Science of Learning

To better understand the factors influencing the success of learning and retention, this chapter serves as a brief introduction to the neuroscientific mechanisms behind our cognitive learning behaviour.

Our five senses: sight, smell, hearing, touch and taste act as the key starting points to detect information and relay it to the brain. External stimuli are picked up by their sensory receptors, triggering a sequence of neurons (electrical impulses) firing towards the brain. Internal signals are detected by special internal receptors; separate from those of the five senses. The electrical impulses reach the brain, are scanned on their importance (sensory filtering) by the sensory register and, if important enough, trigger a reaction. In most cases, this filtering compares the relevance of the new data to past experiences. Thus, what we perceive as light, for example, is no more than the brain’s interpretation of electrical impulses stemming from the light waves picked up by our sight-sensory receptors which are relayed to past interpretations of the same waves. Of course, this all happens so quickly that we are usually unaware of the entire process (Sousa (2022)).

Sensory data enters the short-term memory which can be divided into the immediate memory and the more conscious, working memory. For sustainable learning to occur, this information must be transferred to the long-term memory. This process is conducted by the hippocampus, usually during deep sleep. The main criteria for this transfer from the working memory to the long-term storage areas are twofold: meaning and sense. While independent of each other, ‘Is the information relevant, i.e., does it have meaning for me?’ carries more weight than ‘Does it make sense to me?’ in increasing the likelihood of transfer to long-term storage. Nevertheless, the presence of only one of the two can suffice.

Increasing the Likelihood of Retention

Information fulfilling both criteria is extremely likely to be passed to long-term storage areas. Meaning, for example, is greatly increased through survival-critical or emotional components such as Motivation and Feedback. Processing the data for longer periods through repetition may further increase the likelihood of finding meaning and sense, therefore also heightening the probability of retention. Even after passing to long-term storage areas, long-term memory is not guaranteed – the greatest memory loss of newly acquired information occurs during the first 18 to 24 hours. If the information is still present once this threshold is surpassed, the individual is likely to be able to recall it at a (much) later point (Sousa (2022)).

Past experiences play a major role in this process since they greatly influence the likelihood of information either being discarded to the sensory memory for less than a second or relayed to the short-term memory where it may then enter the long-term memory. With every new stimulus, our brain cells change and new fibre connections are created (Belham (2018)). ‘Old’, or previously received information will not diversify these fibre connections between different brain cells but make existing ones stronger. Goswami (2008) classifies these connections into two different processes: “experience expectant” and “experience-dependent”. The expectant processes predominantly stem from evolutional features and are thus predictable and expected. Dependent, on the other hand, signals that the individual is encountering new information for the brain to encode, such as is often the case in educational settings. The latter will form new neural connections. Unused connections are aggressively pruned, emphasising the importance of repetition and application (Goswami (2008)).

As behavioural motivators, emotions have great power over our actions (Higgins (2006)), which are driven by reinforcements, either extrinsic or intrinsic (Robson et al. (2015)). Habits feed off of reinforcement: they form when certain behaviours are repeatedly rewarded over time, eventually requiring fewer cognitive resources for their performance (Duhigg (2014)). Gamification targets this reinforcement of desired outcomes to promote successful learning (Robson et al. (2015)).

In summary, learning largely depends on two aspects: the meaning and sense of the information, as well as the time it is processed by our brain. To maximise sustainable learning, therefore, one can either increase the relevance and ensure an individual’s understanding through Motivation or Feedback, or raise repetitions and reinforcements and thus the processing time. Not only is the time relevant but also the number of confrontations with the information: ‘exposure effects’ positively influence the probability of retention (Johnson and Hasher (1987)). Information becomes more likely to pass to long-term memory areas and be recalled through stronger fibre connections.