The phenomenon of human learning is not a unitary construct, rather it comprises a gamut of cognitive traits including memory, attention, decision making and social functioning. According to David Ausubel, an eminent educational psychologist: “The single most important factor influencing learning is what the learner already knows. Ascertain this and teach him accordingly”.

What we already know and can retrieve is underpinned by the neural system of memory, and the use of pre-existing neural networks can form the basis of further learning. Retrospective evaluations of events in the “long term” (in behavioural neuroscience, this refers to a period longer than a day) have found memory processing to be a high fidelity system. However, the transient storage of information, i.e., working memory, appears to be less resilient and prone to rapid deterioration.

“Consolidation” is the term attributed to the hypothetical transformation of a memory trace from an unstable, short-term form to a stable, long-term form. Recent research has focused on a rather enigmatic aspect of memory processing, dubbed “reconsolidation” – it is a special state brought about by the retrieval of items in the long-term memory, which makes them prone to alterations.

Learning is not simply based on enhanced neural activity, but also structural modifications that can be determined by changes in synaptic density (synaptogenesis). In a study involving rats, this question was explored by training a test group for a low-intensity but challenging motor skill, compared to the other groups that were exposed to high-intensity physical exercise but with relatively little learning involved. Notably, a higher density of blood vessels was found in the latter (angiogenesis, a compensatory response to increased/repetitive synaptic activity), but a significant increase in synaptic density was only found in the former, thereby demonstrating that learning is underpinned by neuro-structural changes in the brain.

The cortical-hippocampal system – comprising complex, bi-directional flow of information between the neocortex, the parahippocampal region and the hippocampus – underpins the neural coding mechanisms of conscious memory. The latter is particularly important in the organisation of memories in space and time.

Consistent with the recent advances in the neurobiology of learning, a list of potential correlates will be discussed from the literature that either inform the basis of accepted teaching practices or provide ideas for further exploration with the aim of improving the current design of learning environments. It must be acknowledged, however, that cognitive neuroscience has not advanced to a point yet where it could translate into guidelines for effective teaching practices (nor would such a circumscribed approach necessarily provide the desired outcomes), but drawing parallels between the two fields illustrate the neural underpinnings of the pedagogy of education, and highlight some of the pervasive ‘neuromyths’ that have taken root in the education sector and the society at large by courtesy of the so-called ‘brain-based learning’ industry.

Repetition

It has been proposed that repetition of information can improve normal retention and retrieval processes. The neural execution of the reconsolidation phase is energy efficient (using pre-existing neural connections). Moreover, it provides an opportunity to modify the memory trace both in terms of content and structure.

Previous psychophysiological studies in humans have used a range of somatosensory stimuli or verbal suggestions (stressors) during the retrieval phase in order to improve memory performance; immersion of arm in ice-cold water and the use of negatively arousing pictures are amongst the different stressors used in experimental conditions. In the real world, students can exploit reconsolidation by practicing self-testing. This can produce a moderate level of stress – a mnemonic enhancer – by facilitating synaptic potentiation mediated by a moderate release of stress hormones, glucocorticoids. In contrast, high levels of stress/glucocorticoids can have the opposing effect on memory and learning processes. The seeming malleability of memory trace upon retrieval/reactivation has an important clinical implication in the context of consolidated fear memories which could then be blocked by amnesic agents.

Repeated testing has been shown to improve the retention of information, a phenomenon termed the “testing effect”, over and above any effect of repeated study. This effect is particularly robust when the tests require effortful recall, e.g. mechanistic questions rather than recognition tests such as multiple choice, and when testing is spaced out over time.

Spacing of learning

In addition to repeated retrieval, the value of spacing in learning is another interesting concept. However, further examination is warranted of the optimal intervals/spacing times for revisiting content for long-term consolidation. These observations support the concept of the spiral curriculum, which advocates revisiting topics in increasing levels of difficulty throughout the course. The latter point of the deepening of content upon successive encounters is equally important. It appears that our brains are better at retaining information when it is structured/mechanistic, context-based and goal-oriented. The use of similes, metaphors, analogies and other short mnemonics can also be helpful in memory retention.

Small learning groups

It could be argued that teaching in small groups is beneficial, not least because of the potential activation of stressor pathways triggered by the need to share the underlying reasoning processes. Breaking down a question into small parts could facilitate incremental/structured learning across the multiple levels of difficulty. Such an approach may also facilitate active engagement of students, including those who otherwise opt out from the learning process often with little engagement in the first place. With interactive, small-group teaching, as compared to the traditional, didactic forms of teaching to large groups of students, the students are more likely to embrace responsibility and ownership of the learning process, in part due to the engagement of the motivational and reward circuitry.

Reward

Reward is an important tenet of the learning process. It appears that our brains engage in “temporal discounting” to measure the relative value of a choice. For example, the seemingly short-term reward of having learnt a new skill as compared to the more long-term, greater reward of having a respected career, income, etc.

It is plausible that the reward system could be incorporated into the learning design by, for example, sharing with the students the scientific rationale underpinning the instructor’s choice for a particular learning model or teaching practice. It is tempting to suggest a more dynamic role of a tutor with the position being swapped with the students following an initial period of formalised tutorship. Indeed, it has been shown that social and cognitive concordance between the teacher and the learner can improve the latter’s perception of their learning experience.

While inclusion of a reward component in the learning design seems important, it may well be equally important to address the fear of failure associated with learning. Could it be a learnt effect? If so, could it be unlearnt then? In a sense, this is what the pain rehabilitation specialists do to reverse those avoidance/compensatory responses that contribute to the therapeutic intractability of chronic pain. Indeed, the phenomenon of fear is complicated, not least because of the myriad social and cultural connotations. However, it is plausible that individuals who find the learning process intrinsically rewarding are less likely to be overwhelmed by the fear of failure.

While emphasising the value of interactive, small-group teaching, it is important to acknowledge that learning preferences can vary greatly across individuals, and hence a combination of different teaching strategies should be adopted. Mental rehearsal of actions or thoughts, regardless of an external or an internal trigger, could facilitate the learning of an advanced skill, e.g. a complex surgical procedure. Likewise, it may help to overcome the fear of failure, for instance, in case of public speaking. The mirror neuron system is believed to subserve the inner imitation of an external event. Where feasible, visualisation technologies could be incorporated into the established learning paradigms. More generally, a multi-media approach of content delivery might also help to minimise cognitive distraction and improve attention, in addition to promoting memory retention by repetition of content.

Emotional state

Consistent with the findings in brain-damaged patients, our apparent rational thinking is in fact underpinned by hidden emotional processes. The role of emotions is vitally important as all the cognitive traits pertinent to education are inextricably linked to emotion. This poses a serious question in terms of the translation of knowledge from a structured educational setting to a real-world situation. According to Immordino-Yang and Damasio (2007):

“Knowledge and reasoning divorced from emotional implications and learning lack meaning and motivation and are of little use in the real world.”

Hence, it is important that a learning environment is not devoid of emotion, and that students are provided ample opportunities to engage in real-life problem solving as an integral part of the learning experience.

Conclusions

A greater integration between the science of learning and the practice of teaching is highly warranted, not least because of the “frequently exaggerated” and “at times misleading” claims of the brain-based learning industry about “improvements in the speed and efficiency of cognitive processing and dramatic gains in “intelligence”” by the use of “brain-training games”. These observations were shared in a consensus report by The Stanford Center on Longevity and the Berlin Max Planck Institute for Human Development.

While there is some evidence of short-term task-specific improvements in working memory, there is no clear evidence that these effects are transferrable to other untrained working memory tasks or broader everyday skills. Not to mention, financial, social and other opportunity costs associated with brain-training games warrant due consideration. Indeed, a range of other strategies are promoted to improve learning: for instance, choosing a learning design based on whether a student is “left-brained” or “right-brained” or the use of “brain buttons” (by applying pressure to an area between the first and second ribs under the collar bone) to reorganise/refocus the brain for reading and writing. Such learning strategies are often based on an exaggerated or flawed interpretation of scientific facts.

Scientific progression is underpinned by incremental and seemingly small discoveries; however, the claims of the brain-based learning industry are anything but that. Although an effort has been made by the scientific community in recent years to raise awareness about these issues, a lot more work needs to be done in particular to raise awareness amongst the educators as well as the broader community. The role of science communicators could be useful in bridging the current gap between the real neuroscience of learning and the pervasive propaganda of the commercial “brain-based” programs.

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