Learning

For theories of learning that pertain to educational psychology, see Learning theory (education). For the album by Perfume Genius, see Learning (album).

• Several terms redirect here. For other uses, see Learn (disambiguation), Learned (disambiguation), and Learners (film).

American students learning how to make and roll sushi

Cognitive psychology

• Perception
  • Visual
  • Object recognition
  • Face recognition
  • Pattern recognition
• Attention
• Memory
  • Aging
  • Emotional
  • Learning
  • Long-term
• Metacognition
• Language
• Metalanguage
• Thinking
  • Cognition
  • Concept
  • Reasoning
  • Decision making
  • Problem solving
• Numerical cognition
  • Number sense
  • in animals
  • Numerosity adaptation effect
  • Approximate number system
  • Parallel individuation system

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• v • t • e

Learning, in its most fundamental and perhaps most exhausting sense, is the relentless, often unbidden, acquisition of new understanding, the accumulation of knowledge, the shaping of behaviors, the honing of skills, the absorption of values, the subtle shifts in attitudes, and the formation of preferences. It's the universe's way of ensuring nothing truly remains static, a constant, low-level hum of change in every living (and some non-living) entity. This capacity for adaptation, for absorbing information and modifying internal states or external actions, is not exclusively the domain of humans. Indeed, it is demonstrably present in non-human animals, and, with a certain algorithmic grace, in some machines. Furthermore, for those who truly enjoy questioning the boundaries of consciousness and biological imperatives, there is even emerging, if somewhat contentious, evidence suggesting that certain plants exhibit rudimentary forms of learning.

One might observe learning as an instantaneous, almost brutal, epiphany, triggered by a singular, undeniable event—such as the unforgettable, searing lesson delivered by a hot stove when one is burned. Such immediate, high-impact lessons often prove remarkably effective, if not entirely pleasant. However, the vast majority of skill and knowledge accumulation is a far more protracted and tedious affair, a slow accretion built upon the bedrock of repeated experiences, iterations, and the often-frustrating cycle of trial and error. The profound changes wrought by this continuous process of learning frequently endure for a lifetime, becoming so deeply embedded as to be indistinguishable from inherent traits. Ironically, it is often a challenge to discern whether learned material is genuinely "lost" to the sands of time, or merely inaccessible, lurking in some unindexed corner of the mind, patiently awaiting the precise, elusive retrieval cue.

For humans, this ceaseless journey of learning commences not with the first conscious thought, but rather at birth—and, intriguingly, perhaps even prior to it, a notion that suggests our foundational programming begins earlier than we often assume. It then persists without interruption until the final cessation of life, a direct and unavoidable consequence of the perpetual, complex interactions between individuals and their ever-shifting environment. The intricate nature and multifaceted processes that underpin learning are subjects of rigorous investigation across a multitude of established academic disciplines. These include the insightful, if occasionally overly earnest, inquiries of educational psychology, the meticulous cerebral mapping of neuropsychology, the controlled observations of experimental psychology, the interdisciplinary explorations of cognitive sciences, and the practical, often aspirational, frameworks of pedagogy. Beyond these traditional bastions of inquiry, newer, more specialized fields are also emerging, demonstrating a shared, urgent interest in topics such as learning from safety events like incidents/accidents, a rather grim but undeniably crucial form of experiential education, or the collaborative endeavors within learning health systems, which aim to refine healthcare through continuous, shared knowledge acquisition.

The extensive research conducted within these diverse fields has illuminated a fascinating array of learning modalities. For instance, learning can manifest as a straightforward reduction in response to a repeated, innocuous stimulus, a phenomenon known as habituation. Alternatively, it can involve the formation of potent associations between stimuli, as observed in classical conditioning, or between behaviors and their consequences, the cornerstone of operant conditioning. Beyond these more mechanistic forms, learning also encompasses profoundly more complex activities, such as play, a seemingly frivolous pursuit that, paradoxically, is observed almost exclusively in animals endowed with relatively higher intelligence. Whether one is aware of it or not, learning can unfold both consciously—when one deliberately applies oneself to a task—or entirely without conscious awareness, an insidious, often profound, background process. A particularly stark and rather depressing outcome of certain learning experiences is a state termed learned helplessness, which arises when an individual learns that an unpleasant event is utterly unavoidable or inescapable, leading to a profound resignation. The earliest demonstrations of human behavioral learning are compelling, with evidence of habituation having been observed prenatally, as early as 32 weeks into gestation. This early observation strongly suggests that the nascent central nervous system is already sufficiently developed and primed for the foundational processes of learning and memory to begin their intricate dance, long before the grand entrance into the world.

The concept of play, often dismissed as mere recreation, has been approached by numerous influential theorists as a critically important, albeit often overlooked, form of learning. Children, in their boundless and often chaotic explorations, actively experiment with the parameters of their world, gradually internalizing its unspoken rules, and, through these interactions, learning the complex art of social engagement. Lev Vygotsky, a towering figure in developmental psychology, emphatically concurred with this perspective, asserting that play is absolutely pivotal for children's holistic development. He argued that through engaging in educational games and imaginative scenarios, children construct meaning from their surrounding environment. For Vygotsky, however, the significance of play extended even further: it served as the primordial arena for the acquisition of language and the development of communication skills, marking the critical stage where a child first grapples with the understanding of abstract rules and symbolic systems. This insightful perspective has subsequently given rise to the broader view that learning in all organisms is inextricably linked to semiosis—the process of making and interpreting signs—and is, more often than not, intimately associated with the development and utilization of sophisticated representational systems and their corresponding activities. A rather elegant, if somewhat inconvenient, truth to consider when you're just trying to remember where you left your keys.

Types

The sheer complexity of how information is acquired and retained has led to the development of various functional categorizations of memory, each attempting to carve out a coherent understanding of this elusive process. Some memory researchers, in their quest for clarity, distinguish between types of memory based on the inherent relationship between the stimuli involved, often classifying them as either associative or non-associative. Others opt for a different dichotomy, categorizing memory based on whether its content can be articulated and shared through language—leading to the distinction between declarative (explicit) and procedural (implicit) forms. To complicate matters further, many of these broader categories can, in turn, be meticulously parsed into even finer sub-types. For example, declarative memory, which is ostensibly about recalling facts and events, encompasses both the deeply personal narratives of episodic memory and the more impersonal, factual repository of semantic memory. It's almost as if the brain enjoys making things unnecessarily complicated.

Children learning to bike in the eighties in Czechoslovakia. A testament to practical, if slightly wobbly, application of learned skills.

Non-associative learning

Non-associative learning, a concept that sounds rather dry but is profoundly fundamental, refers to "a relatively permanent change in the strength of response to a single stimulus due to repeated exposure to that stimulus." It's the brain's way of economizing its reactions, deciding what's worth a full-blown response and what can be safely ignored. This definition, it's crucial to note, meticulously exempts changes that are merely the transient result of sensory adaptation, the simple exhaustion of fatigue, or the unfortunate consequences of physical injury. These are temporary states, not genuine learning.

This foundational form of learning can be further, and rather neatly, divided into two opposing, yet complementary, processes: habituation and sensitization. One involves tuning things out, the other involves turning the volume up.

Habituation

• Main article: Habituation

Habituation stands as a quintessential example of non-associative learning, illustrating how an organism's innate response to a particular stimulus can diminish over time with repeated, non-threatening exposure. This isn't about forgetting; it's about discerning what requires attention. When a stimulus is presented repeatedly without any significant consequence, one or more components of the initial, innate response—be it the probability of the response occurring, its duration, or its intensity—gradually wanes. Thus, it is imperative to distinguish habituation from extinction, which operates on an entirely different, associative principle. In operant extinction, for instance, a learned response decreases because it is no longer followed by a reward, implying a previous association has been broken. Habituation, however, is a more primitive filtering mechanism.

A common, illustrative example can be observed in small songbirds. If a stuffed owl, or any similar effigy of a predator, is introduced into their cage, the birds will initially react with alarm, treating it as a genuine threat. However, with sustained exposure to this inert, unchanging 'predator,' the birds' alarm response will predictably lessen, demonstrating habituation. Yet, if an entirely different stuffed owl is subsequently introduced, or if the original one is temporarily removed and then re-introduced in a slightly altered context, the birds will often react with renewed alarm. This critical detail underscores that habituation is typically highly specific to the exact stimulus encountered (e.g., one particular, unmoving owl in a fixed location), not a generalized dismissal of all owls. The efficiency of the habituation process itself is also influenced by stimulus characteristics: it tends to occur more rapidly for stimuli that are presented at a high frequency rather than a low rate, and, somewhat counterintuitively, for both very weak and very strong stimuli, though the mechanisms might differ. This fundamental form of learning has been rigorously demonstrated across virtually every species of animal examined, extending even to the surprisingly responsive sensitive plant, Mimosa pudica, and the remarkable large protozoan, Stentor coeruleus. It functions, quite literally, in direct opposition to the process of sensitization.

Sensitization

• Main article: Sensitization

Sensitization, in stark contrast to its habituating counterpart, represents a form of non-associative learning where the response to a stimulus becomes progressively amplified following repeated administrations. It's the nervous system's way of shouting, "Pay attention! This might be important!" This heightened reactivity is predicated on the idea that a defensive reflex, such as withdrawal or escape, becomes markedly stronger after an organism has been exposed to a different, often harmful or threatening, stimulus. The system becomes generally more alert, more reactive.

An easily relatable, everyday example of this physiological mechanism can be experienced by continuously rubbing one's arm. Initially, the repeated tonic stimulation of the peripheral nerves might be benign, perhaps even pleasant. However, after a sustained period, this stimulation often transitions into a warm sensation, which can, for some, eventually become distinctly painful. This escalation to pain is a direct consequence of a progressively amplified synaptic response within those peripheral nerves, essentially sending an urgent warning signal that the stimulation is becoming detrimental. Clarification needed on the precise neural pathways for this everyday example, but the principle holds. Sensitization is believed to underpin a wide spectrum of learning processes within an organism, encompassing both beneficial, adaptive responses (where heightened awareness is advantageous) and, unfortunately, maladaptive ones, such as the amplification of pain or anxiety responses in certain disorders. Citation needed to confirm the full breadth of its maladaptive implications, but the potential is clear.

Active learning

• Main article: Active learning

Active learning is not merely a pedagogical buzzword; it describes a profound shift in the learning paradigm, one where the individual seizes control of their own educational journey. It's about moving beyond passive reception and engaging directly with the material, much like a seasoned detective interrogating a suspect rather than merely reading a cold case file. Given that genuine understanding of information is the absolute linchpin of effective learning, it becomes critically important for learners to cultivate the ability to accurately discern what they truly grasp versus what remains a murky, unexplored territory. By actively monitoring their own cognitive state, they can meticulously track their mastery of subjects, identifying gaps and areas requiring further attention.

Active learning deliberately fosters an internal dialogue, encouraging learners to articulate their emerging understandings, to question, to hypothesize, and to consolidate knowledge in their own words. This, alongside a suite of other meta-cognitive strategies—the very act of thinking about thinking—can be systematically imparted to a child over time, transforming them into more autonomous and effective learners. Extensive studies within the field of metacognition have consistently underscored the undeniable value of active learning, demonstrating that the resulting learning is typically far more robust, deeper, and enduring. Furthermore, there's a powerful motivational component at play: learners exhibit a significantly greater incentive to engage when they possess agency, not only over the how of their learning methods but also, crucially, over the what of the content itself. This self-directed engagement transforms a chore into a quest. Consequently, active learning is considered a hallmark characteristic of student-centered learning approaches, which prioritize the learner's needs and autonomy. Conversely, its antithesis, passive learning, often characterized by rote memorization and the unidirectional flow of direct instruction, remains a defining feature of teacher-centered learning (or, as some might prefer, traditional education), where the instructor is the primary dispenser of knowledge and the student merely an empty vessel.

Associative learning

Associative learning is the cognitive bedrock upon which much of our understanding of cause-and-effect, prediction, and consequence is built. It is the fundamental process by which an individual, whether human or animal, forms a mental association or link between two distinct stimuli or events that occur in close proximity in time or space. It's how we learn that A often leads to B, and how we adjust our expectations and behaviors accordingly.

Within this broad category, two primary mechanisms stand out for their profound impact on behavior. In classical conditioning, a previously innocuous, neutral stimulus is systematically and repeatedly paired with another stimulus that inherently and reliably elicits a reflexive response. Through this repeated pairing, the once-neutral stimulus eventually acquires the power to elicit that response entirely on its own. It's the involuntary, unconscious reprogramming of our reactions. In contrast, operant conditioning focuses on the consequences of voluntary actions. Here, a specific behavior that is either reinforced (rewarded) or punished in the presence of a particular stimulus becomes, over time, either more or less likely to recur when that same stimulus is encountered again. This is the conscious, or at least volitional, shaping of behavior based on its perceived outcomes.

Operant conditioning

• Main article: Operant conditioning

Operant conditioning stands as a powerful, if somewhat manipulative, framework through which behavior can be meticulously shaped or modified to align with the objectives of a trainer, educator, or even, in a broader sense, the demands of the environment. The underlying premise, almost embarrassingly simplistic yet profoundly effective, posits that living organisms are fundamentally driven by the pursuit of pleasure and the avoidance of pain. Consequently, an animal or human can be guided to learn specific behaviors through the judicious application of either reward (reinforcement) or punishment, delivered at a precisely timed moment. This critical timing is often referred to as trace conditioning, which describes the brief, ideal window between the subject performing the desired behavior and subsequently receiving the positive reinforcement that solidifies the learning. For maximum efficacy, the reward must be delivered almost immediately following the successful execution of the wanted behavior, creating an undeniable link in the learner's mind.

It is crucial to differentiate operant conditioning from classical conditioning. The latter primarily focuses on modifying reflexive, involuntary bodily responses that naturally occur in reaction to specific stimuli. Operant conditioning, however, concerns itself with the deliberate shaping of voluntary, conscious behaviors—actions that necessitate active thought and, ultimately, a genuine process of learning. It's the difference between a knee-jerk reaction and a calculated decision.

The two principal, and often misunderstood, mechanisms through which operant conditioning operates are punishment and reinforcement. Punishment, despite its common usage, is primarily employed to reduce unwanted behavior. It's vital to recognize that from the learner's perspective, punishment often leads to the avoidance of the punishment itself, rather than necessarily fostering an understanding or avoidance of the underlying unwanted behavior. Indeed, punishment is generally considered an inappropriate and often counterproductive method for increasing a desired behavior in either animals or humans, frequently leading to resentment, fear, or suppression rather than genuine learning. Punishment itself is further subdivided into two categories: positive punishment and negative punishment. Positive punishment involves the addition of an aversive aspect or thing to the subject's experience. For example, a parent spanking a child would constitute positive punishment, as a physical discomfort (the spanking) is added to the child's situation. Negative punishment, conversely, involves the removal of something valued or desirable from the subject. When a parent places a child in "time out," the child is, in essence, losing the opportunity to engage with friends or enjoy the freedom to do as they please. In this scenario, the removal of the child's desired rights (to play, to interact) serves as negative punishment.

Reinforcement, on the other hand, is the preferred and more effective strategy, used specifically to increase the likelihood of a wanted behavior. Like punishment, it also has two subcategories: negative reinforcement and positive reinforcement. Negative reinforcement is defined by the removal of an undesirable aspect or thing from an individual's life. For example, a dog might learn to sit not because it's inherently pleasurable, but because when it sits, the trainer stops scratching its ears, thereby removing an irritating itch (the undesirable aspect). The dog learns to sit to make the unpleasant stimulus go away. Positive reinforcement, the most widely recognized and often most effective method, involves the addition of a desirable aspect or thing. For instance, a dog might rapidly learn to sit if, upon doing so, it immediately receives a delicious treat. In this clear example, the treat, a desirable item, is added to the dog's experience, increasing the likelihood of the sitting behavior recurring. The distinction is subtle but critical: punishment suppresses, reinforcement encourages, and both can be achieved through addition or subtraction of stimuli.

Classical conditioning

• Main article: Classical conditioning

The quintessential paradigm for classical conditioning, a fundamental mechanism of associative learning, involves the repeated, systematic pairing of an unconditioned stimulus (US)—an event that inherently, without any prior learning, triggers a reflexive, often involuntary, response—with another stimulus that was previously neutral (NS), meaning it did not naturally evoke that response. Through this diligent pairing, the once-neutral stimulus eventually transcends its neutrality and acquires the capacity to elicit a response all on its own. At this point, the previously neutral stimulus is re-designated as the "conditioned stimulus" (CS), and the response it now elicits is termed the "conditioned response" (CR). It's the brain making an arbitrary connection, then treating it as fact.

The most iconic and frequently cited example of this process is, of course, Ivan Pavlov and his famously salivating dogs. Pavlov, ever the meticulous observer, noted that when his dogs were presented with meat powder, they would naturally salivate—an unconditioned, reflexive response to a biologically significant stimulus. Here, the meat powder served as the unconditioned stimulus (US), and the involuntary salivation was the unconditioned response (UR). Pavlov then introduced a seemingly unrelated element: he would ring a bell just before presenting the meat powder. Initially, when the bell, a neutral stimulus, was rung for the first time, the dogs showed no particular salivation response. However, the moment the meat powder was placed in their mouths, the salivation began. After numerous such pairings of the bell and the subsequent food presentation, a profound shift occurred: the dogs learned to anticipate the food upon hearing the bell. Consequently, they began to salivate at the sound of the bell alone. At this juncture, the bell had transformed into the conditioned stimulus (CS), and the salivation elicited by the bell had become the conditioned response (CR). This elegant demonstration of classical conditioning has since been replicated and observed across an astonishing array of species, illustrating its fundamental role in adaptive behavior. For instance, it's evident in honeybees, particularly within the context of the proboscis extension reflex paradigm, where they learn to extend their proboscis in anticipation of a sugary reward. More recently, and rather surprisingly, this form of learning has even been demonstrated in garden pea plants, challenging conventional notions of what constitutes a 'learner.'

Another profoundly influential figure in the development of classical conditioning theory was John B. Watson. Watson's work was not only highly impactful but also laid foundational groundwork for the more radical behaviorism later championed by B.F. Skinner. Watson's behaviorist philosophy, extending to his views on the philosophy of science itself, stood in stark and deliberate opposition to the prevailing psychoanalytic theories of Freud and other psychological accounts that relied heavily on subjective introspection. Watson's core contention was that the introspective method was inherently too subjective and unreliable for a truly scientific psychology. He argued vehemently that the study of human development should be rigorously confined to directly observable behaviors, those that could be objectively measured and analyzed. In 1913, Watson solidified this stance with the publication of his seminal article, "Psychology as the Behaviorist Views It," advocating for laboratory studies as the optimal approach for psychology to establish itself as a legitimate science. Watson's most famous, and certainly his most ethically controversial, experiment was the "Little Albert" study. In this disturbing demonstration, he purported to show how psychologists could account for the learning of complex emotions, specifically fear, through the precise application of classical conditioning principles. The implications of such a demonstration, both scientific and ethical, resonated for decades.

Observational learning

• Main article: Observational learning

Observational learning is precisely what it sounds like: the acquisition of new knowledge, skills, or behaviors simply by observing the actions of others. It’s a sophisticated form of social learning, one that allows for rapid, efficient transfer of information without the need for direct, often costly, personal experience. This capacity manifests in various forms, underpinned by a spectrum of cognitive processes that allow for imitation, modeling, and vicarious reinforcement. Crucially, in humans, this type of learning appears to operate quite effectively even without the immediate presence of direct reinforcement or punishment for the observer. Instead, it critically relies on the presence of a credible social model—be it a parent, a sibling, a peer, or a teacher—within a relevant social context. We learn not just by doing, but by watching others stumble, succeed, and navigate the complexities of their environment. It's a shortcut to wisdom, often, or at least a path to knowing what not to do.

Imprinting

• Main article: Imprinting (ethology)

Imprinting represents a particularly striking and often irreversible form of learning, characterized by its rapid onset and its occurrence during a highly specific, sensitive period in an animal's early life stage. What makes it so distinct is its apparent independence from the usual consequences of behavior—it doesn't seem to require rewards or punishments to solidify. In the context of filial imprinting, a phenomenon most vividly observed in young animals, particularly precocial birds, the newly hatched or born individual forms an incredibly strong, often unwavering, association with another individual or, in some peculiar cases, even an inanimate object. This bond is so powerful that the young animal subsequently responds to this imprinted figure as it would to a biological parent, seeking proximity, comfort, and protection.

The seminal work on this fascinating behavior was conducted by the Austrian Zoologist Konrad Lorenz. In 1935, Lorenz famously discovered that certain species of birds, notably geese and ducks, would follow and form an indelible bond with the first moving object they encountered during a critical developmental window, provided that object also emitted sounds. His experiments, which included him becoming the 'mother' to a brood of goslings, vividly illustrated the power and specificity of this early learning mechanism. Imprinting demonstrates that not all learning is a gradual process; some foundational knowledge is laid down with astonishing speed and permanence, shaping an individual's social and behavioral trajectory from its earliest moments.

Play

• Main article: Play (activity)

Play, in its broadest and most enigmatic sense, generally describes a suite of behaviors that appear to have no immediate, utilitarian end goal in themselves. Yet, this seemingly purposeless activity paradoxically serves a critical function: it measurably improves an organism's performance in similar, more consequential situations in the future. It's practice, but without the pressure of a looming deadline. This profound, developmental behavior is not exclusive to humans; it is observed across a remarkably wide variety of vertebrates, though it is largely confined to the more cognitively advanced classes of mammals and birds.

Consider, for example, young cats, which are notoriously known for their playful interactions with a simple ball of string. This seemingly trivial game provides them with invaluable, hands-on experience in stalking, pouncing, and catching, honing the very skills that will be essential for hunting actual prey in adulthood. Beyond inanimate objects, animals frequently engage in play with other members of their own species, forging social bonds and practicing complex social dynamics. Even more astonishingly, highly intelligent animals, such as orcas, have been observed engaging in what appears to be playful manipulation of seals they have already caught, suggesting a sophisticated, perhaps even cruel, form of practice or entertainment.

The act of play carries a significant cost for animals. It invariably increases their vulnerability to opportunistic predators, exposes them to a heightened risk of physical injury, and potentially even subsequent infection. Furthermore, it consumes precious energy that could otherwise be directed towards survival-critical activities like foraging or reproduction. Given these considerable biological expenditures, the widespread evolution of play strongly implies that it must confer substantial, enduring benefits to outweigh these risks. The observation that play is predominantly concentrated in younger animals powerfully suggests a strong, intrinsic link with learning and development. However, it is also plausible that play offers additional benefits not directly tied to cognitive acquisition, such as the enhancement of physical fitness, the maintenance of social hierarchies, or even the sheer joy of movement.

When we consider play as it pertains specifically to humans, it moves from a mere adaptive behavior to a central, indispensable pillar of a child's learning and overall development. Through the seemingly simple act of play, children acquire a vast repertoire of fundamental social skills, learning the intricacies of sharing, the necessity of collaboration, and the delicate art of negotiation. Moreover, play is a crucial crucible for the development of robust emotional skills; it provides a safe, low-stakes arena for children to explore, express, and ultimately learn to manage powerful emotions, such as anger or frustration, in constructive ways. As a powerful form of learning, play also profoundly facilitates the development of sophisticated thinking processes and crucial language skills in children, allowing them to construct narratives, understand symbols, and experiment with communication.

The landscape of human play is remarkably diverse, typically categorized into five distinct, yet often intersecting, types:

• Sensorimotor play, also known as functional play, is characterized by the pure, often repetitive, enjoyment of an activity for its own sake, exploring the physical capabilities of one's body and the properties of objects.
• Roleplay, a more complex form, typically emerges around the age of three, where children begin to mimic and enact various roles, exploring social identities and narratives.
• Rule-based play involves activities where authoritatively prescribed codes of conduct and explicit regulations become the primary organizing principle, teaching children about fairness, strategy, and adherence to structure.
• Construction play engages children in experimentation and the active process of building, fostering spatial reasoning, creativity, and problem-solving.
• Movement play, also referred to as physical play, encompasses energetic activities that develop gross motor skills, coordination, and physical prowess.

Critically, all five of these play types, in their myriad manifestations, serve as powerful catalysts for the generation of sophisticated thinking and problem-solving skills in children. When children learn through play, they are actively encouraged and enabled to think creatively, to innovate solutions, and to approach challenges with flexibility. The specific activities encompassed within each type of play naturally evolve and transform over time, adapting as individuals progress through the various stages of the human lifespan. Furthermore, play, as a profound mechanism for learning, can unfold either solitarily, allowing for introspective exploration and skill development, or, more commonly, through rich, dynamic interactions with others, cementing its role as a cornerstone of both individual and social development.

Enculturation

• Main article: Enculturation

• See also: Cultural learning

Enculturation is the subtle, pervasive, and often unconscious process through which individuals absorb and internalize the values and behaviors that are deemed appropriate, necessary, and often unquestionable within their immediate surrounding culture. It's the silent curriculum of society, taught through observation, participation, and subtle correction. This profound shaping of identity and conduct is primarily mediated by significant figures in an individual's life: parents, other influential adults, and peer groups all play critical roles in molding one's nascent understanding of these deeply embedded cultural norms. If this intricate process is successful—and it usually is, for better or worse—enculturation culminates in a demonstrable competence in the specific language, the core values, and the intricate rituals that define that particular culture. This is a distinct process from acculturation, which describes the adoption of the values and societal rules of a culture that is different from one's native one, implying a conscious shift rather than an organic absorption.

Numerous compelling examples of enculturation can be observed across diverse cultural landscapes, illustrating its universal yet context-specific nature. Among the Mazahua people, for instance, collaborative practices deeply embedded in everyday interactions and subsequent learning activities have been shown to contribute significantly to an enculturation process rooted in nonverbal social experience. As children actively participate in daily routines and communal tasks, they organically absorb the profound cultural significance and implicit meanings embedded within these interactions. Similarly, the collaborative and inherently helpful behaviors frequently exhibited by Mexican and Mexican-heritage children are a culturally ingrained practice known as being "acomedido," reflecting a deep-seated value of mutual assistance. In the remote Chillihuani communities of Peru, girls describe themselves as weaving almost constantly, a direct reflection and internalization of the behavior consistently modeled by the adult women around them. These examples underscore how enculturation is not merely about instruction, but about immersion and participation in the living fabric of a culture.

Episodic learning

Episodic learning refers to a distinct category of learning where a change in behavior occurs as a direct and often singular consequence of a specific, personally experienced event. It's the "I learned my lesson the hard way" kind of knowledge acquisition. For instance, developing a profound fear of dogs immediately following a traumatic incident of being bitten by one is a classic example of episodic learning. The memory of that event, vivid and impactful, directly alters subsequent behavior.

This form of learning is aptly named because such significant events are meticulously recorded and stored within our episodic memory. Episodic memory itself is one of the three primary forms of explicit learning and retrieval, working in conjunction with perceptual memory (the memory for sensory experiences) and semantic memory (the memory for facts and general knowledge). The defining characteristic of episodic memory is its capacity to recall specific events and personal histories, complete with their embedded experiential context—the "what, where, and when" of an experience. This stands in clear contrast to semantic memory, which endeavors to extract generalized facts and concepts from their original experiential context, organizing them into a more abstract, timeless structure of knowledge. For example, if an individual vividly recalls their recent visit to the Grand Canyon—the sights, the sounds, the feelings—that is an episodic memory. However, if someone were to inquire about factual information, such as the geographical location of the Grand Canyon or its geological formation, the individual would draw upon their semantic memory to provide an answer. Interestingly, research has revealed that humans possess an astonishing degree of accuracy in recognizing episodic memory, even when there was no deliberate intention to memorize the event. This remarkable capacity is often interpreted as an indication of the brain's extraordinarily large storage capabilities for information to which individuals pay even a modicum of attention. It seems we are constantly, if unconsciously, archiving our lives.

Multimedia learning

• Main article: Multimedia learning

Multimedia learning is a pedagogical approach that leverages the power of multiple sensory channels, specifically when a person utilizes both auditory and visual stimuli concurrently to acquire and process information. It's the brain's way of getting a richer, more redundant input, ideally leading to deeper encoding. This particular type of learning is deeply rooted in and strongly supported by dual-coding theory, a cognitive framework that posits that information is processed and stored in memory through two distinct, yet interconnected, systems: a verbal system (for linguistic information) and an imaginal system (for nonverbal information, such as images). When both systems are engaged simultaneously, as in multimedia learning, the chances of successful encoding and retrieval are significantly enhanced. It’s like having two separate, reinforcing pathways to the same destination.

E-learning and augmented learning

• Main article: Electronic learning

Electronic learning, more commonly known as e-learning, encompasses any form of learning that is facilitated or enhanced by computer technology. It represents a vast and ever-evolving landscape of digital education. A particularly prevalent and increasingly widespread subset of e-learning is mobile learning (m-learning), which ingeniously harnesses the ubiquitous nature of various mobile telecommunication devices, such as cellular phones and tablets, to deliver educational content and experiences. It's education on the go, whether you want it or not.

When a learner actively interacts with a dynamically designed e-learning environment, this engagement is often termed augmented learning. The defining characteristic of augmented learning is its capacity to adapt precisely to the individual needs and specific context of the learner. This context-driven instruction can be dynamically tailored, providing content and experiences that are uniquely relevant to the learner's natural environment and current situation. Augmented digital content is rich and varied, potentially incorporating text, still images, dynamic video, and diverse audio elements (including both music and spoken voice). By meticulously personalizing the instructional experience, augmented learning has demonstrated a remarkable ability to significantly improve learning performance, with benefits that can potentially last a lifetime. For those interested in alternative, less intrusive approaches, the concept of minimally invasive education offers a complementary perspective.

Moore (1989) articulated a foundational framework, purporting that three core types of interaction are absolutely essential for fostering quality, genuinely effective online learning experiences:

• Learner–learner interaction: This refers to the vital communication that occurs both between and among peers, with or without the direct presence of the instructor. It acknowledges the power of peer-to-peer learning and collaborative knowledge construction.
• Learner–instructor interaction: This encompasses the direct communication and engagement between the student and the teacher. It highlights the instructor's role in guiding, clarifying, and facilitating the learning process.
• Learner–content interaction: This describes the crucial intellectual engagement learners have with the educational material itself. It's the cognitive wrestling that results in tangible changes in learners' understanding, perceptions, and underlying cognitive structures.

Expanding on these ideas, Moore (1993), in his influential theory of transactional distance, further contended that both the inherent structure of the learning experience and the quality of interaction or dialogue serve as critical bridges. These elements work to span the inherent gap in understanding and communication that is inevitably created by geographical distances in online or remote learning environments—a phenomenon he termed transactional distance. It's about making the distant feel less remote through deliberate design.

Rote learning

• Main article: Rote learning

Rote learning is a method of memorizing information that prioritizes the exact recall of material precisely as it was initially encountered—read, heard, or seen—without necessarily deep understanding of its underlying meaning or context. It's the brute-force approach to memory, often employed when speed and fidelity of reproduction are paramount over comprehension. The primary technique deployed for rote learning is, unsurprisingly, relentless repetition. This method operates on the straightforward, if somewhat uninspired, premise that a learner can achieve perfect recall of the material—even if they grasp little of its significance—by repeatedly processing the information until it is firmly embedded. Rote learning finds application in an astonishingly diverse range of fields, from the memorization of mathematical formulas and sequences to the learning of musical scales and scores, and even the recitation of sacred texts in religious contexts. It's efficient for surface-level recall, but often brittle under pressure.

Meaningful learning

• See also: Deeper learning

Meaningful learning stands as a direct conceptual counterpoint to the more superficial approach of rote learning. It is predicated on the profound idea that newly acquired knowledge—be it a simple fact, a complex concept, or an intricate procedure—is truly and fully understood only to the extent that it can be logically and coherently related to an individual's existing cognitive structures and prior knowledge. It's not about isolated facts, but about building a robust, interconnected web of understanding. To this end, meaningful learning sharply contrasts with rote learning, where information is absorbed and recalled with little to no regard for its deeper significance, context, or connections to other concepts. Meaningful learning, on the other hand, inherently implies a comprehensive, integrated knowledge of the context surrounding the facts being learned. It demands not just knowing what, but also why and how it connects. This deeper engagement fosters greater retention, transferability, and application of knowledge, making it a far more resilient and useful form of acquisition.

Evidence-based learning

• Main article: Evidence-based learning

Evidence-based learning represents a pragmatic and scientifically rigorous approach to education, advocating for the systematic application of findings from well-designed scientific studies to optimize and accelerate the learning process. It's about stripping away assumptions and relying on what demonstrably works. This methodology draws heavily from cognitive psychology and neuroscience, identifying and promoting instructional techniques that have been empirically proven to enhance retention, comprehension, and skill acquisition. Evidence-based learning methods, such as the highly effective technique of spaced repetition, have been shown to significantly increase the rate at which a student can learn and retain information. By grounding educational practices in robust scientific data, this approach aims to make learning more efficient, more effective, and ultimately, less reliant on guesswork or tradition.

Formal learning

• Main article: Education

A depiction of the world's oldest continually operating university, the University of Bologna, Italy. A rather ancient example of formal learning.

Formal learning represents a highly deliberate, structured, and often institutionalized pathway for the attainment of knowledge and skills. It typically unfolds within a clearly defined teacher-student environment, such as the structured curricula of a school system or the targeted training programs within a professional work environment. The term "formal learning" itself does not, perhaps counter-intuitively, refer to the formality of the social interactions or the instructional style, but rather to the highly organized and directed nature of the learning experience. In the context of formal learning, the learning or training departments meticulously set out specific goals and measurable objectives for what is to be learned. A defining characteristic is that learners are often awarded with a diploma, a certificate, or some other form of official recognition upon successful completion, signaling their mastery of the prescribed content. It’s a standardized, often credentialed, path to knowledge.

Non-formal learning

• Main article: Nonformal learning

Non-formal learning occupies a fascinating middle ground, existing as organized learning that deliberately takes place outside the rigid confines of the formal learning system. It's structured, but without the institutional baggage. Consider, for instance, the rich learning that occurs when individuals with shared interests convene in clubs, participate in (international) youth organizations, or engage in focused workshops, exchanging diverse viewpoints and collaborating on projects. While this type of learning is organized, from the organizer's perspective, it does not always necessitate a primary objective or a predefined learning outcome in the same way formal education does. However, from the perspective of the learner, non-formal learning, despite not being fixated on explicit outcomes, frequently results in a highly intentional and meaningful learning opportunity. Individuals choose to engage, and thus, often learn with purpose, even if the "syllabus" is somewhat fluid.

Informal learning

• Main article: Informal learning

Informal learning represents the most ubiquitous and least structured form of knowledge acquisition, distinct from even the relatively relaxed framework of "non-formal learning." It is the constant, often unnoticed, learning that accrues through the sheer experience of day-to-day situations. For example, one learns, quite organically, to look ahead while walking not through explicit instruction, but through the implicit understanding of the myriad dangers inherent in failing to pay attention to one's path. It is the wisdom gleaned from life itself: during a casual meal at the table with parents, amidst the spontaneous chaos of play, or through the boundless curiosity of exploring one's environment. For the learner, informal learning is most often an experience of happenstance, a serendipitous discovery rather than a deliberately planned educational endeavor. Consequently, it does not necessitate enrollment in any class or program, nor does it typically lead to formal accreditation, unlike its formal counterpart. Informal learning truly begins to unfold as the learner actively ponders and reflects upon his or her situation, extracting insights from lived experience. This type of learning, by its very nature, requires no professor or designated instructor, and its outcomes are often unforeseen, emerging organically from the learning experience itself.

The inherent value of informal learning can be considered remarkably high, precisely because it is self-directed and intrinsically focused on the immediate, practical demands of day-to-day situations. As a direct consequence, the information and insights gleaned from informal learning experiences are highly likely to be directly applicable and relevant to daily life. Intriguingly, studies have occasionally suggested that children who predominantly engage in informal learning can, at times, demonstrate a stronger grasp and more robust support for concepts, particularly in subjects like mathematics, compared to their counterparts who primarily undergo formal instruction. This suggests a powerful, if unconventional, pathway to competency. Daily life experiences that drive informal learning are pervasive, occurring within the dynamics of the workforce, the complexities of family life, and virtually any other situation that may arise over the course of an individual's lifetime. From the learner's perspective, informal learning is fundamentally voluntary, empowering the individual to choose their own pace and preferred methods of learning. Furthermore, because this type of learning often takes place within smaller, more intimate groups or even by oneself, it provides a safe space for individuals to make mistakes and, crucially, to learn from them, fostering resilience and the discovery of effective coping strategies for difficult emotions that inevitably arise during the learning process. It's messy, undirected, and often deeply effective.

Nonformal learning and combined approaches

The intricate landscape of modern education rarely adheres to a single, monolithic approach; rather, it frequently employs a sophisticated combination of formal, informal, and nonformal learning methods to achieve its multifaceted objectives. International bodies such as the United Nations and the European Union explicitly recognize and endorse these distinct yet complementary forms of learning, acknowledging their collective contribution to holistic development. In certain progressive educational institutions, students may even be granted academic credit or "points" that count towards their formal-learning credentials for work accomplished through involvement in informal learning circuits. This might involve, for example, being allocated time to attend international youth workshops and training courses, contingent upon their willingness to prepare diligently, actively contribute, share their insights, and, crucially, demonstrate that these experiences provided valuable new perspectives, facilitated the acquisition of new skills, or offered practical experience in organizing events or even teaching others. It's a pragmatic recognition that valuable learning happens everywhere.

To illustrate the multifaceted nature of skill acquisition, consider the process of learning to solve a Rubik's Cube with impressive speed—a seemingly simple task that, in reality, draws upon a confluence of learning factors simultaneously:

• Reading directions provides the foundational knowledge for a player to understand the algorithmic patterns and sequences of moves required to solve the Rubik's Cube. This is a form of explicit, often formal learning.
• Practicing the moves repeatedly is essential for building "muscle memory" (a form of procedural memory) and significantly enhancing speed and fluidity. This is a classic example of rote learning combined with operant conditioning for skill refinement.
• Thinking critically about moves and analyzing potential sequences helps the solver identify shortcuts, optimize strategies, and develop a deeper, more meaningful understanding of the cube's mechanics, which dramatically speeds up future attempts. This involves problem-solving and metacognition.
• Observing the Rubik's Cube's six colors and their relative positions helps to anchor solutions in the mind, providing crucial visual cues and enhancing pattern recognition. This draws upon visual perception and associative learning.
• Revisiting the cube occasionally after periods of inactivity is vital for retaining the acquired skill, counteracting the natural decay of memory over time. This highlights the importance of spaced repetition and active recall.

Tangential learning

Tangential learning describes a rather elegant and often self-motivated process by which individuals embark on a journey of self-education after encountering a particular topic or concept within a context they already find inherently enjoyable or engaging. It's the accidental acquisition of knowledge, sparked by genuine interest rather than obligation. For example, a person might become deeply engrossed in a music-based video game, and through this enjoyment, find themselves unexpectedly motivated to learn how to play a real musical instrument. Similarly, watching a captivating television show that subtly references literary figures like Faust or authors like Lovecraft might inspire some individuals to seek out and read the original, complex works themselves. The enjoyment of the primary activity acts as a gateway to deeper, self-directed exploration.

The efficacy of self-education can be significantly amplified through systematization and structured approaches. According to experts in natural learning, specialized self-oriented learning training programs have proven to be remarkably effective tools for assisting independent learners in navigating the inherent, often cyclical, phases of learning with greater efficiency and purpose. The concept of games as a potential, powerful venue for "tangential learning" was first notably suggested by James Portnow, a writer for Extra Credits and a game designer, who articulated how entertainment could inadvertently lead to enlightenment.

Mozelius et al. further emphasize that the intrinsic integration of learning content within the enjoyable medium appears to be a crucial design factor for successful tangential learning. They note that games which thoughtfully incorporate modules for further self-studies tend to yield particularly positive results. A prime example cited is the built-in encyclopedias found within the Civilization series of games. By providing these accessible modules, gamers are empowered to delve deeper into historical events and figures that are interwoven into the gameplay, transforming mere entertainment into a catalyst for genuine historical knowledge acquisition. The critical importance of the rules that govern the interplay between learning modules and the overall game experience is also a significant point of discussion, as highlighted by Moreno, C., in a case study examining the mobile game Kiwaka. This particular game, developed by Landka in collaboration with prestigious organizations like ESA and ESO, employs an innovative reward structure: progress within the game is directly rewarded with access to educational content, a clever inversion of the traditional educational game model where learning activities are typically rewarded with gameplay time or in-game items. It's a subtle but powerful shift in motivational design.

Dialogic learning

• Main article: Dialogic learning

Dialogic learning is a pedagogical approach that, at its core, is founded on the principle of dialogue. It posits that genuine, transformative learning occurs most effectively through rich, interactive communication and the exchange of ideas among participants. This isn't just about talking; it's about listening, questioning, challenging, and collectively constructing meaning. In a dialogic learning environment, knowledge is not simply transmitted from an authority figure to a passive recipient; instead, it is actively co-created through collaborative discussion, critical reflection, and the respectful consideration of diverse perspectives. It emphasizes the social and intersubjective nature of learning, recognizing that our understanding is often deepened and refined through engagement with the viewpoints of others. It's a messy, often challenging, but ultimately powerful way to learn.

Incidental learning

In incidental teaching, learning is not a pre-planned objective, either by the instructor or the student. Instead, it occurs spontaneously, often as an unlooked-for byproduct of another activity—an experience, a casual observation, a moment of self-reflection, an interaction, a unique and unexpected event (such as responding to an incident or accident), or even the routine execution of a common task. This form of learning happens in addition to, or entirely apart from, the instructor's explicit plans and the student's conscious expectations. It's the universe teaching you things you didn't even know you needed to learn.

An illustrative example of incidental teaching can be seen in a therapeutic setting. An instructor might strategically place a desirable item, such as a train set, on top of a cabinet, within the student's sight but just out of reach. If the child then points towards the cabinet or begins to walk in its direction, thereby initiating engagement, the instructor seizes this natural opportunity. They might prompt the student to say "train." Once the student correctly articulates the word "train," they are granted access to the desired item. The learning of the word "train" is incidental to the child's primary motivation of wanting to play with the toy.

Here are some steps most commonly utilized in incidental teaching paradigms:

• An instructor meticulously arranges the learning environment in such a way that necessary and desirable materials are clearly within the student's visual field, but deliberately positioned beyond their immediate reach. This strategic placement ingeniously leverages the student's intrinsic motivation to seek out those materials.
• The instructor then patiently waits for the student to initiate engagement, allowing their natural curiosity or desire to drive the interaction. This is not about forcing; it's about facilitating.
• Should the student require assistance, the instructor provides a prompt, gently guiding them towards the desired response, but only if needed.
• Crucially, the instructor grants access to the desired item or activity contingent upon a correct response from the student, immediately reinforcing the learned behavior.
• Over a series of trials and a period of time, the instructor gradually "fades out" the prompting process, encouraging the student to perform the correct response independently, thereby cementing the learning.

Incidental learning is an occurrence that, by its very nature, is not generally captured or accounted for using traditional methods of instructional objectives and formal outcomes assessment. This type of learning emerges, in part, as a direct product of rich social interaction and active involvement, whether within online or onsite courses. Research has implied that certain un-assessed aspects of both onsite and online learning challenge the notion of educational equivalency between the two modalities. Specifically, traditional on-campus students tend to experience higher degrees of incidental learning in three times as many areas as their online counterparts. This disparity calls for additional research to thoroughly investigate the conceptual and pedagogical implications of these findings, ensuring that the nuances of learning are fully understood across all educational formats.

Domains

Benjamin Bloom, a pivotal figure in educational theory, famously proposed a taxonomy that delineates three distinct yet interconnected domains of learning. These domains, far from being mutually exclusive, represent different facets of human capability and growth, often working in concert to achieve comprehensive learning outcomes. They are:

• Cognitive domain: This domain encompasses mental skills and the acquisition of knowledge. It involves processes such as recalling facts, performing calculations, engaging in discussions, meticulously analyzing information, and, critically, solving problems. It's the realm of the intellect, the knowing and understanding.
• Psychomotor domain: This domain is concerned with physical skills and the coordination of movement. It involves the execution of actions such as dancing gracefully, swimming efficiently, skiing down a slope, diving expertly, driving a car competently, or riding a bike with balance and control. It's the realm of doing, the physical application of learning.
• Affective domain: This domain addresses the development of emotions, feelings, values, and attitudes. It involves the capacity to like something or someone, to love, to appreciate beauty or complexity, to experience fear, to harbor hate, or to engage in worship. It's the realm of feeling, the emotional and attitudinal responses to the world.

As noted, these domains are rarely, if ever, entirely separate. Consider, for a moment, the process of learning to play chess. Initially, the aspiring player must diligently learn the rules of the game, understanding how each piece moves and the objectives of play—this firmly engages the cognitive domain. Simultaneously, they must also acquire the physical dexterity to correctly set up the chess pieces on the board and to properly hold and manipulate each piece during a game—these are clearly psychomotor skills. Furthermore, as the player progresses, deepens their strategic understanding, and experiences the intellectual richness of the game, they may eventually cultivate a profound love for chess itself, come to appreciate its intricate applications in life, and develop a genuine interest in its rich history—these emotional and valuing responses squarely fall within the affective domain. True mastery, it seems, demands engagement across all three.

Transfer

Transfer of learning is the rather elusive phenomenon where previously acquired skills, knowledge, or understanding are successfully applied to resolve a novel problem or navigate a new situation. It's the cognitive leap from what you know to what you need to know, but it doesn't happen nearly as often as one might hope. Research consistently indicates that this transfer of learning is, unfortunately, infrequent. It is most commonly observed when learners are "... cued, primed, and guided..." through the process, suggesting it's not an automatic consequence of learning but rather a deliberate act requiring scaffolding. Extensive scholarly effort has been dedicated to meticulously clarifying what exactly constitutes transfer, and, more importantly, how it might be systematically promoted through thoughtful instructional design.

Over the protracted history of its discourse, various hypotheses and nuanced definitions have been advanced, reflecting the complexity of the concept. Firstly, it has been speculated that different types of transfer exist, each with its own characteristics. Near transfer involves the application of a skill to solve a novel problem within a highly similar or analogous context. It's like applying what you learned in one specific math problem to another, very similar one. Far transfer, conversely, represents a more challenging cognitive feat: the application of a skill to resolve a novel problem that is presented in a distinctly different or dissimilar context, requiring a deeper, more abstract understanding. Furthermore, Perkins and Salomon (1992) introduced the crucial distinction between positive transfer, which occurs when prior learning genuinely facilitates and supports the solving of a novel problem, and negative transfer, which, rather inconveniently, happens when prior learning actually inhibits or interferes with performance on highly correlated tasks. A classic example of negative transfer can be observed in the challenges faced during second or third-language learning, where the grammatical structures or phonetics of a previously learned language interfere with the acquisition of new linguistic patterns. The concepts of positive and negative transfer have a venerable history; researchers in the early 20th century, already grappling with these complexities, described the possibility that "...habits or mental acts developed by a particular kind of training may inhibit rather than facilitate other mental activities." Finally, Schwarz, Bransford, and Sears (2005) proposed an intriguing distinction: that transferring knowledge into a new situation may fundamentally differ from transferring knowledge out to a situation. This nuanced perspective attempts to reconcile the seemingly contradictory findings that transfer can be both frequent in some contexts and remarkably challenging to promote in others.

A substantial and long-standing body of research has also diligently attempted to explicate the precise conditions under which this elusive transfer of learning might reliably occur. Early, foundational research by Ruger, for example, identified several valuable approaches for promoting transfer, including the "level of attention" paid, the "attitudes" brought to the task, the chosen "method of attack" (or the strategy employed for tackling a problem), a proactive "search for new points of view," a "careful testing of hypothesis," and the crucial cognitive act of "generalization." To actively encourage transfer through pedagogical instruction, Perkins and Salomon recommend two primary strategies: "hugging" (aligning instruction closely with practice and assessment, making the learning context as similar to the application context as possible) and "bridging" (explicitly encouraging learners to reflect on their past experiences or to consciously forge connections between their prior knowledge and the current content being learned). It seems that for learning to truly migrate, it often needs a map and a guide.

Factors affecting learning

• Main article: Learning theory (education)

Learning, a process central to existence, is not simply a matter of exposure; it is intricately modulated by a myriad of factors, both internal and external. Understanding these influences is paramount for optimizing educational outcomes and, frankly, for understanding why some things stick and others evaporate.

Instructional techniques

• Main article: Instructional theory

The deliberate design and application of certain instructional techniques play a pivotal role in determining the efficacy and sustainability of long-term retention. Not all teaching methods are created equal, and some are demonstrably better at making knowledge endure:

• The spacing effect is a robust cognitive phenomenon demonstrating that lessons or study sessions that are deliberately spaced out over time—a technique known as spaced repetition—are significantly more effective for retention than the concentrated, frantic effort of "cramming" information shortly before it's needed. This superiority is largely attributed to the brain's natural tendency to forget over time, as described by the forgetting curve, which spacing helps to counteract.
• Desirable difficulty refers to the strategic introduction of certain challenges into the learning process that, while initially making learning harder, ultimately lead to more robust, deeper, and more durable learning. It's the cognitive equivalent of resistance training.
• Learning by teaching, also known as the "protégé effect," is a powerful method where individuals learn material more effectively when they anticipate or actually engage in teaching it to others. The act of preparing to teach forces a deeper level of processing, organization, and synthesis of the information.
• "Self-explaining" involves the active process of paraphrasing, elaborating on, or explaining material to oneself, rather than passively reading or listening. This metacognitive strategy forces deeper engagement and helps to identify gaps in understanding.
• The testing effect, or the practice of low-stakes quizzing, demonstrates that actively retrieving information from memory through testing significantly enhances long-term retention, even more so than simply re-studying the material. Tests aren't just for assessment; they're powerful learning tools.

Genetics

• Main article: Heritability of IQ

It's an inconvenient truth that not all learners are created equal, nor do they progress at the same pace. Some aspects of intelligence and cognitive aptitude are, to a measurable degree, inherited genetically. Consequently, different learners possess varying innate abilities with regard to both the capacity for learning itself and the speed at which they can acquire new information and skills. This isn't to say effort is irrelevant, but the starting lines are undeniably different. Citation needed for the precise quantification of this heritability, but the general principle is well-established in behavioral genetics.

Socioeconomic and physical conditions

Beyond the internal wiring, external circumstances exert a profound influence on an individual's capacity to learn. Problems stemming from malnutrition, chronic fatigue, and generalized poor physical health can significantly impede cognitive function and demonstrably slow down the learning process. These aren't minor inconveniences; they are fundamental barriers. Furthermore, the quality of the immediate environment plays a critical role: inadequate ventilation, insufficient lighting at home, or unhygienic living conditions all contribute to a suboptimal learning landscape, compounding existing challenges.

The very physical characteristics of a learning space—be it a school building, a classroom, or even a personal study area—are each critically important determinants of the success of any learning environment. The sheer size, the precise configuration, and the overall comfort level of a space—including factors like the availability of fresh air, the ambient temperature, the quality and quantity of light, the acoustic properties, and the ergonomic design of furniture—can all profoundly affect a student's ability to focus, engage, and retain information. Moreover, the tools employed by both instructors and students directly mediate how information is conveyed and processed, ranging from traditional display and writing surfaces (such as blackboards, markerboards, and tack surfaces) to advanced digital technologies. For instance, an overcrowded room invariably leads to elevated stress levels, diminished student attention spans, and severely restricted flexibility in furniture arrangement. If furniture is improperly arranged, sightlines to the instructor or instructional materials become compromised, and the ability to adapt the space to suit varying learning or lesson styles is severely curtailed. Even aesthetics can play a subtle yet significant role; if the student morale suffers due to an unappealing or uncomfortable environment, so too does their intrinsic motivation to attend school and engage in the learning process. It seems even the walls have an impact.

Psychological factors

The internal psychological landscape of a learner is arguably one of the most potent determinants of their educational trajectory. Intrinsic motivation—that deep-seated, internal drive stemming from a student's own intellectual curiosity, their innate desire to experiment, or their urge to explore—has been consistently found to sustain learning far more effectively and profoundly than any form of extrinsic motivation. External incentives, such as the pursuit of high grades or the fulfillment of parental requirements, can compel action, but they rarely inspire true, enduring engagement. Rote learning, while efficient for surface-level memorization, relies heavily on repetition to reinforce facts in memory. However, it has been widely criticized as an ineffective method for genuine understanding and is often derided as "drill and kill" precisely because it tends to extinguish that crucial intrinsic motivation. More effective alternatives to this uninspired approach include the engaging and interactive methods of active learning and the deeper, more contextualized approach of meaningful learning.

Ultimately, the speed, accuracy, and long-term retention of learned material are inextricably linked to a constellation of individual psychological factors: a student's inherent aptitude, their prevailing attitude towards the subject, their level of genuine interest, their capacity for sustained attention, their overall energy level, and, critically, their underlying motivation. It stands to reason that students who provide correct answers or demonstrate strong results should be genuinely praised. This form of positive encouragement serves to bolster their self-efficacy, reinforce desired behaviors, and ultimately contribute to their ability to produce even better results in the future. Conversely, certain counterproductive attitudes on the part of educators—such as consistently finding fault in a student's answer, or worse, provoking or deliberately embarrassing a student in front of their peers—are demonstrably detrimental. Such approaches erode trust, foster fear, and invariably diminish a student's willingness to engage and learn. Need quotation to verify that these specific negative behaviors are universally counterproductive, but anecdotal evidence certainly suggests it.

Epigenetic factors

• Further information: Epigenetics in learning and memory

The profound and intricate molecular basis of learning appears to involve dynamic changes in gene expression that occur specifically within the neurons of the brain. These changes are not simply random fluctuations; they are precisely orchestrated and introduced by complex epigenetic mechanisms. Epigenetic regulation of gene expression, a field that continually challenges our understanding of biological inheritance and plasticity, primarily involves chemical modifications to DNA itself, or to the histone proteins that are intimately associated with DNA and help package it within the cell nucleus. These seemingly subtle chemical alterations have the remarkable capacity to induce long-lasting, stable changes in how genes are expressed, thereby influencing cellular function and, ultimately, cognitive processes like learning.

During the very act of learning, the intricate information processing within the brain appears to involve the induction of oxidative modification in neuronal DNA. This initial alteration is then followed by the sophisticated employment of various DNA repair processes, which, in a remarkable twist, simultaneously introduce the very epigenetic alterations necessary for learning and memory formation. Specifically, the DNA repair pathways of non-homologous end joining and base excision repair have been identified as being critically involved in the molecular machinery underpinning learning and the subsequent formation of enduring memory. It's a testament to the brain's astonishing ability to not only process information but to physically re-write its own operating instructions in response to experience.

General cognition-related factors

• This section is an excerpt from Development of the nervous system in humans § Adult neural development.[edit]

The astonishing process of nervous system development does not, contrary to earlier beliefs, simply cease at some arbitrary point in early adulthood. Instead, it continues its dynamic trajectory throughout an individual's entire lifespan, persisting right up until the point of brain death. This ongoing plasticity means that the brain is constantly being shaped and reshaped by a multitude of factors, some beneficial, some detrimental:

• Physical exercise, far from being solely about bodily health, demonstrably exerts significant neurobiological effects, promoting neurogenesis and enhancing cognitive function.
• The consumption of specific foods or nutrients, the presence of obesity, alterations in the delicate balance of the microbiome, the intake of various drinks, the use of dietary supplements, and the recreational use of certain drugs and medications can all, potentially, have profound and complex effects on the ongoing development and function of the nervous system.
• A range of various diseases, including the more recently recognized impact of the COVID-19 pandemic on neurological, psychological and other mental health outcomes, can exert significant and often debilitating effects on the healthy development and maintenance of the nervous system.
• For example, several genes have been meticulously identified as being associated with observable changes in brain structure over the lifespan. These genetic "hotspots" represent potential therapeutic targets for debilitating conditions such as Alzheimer's disease, offering a glimmer of hope for future interventions.
• Psychological events, particularly severe mental trauma, can profoundly alter neural pathways and cognitive function, while conversely, active resilience-building strategies can foster adaptive neural changes.
• Exposure to environmental pollution and various toxins, such as air pollution, can unfortunately exert deleterious effects on the continued development and integrity of the nervous system.
• Other broad categories of activities, including the pursuit of lifelong learning, engaging in retraining for new skills, and participation in specific types of media- and economic activities, can also significantly influence the ongoing development and plasticity of the nervous system.
• Broadly, the overarching process of brain aging encompasses a complex interplay of all these factors, leading to both inevitable decline and surprising resilience in cognitive function.

Adult learning vs children's learning

• See also: Aging brain

It's a commonly observed, and often lamented, phenomenon that learning is frequently more efficient in children and tends to become a more protracted or difficult endeavor with advancing age. This isn't just a subjective feeling; scientific inquiry is beginning to unravel the underlying neurobiological reasons. A recent study, employing sophisticated neuroimaging techniques, identified a rapid boost in the neurotransmitter GABA—a key inhibitory neurotransmitter—as a major potential explanatory component for this observed difference in learning efficacy between young and old. It seems children's brains are simply better primed for rapid neuronal reorganization.

Specifically, the brains of children contain a significantly higher proportion of "silent synapses." These are synaptic connections that are functionally inactive, lying dormant and awaiting activation until recruited as an integral part of neuroplasticity and the processes of flexible learning or the formation of new memories. This heightened neuroplasticity is particularly pronounced during critical or sensitive periods of brain development, which primarily coincide with child development, offering windows of opportunity for rapid skill acquisition and adaptation.

However, it's not an entirely bleak outlook for the older generation. Researchers have also conducted studies where late middle-aged participants were enrolled in university courses. The findings from such studies suggest that perceived age differences in learning ability may not be solely attributable to inherent biological decline. Instead, these differences could largely be a consequence of variations in the amount of time available for learning, the level of support provided, the nature of the learning environment, and, crucially, the prevailing attitudes towards adult learning, rather than an unalterable deficit in inherent cognitive capacity. It seems the "old dog, new tricks" adage might be a bit premature.

What humans learn during the early, formative stages of life, and critically, what they learn to apply from that initial knowledge, sets individuals on a trajectory for life, often having a disproportionately significant and lasting impact. The foundational knowledge and skills acquired in childhood shape future learning, opportunities, and even personality. In adulthood, individuals typically possess a considerably higher capacity for agency in their learning journey. They can actively select what they wish to learn, determine the extent of their engagement, and choose how they will approach the learning process. For example, children in a traditional school setting are often constrained to learning predefined subjects and topics dictated by school curricula, frequently through methods like blackboard transcription and handwriting. They generally lack the autonomy to choose specific topics or skills to learn, to select career paths, or to dictate their preferred learning styles. This stark contrast arises because children may not yet have developed consolidated interests, a robust ethical framework, a clear sense of purpose or meaningful activities, comprehensive knowledge about real-world requirements and demands, or well-defined personal priorities. These are the burdens and privileges of maturity.

In animal evolution

Animals acquire knowledge about their world through two primary, yet distinct, evolutionary pathways. The first is through learning—an active process where an animal gathers information about its environment and subsequently utilizes this information to modify its behavior or internal states. For example, if an animal consumes something toxic that causes stomach distress, it quickly learns to avoid that particular food source in the future. The second pathway is through innate knowledge (or instinct)—information that is genetically inherited and hardwired into the organism's biology, requiring no prior experience to manifest. A classic example is a newborn horse, which is capable of walking almost immediately after birth. This complex motor skill is not learned; it is an intrinsic, pre-programmed behavior. In certain ecological scenarios, innate knowledge confers a distinct advantage over learned knowledge, offering immediate, life-saving responses. However, in other, more dynamic scenarios, the inverse holds true: animals must learn specific behaviors when having a fixed, innate response would prove disadvantageous or even fatal. It is in these situations that the capacity for learning itself evolves within a species, providing the crucial flexibility needed for survival.

Costs and benefits of learned and innate knowledge

The evolutionary trajectory of an animal's learning capacity is fundamentally determined by a finely tuned calculus of costs and benefits. In a constantly fluctuating environment, an animal must continuously acquire new information to successfully navigate its surroundings and ensure its survival. However, in an exceedingly stable and predictable environment, the same individual might only need to gather essential information once, and then reliably depend on that acquired knowledge for the remainder of its life. Consequently, different environmental contexts are optimally suited for either learning or relying on innate knowledge.

Essentially, the evolutionary decision—whether an animal develops the capacity to learn in a given situation, or whether it innately possesses the information—hinges on the cost associated with obtaining that knowledge versus the benefit of already having it. If the cost of acquiring certain knowledge (e.g., time, energy, risk of error) outweighs the benefit of possessing it, then the capacity for learning is unlikely to evolve in that specific scenario. Instead, non-learning (reliance on innate behaviors or random chance) becomes the favored evolutionary outcome. Conversely, if the benefit of possessing particular information profoundly outweighs the cost of obtaining it, then the animal is far more likely to evolve the capacity to learn this information, as it provides a crucial adaptive edge.

Non-learning, rather than being a deficit, is more likely to evolve and persist under two specific environmental conditions. Firstly, if an environment is remarkably static and unchanging, where significant alterations occur rarely or not at all, then learning is simply superfluous. There is no adaptive pressure to acquire new information if the old information remains perpetually relevant. In such a scenario, and because learning itself can be costly (demanding time and energy), non-learning is the more efficient evolutionary strategy. Secondly, and somewhat paradoxically, if an environment is in a perpetual state of unpredictable change, learning also proves disadvantageous. Any information acquired quickly becomes irrelevant due to the ceaseless flux, rendering the effort of learning moot. In such highly volatile situations, the animal would be just as successful relying on random guesswork as it would be attempting to learn, as the learned information no longer applies. Thus, in these extreme conditions, non-learning again evolves. Indeed, a study conducted on Drosophila melanogaster (fruit flies) even indicated that learning could, in certain contexts, lead to a decrease in productivity. This potential decrement was hypothesized to result either from the impairment of egg-laying behaviors and decisions due to interference from newly acquired memories, or simply from the significant energetic cost associated with the learning process itself.

However, in environments characterized by change that occurs within an animal's typical lifespan but is not constant or utterly unpredictable, the capacity for learning is far more likely to evolve and be favored. Learning is profoundly beneficial in these intermediate scenarios because an animal can effectively adapt its behavior to new situations, yet still apply the knowledge it acquires for a reasonably extended period. Thus, learning significantly increases the chances of survival and reproductive success, offering a clear advantage over mere guesswork. An excellent illustration of this dynamic can be observed in aquatic environments where the physical landscape is subject to periodic, yet not constant, change. In these settings, learning is demonstrably favored, as fish are predisposed to learn and utilize specific spatial cues within their habitats, allowing them to navigate and locate resources effectively in a moderately dynamic world.

In plants

In recent years, the once-unquestioned boundaries of cognition and learning have been vigorously challenged, particularly by plant physiologists who have meticulously examined the nuanced physiology of plant behavior and what might be termed "plant intelligence." The very concepts of learning and memory, traditionally reserved for the animal kingdom, are proving increasingly relevant in identifying and understanding the sophisticated ways in which plants respond to external cues—a fundamental requirement for their survival. Monica Gagliano, an Australian professor specializing in evolutionary ecology, has emerged as a prominent voice in this intriguing field, making a compelling argument for the presence of associative learning in the humble garden pea, Pisum sativum. The garden pea, a species not endemic to a single region, thrives in cooler, higher altitude climates, exhibiting a remarkable adaptability. Gagliano and her colleagues, in their groundbreaking 2016 paper, aimed to meticulously differentiate between innate phototropism (the plant's natural tendency to grow towards light) and genuinely learned behaviors.

Plants, in their silent and often underestimated existence, utilize light cues in a myriad of sophisticated ways, not merely to sustain their metabolic needs through photosynthesis, but also to precisely calibrate and maintain their internal circadian rhythms. These intrinsic biological clocks in plants are intricately modulated by endogenous bioactive substances that orchestrate rhythmic leaf-opening and leaf-closing movements, forming the basis of nyctinastic behaviors—the daily sleep and wake cycles of leaves.

To rigorously test her hypothesis, Gagliano and her team ingeniously constructed a classical conditioning experiment. Pea seedlings were divided into two experimental categories and carefully placed within Y-shaped tubes. Over a series of meticulously designed training sessions, the plants were exposed to light emanating from different arms of the tube. Crucially, in each instance, a fan was positioned to blow lightly down the tube, either from the same arm as the light or from the opposite arm. The unconditioned stimulus (US) in this setup was the predictable occurrence of light, a biologically significant cue for plants. The conditioned stimulus (CS) was the seemingly innocuous wind generated by the fan. Prior experimentation has firmly established that plants respond to light by bending and growing towards it—a process mediated by differential cell growth and division on one side of the plant stem, orchestrated by complex auxin signaling pathways.

During the subsequent testing phase of Gagliano's experiment, the pea seedlings were transferred to fresh Y-pipes and exposed only to the fan, without any light cues. Their resulting direction of growth was then meticulously recorded. The 'correct' response for the seedlings was operationally defined as growing into the arm where the light was "predicted" to appear, based on the fan's position during the previous day's training. Remarkably, the majority of plants in both experimental conditions exhibited growth in a direction consistent with the predicted location of light, inferring this prediction from the fan's position on the preceding day. For example, if a seedling had been trained with the fan and light consistently coming from the same arm of the Y-pipe, the following day, in the absence of light, that seedling would grow towards the fan, even if the fan was now placed in the opposite Y-arm. In stark contrast, plants in the control group, which had not undergone the associative training, displayed no discernible preference for a particular arm of the Y-pipe. The statistically significant percentage difference in population behavior observed between the control and experimental groups was interpreted as a crucial distinction between innate phototropism and genuine, active associative learning.

While the precise physiological mechanism underpinning associative learning in plants remains an area of active investigation, Telewski et al. proposed a compelling hypothesis that positions photoreception as a fundamental basis for mechano-perception in plants. One proposed mechanism for mechano-perception relies on specialized MS ion channels and calcium channels. Mechanosensory proteins, embedded within the cell lipid bilayers (the MS ion channels), are activated when they are physically deformed in response to external pressure or tension. Crucially, Ca2+ permeable ion channels are "stretch-gated," meaning they open in response to mechanical deformation, allowing for an influx of osmolytes and calcium ions—calcium being a well-known and versatile second messenger in cellular signaling—into the cell. This influx of ions subsequently triggers a passive flow of water into the cell, driven by osmotic gradients, effectively increasing turgor pressure and causing the cell to depolarize. Gagliano herself hypothesizes that the molecular basis of associative learning in Pisum sativum involves the intricate coupling of mechanosensory and photosensory pathways, with this complex interplay being mediated by the ubiquitous auxin signaling pathways. The ultimate, adaptive result is directional growth that strategically maximizes the plant's capture of vital sunlight.

Gagliano et al. further expanded this provocative line of inquiry with another paper, this time focusing on habituation behaviors in the Mimosa pudica plant. In this study, they demonstrated that the plant's innate folding response to touch—a defensive mechanism—was significantly diminished by repeated exposure to a non-threatening stimulus. However, this work, and indeed the broader topic of plant cognition, has not been without its share of controversy. Charles Abramson, a psychologist and behavioral biologist, highlights a key issue contributing to the scientific disagreement regarding plants' capacity to learn: researchers often fail to employ a consistent, universally accepted definition of "learning" and "cognition." Similarly, Michael Pollan, a renowned author and journalist, in his thought-provoking piece "The Intelligent Plant," notes that many researchers do not necessarily doubt Gagliano's empirical data. Rather, their discomfort often stems from her choice of language, specifically her application of terms like "learning" and "cognition" to plants, which traditionally carry anthropocentric connotations. A promising direction for future research involves rigorously testing whether circadian rhythms in plants modulate learning and behavior, and, perhaps more fundamentally, conducting a comprehensive survey of researchers' diverse definitions of "cognition" and "learning" to foster greater conceptual clarity in this rapidly evolving field.

Machine learning

• Main article: Machine learning

Robots can learn to cooperate. A rather unsettling thought for some, a practical inevitability for others.

Machine learning, a dynamic and rapidly expanding branch of artificial intelligence, is entirely dedicated to the construction, rigorous study, and continuous refinement of systems that possess the remarkable ability to learn directly from data, rather than being explicitly programmed for every conceivable scenario. It's about teaching machines to discern patterns, make predictions, and adapt their behavior without human intervention in every instance. For example, a sophisticated machine learning system could be meticulously trained on an immense dataset of email messages. Through this training, it would learn to autonomously distinguish between unwanted spam messages and legitimate, non-spam communications, constantly improving its accuracy with more data. The vast majority of Machine Learning models are fundamentally rooted in probabilistic theories, where each input—be it an image, a block of text, or a numerical sequence—is associated with a calculated probability of yielding a desired output. This probabilistic framework allows these systems to make informed decisions and predictions even in the face of uncertainty, mimicking, in a rather cold and calculating way, a form of digital intuition.

See also

• 21st century skills – The ever-shifting goalposts for success in the modern era.
• Anticipatory socialization – The somewhat premature adoption of values for groups one merely aspires to join.
• Educational aims and objectives – The desired (and often elusive) results of the educational process.
• Epistemology – The philosophical pursuit of what we think we know.
• Implicit learning – The insidious acquisition of complex information without even realizing it.
• Lifelong learning – The ongoing, voluntary, and self-inflicted pursuit of knowledge until death do us part.
• Media psychology – The study of how media messes with our minds.
• Subgoal labeling – A cognitive process that sounds more exciting than it probably is.

Information theory

• Algorithmic information theory – A rather dense subfield of information theory and computer science, for those who enjoy complexity.
• Algorithmic probability – A mathematical method for assigning prior probabilities, useful for predicting the unpredictable.
• Bayesian inference – A statistical method that allows one to update beliefs with new evidence, a concept many humans struggle with.
• Inductive logic programming – Learning logic programs from data, because even machines need to make inferences.
• Inductive probability – Determining the probability of future events based on past events, a perilous endeavor.
• Information theory – The scientific study of digital information, a surprisingly philosophical pursuit.
• Minimum description length – A model selection principle that values conciseness, a trait often lacking in human communication.
• Minimum message length – A formal information theory restatement of Occam's Razor, because simplicity is often best.
• Occam's razor – The philosophical principle that the simplest explanation is usually the correct one, a truth often ignored.
• Solomonoff's theory of inductive inference – A mathematical theory for inductive inference, a rather ambitious undertaking.
• AIXI – A mathematical formalism for artificial general intelligence, the holy grail of some, the existential dread of others.

Types of education

• Autodidacticism – The independent pursuit of education without the burden of teachers, for the truly self-motivated.
• Andragogy – The methods and principles specific to adult education, because adults are often more stubborn.
• Pedagogy – The theory and practice of education, for those who enjoy dissecting how we learn.