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Developing a Reflective Mind: From Core Metacognition to Explicit Self-Reflection

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Abstract

Metacognition is the ability to monitor and control cognition. Because young children often provide inaccurate metacognitive judgments when prompted to do so verbally, it has long been assumed that this ability does not develop until late childhood. This claim is now challenged by new studies using nonverbal paradigms and revealing that basic forms of metacognition—such as the ability to estimate decision confidence or to monitor errors—are present even in preverbal infants. This new line of evidence suggests that young children adapt to their environment not only by considering their physical and social surroundings but also by reflecting on their own cognitive states.
https://doi.org/10.1177/0963721419848672
Current Directions in Psychological
Science
2019, Vol. 28(4) 403 –408
© The Author(s) 2019
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DOI: 10.1177/0963721419848672
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PSYCHOLOGICAL SCIENCE
Metacognition is our ability to reflect on our own mental
representations to regulate cognition and optimize learn-
ing. Given metacognition’s importance for education, its
development has been studied intensively since the
1970s. For several decades, on the basis of studies that
primarily relied on verbal reports, researchers argued
that young children have poor and inefficient self-
reflective abilities (for reviews, see Flavell, 2000; Sodian,
Thoermer, Kristen, & Perst, 2012). Yet it now appears
that young children’s limitations largely reflect an inabil-
ity to provide accurate metacognitive reports rather than
an absence of metacognition per se. Indeed, a new line
of investigation relying on nonverbal paradigms and
focusing on error monitoring (i.e., detecting one’s own
mistake) and decision confidence (i.e., estimating the
probability that a choice was correct) has revealed that
even preverbal infants engage in rudimentary forms of
metacognition. In this article, we briefly review this bur-
geoning literature before proposing a framework that
integrates recent findings with more traditional research
documenting a slow and effortful development of explicit
aspects of metacognition.
Early Forms of Metacognition
Over the last decade, several approaches have been
elaborated to examine the development of metacogni-
tion without relying on verbal reports. A first approach
revealed that when 3- to 5-year-olds are trained to use
a nonverbal confidence scale depicting pictures of a
confident or a doubtful peer, they quickly learn how
to use it appropriately (Ghetti, Hembacher, & Coughlin,
2013). That is, they provide higher confidence judg-
ments for correct compared with incorrect responses,
thereby displaying metacognitive sensitivity (i.e., accu-
rate evaluations of their performances). One limit of
this approach, however, is that nonverbal confidence
scales still require an understanding of the concept of
confidence: To use them appropriately, children must
understand how the symbolic representations depicted
by the scale map onto their internal states of uncer-
tainty. Thus, this type of measure cannot be extended
to test younger children, who cannot be verbally
instructed on how to use such a scale.
Consequently, a second approach consisted of adapt-
ing behavioral methods stemming from the animal lit-
erature. In particular, in the opt-out paradigm (Hampton,
848672CDPXXX10.1177/0963721419848672Goupil, KouiderDeveloping a Reflective Mind
research-article2019
Corresponding Authors:
Louise Goupil, Institut de Recherche et Coordination en Acoustique et
Musique, 1 Place Igor Stravinsky, 75001, Paris, France
E-mail: louise.goupil@ircam.fr
Sid Kouider, École Normale Supérieure, Laboratoire de Sciences
Cognitives et Pscyholinguistique, Pavillon Jardin, 29 Rue d’Ulm, 75005,
Paris, France
E-mail: sid.kouider@ens.fr
Developing a Reflective Mind: From Core
Metacognition to Explicit Self-Reflection
Louise Goupil1 and Sid Kouider2
1Science and Technology of Music and Sound, Unités Mixtes de Recherche 9912, Centre National
de la Recherche Scientifique/Institut de Recherche et de Coordination en Acoustique/Musique,
Paris, France, and 2Brain and Consciousness Group, Département d’Études Cognitives,
École Normale Supérieure, Centre National de la Recherche Scientifique, École des Hautes
Études en Sciences Sociales, PSL Research University
Abstract
Metacognition is the ability to monitor and control cognition. Because young children often provide inaccurate
metacognitive judgments when prompted to do so verbally, it has long been assumed that this ability does not develop
until late childhood. This claim is now challenged by new studies using nonverbal paradigms and revealing that basic
forms of metacognition—such as the ability to estimate decision confidence or to monitor errors—are present even
in preverbal infants. This new line of evidence suggests that young children adapt to their environment not only by
considering their physical and social surroundings but also by reflecting on their own cognitive states.
Keywords
metacognition, confidence, error monitoring, development, self-reflection
404 Goupil, Kouider
2009), participants are presented with a binary choice,
either in a condition in which they have no option but
to choose by themselves (forced choice) or in a condi-
tion in which they are also given the additional option
to avoid responding (i.e., opt out). The rationale behind
this paradigm is that if participants are able to monitor
their own uncertainty, they should opt out specifically
when they are uncertain, and thereby avoid making
errors in choosing between the two alternatives. In such
a task, 3-year-olds (Balcomb & Gerken, 2008) and even
20-month-olds, who cannot yet verbally communicate
their knowledge states (Goupil, Romand-Monnier, &
Kouider, 2016), have been found to opt out appropri-
ately to avoid errors. In one of these experiments,
20-month-old toddlers had to remember the location
of a toy hidden for variable durations (to induce several
levels of difficulty) before pointing to indicate where
they wanted to recover it (Goupil etal., 2016). Although
toddlers in a control group had no option other than
to decide by themselves, toddlers in a test group were
given the extra option of asking their caregiver for help
through nonverbal communication. In this test group,
only two training trials allowed toddlers to understand
that they could withhold their response when feeling
uncertain and ask their caregiver for help instead.
Toddlers opted out not only to avoid difficult choices
but also to avoid making errors irrespective of task dif-
ficulty; even in easy trials, toddlers in the test group
made fewer errors than toddlers in the control group.
Importantly, the rate of correct choices remained the
same across the two groups, demonstrating that the
toddlers opted out specifically to avoid making errors.
Overall, the results revealed that toddlers were not
merely responding on the basis of risk avoidance (e.g.,
escaping from difficult choices) or other first-order (i.e.,
cognitive) mechanisms. Rather, the results showed that
children appraised their probability of success (i.e.,
asked for help when confidence was low; see Goupil
etal., 2016, for further information).
Converging evidence comes from a third approach
elaborated by comparative psychologists to measure
metacognition while ruling out first-order interpreta-
tions: postdecision wagering. In such a task, 5-year-old
children place higher bets on correct compared with
incorrect responses (Vo, Li, Kornell, Pouget, & Cantlon,
2014). Recently, we used a totally nonverbal variant of
this paradigm to demonstrate that preverbal infants also
display such metacognitive sensitivity (Goupil &
Kouider, 2016). Infants made a decision (18-month-olds
pointed to indicate the location of a hidden toy;
12-month-olds gazed toward the location of a briefly
presented face) followed by a measure of postdecision
persistence. This measure relies on the fact that one
will wait longer for a reward if one thinks that one’s
response was correct; it has proven to be a reliable
proxy for decision confidence in rats and chimpanzees
(Beran etal., 2015; Lak etal., 2014). Infants persisted
more after making a correct compared with an incorrect
decision. Importantly, they did so in the total absence
of external feedback on their performance. Further,
their persistence did not vary with stimulus or task
properties (i.e., memorization delay for 18-month-olds;
duration of the masked-face presentation for 12-month-
olds), but rather constituted a characteristic pattern in
which confidence decreased with difficulty for correct
judgments but increased for errors (Lak etal., 2014).
This suggests that infants’ postdecision persistence does
not simply reflect properties of external events (e.g.,
that the face was presented for 100 ms vs. 300 ms), but
rather is contingent on the accuracy of their own deci-
sions and reflects a subjective evaluation of perfor-
mance (see Goupil & Kouider, 2016).
One might still argue that it remains debatable
whether postdecision persistence unambiguously
reflects second-order (i.e., metacognitive) computations
(Fleming & Daw, 2017) and that, ultimately, it may be
difficult to make conclusions about this issue on the
basis of behavioral data alone. Fortunately, a fourth
approach using neuroimaging provides more decisive
evidence, as it allows researchers to dissociate brain
areas associated with metacognitive versus cognitive
processes. Regarding confidence, experiments with
both rats and monkeys revealed that pharmacological
inactivation of specific prefrontal areas impairs meta-
cognitive sensitivity while sparing perceptual decisions
(Lak etal., 2014; Miyamoto etal., 2017). Similarly, meta-
cognition causally involves the prefrontal cortex in
human adults (Fleming & Dolan, 2012), and decision
confidence is automatically encoded in the ventrome-
dial prefrontal cortex even when no reports are required
from the participants (Lebreton, Abitbol, Daunizeau, &
Pessiglione, 2015). The metacognitive system support-
ing error monitoring also elicits characteristic neural
activity originating in the anterior cingulate cortex and
reflected in an electroencephalographic potential called
the error-related negativity (ERN). This component is
thought to reflect a second-order, postdecisional mecha-
nism signaling a mismatch between a just-made (incor-
rect) decision and the choice that should have been
made on the basis of the available evidence (Charles,
King, & Dehaene, 2014).
Consistent with the idea that core metacognition
emerges early in development, studies have shown that
some of these key prefrontal structures are already
functional in infancy (Dehaene-Lambertz & Spelke,
2015; Goupil & Kouider, 2016). Although unfortunately
no study to date has measured neural markers of deci-
sion confidence in young children, a few studies have
shown that the mechanisms of error monitoring sub-
tended by the anterior cingulate cortex are already
Developing a Reflective Mind 405
functional (Tamnes, Walhovd, Torstveit, Sells, & Fjell,
2013). For instance, we recently found that following
perceptual decisions, infants as young as 12 months of
age display an ERN component after making an incor-
rect choice (Goupil & Kouider, 2016).
Core Metacognition
The evidence reviewed above suggests that human
infants are already endowed with rudimentary forms of
metacognition. Several lines of research suggest that
these abilities primarily rely on a phylogenetically
ancient metacognitive system that is not strictly tied to
explicit reports. Indeed, as mentioned above, confidence
and error monitoring are present in several other species,
including rats and monkeys (Hampton, 2009). Further-
more, neuroimaging and computational-modeling stud-
ies in human adults have revealed that confidence and
error monitoring can be reduced to simple computa-
tional mechanisms (Fleming & Daw, 2017; Yeung &
Summerfield, 2012) and can automatically induce self-
regulation even when they are not introspectively accessed
(Logan & Crump, 2010; Nieuwenhuis, Ridderinkhof, Blom,
Band, & Kok, 2001). Consequently, modern frameworks
emphasize the fact that metacognition does not reduce to
its explicit manifestations and stress the importance of
implicit forms of self-monitoring and regulation (Proust,
2012; Shea etal., 2014).
Building on these views, we here propose that start-
ing in the first years of life, humans are already endowed
with a system of core metacognition allowing them to
automatically evaluate and regulate their own cogni-
tion. Core metacognition is complementary to other
core systems that evolved to fulfill a dedicated function
(e.g., representing objects) and on which flexible and
explicit capacities build later in development (Carey,
2009; Spelke & Kinzler, 2007). Whereas other core sys-
tems represent properties of the external world, core
metacognition specifically evolved to enable the moni-
toring of internal cognitive states, allowing endogenous
engagement in self-regulation. Specifically, core metacog-
nition encompasses any mechanism whereby a first-
order (cognitive) representation (e.g., a belief) is
assessed through a second-order (metacognitive) pro-
cess that evaluates its quality (e.g., the likelihood that
the belief is correct given the sensory evidence) without
necessarily reaching awareness or being represented
explicitly. Importantly, core metacognition is not simply
equivalent to cognitive control: It concerns processes
that use metacognitive representations (i.e., representa-
tions that contain some information about the proper-
ties of an underlying cognitive representation; e.g., the
reliability of a belief) for self-regulation (for more
details, see Shea etal., 2014; for an alternative position
on this issue, see Carruthers, 2009). Such a system
would be present not only in humans but also in other
animals whenever their neural architecture implements
second-order structures evaluating first-order represen-
tations computed in sensorimotor and other associative
areas.
As with other core systems, core metacognition can
be considered an innate component relying on the mat-
uration of dedicated brain structures that were shaped
by evolution to constrain and optimize our representa-
tional space. However, the emergence of core metacog-
nition is certainly protracted compared with other core
systems, such as naive physics. Indeed, whereas sensory
systems develop rapidly over the first year of life, the
prefrontal cortex shows a dramatic increase in synaptic
density and long-range connectivity only by the end of
the first year (Dehaene-Lambertz & Spelke, 2015) and
substantially matures until adolescence (Lebel, Walker,
Leemans, Phillips, & Beaulieu, 2008). Thus, although the
structures that support core metacognition are already
functional during the first years of life, they remain
largely immature and undergo substantial development
throughout childhood. So far, the youngest age at which
core metacognition has been observed is 12 months
(Goupil & Kouider, 2016). Whether the maturation of
the prefrontal cortex and its long-range connections are
sufficient to support metacognition in infants below 1
year of age remains an open question.
Signature Limits of Core Metacognition
If core metacognition emerges early, why does self-
reflection appear so limited and unreliable until much
later in childhood, as evidenced by decades of research
in developmental psychology? As mentioned above, a
first developmental constraint concerns the maturation
of the prefrontal areas supporting core metacognition
that undergo substantial maturation during childhood.
But beyond this slow maturation, the core metacogni-
tive system presents several intrinsic limitations. Below,
we characterize these restrictions and detail how the
core system interacts with the late-developing system
of explicit metacognition.
Core systems are defined not only by a dedicated
function but also by distinctive signature limits (e.g.,
the core system dedicated to object representations is
limited to a set size of four; Carey, 2009). A first signa-
ture limit of core metacognition is that it is restricted
to the evaluation of simple perceptual and value-based
decisions. Even human adults tend to shift to inferential,
heuristic strategies relying on the interpretation of cues
(e.g., response times)—as opposed to relying on opti-
mal metacognitive computations—to evaluate complex
decisions and reasoning (Ackerman & Thompson, 2017).
406 Goupil, Kouider
A second and perhaps more important limitation of
core metacognition is that, in and of itself, it is not suf-
ficient to enable a crucial aspect of human metacogni-
tion: the ability to share metacognitive representations
with other people (Shea etal., 2014). This latter capac-
ity relies on explicit metacognition, a heterogeneous
system that supports the exploitation of consciously
accessed metacognitive representations. Decades of
developmental research suggest that this system
requires the development of several additional abilities
(Flavell, 2000; Sodian etal., 2012) that progressively
come together to enable children to engage in explicit
metacognition and provide accurate metacognitive
reports.
First, the ability to focus on metacognitive monitor-
ing and inhibit the use of irrelevant information when
providing self-reports is limited in children. Their inac-
curate reports reflect an inability to select relevant
sources of information (e.g., error signals) while inhibit-
ing inappropriate ones (e.g., desires to succeed). This
often results in a “liberal” metacognitive bias with a
high propensity to give affirmative (e.g., “Yes I know”)
responses (i.e., overconfidence; Butterfield, Nelson, &
Peck, 1988; Lipowski, Merriman, & Dunlosky, 2013).
Importantly, this bias is also often observed in human
adults (Dunlosky & Metcalfe, 2009). Children still lack
the executive functions necessary to inhibit such pre-
potent responses and provide accurate metacognitive
reports. Indeed, executive functions, and in particular
inhibitory control, do not consistently drive behavior
before 4 years of age and continue developing until late
childhood (Posner, Rothbart, Sheese, & Voelker, 2014;
see also Roebers, 2017, for more details on this issue).
Another developmental constraint concerns the abil-
ity to shift from an implicit to an explicit mode of
processing. The latter implies directing attention toward
metacognitive representations in order to globally
broadcast them, thereby rendering them conscious and
reportable (Dehaene, Lau, & Kouider, 2017). To illus-
trate this contrast between implicit and explicit meta-
cognition, we can return to the neural signatures of
error monitoring mentioned above. Although neural
markers of implicit error monitoring are observable in
the anterior cingulate cortex following incorrect
responses and are reflected in the ERN component
regardless of introspective access to the error, conscious
error detection elicits broader activations in a fronto-
parietal network that are reflected in a later component
called the error-related positivity (Yeung & Summerfield,
2012). This pattern is similar to what is found for con-
scious versus unconscious perceptual processes in
adults and infants, as the former generally involves
early responses that are restricted in time and space
whereas the latter evokes late, long-lasting, and wide-
spread activations (Dehaene etal., 2017; Kouider etal.,
2013). Taken together, these data suggest that con-
sciously accessing metacognitive representations
involves additional neural processes entailing their
global broadcasting. Given that the mechanisms
enabling conscious access are already in place during
the first year of life (Kouider etal., 2013), it is plausible
that, even in infancy, metacognitive representations
eventually become conscious when they represent a
very strong signal (e.g., when a decision differs greatly
from the option favored by sensory evidence). Yet it is
also probable that, initially, metacognitive representa-
tions remain for the most part unconscious, either
because their representational content remains too
weak to capture attention or because they are overwrit-
ten by stronger alternative signals (e.g., external feed-
back, desires to succeed).
Finally, beyond executive functions and conscious
access, language and culture play a crucial role in build-
ing the late-developing system (Flavell, 2000; Sodian
etal., 2012). Interactions with caregivers shape and
normalize explicit aspects of metacognition (Roebers,
2017; Schneider, 2008), and cultural norms deeply mod-
ulate individual strategies when giving self-reports (Ma
etal., 2014). Learning a set of linguistic expressions
that are efficient to share metacognitive representations
in one’s own culture is a challenge, as shown by the
fact that the acquisition of cognitive-state vocabulary
lags behind the acquisition of other lexicons (Bretherton
& Beeghly, 1982) and that even in human adults, effi-
cient communication of confidence depends on linguis-
tic convergence (Fusaroli etal., 2012). Thus, whereas
core metacognition is likely to be an innate module
evolved through natural selection (like other core sys-
tems; Carey, 2009), the emergence of explicit metacog-
nition is largely constrained by the development of
higher-order cognitive functions and culturally situated
learning.
Conclusion
We suggest that a core system of metacognition appears
very early in development, whereas explicit and human-
specific forms of metacognition slowly emerge to progres-
sively allow children to communicate their metacognitive
representations to others. In the field of mind reading,
distinctions between implicit and explicit processes have
also been used to account for the finding that young
children’s spontaneous behaviors reveal a sensitivity to
other people’s beliefs years before they manage to pass
explicit false-belief tasks (Low & Perner, 2012), and simi-
lar arguments have been made regarding empathy
(Heyes, 2018). How are these two aspects of mind reading
and empathy related to the two metacognitive systems?
Some evidence suggests that explicit mind reading and
metacognition develop together (Flavell, 2000; Lockl &
Developing a Reflective Mind 407
Schneider, 2007), but little empirical data are available
regarding implicit aspects. A stimulating avenue for
future research will thus be to examine the relation-
ships between these constructs while considering the
fact that they cannot be reduced to their explicit mani-
festations. Another promising avenue for future research
will be to examine the potential involvement of meta-
cognition in early learning. Metacognition is a privi-
leged tool to optimally acquire new information, as it
allows organisms to assess their own knowledge states
and flexibly adapt their strategies to learn optimally in
the absence of external feedback (Guggenmos, Wilbertz,
Hebart, & Sterzer, 2016). At the earliest stages of devel-
opment, when everything remains to be learned, this
ability might be one of the key ingredients that allow
young children to learn actively and optimally.
Recommended Reading
Goupil, L., & Kouider, S. (2016). (See References). An empiri-
cal article revealing that core metacognitive mechanisms
are already present in 12- and 18-month-old infants.
Proust, J. (2012). (See References). An opinion piece discuss-
ing the possibility that metacognition does not reduce to
its explicit manifestations.
Shea, N., Boldt, A., Bang, D., Yeung, N., Heyes, C., & Frith, C. D.
(2014). (See References). An opinion article arguing that
whereas implicit metacognition is shared with several ani-
mal species and serves functions at the subpersonal level,
explicit metacognition has evolved to fulfill a social function.
Sodian, B., Thoermer, C., Kristen, S., & Perst, H. (2012). (See
References). A review on the development of metacogni-
tion in young children.
Action Editor
Randall W. Engle served as action editor for this article.
Acknowledgments
We thank J. Sackur and J. Proust for discussions on the
manuscript.
Declaration of Conflicting Interests
The author(s) declared that there were no conflicts of interest
with respect to the authorship or the publication of this
article.
Funding
This research was supported by funding from the Agence Natio-
nale de la Recherche (ANR-17-EURE-0017) and from the Euro-
pean Research Council to S. Kouider (METAWARE project).
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... Here, we offer a detailed account of how metacognition supports curiosity. A large body of research indicates that metacognition does not reduce to its conceptual, meta-representational forms, and that preverbal children and some nonhuman animals possess rudimentary metacognitive ressources (Goupil & Kouider, 2019;Proust, 2012Proust, , 2019Shea et al., 2014, see Appendix 1). We argue that intrinsic curiosity involves at least such minimal forms of metacognitive monitoring and regulation that allow agents to identify and satisfy their informational needs, which we refer to as "core" or "procedural" metacognition. ...
... Low confidence already predicts information-seeking early on in development (Coughlin, Hembacher, Lyons, & Ghetti, 2014;Goupil & Kouider, 2019;Lapidow, Killeen, & Walker, 2022). For instance, in a perceptual task, 3-to 5-year-old children preferentially seek additional informationinstead of responding by themselvesin conditions in which they also report low confidence on a picture-based scale (Coughlin et al., 2014). ...
... 3. In human ontogeny, children display behavioral markers suggesting that they experience feelings of curiosity and confidence before they can conceptually represent themselves as having these mental states (Baer & Kidd, 2022;Goupil & Kouider, 2019). 4. In human adults, dissociations have been documented in metacognitive monitoring according to task demands, between feelingbased and concept-based incompatible evaluations (Koriat & Ackerman, 2010;Nussinson & Koriat, 2008). ...
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Curious information-seeking is known to be a key driver for learning, but characterizing this important psychological phenomenon remains a challenge. In this article, we argue that solving this challenge requires qualifying the relationships between metacognition and curiosity. The idea that curiosity is a metacognitive competence has been resisted: researchers have assumed both that young children and non-human animals can be genuinely curious, and that metacognition requires conceptual and culturally situated resources that are unavailable to young children and non-human animals. Here, we argue that this resistance is unwarranted given accumulating evidence that metacognition can be deployed procedurally, and we defend the view that curiosity is a metacognitive feeling. Our metacognitive view singles out two monitoring steps as a triggering condition for curiosity: evaluating one's own informational needs, and predicting the likelihood that explorations of the proximate environment afford significant information gains. We review empirical evidence and computational models of curiosity, and show that they fit well with this metacognitive account, while on the contrary, they remain difficult to explain by a competing account according to which curiosity is a basic attitude of questioning. Finally, we propose a new way to construe the relationships between curiosity and the human-specific communicative practice of questioning, discuss the issue of how children may learn to express their curiosity through interactions with others, and conclude by briefly exploring the implications of our proposal for educational practices.
... Though traditional accounts have long assumed that metacognition (i.e., the ability to evaluate one's own cognitive representation) is limited in children below four (e.g., Flavell, 1999), recent research outside the language domain has suggested that certain core aspects of metacognition develop much earlier, long before children can talk about their own cognition (Balcomb and Gerken, 2008;Geurten and Bastin, 2019;Ghetti et al., 2013;Goupil and Kouider, 2019). For example, there is evidence that infants are able to estimate confidence (i.e., the likelihood that a decision is correct (Kepecs et al., 2008;Pouget et al., 2016)) years before they can provide metacognitive verbal reports (Balcomb and Gerken, 2008;Geurten and Bastin, 2019;Goupil and Kouider, 2016;Hembacher and Ghetti, 2014;Kuzyk et al., 2019;Vo et al., 2014). ...
... It may be that confidence directly reflects properties of the decision-making process (e.g., the distance between accumulated evidence and a decision bound, or an evaluation of decision time) (Kiani and Shadlen, 2009;Pereira et al., 2021). Alternatively, it could be that confidence reflects core metacognitive monitoring even in young children (Goupil and Kouider, 2019). The finding that speaker idiosyncrasy can differentially impact first-look accuracy and post-decision persistence favours this latter interpretation. ...
... In sum, our work converges with a growing body of evidence suggesting that monitoring confidence is a fundamental ability that enables humans to actively and adaptively respond to their environment from a very young age (Ghetti et al., 2013;Goupil and Kouider, 2019). It extends previous results by showing that toddlers' capacity for confidence monitoring is not restricted to the evaluation of simple perceptual decisions, but extends to socially-informed conventional knowledge. ...
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... Still, if metacognitive processes and multisensory congruence develop in the first few years of life, the sense of perceptual reality should also become richer but also more confusing at times, as infants and children develop (see Goupil & Kouider, 2019). Similarly, the capacity to entertain counterfactual hypotheses (e.g. ...
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The controversial question of whether machines may ever be conscious must be based on a careful consideration of how consciousness arises in the only physical system that undoubtedly possesses it: the human brain. We suggest that the word “consciousness” conflates two different types of information-processing computations in the brain: the selection of information for global broadcasting, thus making it flexibly available for computation and report (C1, consciousness in the first sense), and the self-monitoring of those computations, leading to a subjective sense of certainty or error (C2, consciousness in the second sense). We argue that despite their recent successes, current machines are still mostly implementing computations that reflect unconscious processing (C0) in the human brain. We review the psychological and neural science of unconscious (C0) and conscious computations (C1 and C2) and outline how they may inspire novel machine architectures.
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Executive function and metacognition are higher-order cognitive processes that undergo steady improvements throughout childhood. They are highly relevant to daily functioning in various domains, including academic achievement. Both concepts have been intensively researched, but surprisingly little literature has sought to connect them theoretically and empirically. In the present review, I elaborate on the similarities between these concepts from a developmental perspective, including the definitions, developmental timetables, factors that lead to changes over time, and relations to academic achievement and intelligence. Simultaneously, the differences between these two domains of cognitive development are discussed. These include, in particular, the relative neglect of quantifying monitoring within research on executive functions and the disregard for the neuropsychological underpinnings of metacognition. Finally, this paper presents several avenues for future research and proposes a possible unifying framework of cognitive self-regulation that integrates executive function and metacognition and may lead to a better understanding of the emergence of cognitive self-regulation in development.