Modern technology

Neurology, coupled with the use of modern technology, have been used to develop erudition approaches that seek at exploring powerful learning mechanisms for children. According to Chavez-Mancilla & Parodi (2015), exploration of learning and development from a biological perspective can lead to insights into why children fail to achieve the results expected. Learning can broadly be defined as changing of the physical structure of the brain through organisation and reorganisation. On other hand, development refers to the growth that occurs in children from infancy to adulthood (Herr, 2011). Brain research has affirmed that no two children are alike; each young one has a different cognitive makeup that influences the way in which they respond to various stimuli (Center for Educational Research and Innovation, 2008). In this case, this paper explores concepts related to the neurobiological basis of learning and development in normally developing children. Thereafter, it states the implications of these tenets in learning and development of children.

A child’s brain is considered as a powerful tool for learning, even before birth. According to Goswami (2015), the foetus in a mother’s womb can hear sounds from the external environment in the last trimester of pregnancy and can develop a memory of the mother’s voice even when in the amniotic sac. These reactions are fostered by the working of the brain, with previous studies confirming cortical activity in the uterus. In this case, the neurons of the brain are linking with each other to from synapses in a process that fosters cognitive growth. More specifically, the brain of a child is believed to learn through four mechanisms; (1) statistical learning by neural networks, (2) learning by imitation, (3) learning by analogy, and (4) causal learning. To begin with statistical learning by neural networks, the brain assimilates the statistical structure of experiences events, creates neural networks to represent information acquired using algorithms revealed through research in machine learning (Goswami, 2015). Young infants can distinguish various visual and auditory forms make modal correspondences. Secondly, studies have shown that children can learn through imitation of actions done by adults. According to studies by Meztoff (1995), children learn to interoperate the goals of other individuals and initiate the same actions to yield the intended behaviour. Thirdly, children are believed to learn by analogy. Analogies can be defined as correlations between circumstances; in essence, children are said to group similar situations and apply parallel solutions according to the problem presented. According to studies by Chen et al. (1997), toddlers progressively develop the propensity to solve analogous solutions as they develop familiarity with their surroundings. Finally, causal learning, also labelled as explanation-based learning, is a concept rooted in machine based learning (Herschkowitz, 2000). Machine based learning involves the structuring of underlying explanations for phenomena based on training models. Children are also said to follow the same method as they face situations that require them to make forecasts about unique circumstances.

In the processes of development, children experience physical, cognitive and social-emotional development (Herr, 2011). Physical development is termed as a relatively predictable process where bodily changes occur. Cognitive or intellectual development involves the processes that human beings use to gain knowledge. Finally, socio-emotional development is learning that occurs relate to others and development of feelings and expression of feelings (Goswami, 2015). Although the two later forms of development are more strongly correlated together, all forms of development are linked to each other. Research in neuroscience has made it possible to understand development and come up with patterns representing the processes of development. These include the cephalocaudal principle, which states that development starts from the head where the child first gains control of its head before the legs; the proximodistal principle, which characterises development that begins from the body centre outwards; and maturation, which represents the series of biological changes in children (Herr, 2011). However, it is key to note that just like learning, developmental patterns among babies are subjective. Additionally, neurologists have confirmed that the brain has various ‘windows of opportunity to change’ (Herschkowitz, 2000). Modern technology has permitted scholars to analyse the various parts of the brain and identify the timing of the development of various skills associated with sections of the brain. These can be summarised as the development of vision in the first 6 months of an infant’s life, development of vocabulary from birth to 3 years, development of emotional control from birth to 3 years, development of logic from 1 to 4 years and the development of motor skills from prenatal to 8 years (Goswami, 2015). In existing research, there is a general consensus that the closing of the window of opportunity for development presents complications in future development of the said skills (Herschkowitz, 2000).

Various theories of development have also been advanced to explain development; some of the models advanced include Erikson’s Psychosocial Theory, Piaget’s Cognitive Development Theory, Vygotsky’s Sociocultural Theory and Gardner’s Multiple Intelligences Theory. To begin with, Erikson’s Psychosocial Model proposes that development occurs throughout the course of a human’s life (Newman & Newman, 2014). Through the model, development is conceptualised via socio-emotional progressing through eight stages. In all of these stages, the person experiences a psychological crisis that must be resolved before progressing to the next stage. Therefore, the model asserts that the first four stages occur during childhood and teachers and parents play a critical part in aiding the children to overcome the stages of challenges presented in each stage.

Piaget’s cognitive development model presents a framework for forecasting thinking for children as they mature (Herr, 2011). Jean Piaget believed that childhood involves the gradual gathering of knowledge via pragmatic experiences. More specifically, he asserted that children constantly create, modify, organise and reorganise concepts known as schemata. When the infants face new challenges in new environments, they either assimilate new information or accommodate what is already known to fit the environment in a process known as adaptation. He further divided the development process into four stages (sensorimotor, preoperational, concrete, and formal operations) with three of them occurring within childhood (Spink, 2010). Although the author did not specifically relate his model to education, scholars have adapted his insights to conceptualise learning as an active process (Center for Educational Research and Innovation, 2008). Teachers in classroom settings are expected to give babies stimulating practical activities that aid in creating knowledge.

Vygotsky’s sociocultural theory is also based on the concept of active learning in children. While Piaget attributed psychosocial development to hands on activities, Vygotsky asserted that children learned through their socio-cultural experiences (Herr, 2011). In this regard, the model is built on the assumption that babies are learn the language, cultures, beliefs and customs of via interaction. This theory implies that teachers and caregivers should avail a myriad of social-interactions for children. The scholar further advanced his argument through the concept of the zone of proximal development (ZPD) (Chavez-Mancilla & Parodi, 2015). The ZPD is a continuum of tasks associated with the child’s development; these tasks range from simple self-manageable tasks to some complex ones which cannot be accomplished even with help. Through scaffolding, or help, adults with the amount of knowledge enough to perform the activities, can aid children in doing the intermediate tasks (Herr, 2011). Therefore, the theory emphasises that social interaction and guided learning are key for child development.

Finally, Gardner’s Multiple Intelligences Theory presents a framework for perceiving the intelligence in children. Rather than focusing on the conventional intelligence interpretations (language and logic), Gardner asserts that there are many other forms of intelligences in the human brain (Spink, 2010). These include bodily-kinesthetic intelligence – involving the aptitude to control body movements, musical-rhythmic intelligence –involving the capacity to recognise music patterns, logical-mathematical Intelligence – incorporating the ability to use logic for problem-solving, verbal-linguistic intelligence – concerning the capability to use language for communication, interpersonal intelligence – involving the capacity to exhibit outstanding communication and social skills, intrapersonal intelligence – concerning the ability to understand one-self, visual – spatial intelligence – concerning the use of vision to create cognitive representations and naturalistic intelligence – created from the necessity to survive (Herr, 2011). Gardner asserted that there was the need to develop these skills from their rudimentary from specifically seeking to grow the strongest skill in various children. It implication for teaching practice is the subjective consideration of children’s learning needs seeking to create the maximum amount development in a child (Center for Educational Research and Innovation, 2008).

Overall, learning and development are imperative in human cognition and occur in basic form after birth. In this case, teachers and caregivers are expected to consider the neuroplasticity of young children and consider approaches that foster cumulative learning. Multisensory approaches towards learning are encouraged over uni-sensory means that focus on one mode of knowledge transfer. Connectionism has also revealed that continuous erudition mechanisms can produce learning results formerly deliberated as developmentally distinctive. The regularity with which learning actions are practised and the feature of the education environment are consequently crucial to the gaining of expertise.

References

Center for Educational Research and Innovation. (2008). Understanding the Brain: the Birth of a Learning Science. OECD/CERI International Conference - Learning in the 21st Century: Research, Innovation and Policy” (pp. 1-14). Paris: OECD/CERI.

Chavez-Mancilla, V., & Parodi, J. (2015). Neurobiological Bases of Learning and Their Role for the Paradigm Shift in Education. Psychology, 6, 1741-1749.

Chen, Z., Sanchez, R., & Campbell, T. (1997). From beyond to within their grasp: the rudiments of analogical problem solving in 10- and 13-month-olds. Developmental Psychology, 33, 790-801.

Goswami, U. (2015). Children's Cognitive Development and Learning. Cambridge: Cambridge Primary Review Trust.

Herr, J. (2011). Working with Young Children. Creek Dr, Tinley Park: The Goodheart-Willcox Co., Inc.

Herschkowitz, N. (2000). Neurological bases of behavioral development in infancy. Brain & Development, 22, 411±416.

Leff, P., Romo, H., Matus, M., Hernández, A., Calva, J. C., & Acevedo, R. (2002). Understanding the neurobiological mechanisms of learning and memory: Memory systems of the brain,long term potentiation and synaptic. Salud Mental, 25(4), 78-94.

Meltzoff, A. (1995). Understanding the intentions of others: re-enactment of intended acts by 18-month-old children. Developmental Psychology, 31, 838-50.

Newman, B. M., & Newman, P. R. (2014). Development Through Life: A Psychosocial Approach. Boston, Massachusetts: Cengage Learning.

Quartz, S. R., & Sejnowski, T. J. (1997). The neural basis of cognitive development: A constructivist manifesto. Behavioural and Brain Sciences, 20, 537–596.

Spink, A. (2010). Information Behavior: An Evolutionary Instinct. New York: Springer Science & Business Media.

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