What Is the Impact of the Changing Brain on Learning (The Adolescent Brain?)

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According to Zarantello et al. (2020), adolescence is the stage of life between childhood and adulthood. Yaple et al. (2019) even go so far as to claim that a concept of adolescent growth that spans 10 to 24 years is better in line with this stage of life than the earlier views of 10 to 19 years. They argue that people's ideas about when maturity actually begins have changed as a result of delayed dates for getting married, having children, and finishing school. Perhaps far more than at any other point in history, the transition from childhood to adulthood affects health and welfare throughout these years because it occurs at a time when hitherto unheard-of social forces like popular marketing, digital or social media and culture are at play. WHO (2020) states that teens' involvement in school is essential to their success in the future.

The comprehension of the mind of adolescents is evolving as a result of discoveries. Although comprehensive research is yielding consistent findings, the fact that the adolescent brain undergoes considerable changes is no longer up for debate. The study of adolescent brain development is still relatively new (about 20 years). The adolescent brain is a myth, according to Smith and Victor (2019), who refute assertions made by non-neuroscientists such as the University of Cambridge (2013). A completely new understanding of the adolescent brain has been made possible by advancements in neuroimaging technology over the past 20 years, notably those related to structural and functional magnetic resonance imaging (MRI and fMRI) (Sloane-Seale & Kops, 2008). These recent findings are obviously relevant to the study of teenage academic achievement and, eventually, their capacity for post-educational functioning. 

The essay examines how brain growth during childhood affects a person's capacity for successful learning. First of all, the adolescent brain differs significantly from the brains of children and adults (Salthouse and Madden, 2013). The levels of brain areas, structures, veins, and systems vary, as do their shape and function (WHO, 2020). According to Yaple et al. (2019), research has surprisingly demonstrated that the adolescent brain continues to develop during this stage of life, especially in the frontal (which is involved in a wide range of reasoning and movement) and parietal (which is primarily responsible for integrating information from various sources and some mathematical skill) regions. According to Andersson et al. (2006), myelination and synaptic pruning may have contributed to the rise in white matter and decrease in grey matter in this region. 

One significant alteration that takes place in the brain during adolescence is synaptic pruning, which permits the removal of unneeded connections while maintaining crucial ones (Park et al., 2001). In order to fine-tune brain tissue functional networks and increase the efficiency of the remaining synaptic circuits, there must be a net drop in synaptic density in the pre-frontal cortex during adolescence (Park and Reuter-Lorenz, 2009). Throughout adolescence, synaptic pruning supports the growth of frontal lobe-related cognitive activities. 

Another fatty layer called graphene coats nerve fibres, facilitating faster and more effective electrical message transmission and enabling connections to regions of the brain that were previously more widely distributed (Pani-Harreman et al., 2021). Myelination is the process that occurs more frequently during puberty. The ONS (2019) indicates that myelination enhances the effectiveness of information transmission and that this process may promote a rise in the rate of brain communication. 

The above steps are collectively referred to as neuroplasticity. From the standpoint of an educator, adolescent neuroplasticity is fundamental due to the ongoing development of the teenage brain. The teenage brain rewires itself in response to experiences and environmental cues, and this has significant implications for adulthood, according to NHS (2016b). It is further supported by ONS (2021), which emphasises the value of schooling at this age by claiming that social experiences and formal Education may both have a significant impact on how the adolescent brain develops. According to him, the brain needs to be sculpted and shaped because it is still developing and is, therefore, probably malleable. 

The pre-frontal cortex (PFC) is the last region of the brain to be myelinated and pruned. This means that the parts of the brain in charge of executive functions—such as impulse control and decision-making—are not at their most effective level until mid-adolescence. This fact is relevant to an adolescent's capacity for effective learning (NHS, 2016). The brain's emotional centre includes the frontal lobes as well. According to Zarantonello et al. (2020), middle school instructors must monitor and provide an example of a supportive emotional climate for their children because they have not yet attained the mental maturity necessary to control their emotions fully. The ways in which this support might be provided to maximise teenagers' effective learning are examined in the second section of this essay. 

Through 15 years of experience as a practising neurologist and ten more years as a teacher, board-certified neurologist Judy Willis offers unique insight into learning and the brain. According to her, educators must modify their teaching strategies to support teenagers' learning as they acclimatise to the additional peer pressure of secondary school. 

Aptitude and academic achievement might be hampered by stress and anxiety. According to neuroimaging, adolescents experiencing emotional worry and stress cause the amygdala to become metabolically hyperactive Narushima et al., (2018). This results in a considerable decrease in the activity of the brain networks that typically carry information into and out of the amygdala. As a result, fresh knowledge and insights are prevented from entering the memory banks. Conversely, though, teenagers' brains transfer knowledge quickly when they are entirely engaged in high-interest learning activities (Merriam and Kee, 2014). An alternative viewpoint is additionally worthwhile to mention: Lustig et al. (2009) explain an association between stress (psychological, not physical) and memory promotion, which may benefit teenagers taking exams. 

Teachers working with teenagers cannot help but observe the powerful influence that friends have on one another in adolescence. Neuroimaging studies have demonstrated the power of peers; an fMRI study by Lövdén et al. (2020) indicates that adolescents may be more likely to take more significant risks in exchange for more enormous rewards when they are among their peers. According to the study, when the youngsters realised that two peers of the same age and gender were watching them play a computerised driving simulation game on a television monitor, they were willing to take more significant risks. The study also found that when large rewards were offered, they took much more risks than adults did. According to Coxon et al. (2016), youths are predisposed to react to what their peers think of them in the reward centres of their brains.

When applying this knowledge to an educational situation, it becomes evident that teenagers are more receptive to social learning than to listening to lectures or classes led by teachers. Teachers must use peer relationships to their advantage in order to improve student engagement and learning outcomes in the classroom. According to Chasteen et al. (2015), alterations in the brain during adolescence—specifically, feedforward and feedback between the Superior Temporal Sulcus—improve a teen's neural responses to social stimuli. These changes are significant in peer-to-peer interactions. Chasteen et al. (2015) discuss the interaction between cognitive and emotion-related processes. Building schools that support shared learning, peer coaching programmes, peer teaching, and collaborative learning projects should be educators' goals in light of these changes in the brain. Community and self-esteem building, according to the Centre for Ageing Better (2022), is not just "nice to do" but also reduces threat and stress and "serves to facilitate the successful passage of knowledge through the brain's filters and into cognitive processing," as demonstrated by neuroimaging research. The pupils gain more knowledge as a result. 

Reexamining the notion that teenagers tend to take chances and react to the opinions of their peers raises concerns since it implies that students should be making life-changing decisions before the age of 14. Selecting their GCSE choice subjects at this stage may cause them to select subjects they subsequently come to regret, or worse, they may need to select subjects they subsequently understand they require for their desired vocation. Rather than making the best decisions for themselves, some 14-year-olds could select courses to guarantee they stay in the same classrooms as their peers. 

Zhang and Lim (2022) argue that juveniles' greater predisposition around appetitive tendencies, orientation towards sensation-seeking, and willingness to take risks make perfect evolutionary sense, as this is the time when they are still figuring out who they are. It is the beginning of a journey that will continue for the rest of their lives as they figure out what matters to them (Biggs, 1993). "Taking risks as a teenager is beneficial from an evolutionary standpoint, not detrimental" (Alzheimers.net 2016). 

The present paper has yet to make progress towards acknowledging that adolescence is a period of significant opportunity and challenge for both the adults helping the adolescents and the teenagers themselves. It is critical to reject the antiquated beliefs that teens are insane, sluggish, become insane, or "lose their minds" and to accept the growing body of scientific information that indicates these behaviours are the consequence of significant alterations in brain development. As we now know, adolescent social and cognitive development is greatly influenced by brain maturation. 

Teachers must recognise the valuable contributions that teenagers may make to society, including their motivation and inventiveness in coming up with fresh ideas. According to ONS (2019), adolescents can use their developing intellect to devise novel strategies for coping with these difficult times if they are given the right help. The main goal of secondary school teachers should be to assist teenagers in their academic journey so they can thrive during adolescence rather than survive it. 

Regretfully, an additional challenge that secondary school teachers have is the difference between social and biological time, especially in later adolescence. Pani-Harreman et al.'s (2021) study looked at how the traditional school day, which runs from 9 a.m. to 3 p.m., affected adolescents. According to their research, moving secondary school start times to later times could have a significant positive impact on Education overall, including academic results. They contend that teens who attend school today experience chronic sleep deprivation (ONS, 2019), which hinders their ability to learn well. Teaching matched to the nature of adolescence can only be beneficial during what is already a difficult time for teenagers and potentially address what seems to be a severe drawback. This theory is supported by Park and Reuter-Lorenz (2009), who claim that getting enough sleep helps the brain consolidate the knowledge gained throughout the day. He contends that regular and enough sleep is necessary for the brain to learn efficiently, suggesting that sleep not only aids in understanding what has been learned that day but also prepares us for more learning the next day. Persson & Associates (2006). Teenagers who experience significant sleep deprivation during the school year as a result of school schedule conflicts may only have adverse effects on their ability to learn. 

According to Salthouse and Madden's (2013) studies, there may need to be a change in the time of day that some academic courses are taught. Sloane-Seale and Kops (2008) quote a prior study by Smith and Victor (2019), in which students in the 13–14 age range took a word pair exam at 10:00 and again at 14:00. All of the students did better on the later test, indicating that teenagers are more aware in the latter part of the day. If teenagers pay greater attention in the afternoons, then why are our main subjects—math and English—taught to Year 6 students (11-year-olds) first thing in the morning? According to this research, in order to maximise the learning outcomes for such students, upper Key Stage 2-year groups should think about shifting Math and English to the afternoons.

Similarly, National Curriculum Assessments for Year 6 Teenagers take tests in understanding texts, punctuation, grammar, spelling, calculation and arithmetic, and punctuation between the hours of 9:00 and 11:30, which further suggests that these students need to receive equal treatment. Even though there is evidence that altering the length of the school day can maximise learning and enhance academic performance, any changes made to school policy to accommodate it—particularly a later start for teenagers, though this is not always the case for younger primary-aged children—may make childcare arrangements more challenging for working families. Government policymakers would need to carefully weigh all of their options because the parents may experience both financial and logistical challenges. 

In conclusion, trainers might impact teens' Education by using their growing understanding of the critical period of neurobiological processes that underpin higher cognitive capabilities as well as social and emotional behaviour during adolescence. According to the University of Cambridge (2013), pre-frontal cortex maturation is correlated with enhanced capacities in abstract reasoning, attention shifting, response inhibition, and processing speed. She asserts that the imaging data supports the belief held by educators that, in determining the most effective ways to support adolescents' learning, this development is crucial to the emotional and cognitive behaviours exhibited by teenagers.

References 

• Alzheimers.net (2016) What is the difference beetween Alzheimers and Dementia? Available at: http://www.alzheimers.net/difference-between-alzheimers-and-dementia/ (Accessed 11th March 2016).
• Biggs, S. (1993) Understanding ageing : images, attitudes and professional practice, Bristol, PA, USA: Open University Press.
• Centre for Ageing Better (2022) The State of Ageing in England is Getting Worse. Available at: https://ageing-better.org.uk/summary-state-ageing-2022 (Accessed 17/3/23).
• Chasteen, A., Pichora-Fuller, M., Dupuis, K., Smith, S. and Singh, G. (2015) 'Do negative views of aging influence memory and auditory performance through self-perceived abilities?', Psychology And Aging, 30(4), pp. 881-893.
• Coxon, J. P., Goble, D. J., Leunissen, I., Van Impe, A., Wenderoth, N. and Swinnen, S. P. (2016) ‘Functional brain activation associated with inhibitory control deficits in older adults‘, Cerebral cortex, 26(1), pp.12-22.
• Lövdén, M., Fratiglioni, L., Glymour, M. M., Lindenberger, U. and Tucker-Drob, E. M. (2020) ‚ Education and cognitive functioning across the life span', Psychological Science in the Public Interest, 21(1), pp.6-41.
• Lustig, C., Shah, P., Seidler, R. and Reuter-Lorenz, P (2009) ‚Aging, training, and the brain: a review and future directions’, Neuropsychology review, 19(4), pp.504-522.
• Merriam, S. B. and Kee, Y. (2014) ‘Promoting community wellbeing: The case for lifelong learning for older adults’, Adult Education Quarterly, 64(2), pp.128-144.
• Narushima, M., Liu, J. and Diestelkamp, N. (2018) Lifelong learning in active ageing discourse: Its conserving effect on wellbeing, health and vulnerability’, Ageing & Society, 38(4), pp.651-675.
• NHS (2016a) NHS Choices: Can dementia be prevented? Available at: http://www.nhs.uk/conditions/dementia-guide/pages/dementia-prevention.aspx (Accessed 4th March 2016).
• NHS (2016b) NHS Choices: About dementia Available at: http://www.nhs.uk/Conditions/dementia-guide/Pages/about-dementia.aspx (Accessed 4th March 2016).
• ONS (2019) Average age at death, by sex, UK. Available at: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthandlifeexpectancies/datasets/averageageatdeathbysexuk (Accessed: 17/3/23).
• ONS (2021) National life tables – life expectancy in the UK: 2018 to 2020. Available at: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/lifeexpectancies/bulletins/nationallifetablesunitedkingdom/2018to2020 (Accessed: 17/3/23).
• Pani-Harreman, K., Bours, G., Zander, I., Kempen, G. and Van Duren, J. (2021) ‘Definitions, key themes and aspects of ‘ageing in place’: A scoping review’, Ageing & Society, 41(9), pp.2026-2059. doi:10.1017/S0144686X20000094
• Park, D. C., and Reuter-Lorenz, P. (2009)’The adaptive brain: aging and neurocognitive scaffolding’, Annual review of psychology, 60, pp.173.
• Park, D.C., Polk, T.A., Mikels, J.A., Taylor, S.F. and Marshuetz, C. (2001) ‘Cerebral aging: integration of brain and behavioral models of cognitive function’, Dialogues in clinical neuroscience, 3(3), pp.151-165.
• Persson, J., Nyberg, L., Lind, J., Larsson, A., Nilsson, L., Ingvar, M., and Buckner, R.L. (2006) ‘Structure–function correlates of cognitive decline in aging’, Cerebral Cortex 16(7), pp.907-915.
• Salthouse, T., A., and Madden, DJ (2013)'Information processing speed and aging', in Deluca, J. and Kalmar, J.H. Information Processing Speed in Clinical Populations. Pp.221-242. Hove: Taylor & Francis.
• Sloane-Seale, A, & Kops, B. (2008) 'Older Adults in Lifelong Learning: Participation and Successful Aging', Canadian Journal Of University Continuing Education, 34(1), pp. 37-62. 
• Smith, K. J. and Victor, C. (2019) ‘Typologies of loneliness, living alone and social isolation, and their associations with physical and mental health’, Ageing & Society, 39(8), pp.1709-1730.
• University of Cambridge (2013) Dementia prevalence figures in the UK show decline in last 20 years. Available at: https://www.cam.ac.uk/research/news/dementia-prevalence-figures-in-the-uk-show-decline-over-past-20-years (Accessed 4th March 2016).
• WHO (2020) Decade of healthy ageing: baseline report. Available at: https://www.who.int/publications/i/item/9789240017900 (Accessed 17/3/23).
• Yaple, Z.A., Stevens, W.D. and Arsalidou, M. (2019) 'Meta-analyses of the n-back working memory task: fMRI evidence of age-related changes in pre-frontal cortex involvement across the adult lifespan', NeuroImage, 196, pp.16-31.
• Zarantonello, L., Schiff, S., Amodio, P. and Bisiacchi, P. (2020) ‘The effect of age, educational level, gender and cognitive reserve on visuospatial working memory performance across adult life span’, Aging, Neuropsychology, and Cognition, 27(2), pp.302-319.
• Zhang, W. and Lim, B.Y. (2022) ‘Towards relatable explainable AI with the perceptual process’, in Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. pp. 1-24. DOI: 10.1145/3491102.3501826.