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Revolutionising the Classroom: How Brain Science and AI Can Empower Every Educator


As teachers and educators, we dedicate ourselves to nurturing young minds, but how often do we consider the intricate biological and cognitive processes underpinning learning itself? By exploring the fundamental principles of behaviour, learning, and memory, alongside the fascinating insights from deep learning, we can unlock powerful strategies to truly empower our students.


Understanding Behaviour: The Biological Blueprint for Learning

Behaviour is the range of actions an individual or organism undertakes, often in response to internal or external stimuli. In a biological context, it encompasses the internally coordinated responses of living organisms to various triggers. Crucially, behaviour can be innate, learned, or a combination of both, with more complex nervous systems allowing learning to have a greater influence. This biological foundation suggests that much of what we aim to teach in schools involves shaping and guiding learned behaviours.


A pivotal figure in understanding the biological basis of learning is Nobel laureate Eric Kandel. His groundbreaking work with the marine mollusk Aplysia californica demonstrated that memory storage relies on modifications in the synaptic connections between neurons.


Simple forms of learning, like habituation (a decrease in response to a repeated stimulus) and sensitisation (an increased response to a harmful stimulus), involve specific synaptic changes that are applicable even to humans.


Kandel's research highlighted that long-term memory, unlike short-term memory, requires the synthesis of new proteins, with particular transmitters, receptors, and new synapse pathways reinforcing communicative strength between neurons.

One of the key proteins identified in long-term memory storage is CREB (cAMP response element binding protein), which, when activated, can even lead to an increase in the number of synaptic connections.



What does this mean for teachers?

It reinforces that learning is a physical process of strengthening and forming neural pathways. Consistent practice, repetition (when used strategically), and meaningful engagement aren't just good teaching practices; they are direct mechanisms for building and solidifying these crucial brain connections.



Deciphering Learning: More Than Just Memorisation

Learning is a lifelong process, beginning at birth, through which individuals acquire new understanding, knowledge, behaviours, skills, values, attitudes, and preferences. It's a continuous interaction with the environment. Recognising the diverse ways students learn is paramount:

Active Learning: This occurs when a student takes control of their learning, actively monitoring their understanding and engaging in internal dialogue, often through "self-explaining". This metacognitive strategy leads to stronger, more retained learning.


Meaningful Learning: Unlike rote learning (memorising by repetition without understanding), meaningful learning involves fully comprehending new knowledge by relating it to existing knowledge. It's about building a comprehensive understanding of context.


Associative Learning: Principles like operant conditioning (learning through rewards and punishments) and classical conditioning (associating a stimulus with a response) are foundational. Positive reinforcement, such as praising students for correct answers, can increase their motivation and ability.


Play: For children, play is a vital form of learning, developing social, emotional, thinking, and language skills, and fostering creative thinking and problem-solving.



Beyond these types, several factors significantly impact learning:


Instructional Techniques: Evidence-based methods like the spacing effect (spreading out lessons over time instead of cramming) and the testing effect (using low-stakes quizzes to improve retention) are highly effective.


Psychological Factors: Intrinsic motivation (curiosity, desire to explore) is more effective than extrinsic motivation (grades). Counterproductive attitudes, such as always finding fault or embarrassing students, should be avoided.


Socioeconomic and Physical Conditions: Factors like malnutrition, fatigue, poor health, and inadequate classroom environments (e.g., poor ventilation, lighting, crowded spaces) can impede learning. Awareness of these allows educators to address barriers beyond content delivery.


Epigenetic Factors: Learning involves dynamic changes in gene expression within brain neurons, mediated by epigenetic mechanisms like DNA methylation and histone modifications, highlighting the deep biological impact of learning experiences.



The Role of Memory: Storing and Retrieving Knowledge


Memory is the mind's faculty for encoding, storing, and retrieving information. It's a complex process involving sensory, short-term (working), and long-term components.


Working Memory: This actively maintains information for short-term use and is critical for thought processes and reasoning. Teachers can aid working memory by breaking down complex information into manageable chunks.


Long-Term Memory: This involves more stable and permanent changes in neural connections across the brain. The hippocampus is essential for consolidating new information from short-term to long-term memory.


Memory is highly susceptible to various factors:


Stress: Both chronic and short-term stress significantly impair memory formation and retrieval, particularly affecting the hippocampus. Creating a supportive, low-stress classroom environment is vital. Testing students in a consistent context (e.g., their regular classroom) can also improve recall under stress.


Sleep: Crucial for memory consolidation, as it strengthens neural connections and transfers memories to long-term storage. Sleep deprivation makes learning less efficient and can even lead to false memories.


Memory Construction: Our memories are not perfect recordings but are actively constructed and can be influenced by misleading information, leading to false memories. This highlights the importance of critical thinking and accurate information delivery.


Memory Improvement: Simple lifestyle changes, including memory exercises, healthy eating, physical activity, and stress reduction, can improve cognitive function and brain efficiency.



Lessons from Deep Learning: AI as a Conceptual Mirror


Deep learning, a subset of machine learning, uses multi-layered neural networks inspired by biological neuroscience to process data. While current neural networks aren't direct models of human brain function, they offer conceptual insights for human learning:


Layered Abstraction and Feature Learning: Deep neural networks transform raw input through layers to create progressively more abstract representations, like recognising basic shapes before identifying a face. This mirrors how students build complex understanding by mastering fundamental concepts first. Educators can design curricula that facilitate this hierarchical knowledge construction.


Overfitting: Deep learning models can "overfit" by learning rare dependencies in training data, hindering their ability to generalise to new situations. Analogously, students might rote memorise specific examples without grasping underlying principles, making it hard to apply knowledge flexibly. This underscores the need for diverse examples, real-world application, and assessment that tests conceptual understanding, not just recall.


Bringing It All Together for the Classroom

By integrating these insights, teachers can develop more effective, evidence-based, and human-centred pedagogical approaches:


Design for Brain Health: Recognise the impact of stress and sleep on memory. Advocate for and foster learning environments that are supportive, reduce anxiety, and encourage healthy habits.


Promote Active and Meaningful Engagement: Move beyond rote memorisation. Encourage students to "self-explain," connect new information to existing knowledge, and engage in hands-on, problem-solving activities.


Leverage Spaced Repetition and Testing: Integrate low-stakes quizzes and spaced review sessions into your curriculum to strengthen neural connections and promote long-term retention.


Cultivate Intrinsic Motivation: Tap into students' natural curiosity, provide positive reinforcement, and give them agency in their learning journey.


Build Knowledge Systematically: Just as deep learning models build abstract representations layer by layer, guide students from foundational concepts to more complex ideas, providing diverse examples to ensure deep understanding and generalisation.


By understanding the biological and cognitive mechanisms of behaviour, learning, and memory, informed by the conceptual parallels from deep learning, we can design classrooms that truly resonate with how our students' brains work, unlocking their full potential.

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References

• Aizenberg, I.N., Aizenberg, N.N. and Vandewalle, J. (2000) Multi-Valued and Universal Binary Neurons. Science & Business Media.

• Amari, S. (1967) 'A theory of adaptive pattern classifier', IEEE Transactions, 16, pp. 279–307.

• Baddeley, A.D. (1966) 'The influence of acoustic and semantic similarity on long-term memory for word sequences', The Quarterly Journal of Experimental Psychology, 18(4), pp. 302–309.

• Baddeley, A. (2000) 'The episodic buffer: a new component of working memory?', Trends in Cognitive Sciences, 4(11), pp. 417–423.

Behavior - Wikipedia (2024) Wikimedia Foundation. Available at: https://en.wikipedia.org/wiki/Behavior (Accessed: 18 June 2025).

• Bernstein, C. (2022) 'DNA Methylation and Establishing Memory', Epigenetic Insights, 15.

• Cao, L. (2010) 'In-depth Behavior Understanding and Use: the Behavior Informatics Approach', Information Science, 180(17), pp. 3067–3085.

• Chance, P. and Furlong, E. (2022) Learning and Behavior: Active Learning Edition. 8th edn. Boston, MA: Cengage Learning.

Deep learning - Wikipedia (2024) Wikimedia Foundation. Available at: https://en.wikipedia.org/wiki/Deep_learning (Accessed: 18 June 2025).

• Deng, L. and Yu, D. (2014) 'Deep Learning: Methods and Applications'. Springer.

Eric Kandel - Wikipedia (2024) Wikimedia Foundation. Available at: https://en.wikipedia.org/wiki/Eric_Kandel (Accessed: 18 June 2025).

• Ferrie, C. and Kaiser, S. (2019) Neural Networks for Babies. Sourcebooks.

• Gagliano, M., Vyazovskiy, V.V., Borbély, A.A., Grimonprez, M. and Depczynski, M. (2016) 'Learning by Association in Plants', Scientific Reports, 6(1).

• Goldstein, E.B. (2015) Cognitive Psychology: Connecting Mind, Research, and Everyday Experience. 4th edn. Stamford, CT: Cengage Learning.

• Hinton, G., Deng, L., Yu, D., Dahl, G., Mohamed, A., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T. and Kingsbury, B. (2012) 'Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups', IEEE Signal Processing Magazine, 29(6), pp. 82–97.

• Kandel, E.R. (2000) Nobel Prize in Physiology or Medicine 2000. Available at: https://www.nobelprize.org/prizes/medicine/2000/kandel/biographical/ (Accessed: 7 June 2024).

• Kandel, E.R. (2005) In Search of Memory: The Emergence of a New Science of Mind. New York: W. W. Norton & Company.

• Kandel, E.R. (2012) 'The molecular biology of memory: cAMP, PKA, CRE, CREB-1, CREB-2, and CPEB', Molecular Brain, 5(1).

• Kandel, E.R., Schwartz, J.H., Jessell, T.M., Siegelbaum, S.A. and Hudspeth, A.J. (2012) Principles of Neural Science. 5th edn. New York: McGraw-Hill.

• Krizhevsky, A., Sutskever, I. and Hinton, G. (2012) ImageNet Classification with Deep Convolutional Neural Networks.

Learning - Wikipedia (2024) Wikimedia Foundation. Available at: https://en.wikipedia.org/wiki/Learning (Accessed: 18 June 2025).

• LeCun, Y., Bengio, Y. and Hinton, G. (2015) 'Deep Learning', Nature, 521(7553), pp. 436–444.

• Lillemyr, O.F. (2009) Taking play seriously. Children and play in early childhood education: an exciting challenge. Charlotte, NC: Information Age Publishing.

• Loftus, E.F. and Palmer, J.C. (2005) 'Reconstruction of automobile destruction: An example of the interaction between language and memory', Journal of Verbal Learning & Verbal Behavior, 13(5), pp. 585–589.

• Mangal, S.K. (2007) Essentials of Educational Psychology. PHI Learning Pvt. Ltd.

Memory - Wikipedia (2024) Wikimedia Foundation. Available at: https://en.wikipedia.org/wiki/Memory (Accessed: 18 June 2025).

• Perkins, D.N. and Salomon, G. (1992) 'Transfer of Learning', in International Encyclopedia of Education.

Perception - Wikipedia (2024) Wikimedia Foundation. Available at: https://en.wikipedia.org/wiki/Perception (Accessed: 18 June 2025).

• Pollak, D.D., Monje, F.J., Zuckerman, L., Denny, C.A., Drew, M.R. and Kandel, E.R. (2008) 'An animal model of a behavioral intervention for depression', Neuron, 60(1), pp. 149–161.

• Pryor, K. (1999) Don't Shoot the Dog: The New Art of Teaching and Training. Revised edn. New York: Bantam.

• Schmidhuber, J. (2015) 'Deep Learning in Neural Networks: An Overview', Neural Networks, 61, pp. 85–117.

• Schwabe, L. and Wolf, O.T. (2009) 'The context counts: congruent learning and testing environments prevent memory retrieval impairment following stress', Cognitive, Affective & Behavioral Neuroscience, 9(3), pp. 229–236.

• Schwabe, L. and Wolf, O.T. (2010) 'Learning under stress impairs memory formation', Neurobiology of Learning and Memory, 93(2), pp. 183–188.

• Smolen, P., Zhang, Y. and Byrne, J.H. (2016) 'The right time to learn: mechanisms and optimization of spaced learning', Nature Reviews Neuroscience, 17(2), pp. 77–88.

• Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I. and Fergus, R. (2013) Intriguing properties of neural networks.

• Wu, Y., Schuster, M., Chen, Z., Le, Q.V., Norouzi, M., Macherey, W., Krikun, M., Cao, Y., Gao, Q., Macherey, K., Klingner, J., Shah, A., Johnson, M., Liu, X., Kaiser, Ł., Gouws, S., Kato, Y., Kudo, T., Kazawa, H., Stevens, K., Kurian, G., Patil, N., Wang, W., Young, C., Smith, J., Riesa, J. and Rudnick, A. (2016) Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.

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