How Do We Learn?
"Learning is not a passive recording of information; it is an active process of adaptation and reconstruction that changes the neural connectivity of the brain throughout the lifespan and is shaped by cultural context." — Adapted from NASEM (2018)
The Changing Brain:
Neuroplasticity and Culture
Learning is both a biological and a cultural process, and these two factors are inextricably intertwined. From birth, an individual's brain physically alters its structure in response to environmental experiences; this is called Neuroplasticity.
Contrary to older theories, brain development is not limited to childhood. As highlighted by the National Academies (2018), it is a lifelong process where neural architecture is continually reshaped by use.
Synaptic Pruning: Efficiency by Design
Early in life, the brain produces an overabundance of synaptic connections. Through adolescence and adulthood, frequently used neural pathways are strengthened and preserved, while less active connections are weakened or eliminated. This process, known as "Pruning," increases the efficiency of neural networks.
Crucially, this biological process is shaped by culture. The environment an individual lives in signals which neural pathways are "important," thereby influencing how the brain optimizes its architecture.
The relationship between learning and brain development is reciprocal. Learning changes the brain, and the developing brain opens doors to new learning. Culturally supportive and cognitively engaging environments support the development of denser, more complex neural networks (NASEM, 2018).
Click the button below to observe how the brain strengthens active pathways and deletes passive ones.
Implicit and Statistical
Occurs without conscious effort. The brain automatically detects frequency and patterns (statistical structure) in the environment. Example: A toddler internalizing grammatical rules simply by listening to speech.
Observational and Social
Humans engage in "no-trial learning" by watching others. This is vital for acquiring cultural norms and skills where trial-and-error would be inefficient or risky.
Abductive (Inference)
Inference to the Best Explanation: Unlike simple deduction, abduction involves forming a hypothesis to explain a surprising observation. The learner builds mental models and adapts them to make sense of new, ambiguous situations.
There Is No Single
"Learning Style"
The brain activates different cognitive systems depending on the task. The NASEM report emphasizes that effective learning often combines conscious (explicit) and unconscious (implicit) processes.
Integrated System:
In real-world scenarios, these types overlap. For example, gamers solving protein puzzles in Foldit use rule-based logic (explicit), pattern recognition (implicit), and the observation of other players' strategies simultaneously.
MEMORY RECONSTRUCTED
Remembering is
Reconstructing
Not a Video Camera:
Popular belief often views memory as a library archive or video recording. However, cognitive science confirms the reconstructive nature of memory. When you recall information, you do not retrieve a static file; you reconstruct the event using current context, environmental cues, and existing knowledge.
- Encoding: Transforming an experience into a mental representation.
- Consolidation: Stabilizing the memory trace (sleep is critical here).
- Retrieval & Reconsolidation: Re-accessing the memory. Crucially, every time a memory is retrieved, it becomes malleable and is "re-saved" (reconsolidated), meaning it can be altered by new information.
Because memory relies on cues, what we remember is heavily influenced by the context in which we are asked to recall it.
The Expert Mind:
Organization over Volume
New learning is always built upon existing knowledge. The primary difference between experts and novices is not just the amount of knowledge, but how that knowledge is organized.
Conditionalized Knowledge:
Experts (as synthesized in NASEM, 2018) understand not only "what" information is, but "when," "where," and "why" to use it.
Chunking: Experts process information by grouping distinct pieces into meaningful wholes ("chunks"). This creates efficient schemas that reduce the load on working memory (a concept originally detailed by Miller, 1956, and highlighted in HPL II).
Caution - Expert Blind Spots: Prior knowledge can sometimes create resistance to new learning. Experts may struggle to explain their reasoning to novices because their knowledge has become automated and implicit.
Mental Organization
Scattered, unrelated data pieces. No context.
Chunked and connected schemas.
The Engine of Learning
Learning is as much an emotional and motivational process as it is a cognitive one. Motivation is shaped by an individual's goals, values, and beliefs about themselves.
Mindset and Resilience:
Research synthesized in the report suggests that students' beliefs about intelligence can influence their persistence.
- Growth Mindset: The belief that intelligence is malleable can foster resilience in the face of challenges.
- Fixed Mindset: Viewing ability as static may lead students to interpret failure as a lack of potential.
(Note: While influential, mindset interventions vary in effectiveness depending on implementation and context.)
Self-Regulation: Success is often linked to self-regulation—the ability to monitor one's own understanding, set goals, and adjust strategies when stuck.
Identity and Belonging:
Sense of Belonging: Motivation tends to increase when students feel valued and accepted within the learning environment.
Stereotype Threat: When students feel at risk of confirming a negative stereotype about their social group (e.g., regarding gender or race), the resulting anxiety can consume working memory resources and impair performance. Creating safe, identity-affirming environments is a critical evidence-based intervention to mitigate this risk.
"I believe I can succeed (Self-Efficacy), I control my strategy (Self-Regulation), I belong to this group (Belonging)." (NASEM, 2018).
PREPARED BY
Assoc. Prof. Ă–mer AVCI
Assoc. Prof. Serkan UÇAN
IMU AI & Digital Transformation Office
References
National Academies of Sciences, Engineering, and Medicine. (2018). How People Learn II: Learners, Contexts, and Cultures. The National Academies Press. https://doi.org/10.17226/24783