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Metacognition

Metacognition refers to the awareness of one's own knowledge and the ability to understand, control, and manipulate one's cognitive processes, encompassing both knowledge about cognition and the regulation of cognitive activities.^[1] The term was coined by developmental psychologist John H. Flavell in 1976 and further elaborated in his seminal 1979 paper, where he described it as a form of cognitive monitoring essential for developmental inquiry.^[2] At its core, metacognition comprises two primary components: metacognitive knowledge and metacognitive regulation.^[3] Metacognitive knowledge includes awareness of person variables (such as individual strengths and limitations in thinking), task variables (characteristics of the learning task that influence performance), and strategy variables (methods to achieve cognitive objectives).^[4] Metacognitive regulation, on the other hand, involves active processes like planning an approach to a task, monitoring ongoing comprehension and progress, and evaluating outcomes to adjust strategies as needed.^[1] These elements enable individuals to reflect on their mental activities, often summarized as "thinking about thinking."^[5] Metacognition is fundamental to effective learning and problem-solving across educational and professional contexts, as it fosters self-regulated learning and improves academic performance.^[6] Research indicates that learners with strong metacognitive skills are better able to select appropriate strategies, persist through challenges, and transfer knowledge to new situations, making it a key target for instructional interventions in both children and adults.^[3] In neuroscientific perspectives, metacognition also links to brain regions involved in error detection and decision-making, highlighting its role beyond education in broader cognitive and social functions.^[3]

Fundamentals

Definitions

Metacognition refers to the processes by which individuals become aware of and gain control over their own cognitive activities, often described as "thinking about one's own thinking." This encompasses both knowledge of cognition—such as understanding one's cognitive capabilities and limitations—and the regulation of cognition, including monitoring progress and adjusting strategies during tasks. The term was introduced by developmental psychologist John Flavell in 1976, who framed metacognition as involving interactions among person variables (knowledge about oneself and others as thinkers), task variables (characteristics of the cognitive task), and strategy variables (methods for approaching tasks).^[7] Metacognitive knowledge is typically categorized into three types: declarative (knowing facts about cognition, such as recognizing that distributed practice aids memory), procedural (knowing how to apply cognitive strategies, like outlining a text to improve comprehension), and conditional (knowing when and why to use particular strategies, such as choosing summarization for complex material over rote repetition). In contrast, metacognitive experiences involve subjective feelings and judgments that arise during cognitive activities, including feelings of knowing (a sense that one will recognize correct information upon retrieval) and judgments of learning (assessments of how well material has been mastered). These experiences provide online feedback that informs regulatory decisions. Practical examples illustrate these elements: a student might monitor their comprehension while reading by pausing to summarize key points in their mind (a metacognitive experience tied to regulation), or adjust study time by allocating more effort to difficult topics based on an assessment of task demands (drawing on conditional knowledge). Metacognition overlaps with executive functions, such as planning and inhibitory control, which support these reflective processes in everyday cognition.

Historical Development

The roots of metacognition trace back to ancient Greek philosophy in the 4th century BCE, where thinkers emphasized self-examination and reflection on knowledge. Socrates promoted the idea of the "examined life," asserting that unreflective existence lacks value and advocating continuous self-questioning to achieve self-awareness and wisdom.^[8] Similarly, Aristotle explored the nature of knowledge (epistēmē), distinguishing practical from theoretical cognition and highlighting the role of self-reflective intellectual processes in understanding one's own mental activities.^[9] In the early 20th century, Jean Piaget advanced these ideas through developmental psychology during the 1920s to 1950s. Piaget introduced the concept of reflective abstraction, a mechanism by which individuals reflect on their actions and experiences to construct higher-order cognitive structures, laying groundwork for later metacognitive theories by emphasizing the internalization of thought processes.^[10] The modern field of metacognition emerged in the 1970s with John Flavell's foundational contributions. In his 1976 paper, Flavell coined the term "metacognition" to describe knowledge about one's own cognitive processes and their regulation during problem-solving, marking a shift toward empirical study in cognitive developmental psychology.^[7] He expanded this in a 1979 article, outlining metacognition as involving active monitoring and control of cognition, which spurred widespread research on children's cognitive self-regulation. During the 1980s and 1990s, metacognition integrated more deeply with cognitive psychology, particularly through studies on metamemory and child development. Ann L. Brown (1978) investigated how children develop awareness of their memory capabilities, demonstrating age-related improvements in monitoring recall effectiveness and applying strategies adaptively.^[11] From the 2000s onward, research shifted toward neuroscience, employing fMRI to examine brain mechanisms underlying metacognitive judgments; for instance, Fleming et al. (2010) correlated variations in anterior prefrontal cortex structure with differences in metacognitive sensitivity across perceptual tasks.^[12] This neuroscientific turn has also extended briefly to animal models, revealing comparative insights into metacognitive-like behaviors.

Theoretical Frameworks

Key Concepts and Models

One of the foundational models in metacognition is the framework proposed by Nelson and Narens, which conceptualizes metacognition as involving two interacting levels: the object-level, representing ongoing cognitive processes, and the meta-level, which monitors and regulates those processes.^[13] In this model, monitoring flows from the meta-level to the object-level, providing awareness of cognitive states such as confidence in memory retrieval, while control flows in the opposite direction, adjusting object-level activities based on meta-level evaluations, such as deciding to allocate more study time.^[13] This bidirectional interaction enables dynamic regulation, with empirical tests showing its application in metamemory judgments like feeling-of-knowing experiences.^[13] Flavell's influential 1979 model expands metacognition into a system of four interrelated components that facilitate cognitive monitoring and self-regulation.^[14] Metacognitive knowledge encompasses awareness of one's cognitive capabilities (person variables), task characteristics (e.g., difficulty), and effective strategies (strategy variables).^[14] Metacognitive experiences involve momentary cognitive or affective reactions during tasks, such as surprise or ease, which inform ongoing adjustments.^[14] Goals or tasks define the cognitive enterprise, like comprehending a text, while actions include both cognitive strategies (e.g., rehearsal) and metacognitive strategies (e.g., checking comprehension).^[14] These elements interact recursively, with experiences and knowledge influencing goal setting and action selection to optimize performance.^[14] Building on earlier work, Schraw and Moshman's 1995 integrative model organizes metacognition into knowledge and regulation components, emphasizing three types of metacognitive knowledge: declarative (what one knows about cognition, such as task demands), procedural (how to apply cognitive skills, enabling strategy execution), and conditional (when and why to use strategies, supporting adaptive choice).^[15] This framework posits that metacognitive theories—tacit (implicit), informal (explicit but unstructured), or formal (systematic)—guide regulation by integrating knowledge to evaluate and direct cognitive processes, with development progressing from basic awareness to sophisticated self-theories.^[15] Process-oriented approaches, such as Pintrich's 2000 framework for metacognitive regulation in self-regulated learning, structure metacognition across four sequential phases: forethought (planning and goal activation), monitoring (tracking progress), control (adjusting strategies), and reflection (evaluating outcomes). Within these phases, metacognitive regulation involves assessing comprehension, effort, and task fit to enhance learning efficacy.^[16] Empirical support for these models comes from studies on metacognitive accuracy in perceptual decision-making tasks, where participants judge their own performance reliability. For instance, research demonstrates metacognitive inefficiency, with confidence ratings often underestimating or overestimating actual accuracy due to noise in meta-level representations, as quantified by meta-d' measures showing systematic biases across trials.^[17] Neuroimaging studies further corroborate prefrontal involvement in monitoring perceptual choices, aligning with model predictions of meta-level control.^[18] Metamemory represents a specific subset of metacognition, focusing on individuals' knowledge, monitoring, and control of their own memory processes.^[2] Introduced as part of the broader metacognitive framework, metamemory encompasses judgments about memory capabilities, such as ease-of-learning predictions and retrospective confidence assessments.^[13] A key example is the feeling-of-knowing (FOK) judgment, where individuals assess the likelihood of recognizing an unrecalled item in a future test, which relies on monitoring the strength of memory traces and influences retrieval strategies.^[13] This subprocess highlights metacognition's domain-specific applications, distinguishing it from general cognitive awareness by targeting memory accuracy and regulation. Executive functions share considerable overlap with metacognition in terms of regulatory mechanisms, both involving the orchestration of cognitive resources to achieve goals, but metacognition uniquely emphasizes reflective awareness and subjective evaluation of those processes.^[19] Executive functions, such as inhibition, working memory updating, and task switching, primarily handle automatic control and conflict resolution, often without explicit introspection.^[20] In contrast, metacognition adds a layer of conscious monitoring, enabling individuals to appraise their performance and adjust strategies accordingly.^[21] Neuroimaging evidence points to shared involvement of the prefrontal cortex (PFC) in both, with regions like the dorsolateral PFC supporting executive control and the rostrolateral PFC facilitating metacognitive judgments of decision confidence.^[18] This distinction underscores that while executive functions provide the machinery for regulation, metacognition involves meta-level awareness of that machinery's operation.^[22] Theory of mind (ToM) differs from metacognition primarily in its focus on interpersonal versus intrapersonal mental state attribution, with ToM enabling inferences about others' beliefs, intentions, and perspectives, whereas metacognition pertains to self-directed awareness of one's own cognitive states.^[23] ToM operates in social contexts, supporting empathy and prediction of others' behavior through mentalizing networks involving the temporoparietal junction and medial PFC.^[24] Metacognition, by comparison, is intrapersonal, involving self-monitoring of thought processes without necessitating social inference.^[25] Although both may recruit overlapping frontal regions for higher-order processing, their functional boundaries remain distinct: ToM is other-oriented and predictive of external actions, while metacognition is self-oriented and evaluative of internal cognition.^[26] Self-regulation constitutes a broader construct than metacognition, encompassing the directed orchestration of cognitive, motivational, behavioral, and emotional processes to attain personal goals, with metacognition serving as a critical subprocess for monitoring and adjusting those efforts.^[20] In models of self-regulated learning, metacognition provides the reflective component—such as planning, evaluating progress, and adapting strategies—within a cyclic framework that also includes forethought, performance, and self-reflection phases influenced by environmental and motivational factors.^[27] Self-regulation thus extends beyond metacognitive awareness to include volitional control and sustained effort, integrating metacognition with affective and behavioral elements for comprehensive goal pursuit.^[28] Metacomprehension applies metacognitive principles specifically to the monitoring and control of text comprehension, involving predictions and judgments about one's understanding of written material, often revealing systematic inaccuracies in self-assessment.^[29] Studies demonstrate that individuals tend to overestimate their grasp of texts, with relative accuracy—measured as the correlation between predicted and actual comprehension test performance—averaging around 0.27 across multiple experiments, indicating moderate but imperfect calibration.^[29] Factors such as absolute confidence levels influence bias, where higher overall confidence reduces sensitivity to errors without improving resolution of judgments.^[30] This domain-specific application underscores metacognition's role in learning from texts, highlighting the need for interventions to enhance monitoring accuracy and subsequent study adjustments.^[29]

Components and Processes

Metacognitive Strategies

Metacognitive strategies refer to the deliberate techniques individuals employ to regulate their own cognitive processes, enabling more effective learning and problem-solving. These strategies are typically divided into three primary phases: planning, monitoring, and evaluation, which help learners actively manage their approach to tasks. This framework, originally outlined in foundational work on metacognition, emphasizes the orchestration of cognitive efforts to achieve goals. Planning strategies involve setting clear objectives and analyzing tasks prior to engagement, such as breaking down complex problems into manageable steps or selecting suitable methods based on the task's demands. For instance, before preparing for an exam, a student might outline key topics, allocate study time, and choose techniques like outlining or diagramming to organize information. These preparatory actions enhance efficiency by aligning cognitive resources with anticipated challenges.^[31] Monitoring strategies occur during task execution and entail ongoing self-assessment to track progress and comprehension. Common practices include self-questioning, such as asking "Do I understand this concept?" while reading a text, or pausing to summarize key points mentally. This real-time awareness allows individuals to detect difficulties early and make mid-course adjustments, like re-reading confusing sections or seeking clarification.^[1] Evaluation strategies take place after task completion, focusing on reflecting on outcomes to assess effectiveness and inform future efforts. This might involve reviewing what worked well in a study session, identifying gaps in understanding, and modifying approaches for subsequent tasks, such as switching from rote memorization to relational mapping if retention was poor. Such post-task analysis promotes adaptive learning over time.^[31] In educational contexts, metacognitive strategies often integrate with specific techniques to bolster retention and understanding. Mnemonics, for example, aid planning by creating structured memory aids like acronyms for lists, while summarization during monitoring helps condense information to verify grasp. Elaboration strategies, such as connecting new material to prior knowledge through analogies, support evaluation by revealing deeper insights into learning successes or failures. These methods are particularly effective when taught explicitly to students.^[32] Empirical evidence underscores the benefits of training in metacognitive strategies. A meta-analysis of 74 intervention studies at primary and secondary levels found that programs emphasizing strategy components like planning, monitoring, and evaluation yielded an average effect size of 0.69 on academic performance, with higher impacts when trainings included reflection and were delivered by researchers rather than teachers. This indicates that targeted instruction in these strategies significantly enhances self-regulated learning and outcomes across subjects.^[33]

Metastrategic Knowledge

Metastrategic knowledge, a key component of metacognitive knowledge, refers to an individual's explicit awareness and understanding of cognitive strategies, including their relative effectiveness and the conditions under which they are most appropriate.^[34] This includes conditional knowledge, such as recognizing that outlining is more effective for comprehending complex texts than for simple narratives, enabling learners to tailor approaches to task demands.^[35] It is categorized into three main types: declarative knowledge, which involves knowing what strategies exist and their general purposes; procedural knowledge, which concerns how to execute those strategies; and conditional knowledge, which addresses when and why a particular strategy should be applied in varying contexts.^[36] These types facilitate flexible strategy selection, distinguishing metastrategic knowledge from mere strategy use by emphasizing meta-awareness of strategic options.^[37] Developmentally, metastrategic knowledge emerges notably in children around ages 8 to 10, coinciding with advances in metamemory and broader metacognitive abilities, as evidenced by longitudinal studies tracking strategy awareness and application in memory tasks. Prior to this, younger children exhibit limited conditional understanding, but by middle childhood, they demonstrate growing ability to evaluate strategy utility, supporting improved self-regulated learning.^[38] In applications, metastrategic knowledge contributes to adaptive expertise by enabling individuals to dynamically choose and modify strategies based on situational demands, particularly in complex problem-solving domains like chess, where players assess opponent patterns to select optimal opening or mid-game tactics.^[39] This awareness enhances performance across varied challenges, from academic tasks to professional decision-making, by promoting strategic flexibility over rote application.^[40]

Metacognitive Monitoring and Control

Metacognitive monitoring involves the ongoing assessment of one's cognitive processes and performance during task execution, allowing individuals to evaluate the ease or difficulty of learning and recall in real time. This process operates within a dual-level framework where the meta-level observes the object-level cognition, providing judgments such as ease-of-learning (EOL) ratings, in which learners predict how quickly they will comprehend new material based on initial exposure.^[13] For instance, during study sessions, a student might rate a vocabulary word as easy to learn if it feels familiar, influencing subsequent study decisions.^[41] Metacognitive control refers to the regulatory actions taken in response to these monitoring judgments, adjusting cognitive efforts to optimize performance. This includes decisions like prolonging study time on items judged as difficult or skipping those perceived as mastered, thereby directing resources efficiently.^[13] In Nelson and Narens' influential model, monitoring informs control through a feedback loop, where meta-level evaluations influence object-level actions, such as terminating a search when confidence thresholds are met.^[13] Such controls enhance learning outcomes by adapting to perceived progress, distinct from predefined strategies. Despite its utility, metacognitive monitoring often suffers from accuracy limitations, notably overconfidence bias, where individuals overestimate their comprehension or recall abilities. This bias manifests in judgments like EOL or judgments of learning (JOL), leading to understudying and poorer retention.^[42] Accuracy is commonly measured using the gamma correlation, a nonparametric index that assesses the correspondence between predicted and actual performance, with values above 0 indicating better-than-chance resolution; however, typical gammas in memory tasks hover around 0.4-0.6, reflecting persistent overconfidence. Nelson's 1984 work established gamma as a robust metric, emphasizing its insensitivity to response biases. Neurologically, metacognitive monitoring and control engage the anterior cingulate cortex (ACC), particularly its dorsal region, which detects errors and uncertainties to signal the need for adjustments. The ACC integrates conflict signals from ongoing cognition, facilitating shifts in control, such as increased attention to challenging tasks.^[43] Functional imaging studies show ACC activation correlating with metacognitive sensitivity during decision-making, underscoring its role in bridging monitoring outputs to control inputs.^[43] This neural mechanism supports adaptive behavior by linking performance discrepancies to regulatory responses.^[44]

Human Applications

Social metacognition encompasses the reflective processes individuals employ to monitor and regulate their own and others' social cognitions in interpersonal settings, such as evaluating the accuracy of impressions formed about others or detecting personal biases in social judgments.^[45] This involves metacognitive monitoring to assess the validity of social inferences and control mechanisms to adjust biased thinking, thereby influencing how people form and maintain relationships.^[46] For instance, in impression formation, individuals may metacognitively track the influence of initial stereotypes on their evaluations, prompting corrections to achieve more balanced perceptions.^[47] A key link exists between social metacognition and self-concept, where heightened self-focused attention fosters objective self-awareness, enabling individuals to critically examine their self-perceptions and their impact on social identity. According to Duval and Wicklund's theory, this objective self-awareness arises when external cues direct attention inward, leading to a discrepancy between actual and ideal self-views that motivates behavioral adjustments in social contexts.^[48] Such reflective processes enhance metacognitive understanding of how self-perceptions shape interactions with others, promoting greater alignment between internal states and social roles.^[49] In the domain of attitudes, the metacognitive model of attitudes (MCM), developed by Petty, posits that attitudes are not merely evaluative content but also include metacognitive elements like confidence in the attitude's validity, which determine its resistance to persuasion. Under this model, individuals perform validity checks on their attitudes during social influence attempts; low-confidence attitudes are more susceptible to change, while high-confidence ones guide behavior more reliably in interpersonal scenarios.^[50] This framework highlights how metacognitive awareness of attitude strength affects social decision-making and conformity. Regarding stereotypes, Monteith's research illustrates how metacognitive monitoring enables the control of stereotypic responses, particularly among those with egalitarian values who experience discomfort from prejudiced thoughts. In her studies, low-prejudice individuals detect discrepancies between their stereotypic intrusions and personal standards, triggering self-regulatory efforts to suppress and redirect thinking, thus reducing bias expression in social interactions.^[51] This meta-awareness process underscores social metacognition's role in fostering prejudice reduction through ongoing evaluation and correction of biased cognitions.^[52]

Metacognition in Mental Health

Metacognitive deficits play a significant role in the pathophysiology of various psychological disorders, particularly schizophrenia, where impairments in self-monitoring and self-reflectivity hinder accurate awareness of one's thoughts and intentions. In schizophrenia, individuals often exhibit reduced metacognitive capacity, leading to difficulties in forming integrated representations of their mental states, which contributes to symptoms like delusions and poor insight.^[53] For instance, impaired source monitoring—distinguishing internally generated thoughts from external stimuli—is a core metacognitive dysfunction that exacerbates psychotic experiences.^[54] In depression, metacognitive dysregulations manifest as persistent rumination, characterized by repetitive, uncontrolled focus on negative thoughts, which represents a failure in metacognitive control to disengage from maladaptive cognitive processes. This rumination is driven by metacognitive beliefs that such thinking is helpful for problem-solving, perpetuating depressive symptoms through extended cycles of distress.^[55] Empirical evidence supports that positive metacognitive beliefs about rumination predict its maintenance and the severity of depressive episodes.^[56] For anxiety disorders, the metacognitive model posits that worry is sustained by positive metacognitive beliefs about the utility of worrying as a coping strategy, alongside negative beliefs about uncontrollability and danger of intrusive thoughts, as outlined in Wells' framework. This model, developed by Wells in 1995, with application to GAD outlined in a 1997 paper by Wells and Butler, emphasizes how these beliefs lead to meta-worry—worry about worrying itself—entrenched in generalized anxiety disorder.^[57] Metacognitive therapy (MCT), developed by Wells in the 1990s and further detailed in his 2009 book, targets these dysregulations through techniques like detached mindfulness and attention training, aiming to disrupt maladaptive metacognitive cycles without directly challenging content.^[58] MCT promotes flexible thinking styles by fostering awareness of cognitive processes as transient events, reducing reliance on worry and rumination.^[59] Evidence from randomized controlled trials (RCTs) indicates that metacognitive training improves insight, reduces symptom severity, and enhances functioning in disorders like schizophrenia and anxiety, with meta-analyses showing moderate to large effect sizes compared to control conditions. Recent meta-analyses as of 2024 continue to support these findings, showing moderate to large effect sizes for metacognitive interventions across psychiatric disorders.^[60]^[61] For example, MCT has demonstrated sustained reductions in delusions and cognitive biases, underscoring its potential as an adjunctive intervention to boost metacognitive regulation and recovery.^[62]

Organizational Metacognition

Organizational metacognition refers to the collective monitoring and regulation of cognitive processes within groups or institutions, extending individual metacognitive abilities to shared knowledge and decision-making dynamics.^[63] This involves teams developing awareness of their collective thinking patterns, including how information is processed, shared, and adapted in professional contexts. Unlike individual metacognition, it emphasizes emergent group-level phenomena where members collectively reflect on and adjust organizational knowledge flows to enhance efficacy.^[64] A core aspect of team metacognition is the development of shared mental models, which represent collective understandings of tasks, roles, and processes that facilitate coordinated decision-making. These models enable teams to anticipate each other's actions and align efforts, particularly in dynamic environments. For instance, research demonstrates that teams with higher congruence in task- and team-based mental models exhibit improved process efficiency and overall performance.^[65] Such shared representations are foundational to metacognitive regulation at the group level, allowing teams to monitor progress and intervene when discrepancies arise.^[64] In organizational settings, metacognition supports knowledge management by promoting reflection on information-sharing practices, such as evaluating the effectiveness of communication channels and adapting strategies to reduce silos. This reflective approach fosters a culture of intentional learning, where organizations assess what knowledge is accessible, how it is utilized, and barriers to its dissemination.^[66] For example, teams engaging in metacognitive knowledge building actively share and integrate information, leading to more robust collective insights compared to passive exchange.^[67] Empirical evidence highlights the performance advantages of metacognitive teams in complex tasks. Field experiments in collaborative environments show that group metacognition significantly boosts outcomes by enhancing regulation and coordination, outperforming teams reliant on individual-level monitoring alone.^[63] Similarly, studies from the 2010s, including simulations of high-stakes operations, indicate that metacognitively aware teams achieve superior results in multifaceted scenarios due to better adaptation and error detection.^[64]

Metacognition in Animals

Evidence in Nonhuman Primates

Studies on nonhuman primates have provided compelling behavioral evidence for metacognitive abilities, particularly in monitoring uncertainty and confidence in perceptual and numerical tasks. In chimpanzees (Pan troglodytes), research has demonstrated uncertainty monitoring during quantity judgments using token-based choice paradigms. For instance, when faced with ambiguous numerical comparisons between sets of food items or tokens, chimpanzees adjusted their decisions based on prior reward experiences, opting for safer choices when uncertain about the larger quantity, which suggests an ability to assess the reliability of their own judgments. Similar evidence emerges from perceptual metacognition tasks in rhesus macaques (Macaca mulatta). In signal detection paradigms, macaques were trained to report whether they remembered a previously viewed stimulus, with the option to "opt out" of difficult trials by selecting an escape response. Hampton's 2001 study showed that macaques selectively opted out on trials where memory was weak, leading to higher accuracy on committed responses compared to chance levels, indicating confidence-based monitoring of their perceptual states.^[68] Neuroscientific investigations further support these behavioral findings by revealing parallels in brain activity between primates and humans during metacognitive processes. Functional magnetic resonance imaging (fMRI) studies in macaque monkeys have identified activation in the frontopolar prefrontal cortex during tasks requiring metacognitive evaluation of non-experienced or uncertain events, such as confidence judgments about memory or perceptual decisions. This region, homologous to human prefrontal areas involved in introspection, showed selective impairment in metacognitive accuracy when temporarily silenced, underscoring its causal role in integrating subjective confidence with task performance.^[69]

Evidence in Other Species

Studies on metacognition in non-primate species have revealed behaviors suggestive of uncertainty monitoring and information-seeking, extending beyond primates to rodents, birds, and marine mammals. In rats, evidence comes from tasks where animals opt out of or seek information to resolve uncertainty. For instance, in a duration-discrimination task, rats were trained to classify short or long durations of a light stimulus for reinforcement, but on some trials, they could press a "decline" lever to escape difficult discriminations near the boundary between short and long. Rats selectively declined trials with intermediate durations, indicating sensitivity to their own uncertainty about the correct response, which increased as task difficulty rose. This opt-out behavior was not explained by simple perceptual cues, supporting an interpretation of metacognitive-like monitoring in rodents.^[70] Although early studies used perceptual tasks, later work explored information-seeking in spatial contexts like the radial arm maze, where rats pressed a lever to reveal cues about reward locations in uncertain arms, avoiding exploration without information. This proactive seeking of cues before choosing arms demonstrated that rats adjust behavior based on perceived knowledge gaps, akin to metacognitive regulation. Such findings highlight simpler, adaptive manifestations of metacognition in rodents compared to more complex primate analogs. In birds, pigeons have shown metacognition-like responses in memory tasks using delay-of-choice procedures. In a delayed matching-to-sample paradigm, pigeons viewed a sample stimulus and, after a retention interval, chose between matching the sample or opting for an "uncertain" response that postponed the choice, effectively extending the delay to boost memory confidence. Pigeons more frequently selected the delay option on trials with longer retention intervals or when memory was weaker, leading to higher accuracy on subsequent choices. This strategic adjustment suggests pigeons monitor their memory strength and control task engagement accordingly.^[71] Dogs exhibit uncertainty signals in social contexts, such as vocalizations and gaze alternation toward humans during ambiguous situations. In uncertainty monitoring tasks, dogs faced choices between two identical objects hiding food, but when uncertain, they looked toward their owner more often and produced whines or barks, behaviors that increased with task difficulty. These communicative acts imply dogs recognize their lack of information and seek human assistance to resolve it, paralleling metacognitive help-seeking in humans. Although not always replicated in non-social paradigms, this sensitivity to personal uncertainty underscores metacognition's role in canine social cognition.^[72] Marine mammals like dolphins demonstrate metacognitive uncertainty in perceptual discriminations. In an auditory pitch-discrimination task, a bottlenose dolphin classified tones as high or low for reinforcement, with an "escape" option to avoid trials. The dolphin used the escape response more on near-threshold trials where discrimination was uncertain, reducing errors and maintaining high overall performance. This pattern, robust across sessions, indicated the dolphin monitored its perceptual confidence and regulated participation, providing early evidence of metacognition in cetaceans. Similar escape behaviors appeared in visual tasks, reinforcing the dolphin's ability to signal uncertainty.^[73]

Debates on Animal Metacognition

One central debate in animal metacognition concerns the behavioral interpretation problem, where observed uncertainty-monitoring behaviors in animals may be attributable to low-level perceptual or associative cues rather than genuine meta-awareness. Skeptics argue that performances in tasks like perceptual discrimination can be explained by simple reinforcement learning or stimulus-response associations, without invoking higher-order cognitive monitoring. For instance, Carruthers (2008) contends that apparent metacognitive judgments in monkeys and other species can be parsimoniously accounted for by first-order theories of decision-making under uncertainty, such as signal detection processes that do not require self-reflective awareness. This critique emphasizes the risk of anthropomorphic overinterpretation, urging researchers to rule out such alternatives through controlled experiments that isolate meta-level processes.^[74] Evolutionary arguments further complicate the debate, positing a gradual emergence of metacognitive abilities across species, with more robust evidence in primates due to their complex social and ecological demands. Proponents suggest that metacognition likely evolved to enhance adaptive decision-making in uncertain environments, but its presence varies phylogenetically, appearing strongest in great apes and old-world monkeys where cognitive demands for tool use and social navigation are high. Metcalfe (2009) proposes that metacognition represents a relatively recent evolutionary innovation, primarily in humans and select primates, enabling escape from stimulus-bound behavior through prospective monitoring of cognitive states. However, this view is contested by evidence of similar behaviors in birds and rodents, raising questions about whether these reflect homologous metacognitive mechanisms or convergent low-level adaptations. Methodological issues underscore the challenges in distinguishing true metacognition from behavioral mimics, particularly the reliance on non-verbal paradigms designed for animals. Tasks such as uncertainty monitoring, where subjects can opt out of difficult trials to seek more information or avoid penalties, have become standard for probing metacognitive control without linguistic demands. Smith et al. (2003) introduced this approach in studies with rhesus monkeys and a dolphin, demonstrating adaptive uncertainty responses that suggest internal monitoring, yet critics highlight potential confounds like external reward cues influencing choices. Ongoing refinements, including transfer tests and computational modeling, aim to validate these paradigms by ensuring behaviors persist across contexts without low-level explanations.^[75] The current consensus reflects partial acceptance of animal metacognition, acknowledging compelling evidence in primates while recognizing interpretive ambiguities in other species, with active research employing comparative cognition methods to resolve debates. Reviews from the 2020s indicate growing agreement that great apes and some macaques exhibit metacognitive monitoring and control, as seen in consistent performances across diverse tasks, though full phenomenal awareness remains unproven. Beran et al. (2019) highlight a decade of progress, noting that while low-level accounts persist, accumulating data from information-seeking paradigms support higher-order interpretations in nonhumans. Recent syntheses, such as Basile and Hampton (2024), affirm this tempered view, emphasizing the need for interdisciplinary approaches to bridge gaps between behavioral data and cognitive theory. A 2025 study further supports metacognitive abilities in chimpanzees by demonstrating their capacity to rationally revise beliefs in response to new evidence under uncertainty.^[76]^[77]^[78]

Emerging Topics

Mind Wandering and Metacognition

Mind wandering is characterized as a shift in attention away from a primary task toward internal, task-unrelated thoughts, often occurring spontaneously and without immediate awareness. This phenomenon involves metacognitive processes, particularly meta-awareness, which refers to the ability to notice and monitor these attentional lapses as they occur. Without meta-awareness, mind wandering can persist undetected, while its emergence enables metacognitive signals that prompt reflection on one's cognitive state. Detection of mind wandering relies on methods that capture these episodes in real time, distinguishing between unaware and aware instances to highlight metacognitive involvement. Probe-caught techniques interrupt participants during tasks with questions about their current thoughts, estimating mind wandering rates retrospectively based on responses, though they may underestimate unaware episodes.^[79] In contrast, experience sampling methods, such as those used in neuroimaging studies, provide online assessments by prompting participants to report thought content at random intervals, revealing associations between mind wandering and brain activity; for instance, a seminal fMRI study using experience sampling found increased default mode network activation during reported mind wandering episodes.^[80] These approaches underscore how metacognition facilitates the identification of distraction, with self-caught reports—where individuals voluntarily signal awareness of mind wandering—offering direct insight into meta-awareness levels.^[81] Regulation of mind wandering involves metacognitive control mechanisms that detect deviations and redirect attention, often through interplay between neural networks. The default mode network, active during internally directed thought, supports the generation of spontaneous ideas but can lead to prolonged distraction if unchecked. Metacognitive strategies, such as intentional refocusing, engage executive control networks to suppress default mode activity and restore task focus, with evidence suggesting that higher meta-awareness enhances this regulatory capacity. These processes draw on broader metacognitive monitoring, allowing individuals to evaluate and adjust their attentional allocation dynamically. The implications of mind wandering for metacognition reveal both adaptive and maladaptive dimensions, modulated by context and individual traits. Adaptively, meta-aware mind wandering can foster creativity by enabling unconstrained associations and problem-solving insights, as seen in studies linking spontaneous thought to enhanced idea generation, including recent 2025 research showing mind wandering during creative incubation predicts increases in creativity.^[82]^[83] Maladaptively, it impairs performance on error-prone tasks requiring sustained attention, increasing lapse rates and cognitive costs when meta-awareness is low. Individual differences in meta-awareness significantly influence these outcomes; for example, people with higher trait mindfulness or cognitive flexibility report greater detection and control of mind wandering, reducing its disruptive effects while preserving creative benefits. Recent 2025 neuroimaging work further highlights neural dynamics in the default and control networks guiding transitions in spontaneous memory recall and future thinking related to mind wandering.^[84]

Metacognitive Artifacts in Works of Art

Metacognitive artifacts in works of art refer to creative expressions that externalize and stimulate reflection on one's own cognitive processes, such as memory retrieval, perceptual interpretation, and interpretive biases, thereby serving as scaffolding for metacognitive awareness. These artifacts encourage audiences to monitor and evaluate their thinking during engagement, bridging artistic experience with self-regulated cognition. Research in art appreciation highlights how such works facilitate metacognitive monitoring by prompting viewers to visualize and deepen their thought processes, transforming passive consumption into active self-examination.^[85] In literature, Marcel Proust's In Search of Lost Time (1913–1927) exemplifies metacognitive scaffolding through its exploration of involuntary memory, where sensory triggers evoke past experiences without deliberate effort, inviting readers to reflect on the automaticity and reliability of their own memory mechanisms. The narrative's focus on the narrator's sudden recollections, such as the famous madeleine episode, illustrates how art can prompt metacognitive evaluation of memory's non-conscious pathways, enhancing awareness of how emotions and sensations influence recall. This process aligns with psychological accounts of involuntary retrieval as a metacognitive phenomenon that bypasses intentional search, fostering deeper self-insight into cognitive biases in remembering.^[86] Visual arts provide another avenue for metacognitive engagement, particularly through perceptual challenges that reveal the constructed nature of cognition. M.C. Escher's impossible figures, like those in Belvedere (1958), depict spatially incoherent structures that defy three-dimensional logic, compelling observers to monitor and question their perceptual judgments as the brain alternates between conflicting interpretations. These works induce metacognitive reflection on how visual cues are processed and integrated, highlighting errors in spatial reasoning and the subjective nature of sight. Studies on such illusions demonstrate their utility in exploring cognitive and metacognitive processes, as interactive simulations of Escher-like worlds reveal how violations of real-world constraints prompt self-awareness of perceptual limitations.^[87]^[88] In modern media, interactive installations extend this scaffolding by involving participants directly in explorations of perception and adaptation through human-computer interactions. For instance, contemporary digital art pieces that respond to viewer input, such as holographic installations probing techno-perceptions, engage users in real-time feedback on their actions, facilitating reflection on adaptations to novel stimuli in dynamic environments. These 21st-century examples, often found in new media exhibitions, make perceptual processes tangible through interaction, with recent 2025 research highlighting AI-based painting tools' role in enhancing children's creative thinking and metacognitive skills.^[89]^[90]

References

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