Each student brings with them a diversity of developing skills in language, vision, attention, and other cognitive factors that can be measured safely and conveniently in our on-site Brainwave Recording Studio. When students place those nets of sensors on their heads, we can capture a thousand “pictures” of activity per second by measuring the natural electrical fields produced by the child’s brain activity. Teaching students in brain-friendly ways means implementing principles that align with how the human brain encodes, consolidates, and retrieves information. Educational neuroscience points to the importance of a holistic and integrated view of cognitive, emotional, and social aspects to support learning and development [52,75,93,94].
Both instructors and learners can be humans or animals (in the most natural use of the terms), or they can be brain regions or neural signals. Taken together, the study of behavioral learning can benefit from both structural and functional MRI research. We discussed methodological approaches that aim to unravel why learning interventions work, what learning computations change across development, and how learning difficulties are distinct between subgroups of individuals. These corresponding findings indicate that these approaches have the potential to have a lasting impact on promoting children’s and adolescents’ positive development. In the first decades of life, changes in physical appearance, as well as cognitive and social-emotional development, are readily apparent1,2,3,4. What is, however, less readily observed are the profound changes in the structure, function, and connectivity of the brain.
A particularly early study observed that functional connectivity of the sensorimotor network EEG could be modulated by focusing attention on the movements involved in ambulation [67]. Using functional near-infrared spectroscopy (fNIRS), a separate group demonstrated that functional network organization tracked cognitive burden, rising strongly in the middle phase of learning [68]. Indeed, even imagining movements – a common mechanism to drive brain computer interfaces for motor rehabilitation – produces significant changes in the functional connectivity of the default mode network [69] (a constellation of areas known to be active while a subject rests [70]). Importantly, some – but not all – of these changes in functional connectivity persist for some period of time after training [62,71].
Understanding how the human brain processes and retains information is a complex and intriguing field known as neuroscience of learning. This interdisciplinary area of study combines principles from psychology, neuroscience, and education to uncover the underlying mechanisms that drive learning and memory.
Beyond memory improvement, peer tutoring has many further benefits to both the tutor and the learner in academic achievements [58,59], motivation, and ownership over the learning process and results in a deep conceptual understanding of the material [60]. Educational environments that promote neuroplasticity include encouraging and modeling a healthy lifestyle (physical exercise, a balanced diet, sufficient sleep, and regulated stress), —for example, educating students about the counter-productiveness of sleep deprivation (e.g., “all-nighter” study marathons) on learning. In addition, learning systems should invest in intellectual stimulation (novelty and challenge) and the system’s social and emotional climate (human connections). Neuroplasticity and development are optimal in the stretch zone, where learners experience a motivating level of challenge and stimulation while feeling emotionally supported and socially safe. This ratio between support and challenge should be individualized (between learners and within learners over time).
For example, neuroscience research provides insights into how these intuitions contribute to children’s learning of arithmetic—and this has very practical implications for the classroom (Dehaene and Cohen, 2007; Prado et al., 2011; Prado, Mutreja, and Booth, 2014). This research has stimulated intervention studies which that when students practice comparing quantities, their arithmetic skills improve (Hyde, Khanum, and Spelke, 2014; Park and Brannon, 2013). Retrieval practice is very much linked to test-enhanced learning and refers to the practice of retrieving information from memory frequently, as a way of enhancing retention. Unfortunately, the answer is that no one really knows the exact answer, and there is no literature that clearly elucidates it. Network science is a subfield of complex systems science [18] which mathematically codifies systems whose function can be parsimoniously described by the patterns of interactions between components [19,20] or by the dynamics of such patterns.
This analysis showed that the group with higher white matter integrity in the cingulum had profoundly different cognitive abilities. Applying the cingulate-based grouping to independent groups of typically-developing children and struggling learners showed that children with lower cingulum FA showed lower performance across a variety of cognitive performance measures (e.g., fluid intelligence, working memory, and vocabulary)45. The value in this approach may particularly relate to children and adolescents with learning difficulties or psychopathologies that show complex behavioral phenotypes that may be better qualified with brain-based than behavioral subtyping. Computational learning models have been used to investigate questions such as how children, adolescents, and adults learn from positive and negative outcomes and integrate information into subsequent decision-making. An important element of learning in computational reinforcement learning models focuses on the difference between an expected outcome and a received outcome29,30.
The Role of Neuroplasticity in Learning
One of the key concepts in the neuroscience of learning is neuroplasticity. This refers to the brain’s ability to reorganize itself by forming new neural connections in response to learning and experience. Research has shown that engaging in challenging tasks and continuous learning can promote neuroplasticity, leading to improved cognitive function and enhanced learning abilities.
The Impact of Emotions on Learning
Emotions play a crucial role in the learning process, influencing attention, motivation, and memory. The neuroscience of learning has revealed that positive emotions can enhance learning and retention, while negative emotions can hinder these processes. By understanding the emotional aspects of learning, educators can create more effective teaching strategies that cater to students’ emotional needs.
In conclusion, the neuroscience of learning offers valuable insights into how the brain learns and retains information. By studying the underlying neural mechanisms involved in the learning process, researchers can develop innovative educational approaches that optimize learning outcomes for individuals of all ages.
