
almond-shaped part of our inner brain, is the seat of emotions and elicits
the emotional response component of our behaviour. Amygdala activation
during the encoding of a new memory enhances its subsequent retrieval10.

This means that emotional cues linked to learning content forge a deeper
and richer neural pathway than fact-based content alone.

We do not recall memories: we reconstruct them.

The working assumption has been that we store memories in a ‘fixed’ form,
like video footage of our experiences – then replay the tape when we
recall that memory. Emerging research shows that we reconstruct our
memories each time we draw on them. And because the brain is plastic, each
memory is influenced by our experiences since we stored it, our current
context, and our psychological predispositions. In this regard, our
memories are ‘unstable’ or fluid.

spiritual interests, all of which require the continual integration of new
information, people, processes and other demands. All these activities
compete for our available cognitive capacity, so personal motivation and
commitment are hallmarks of effective adult learning. This is why self-
directed learning is such a key principle of adult learning8.

Exercising our cognitive ‘muscle’ by building more and advanced neural
networks is core to our mental fitness and also acts as a barrier to cell
in later life. Cognitive reserve, the building of vast neural networks as a
result of ongoing education and mental challenge, is shown to accrue over
time and provide some insurance against mental decline in older age9.

Further than amplifying memories and consequently learning, new research
highlights that emotions are actually fundamental to cognition itself.

Emotion regulates where we place our attention, and therefore is essential
to recruiting the neural networks on which we build our knowledge. In our
earlier example of learning Braille, emotion (the student’s desire to
assist his sister) generates the motivation to focus his attention on the
task. In this way, emotion and thinking are integrally linked.

Not much of our learning occurs in isolation. Our need for
social interaction is biologically based and fundamental
to our survival, as well as learning. Throughout our
childhood and adolescent years, we learn through direct
experiences or observation of others, as well as being
taught in social establishments, such as schools and
colleges. Through these means, we not only create new
learning, but we test and validate our thinking. Learning
communities reinforce learning outcomes, increase
motivation and challenge and generate more diverse
solutions than individuals operating alone.

Metacognition: thinking about thinking
Want to have an impact on someone’s career or life? Help them think

Too often we rush in to help solve the problem, but that’s my solution,
not yours – it may not be right for you at all. More often than not, when
someone asks for help, they don’t want an answer, they’re just at an
impasse,”What next? Why doesn’t this work? How should I deal with this
person?”. By developing better thinking practices in others, typically by
asking great questions, we build their confidence and capability.

Encourage others to think.

Part Two: Limitations to learning
Prefrontal cortex capacity
The prefrontal cortex is the highest evolved part of the
mammalian brain and is
larger in humans, relative to body size, than all other
mammals. It is the seat of
our ‘executive function’ – our ability to think
consciously, plan, organise, analyse,
make decisions and comprehend complex information and
relationships – it’s what
makes us human. Many scientists believe the prefrontal
cortex is still evolving
and, consequently, has not yet reached the maturity and
capability of the older
regions of our brain. This, coupled with the phenomenal
change in human social
conditions in the past two centuries, including the
availability and need for much
more information on a daily
basis, is testing the limits of our
prefrontal capacity.

The sheer volume of information
to which we are exposed is a
significant challenge for our
processing capabilities. Neurons in
the prefrontal cortex can process
approximately 2,000 units of
data per second – impressive, but
it seems we need much more.

Further, the prefrontal cortex
operates via serial processing –
one step at a time – so speed of
processing is slower than other
parts of the brain, which utilise
distributed processing, and can
deal with multiplicity.

Studies of memory have estimated our abilities at more conservative levels
than was previously assumed. The popular belief that we can store seven,
plus or minus two, pieces of data (such as words or numbers) have been more
recently revised to four and even that figure is challenged when the data
to be memorised is anything complex
or abstract11. Memory degradation, leading to compromised recall, occurs
when we attempt any two cognitive tasks concurrently. This has significant
ramifications in our multi-tasking world.

Our biological limitations represent a relatively fixed constraint on
learning – our perceptions and interpretation of our environment is a
limitation that is much more variable. Stress, like love, is in the eyes of
the beholder: two individuals experiencing the same stressful scenario may
respond very differently. One may deal with it pragmatically and focus on
the opportunities it presents, the other feels paralysed with uncertainty,
frets and procrastinates. It all depends on our perceptions.

The Yerkes-Dodson optimal arousal curve12 explains the relationship between
stress, or arousal, and levels of performance (see below). Optimal
performance is achieved at the mid-point and peak of the curve. This point
is characterized by a level of arousal sufficient to engage and focus the
individual, optimising their skills and creating a mentally stimulating
state. Below the mid-point, performance declines as a result of
insufficient arousal – caused by the levels of challenge being too low to
stimulate interest. Above the mid-point, the challenge becomes increasingly
steep and arousal builds to levels that induce stress and anxiety, caused
the task being beyond the skills, capability and/ or comfort of the
individual. To feel engaged and stimulated by our work and life generally,
a state of optimal arousal is necessary.

|OF| ||||Optimal level|
|PE| |||| |
|RF| |||| |
|OR| |||| |
|MA| |||| |
|NC| |||| |
|E | |||| |
| | ||Mild|||Stress|
| | ||alertne||||
| | ||ss||||
| | || ||||
|QU| |Boredom||||Anxiety |
|AL| ||||| |
|IT| ||||| |
|Y | ||||| |
| |Sleep |||||Pani|
| | |||||c|
| | ||||||
The result is that modern humans too frequently experience chronic states
of stress. This puts us into the over-arousal half of the optimal arousal
curve and is clearly not ideal for high performance. In a state of stress,
our high energy-consuming prefrontal cortex shuts down to allow the limbic
system and body to command the resources required for survival, so we stop

Neuroscience has provided insights into what occurs in our brains during
periods of under, or over, arousal. Stress invokes our limbic system, which
is instinctive, automatic and prepares us for a ‘fight/flight/freeze’
response. Our brains evolved this response for survival, so that when
confronted with a life-threatening situation, our bodies would instantly
redirect our energy and resources away from functions such as digestion,
cell repair and thinking, to mobilising our limbs and torso and
Rational thinking has not developed fully in the adolescent brain
Teenagers’ brains are still maturing and the prefrontal cortex is not
fully developed until late adolescence, even into the early 20s in some.

It requires an adult brain to apply full logic and reason, have mindful
insight and be able to reflect critically on thoughts and behaviors.

Parents will say this explains a lot! It does make you wonder about the
expectations we have, as well as responsibilities we give, to teenagers.

allow us to make a life-saving getaway. It served us well when we were
under regular threat, hunting and gathering on the African savannah and was
designed to have a short, sharp effect and cease when the immediate threat
was overcome13. Our environment has changed dramatically since then, but
our brains have not discarded this ancient survival infrastructure. Rather,
they now apply it in all sorts of, often inappropriate, situations.

Worse still are the potential far-reaching effects on both
mental and physical health that result. ‘Allostatic load’
is used to describe the wear and tear effects of prolonged
stress on the body. High allostatic load leads to impaired
immune function, loss of brain cells in the hippocampus
and prefrontal cortex and growth of the amygdala (or fear
function). Over time, this leads to high blood pressure,
diabetes, osteoporosis, accelerates the aging process and
predisposes us to dementia – we need to contain allostatic

Aha! The moment of insight
The brain can work in mysterious ways. You might be battling with an issue
and forcing all your mental energy on it, without resolution. You’ve brain-
stormed it, repeatedly analysed it, tossed around numerous options –
nothing. Then, one morning, while not even thinking about it, the perfect
answer just comes to you, perhaps in the shower – “aha”! The “aha moment”
is the subject of much neuroscience research. So far, we know that a
spontaneous insight requires a restful state (alpha waves) and a new
neural network created by combining information from numerous, often
unrelated, distributed memories.

Learning barriers
Adults learn by building on existing neural maps, or
networks. Knowledge acquisition is dependent on what has
already been acquired. There are three dimensions to
learning and there are potential barriers that can
interfere with the learning process in each of these
1. Content
What we are about to learn must engage us to focus and
hold our attention and apply prefrontal cognition. With
insufficient concentration, neural networks are weak
and/or incomplete and fail to form adequately, in order to
embed the learning.

2. Incentive
Why we want to learn anything new must align to our
motivation. This becomes a barrier if the individual does
not perceive the value, lacks interest, is overwhelmed or
is fearful of change. In any of these cases, there is no
intrinsic incentive to learn and the dopamine reward
mechanisms, necessary to stimulate and reinforce learning,
fail to be activated.

3. Social
Who is involved in our learning is a critical factor for
our social brain. Quality and quantity of communication,
as well as interaction and support, play a direct role in
learning uptake. Think about your best teachers, coaches
or mentors – they inspire learning and are exhilarating.

Conversely, when we have been in unsupportive environments
or unproductive teams, learning outcomes are compromised.

Learning is a dynamic and complex process thatis
sensitive to many facets that can limit its effectiveness.

Through conscious awareness of theseandproactive
mitigating strategies, we can enhance our own and others’

Part Three: Implications for best practices
Learning today
Participation rates in adult education and training in the Western world
have been growing consistently over the past 25 years. Nordic countries,
including Denmark, Finland, Iceland and Norway, are close to, or exceeding,
50% participation rates. In Anglo-Saxon countries, including USA, UK,
Canada, Australia and New Zealand, it is between 35%-50% (although recent
data is showing the USA now moving into the above 50% category). In other
European countries, the rates vary from 35% to below 20%, with northern
European countries showing higher participation rates15.

Although economic conditions have certainly impacted organisations’
capacity for funding development programs, the critical business issues of
leadership bench strength, accelerating the development of high potentials
and building the core competencies of strategic thinking and inspiring
others, remain top of the list for organisations across all industries16.

Organisations leading the field in learning practices must integrate;
. innovative content
. engaging instruction
. blended methods
. interactive technology
. business alignment
. robust measurement
. program management17
No wonder few people can claim to be comprehensive role-models!
Notwithstanding, organisations recognise the need to invest in their talent
in order to equip them with the requisite skills for high performance.

A model for learning
The field of neuroscience is providing both insights and pragmatic
guidelines for the enhancement of learning and development practices. One
example is the work of Lila Davachi, Associate Professor of Psychology at
New York University, who offers the acronym AGES to highlight four key
criteria that her research has shown to be necessary for effective
A Attention
Focused concentration on the task or concept without distraction
G Generation
Learner to have direct interaction with the learning task to
generate their own thinking
E Emotion
Emotional cues associated with the learning task
S Spacing
Adequate time gaps for new learning to be digested, consolidated
and rehearsed

Learning something new requires focused attention. To learn new
information, it must be of interest or meaningful and there must be limited

Multi-tasking requires that we attend to more than one thing at a time.

Although it is physically possible to multi-task, studies show that
performance on each additional task, including the first, reduces.

So, multi-tasking comes at the expense of time to complete the task, or,
quality of the output. Furthermore, it is almost impossible to learn
something new whilst multi-tasking. This suggests that multi-tasking is
best suited to habitual behaviors that require little or no cognitive

A recent behavioral study of three generations of Americans showed an
increasing, progressive trend toward multi-tasking from Baby-Boomers, to
Generation X and the ‘Net’ Generation, although cognitive limitations
remained the same18. Tests of ‘dual task interference’, the subsequent
reduction in performance by having one task interfere with another,
continually provide evidence that multi-tasking compromises performance
outcomes19, although one recent study does show that participants with
higher than average working memory capacity do perform better than others
in multi-tasking activities20.

The implication for designers of learning and development programs is that
learners need to be in an environment that encourages and allows single
matter concentration for most powerful learning uptake.

Adult learning differs markedly from childhood learning. Children absorb
everything about their world in an uncensored way and place total
confidence in the adults around them. Adults selectively choose what they
learn based on what is relevant and of interest to them. Adults build on
prior learning and take as much responsibility as they want for their
ongoing learning21. As a result, self-directed learning methods are highly
effective in adults.

“The brain is a dynamic, plastic, experience-dependent, social and
affective organ” and is not just engaged in, but driving, its own
learning22. By extension, the more the brain is proactively involved in its
learning, the more effective it becomes. This is why the self-generation of
ideas, strategies and actions is so critical in adult learning. With the
focus on relevance and immediacy, adults learn best by taking a problem-
centered, rather than a subject-centered, approach23. This includes
defining and analysing the problem, challenging the learners’ thinking,
determining approaches to its resolution and encouraging team debate. The
key is that ownership of the process, as well as its outcomes, is with the

Emotions bind memory. Like adding fuel to a flame, an emotional cue ignites
more neuronal activity in more brain centers and, consequently, burns a
deeper pathway. Everyone, for example, knows where they were and what they
were doing on September 11, 2001, but where were you and what were you
doing the day before? The vivid recollections we have of events in our life
that carry rich emotional content are embedded through the activity of many
thousands more neurons than is the case for ‘normal’ or unemotive events.

Emotion, of course, does not need to be negative. We learn better when we
are in a happy, positive mood and when we are having fun. Research, for
example, shows that including games in learning programs with relevant
context, requiring challenging technical skills and appropriately debriefed
on completion, add to the learning outcomes of all four of the Kolb
learning styles (concrete experiences, reflective observation, abstract
conceptualisation and active experimentation)24.

A relatively simply, but underutilised, way of improving learning outcomes
is to reconsider how we ‘space’ content. The limitations to prefrontal
cortex capacity come into direct play when we are learning, as new
information must take this route to be embedded as acquired skills and
knowledge. So, learning programs that begin at 8:30am and cram content back-
to-back until 5:30pm, with only brief comfort and food breaks, actually
contravene our biological limitations and invariably limit learning uptake.

The law of diminishing returns applies to learning due to our cognitive
capacity. We need to respect our biology more and work with, not against,
its limitations.

With this in mind, program designers should consider staging learning
content – within and across days. For example, a leadership program that
introduces new content, such as leadership models, in the morning session,
then applies this content all afternoon in interactive and engaging ways,
will achieve a much better learning outcome than a full day of new content
alone. Programs that stagger sessions over consecutive or even intermittent
days allow for the benefits of memory consolidation during sleep to improve

Stress and learning
The biological evidence is clear: stress and learning do
not mix. Although stress is a subjective response and
will, therefore, vary by individual, program designers
should aim to minimise potential stress by:
. ensuring content is pitched at a level that is
challenging, but within the capability of the target
. providing a supportive environment in which ‘failure’ is
part of the experience and not to be feared
. ensuring adequate food, water, light, temperature,
ventilation and physical space to meet physiological
. adding ‘brain breaks’ for mental rest and physical
activity for re-oxygenation
. ensuring the audience can relax, laugh and interact

Mindfulness versus mindlessness
The growing field of mindfulness is drawing a biological link between the
realms of science and spirituality. With its origins in Buddhist
meditation, fMRI brain scans are showing how brain waves can be altered
through mindful meditation to induce enhanced thinking states. Beta brain
waves, indicative of a busy, ‘noisy’ brain, make focus and concentration
difficult through over-stimulation. The more relaxed alpha wave state can
be activated through meditative practice, leading to mental acuity and

Allowing for these components will be challenging for some
instructional designers, as well as organisations where
training efficiency, in terms of maximum material in
minimum time, are the program drivers. If learning
effectiveness replaces efficiency as the measure, brain-
friendly approaches will be justifiable.

The biological
evidence is clear:
stress and learning
do not mix
Informal ; collaborative learning
We are always learning, sometimes whether we intend to or not. Directed,
intentional learning is usually formal in nature, such as reading
professional material, attending a seminar or listening to a podcast. But,
in fact, most of the learning we experience is of an informal nature and
usually involves others.

The Bersin ; Associates Learning Leaders 2010 report states that “this
year, the biggest buzzword in training is informal learning”. Recognition
that the majority of learning actually occurs outside the
classroom/training room/lecture theatre has come to the fore at a time when
resources are tight and the value of social interaction, coaching and
mentoring have become prevalent – it’s like the perfect storm.

Consistent with this trend, many organisations recognize the simple 70-20-
10 rule:
70% of learning occurs informally and on the job;
20% of learning occurs through observation of others;
10% of learning occurs through formal training.

This also highlights the collaborative nature of learning; potentially 90%
of all learning occurs through interaction at some level with others, which
makes whole-brained learning possible by tapping into the varied approaches
and thinking styles of others in a group.

Technology and learning
It’s hard to think about learning and development in 2011 without
considering the role of technology. With the proliferation of high quality
online learning content supplied by many of the world’s most respected
institutions, the availability and accessibility of knowledge is
unprecedented. Most organisations have, or are moving toward, e-learning
formats to augment and, often, replace traditional classroom-based

Although learning management systems (LMS) have been available and popular
for over a decade, their effectiveness has been mixed with uptake and
engagement by learners variable. Appealing user interfaces, content
quality, ease of access and interactive functionality have been criticisms
of early LMS models. Learning continuance, the ongoing utilisation of e-
learning beyond initial uptake, has seen steep declines. User acceptance of
online learning technologies is proving to be a key facet for predicting
continuance intention. Deci & Ryan’s self determination theory has been
used to explain motivation to persevere with e-learning programs. Research
has shown that learning continuance is strongly influenced by the perceived
usefulness, playfulness and ease of use of the technology25.

As e-learning moves toward m-learning (e-learning gone mobile), there will
be even fewer impediments to accessing learning content. Studies are
already showing advanced learning results when mobile access is
available26. This is a function of devices and connectivity. Interactive
video, already being trialled extensively in the education sector, also
shows promising efficacy in learning and will most likely be a staple of
future learning programs27.

A further challenge for technology in learning is to connect not only
individual, but collective minds to leverage the effects of collaboration
in learning.

The social interface is likely to be a key differentiator in the future
development of learning technologies.

Informal/On the job Training

End note
The brain loves to learn – fundamentally, that is its job. From the
earliest conversion of the basic sensory input an infant sees, hears and
feels, to the ongoing adaptations and growth we experience throughout adult
life, our brains are changing, restructuring and learning. When you go to
sleep tonight, it is with a brain that has changed as a result of today’s
learnings and when you wake up tomorrow, with new consolidated memories,
more learning awaits you.

Neuroscience has not discovered that we learn – this much we already knew.

What neuroscience casts light on is how the brain acquires, stores and uses
information, and what intrinsic and extrinsic factors can limit us from
optimising this process. By understanding more about how humans learn,
educators and organisational learning and development professionals can tap
the learning capacities of the brain that will drive the learning results
toward which they strive.

In a world seeking to build talent and drive exceptional performance,
organisational initiatives guided by scientific breakthroughs will combine
to crystalise the potential of our talent.

1. Cooper, S.J. (2005). Donald O. Hebb’s synapse and learning rule: a
history and commentary. Neuroscience and Biobehavioural Reviews, 28, 851-

2. Collins, J.W. (2007). The neuroscience of learning. (Report). Journal of
Neuroscience Nursing.

3. Shohamy, D., Myers, C.E., Kalanithi, J., ; Gluck, M.A. (2008). Basal
ganglia and dopamine contributions to probabilistic category learning.

Neuroscience and Biobehavioral Reviews, 32, 219-236.

4. Prickaerts, J., Koopmans, G., Blokland, A., ; Scheepens, A.

(2004). Learning and adult neurogenesis: Survival with or without
proliferation? Neurobiology of Learning and Memory, 81, 1-11.

5. Shahar, T.B. (2010). Learn to fail or fail to learn. Keynote speech at
Mind and Its Potential Conference, Sydney.

6. Ferrara, M., Iaria, G., De Gennaro, L., Guariglia, C., Curcio, G.,
Tempesta, D., and Bertini, M. (2006). The role of sleep in the
consolidation of route learning in humans: a behavioural study. Brain
Research Bulletin, 71, 4-9.

7. Curcio, G., Ferrara, M., ; De Gennaro, L. (2006). Sleep loss, learning
capacity and academic performance. Sleep Medicine Reviews, 10, 323-337.

8. Illeris, K. (2010). Characteristics of adult learning.

9. Stine-Morrow, E.A.L. ; Parisi, J.M. (2010). The adult development of
cognition and learning. Elsevier.

10. Diekelmann, S., Wilhelm, I. ; Born, J. (2009). The whats and whens of
sleep-dependent memory. Sleep Medicine Reviews, 13, 309-321.

11. Cowan, N. (2001). The magical number 4 in short-term memory: A
reconsideration of mental storage capacity. BehaviouralandBrain
Sciences, 24, 87-185.

12. Yerkes, R.M. ; Dodson, J.D. (1908). “The relation of strength of
stimulus to rapidity of habit-formation”. Journal of Comparative Neurology
and Psychology, 18, 459-482.

13. Sapolsky, R.M. (2004). Why zebras don’t get ulcers. Henry Holt &
Company, New York, NY.

14. Nielsen, L., Seeman, T. & Hahn, A. (2007). NIA exploratory workshop on
allostatic load. National Institute on Aging; National Institutes of

15. Desjardins, R. (2010). Participation in adult learning. Elsevier.

16. Hagemann, B. & Chartrand, J. (2009). 2009/10 Trends in Executive
Development: A benchmark report. Executive Development Association Inc.

17. Bersin & Associates, Learning Leaders 2010.

18. Carrier, L.M., Cheever, N.A., Rosen, L.D., Benitez, S., & Chang, J.

(2009). Multitasking across generations: Multitasking choices and
difficulty ratings across three generations of Americans. Computers in
Human Behavior, 25, 483-489.

19. Law, A.S., Logie, R.H., & Pearson, D.G. (2006). The impact of secondary
tasks on multitasking in a virtual environment. Acta Psychologica, 122, 27-

20. Colom, R., Martinez-Molina, A., Shih, P.C., & Santacreu, J. (2010).

Intelligence, working memory and multitasking performance. Intelligence, 1-

21. Illeris, K. (2010). Characteristics of adult learning.

22. Immordino-Yang, M.H. & Fischer, K.W. (2010). Neuroscience bases for

23. Merriam, S.B. (2010). Adult education – adult learning, instruction and
program planning. Elsevier.

24. Dieleman, H. & Huisingh, D. (2006). Games by which to learn and teach
about sustainable development: exploring the relevance of games and
experiential learning for sustainability. Journal of Cleaner Production,
14, 837-847.

25. Roca, J.C. & Gagne, M. (2008). Understanding e-learning continuance
intention in the workplace: A self-determination theory perspective.

Computers in Human Behavior, 24, 1585-1604.

26. Motiwalla, L.F. (2007). Mobile learning: A framework and evaluation.

Computers and Education, 49, 581-596.

27. Marsh, B., Mitchell, N., & Adamczyk, P. (2010). Interactive video
technology: Enhancing professional learning in initial teacher education.

Computers and Education, 54, 742-748
About the Author
Sylvia Vorhauser-Smith is Senior Vice President of Global
Research at PageUp People. She is responsible for driving
thought leadership in the field of human capital management
for global organisations facing cross border expansion and

Vorhauser-Smith has more than 25 years of experience in
corporate and entrepreneurial business environments,
including positions as Head of Selection and Development at
Westpac Banking Corporation, Human Resources Manager for
Citibank Limited, and General Manager of Integrated Talent
Management for PageUp People. Prior to joining PageUp
People, Vorhauser-Smith was Founder and Chief Executive
Officer of consulting firm Talent Edge, specialising in
bespoke leadership development and talent management

She is a regular national and international speaker on
neuroscience, talent and human capital management, having
addressed audiences in Boston, Singapore, Kuala Lumpur and
across Australia. Vorhauser-Smith holds a Bachelor of
Business and Graduate Diploma of Psychology from Monash
University, Post Graduate Certificate in NeuroLeadership and
is currently completing her Master of Science in
NeuroLeadership at Middlesex University.

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Published February 2011
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