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While an abundance of research has investigated the development of the automatic and controlled processes through which individuals control their thoughts, emotions, and actions, less research has emphasized the role of the self in self-regulation. This chapter synthesizes four literatures that have examined the mechanisms through which the individual acts in a managerial role, evaluating the current status of the system and initiating regulatory actions as necessary. Taken together, these literatures (on executive function, error monitoring, metacognition, and uncertainty monitoring) suggest that self-reflection plays a critical role in self-regulation, and that developmental improvements in self-reflection (via increasing levels of conscious awareness and enhanced calibration of monitoring systems) may serve as driving forces underlying developmental improvement (and temperamental individual differences) in children's ability to control their thoughts and actions.
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From: Kristen E. Lyons and Philip David Zelazo, Monitoring, Metacognition, and
Executive Function: Elucidating the Role of Self-Reflection in the Development of
Self-Regulation. In Janette Benson, editors: Advances in Child Development and
Behavior, Vol. 40, Burlington: Academic Press, 2011, pp. 379-412.
ISBN: 978-0-12-386491-8
© Copyright 2011 Elsevier Inc.
Academic Press
Kristen E. Lyons and Philip David Zelazo
While an abundance of research has investigated the development of the
automatic and controlled processes through which individuals control
their thoughts, emotions, and actions, less research has emphasized the
role of the self in self-regulation. This chapter synthesizes four literatures
that have examined the mechanisms through which the individual acts in a
managerial role, evaluating the current status of the system and initiating
regulatory actions as necessary. Taken together, these literatures
Advances in Child Development and Behavior Copyright ©2011 Elsevier Inc. All rights reserved.
Janette B. Benson : Editor
Author's personal copy
(on executive function, error monitoring, metacognition, and uncertainty
monitoring) suggest that self-reection plays a critical role in self-regulation,
and that developmental improvements in self-reection (via increasing
levels of conscious awareness and enhanced calibration of monitoring sys-
tems) may serve as driving forces underlying developmental improvement
(and temperamental individual differences) in childrens ability to control
their thoughts and actions.
I. Introduction
The development of self-regulation has long been a focus of developmen-
tal research. From early observations by Piaget and Vygotsky through con-
temporary behavioral and neuroscientic investigations, this line of inquiry
provides insight into the genetic, neurophysiological, and behavioral
mechanisms underlying the willful control of thought, emotion, and action.
Self-regulation frees children from reactive, stimulus-driven patterns of
responding, allowing them to plan for their future, maintain optimal levels
of emotional reactivity, and act in a manner that is consistent with their
higher order goals or standards for behaving. As such, this core capacity
has critical implications for emotional well-being, social competence, and
academic and professional success (Blair, 2002; Blair & Diamond, 2008;
Eisenberg, Valiente, & Eggum, 2010; Moftt et al., 2011).
Accordingly, an extensive body of research has investigated the myriad of
automatic and controlled processes that underlie the development of self-
regulation (Kochanska, Coy, & Murray, 2001; Schneider & Lockl, 2008;
Zelazo, Carlson, & Kesek, 2008). Overall, this line of research has revealed
that self-regulation begins to emerge in the rst few months of life, as chil-
dren develop basic motor skills allowing them to engage in rudimentary
forms of self-soothing (e.g., shifting their gaze from aversive stimuli, seeking
proximity to their caregivers; Buss & Goldsmith, 1998; Rothbart, Ziaie, &
OBoyle, 1992). Dramatic improvements in self-regulation occur during
early childhood as children become increasingly able to control their
thoughts (e.g., Paz-Alonso, Ghetti, Matlen, Anderson, & Bunge, 2009),
emotions (e.g., Lewis & Stieben, 2004), and actions (e.g., Zelazo, Müller,
Frye, & Marcovitch, 2003). However, self-regulation continues to mature
until well into adolescence (Best & Miller, 2010; Lewis, Lamm, Segalowitz,
Stieben, & Zelazo, 2006; Olson & Luciana, 2008) and probably beyond (e.g.,
Weintraub et al., 2011). In short, an abundance of research has revealed that
clear age-related improvements in the ability to purposefully adjust ones
thoughts and behavior are observed in the rst two decades of life.
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To date, relatively little attention has been directed toward the self
aspect of self-regulation, including the self-reective processes that allow
children to evaluate their current (internal and contextual) status and ini-
tiate corrective adjustments to their ongoing activity. Just as regulatory
agencies cannot enforce laws without actually monitoring whether com-
panies are adhering to them, human self-regulatory systems cannot ade-
quately control their behavior without some degree of awareness of the
ongoing operations of the system.
How do children develop the ability to monitor and modify their ongo-
ing thoughts, emotions, and actions? The aim of this chapter is to provide
an integrative review of four diverse literatures (on executive function
(EF), metacognition, uncertainty monitoring, and error monitoring) that
are beginning to converge on this question and that collectively provide
some promising answers to it.
Before proceeding, we note that self-regulation encompasses a broad
range of automatic and controlled processes (Lewis & Todd, 2007). Our
primary focus will be the development of the latter. However, age-related
changes and individual differences in automatic processes likely interact
with more controlled operations to yield self-regulation, as discussed in
later sections of this chapter. We also note that the terms self-monitoring
and self-regulation are used here as functional constructs. That is to say,
these and related terms (see Table I for a list of key constructs) are
intended to describe the processes that make it possible for individuals
to track and adjust their behavior (e.g., Zelazo et al., 2008), and not as
the operations of a homunculus or neural module.
II. Four Literatures Investigating the Development
of Self-Regulation
The question of how children acquire the ability to purposefully control
their thoughts and actions has received considerable attention in recent
years, in part due to the well-documented importance of self-regulation
for daily functioning and long-term interpersonal, academic, and profes-
sional success (Blair, 2002; Blair & Diamond, 2008; Eisenberg et al.,
2010; Manly, Hawkins, Evans, Woldt, & Robertson, 2002; Moftt et al.,
2011). Given that self-regulation involves a highly complex array of pro-
cesses, different researchers have focused on different aspects of self-reg-
ulation and approached the topic in different ways, generating at least four
disparate research literatures on EF, error detection, metacognition, and
uncertainty monitoring. While each approach offers distinct methodological
advantages and unique insight into the development of self-regulation, they
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have progressed relatively independently of one another. However, even a
cursory review of these literatures reveals important ways in which the core
processes under investigation may be fundamentally intertwined. In what
follows, we survey these literatures and emphasize how developmental
changes in each may be critically dependent on age-related increases in self-
reection. Taken together, these literatures provide a more comprehensive
characterization of the development of self-reection and its myriad con-
sequences for behavior.
EF entails the conscious control of thoughts and actions (Zelazo et al.,
2008) and refers to the more controlled, top-down processes in self-regu-
lation that depend importantly on neural circuits involving prefrontal
Table I
Key Constructs
Key construct Denition
Self-regulation The broad range of automatic and controlled processes through which
thoughts, emotions, and actions are adjusted
Self-control The deliberate adjustment of ones cognitive, emotional, or
behavioral responses
The capacity to evaluate ones ongoing thoughts, emotions, and actions
Executive function The deliberate adjustment of ones cognitive, emotional, or behavioral
responses, often conceptualized as the cognitive processes of
exibility (task switching), inhibitory control, and working memory
Error monitoring Tracking ones performance on a task and noticing when one has
committed an error, often assessed using ERP
Metacognition Awareness and control of ones cognitive activity
Reecting on ones ongoing cognitive activity
Top-down control of cognitive activity based on metacognitive
monitoring evaluations
Evaluating how certain one feels about the likely accuracy of ones
Interoception Subjective awareness of ones physiological, emotional, and cognitive
An indirect means of monitoring, such that individuals are implicitly
aware of lower-order cognitive operations, which gives rise to
subjective feelings of knowing (although they cannot explicitly
reect on the source of the subjective feelings)
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cortex (PFC). Although it has widespread consequences for daily func-
tioning (e.g., maintaining focus on ones current task, inhibiting oneself
from becoming distracted, exibly shifting ones attention during multi-
tasking), EF is typically assessed using neuropsychological tests of pre-
frontal cortical function that have been modied for use with children
(e.g., go/no-go, backward digit span, anker; Fernandez-Duque, Baird,
& Posner, 2000). Often, these tasks require children to overcome the ten-
dency to respond reexively, impulsively, or by habit (Davidson, Amso,
Anderson, & Diamond, 2006; Shimamura, 2000) and instead purposefully
select the appropriate course of action.
EF emerges relatively early, as indicated by infantspassing of the A-not-B
task toward the end of the rst year of life. In this task, infants are repeatedly
shown an object being hidden in a certain location (location A) where they
repeatedly retrieve the object. Next, the object is conspicuously hidden in a
different location (location B). Whereas 8- to 10-month-old infants typically
search for the object in location A, older infants typically search for the object
in location B, indicating that they were able to inhibit their habitual, prepotent
response to search for the object where it was previously retrieved
(Marcovitch & Zelazo, 2009). According to one view, this achievement is crit-
ically dependent upon infantsemerging ability to mentally represent
elements of the task at hand by reecting upon the contents of lower levels
of processing. This psychological distancing allows infants to decouple them-
selves from the stimulusresponse pattern of searching (in location A),
permitting them to selectively direct their searching to location B
(Marcovitch & Zelazo, 2009).
EF continues to improve throughout childhood and adolescence as
individuals become able to achieve increasingly higher levels of reections
of their ongoing mental activity. Developmental improvements in EF
accuracy are particularly dramatic during early childhood, when rapid
increases are observed in the highest level of consciousness that children
can experience (Zelazo, Gao, & Todd, 2007). During middle childhood,
as children gain metacognitive awareness of the effects of response speed
on performance accuracy (namely that faster responses are more likely to
be incorrect), a trade-off between speed and accuracy begins to emerge
(Best, Miller, & Jones, 2009; Davidson et al., 2006) along with overall
improvements in reaction times on EF tasks. Performance on many EF
tasks does not reach adult levels until well into adolescence, coinciding
with the rather protracted structural and functional maturation of PFC,
which supports EF (Barnea-Goraly et al., 2005; Blakemore & Choudhury,
2006; Gogtay et al., 2004).
Research with adults indicates that distinct aspects of EF are supported
by distinct regions of PFC. Specically, the capacity to inhibit oneself from
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responding impulsively and the capacity to adjust ones behavior so that
the correct course of action is selected (e.g., on conict tasks such as the
Stroop colorword task or the anker task; Gerstdat, Hong, & Diamond,
1994; Rueda et al., 2004) have distinct neural substrates (Garavan, Ross,
Murphy, Roche, & Stein, 2002). These ndings are relevant for the devel-
opment of self-regulation in two ways. First, given that distinct regions of
PFC mature at different rates (e.g., Bunge & Zelazo, 2006; Gogtay et al.,
2004), these nding suggest that subdomains of EF may follow distinct
developmental trajectories. This notion is well supported by the literature
(Best et al., 2009; Huizinga, Dolan, & van der Molen, 2006): Whereas inhib-
itory control and performance on conict tasks (requiring exible shifting of
attention to relevant task dimensions) undergo substantial developmental
improvement during early childhood (Gerstdat et al., 1994; Jacques &
Zelazo, 2001; Rueda et al., 2004), selective attention, working memory,
problem solving, and planning ability continue to improve steadily through-
out childhood and adolescence (Anderson, Anderson, Northam, Jacobs, &
Catroppa, 2001; Best et al., 2009; Huizinga et al., 2006).
Second, these ndings underscore two critical roles of the executive
in executive functioning: rst, to evaluate ones ongoing performance in
order to reign in responding when contextual cues indicate that it is neces-
sary to do so; and second, to reectively adjudicate among response
alternatives to select the appropriate course of action. Such distinctions
are helpful in understanding how different aspects of EF develop
(Garavan et al., 2002). While there is some debate concerning the under-
lying structure of EF (i.e., whether it is best characterized as a unitary or
modular function; e.g., Best et al., 2009), it is generally agreed that EF
includes at least three core skills: working memory, inhibitory control,
and cognitive exibility (e.g., Hughes, 1998; Miyake, Friedman, Emerson,
Witzki, & Howerter, 2000).
1. Working Memory
Working memory, individualscapacity to maintain and manipulate infor-
mation in short-term memory, steadily improves throughout childhood and
adolescence (Siegel & Ryan, 1989). With age, the maximum number of items
that individuals can retain (i.e., working memory capacity) steadily increases
(e.g., Klingberg, Forssberg, & Westenberg, 2002), as does their ability to
mentally manipulate information (e.g., Kwon, Reiss, & Menon, 2002). Ones
ability to maintain and manipulate information likely has critical con-
sequences for self-regulation, as appropriate regulation requires that one
reason about two or more potential response alternatives in accordance with
the parameters of the current context and knowledge about the capabilities
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and limits of the system. As such, age-related improvements in the ability to
reect upon and reason about relevant features of task performance likely
are an important factor underlying age-related improvements in self-regula-
tion (e.g., Zelazo, 2004).
2. Inhibitory Control
Inhibitory control entails the capacity to willfully withhold or suppress a
thought or action (Best et al., 2009; Paz-Alonso et al., 2009; Williams,
Ponesse, Schachar, Logan, & Tannock, 1999). This capacity is often
assessed by examining childrens ability to refrain from producing a pre-
potent response (e.g., on a go/no-go task; Thorell, Lindqvist, Nutley,
Bohlin, & Klingberg, 2009), although it is sometimes also assessed in more
emotional contexts (e.g., by examining childrens ability to refrain from
peeking at a present or their ability to suppress their disappointment in
receiving an undesirable gift; e.g., Carlson & Wang, 2007). In both types
of task, successful inhibition requires that children maintain awareness
of their ongoing performance and consciously suppress responses that
are inappropriate.
Inhibitory control develops throughout childhood and adolescence
(Best & Miller, 2010), but improvements in this capacity are particularly
dramatic during early childhood (Carlson, 2005; Carlson, Mandell, &
Williams, 2004). During this period, children also become increasingly
able to delay gratication, electing to forgo smaller immediate rewards
in order to receive larger rewards in the future. Whereas elementary
school-aged children typically make the advantageous selection,
preschoolers are less consistent in their choices, frequently succumbing
to their desire for immediate gratication over the long-term benets of
waiting (Mischel, 1974; Thompson, Barresi, & Moore, 1997).
Developmental improvement in the ability to delay gratication
appears to be dependent upon childrens ability to mentally connect their
present and future selves (Lemmon & Moore, 2007). Although children
display mirror self-recognition around 2 years of age (as indicated by pass-
ing the mirror test; Amsterdam, 1972), and some aspects of self awareness
likely emerge gradually before that (Rochat, 2004), it is not until around
age 4 that children seem to appreciate that who they are in the present
moment is the same individual who experienced past events and who will
experience future events (Moore & Lemmon, 2001; Povinelli, Landau, &
Perilloux, 1996). Thus, younger children may fail delay of gratication
tasks because they simply fail to appreciate that their actions will affect
their future (so for them, choosing an immediate reward may represent
the logical decision). As children develop the ability to represent their
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both present and future selves and to reason about the consequences of
current actions on the future self, children more consistently make the
decision that is more advantageous over the long run.
In addition to dramatic developmental differences in inhibitory control,
there are substantial individual differences in inhibitory control that are rela-
tively stable throughout early childhood, as indicated by performance on
behavioral measures and by parental reports of aspects of temperament
related to self-regulation (e.g., Carlson et al., 2004; Kochanska, Murray, &
Harlan, 2000). Moreover, it has long been known that children vary signi-
cantly in their performance on delay of gratication tasks (with individual
differences at age 4 predicting academic and social success into adolescence;
e.g., Shoda, Mischel, & Peake, 1990). The presence of systematic differences
in individualsability (or propensity) to inhibit inappropriate thoughts or
actions raises intriguing questions about whether individuals differ in their
ability to access the contentsof their mental activity and/or whether they differ
in the quality of the to-be-accessed material (i.e., whether they are actually
receiving a stronger signalto be read). Of course these alternatives are
not exclusive, and the source of differences in inhibitory control may vary.
3. Cognitive Flexibility
Although inhibitory control can be isolated in laboratory tasks, in the real
world, inhibitory control demands are often intertwined with demands for
shifting ones attention or response set to coincide with an updated context
(e.g., Bunge & Zelazo, 2006). Similar to inhibitory control, this capacity
undergoes substantial developmental improvement during early childhood.
For example, on the dimensional change card sort task, children are pres-
ented with cards varying in two dimensions (e.g., color and shape). Children
are rst asked to sort the cards by one dimension (e.g., color) and then to sort
the cards by the other dimension (e.g., shape). While most 4-year-olds typi-
cally succeed in sorting by the second dimension, the majority of 3-year-olds
usually fail to do so, persisting in sorting by the rst dimension (despite being
able to articulate the rules of the current task; Zelazo, Frye, & Rapus, 1996).
This failure appears to arise from young childrens inability to consider the
two dimensions in contradistinction (i.e., in the color game, you should sort
by color with red here and blue there, BUT in the shape game you should
sort by shape, with rabbits here and boats there), arising from limitations
in the degree of iterative self-reection that they can engage in. As children
become increasingly capable of integrating mental representations of lower-
order cognitive operations, they are increasingly able to willfully and exibly
shift their responses, overcoming their perseverative tendencies (Zelazo
et al., 2003).
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The preschool years are marked by substantial age-related
improvements in cognitive exibility, as indexed by childrens perfor-
mance on conict EF tasks (in which children must inhibit a prepotent
response and instead engage in a less automatized response; e.g., Carlson
&Moses, 2001). For example, performance on Stroop-like tasks (in which
the correct response conicts with ones natural tendency, e.g., to say
dayto a picture of a moon and to say nightto a picture of a sun)
improves signicantly between early and middle childhood (Gerstdat
et al., 1994), as does performance on Simon Says (Strommen, 1973)and
anker tasks (in which children must indicate which direction a central
arrow points, while the surrounding arrows may point in similar or oppo-
site directions; e.g., Rueda et al., 2004). As in the A-not-B task (e.g., Dia-
mond & Doar, 1989; Marcovitch & Zelazo, 1999), exible responding
requires that one reectively choose the appropriate response, rather than
reexively responding with the prepotent response.
The results of event-related potential (ERP) studies suggest that suc-
cessful performance on such tasks involves two phases: conict detection
and conict resolution (i.e., selecting the appropriate response; e.g.,
Rueda et al., 2004). ChildrensERP responses on both of these phases
are slower than adults, suggesting that developmental improvement in
exible responding in the face of conict may result from improvements
in childrens ability to detect conict and their ability to resolve conict
(by selecting the appropriate response; Rueda et al., 2004).
4. Summary
In sum, research on EF indicates that childrens ability to control their
thoughts and actions improves substantially during early childhood and
continues to improve gradually into adolescence. One approach to these
improvements suggests that they arise from age-related increases in
childrens capacity to consciously reect upon their lower-order mental
processes, affording them with the psychological distance to evaluate their
ongoing performance, adjudicate among response alternatives, and exi-
bly adapt their behavior to changing contexts.
Originating from research in cognitive neuroscience, the error monitor-
ing approach to the study of self-regulation focuses on individualsability
to monitor their performance on a task. Specically, this approach focuses
on whether individuals detect when they have committed an error and
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whether they adjust their behavior accordingly in order to improve the
accuracy of their performance on subsequent trials (e.g., Ridderinkhoff,
van den Wildenberg, Segalowitz, & Carter, 2004).
An abundance of research with adults has implicated the medial PFC
generally, and the anterior cingulate specically, as critical areas
supporting performance monitoring, response selection, and performance
adjustment (e.g., Ridderinkhoff, van den Wildenberg, et al., 2004). The
basis of performance monitoring is a topic of debate, with some con-
tending that performance monitoring is achieved via conict monitoring
(i.e., detecting when the appropriate response is not clearly apparent,
and thus, one should proceed with caution; e.g., Carter & van Veen,
2007) and others contending that performance monitoring is achieved
via outcome monitoring (i.e., evaluating whether outcomes are worse than
expected; e.g., if one has made an erroneous response, missed a response
deadline, or received negative feedback; Holroyd & Coles, 2002). How-
ever, it is generally accepted that the function of performance monitoring
operations is to alert the cognitive control system when increased control
is required to achieve acceptable performance levels (e.g., McGuire &
Botvinick, 2010; Ridderinkhof, Ullsperger, Crone, & Nieuwenhuis, 2004).
The neural hallmark of the error monitoring system is a frontally gener-
ated negative deection in the ERP waveform, termed the error-related
negativity or ERN, that is initiated at the onset of an erroneous response
and peaks about 100 ms post-response. This is sometimes followed by a
positive deection (PE) that peaks at about 500 ms post-response.
Whereas the ERN appears to be automatically generated and observed
for all errors, the amplitude of the PE predicts subsequent response
slowing and seems specically associated with errors that an individual
consciously recognizes (Nieuwenhuis, Ridderinkhof, Blom, Band, &
Kok, 2001). It has been suggested that the PE may be indicative of
individualsevaluation of the error (as its time course and topography is
similar to the P3; Overbeek, Nieuwenhuis, & Ridderinkhof, 2005).
The ERN and PE have been functionally localized to the anterior cin-
gulate cortex (ACC), a region that is ideally positioned to serve as an
interface between monitoring and control operations, as its dorsal region
has projections to areas involved in response selection and cognitive con-
trol, including the dorsolateral PFC and motor regions, and its
rostralventral region has projections to limbic structures (which may
result in negative affective reactions in response to erroneous responses;
Wiersema, van der Meere, & Roeyers, 2007,cf. the somatic marker
hypothesis; Damasio, 1996). Consistent with such a division, the ERN
has been localized to the dorsal region of ACC, while the PE has been
localized to the rostral/ventral region (Herrmann, Rommler, Ehlis,
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Heidrich, & Fallgatter, 2004; Van Boxtel, Van der Molen, & Jennings,
2005; van Veen & Carter, 2002).
Although the ERN was initially noted as occurring just before the com-
mission of an error (e.g., on a go/no-go task), it has since been shown that
the ERN also appears following negative feedback and after late
responses on tasks with a response deadlines (Holroyd & Coles, 2002).
The ERN is also observed on correct responses when trials involve a high
degree of conict (e.g., on incongruent trials on a anker task). Moreover,
the amplitude of the ERN correlates with the magnitude of the error (e.g.,
if ones response was similar versus very different from the correct
response) and error value (e.g., if one will receive a small or large penalty
for the mistake; Ridderinkhoff Ullsperger et al., 2004). Thus, this system
appears to be quite adept at evaluating the quality of ones performance
using a variety of indicators of performance acceptability.
Developmental research indicates that ERN amplitude increases with age
from at least around age 8 years through early adulthood, while PE amplitude
remains relatively age invariant (e.g., Davies, Segalowitz, & Gavin, 2004;
Wiersema et al., 2007). Further, although childrens reaction times are gener-
ally slower than adults, post-error slowing (i.e., the tendency to respond more
slowly following trials on which one has committed an error, as compared to
following trials on which one responded correctly) is relatively age invariant
between childhood and adulthood (Wiersema et al., 2007; but see also Hogan,
Vargha-Khadem, Kirkham, & Baldeweg 2005). Hence, error monitoring (i.e.,
ERN amplitude) increases with age, but self-correction in the face of errone-
ous responding remains relatively constant across age.
This curious collection of developmental ndings surrounding the ERN
has generated speculation concerning error monitoring systems and their
neural generators. One account posits that the ERN and PE may arise
from parallel error monitoring systems supported by distinct regions (with
those generating the PE maturing earlier in development than those
generating the ERN; Wiersema et al., 2007). From this perspective,
individuals monitor their performance at a relatively implicit level
(generating the ERN) as well as at more explicit level (generating the
PE). Given the neural connectivity between ACC and PFC
(Ridderinkhoff et al., 2004), implicit monitoring operations (of conict
or outcomes) could automatically signal to prefrontal structures that
enhanced cognitive control is required. This would result in enhanced per-
formance accuracy on subsequent trials, without the need for explicit
reection. That is, the system may be aware of its performance, without
the individual having access to this knowledge about the system. Con-
scious error monitoring (signied by the PE) may offer an alternative
route to self-regulation, with explicit awareness of inadequate
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performance yielding additional reasoning-based adjustments (e.g., the
implementation of strategies for increased performance accuracy).
Alternatively, this collection of ndings may be observed because the
ERN is generated as a result of neural connectivity between PFC and
ACC, rather than being generated simply from the ACC, as is commonly
believed (Luu, Tucker, Derryberry, Reed, & Poulsen, 2003). Support for
this notion comes from the ndings that patients with ACC lesions are
aware of errors but fail to produce an ERN (Stemmer, Segalowitz,
Witzke, & Schönle, 2004) and adolescents with white-matter lesions in
PFC exhibit reduced ERN amplitudes (Gehring & Knight, 2000). This
theory would also account for the nding that ERN amplitude is
associated with post-error slowing in adult populations (Ridderinkhoff
et al., 2004). From this perspective, error detection may be decoupled
from error correction, especially in young children. With increasing age,
however, the two systems may become functionally intertwined, such that
in adults, error correction more reliably follows error detection.
In addition to striking developmental differences, marked individual
differences in ERN have been noted. Higher degrees of socialization in chil-
dren (e.g., increased understanding of manners and norms for behavior) are
associated with increased ERN amplitude (Santesso, Segalowitz, & Schmidt,
2005). Increased ERN amplitude is also observed in children with anxiety
disorders compared to age-matched controls. However, no differences in
PE amplitude are observed between these groups (Ladouceur, Dahl,
Birmaher, Axelson, & Ryan, 2006; McDermott et al., 2009). ERN amplitude
is also negatively correlated with risk taking and sensation seeking in adoles-
cent males (Santesso & Segalowitz, 2009). Experimentally increasing the
stakes for erroneous responses yields increases in ERN amplitude.
Individuals high in conscientiousness are not affected by this manipulation,
however, presumably because they already exhibit high-amplitude ERNs,
even for low-consequence errors (Pailing & Segalowitz, 2004). Thus, while
children become generally more capable of monitoring their performance
on a task with increasing age, there may also be endophenotypic differences
in the degree to which individuals are neurophysiologically sensitive to
errors. Similar to inhibitory control, these differences may arise as a result
of differences in the strength of the neural signal or in individualsability
or propensity to reect upon that signal.
1. Summary
In short, the error monitoring literature offers a neural account for how
individuals are able to adaptively control their behavior by monitoring
their ongoing performance and adjusting their attentional control and
390 Kristen E. Lyons and Philip David Zelazo
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behavioral responses, based on the results of monitoring evaluations. Age-
related improvements in self-regulation are generally thought to arise
from age differences in childrens ability to monitor their performance
accuracy, consistent with the emphasis on self-reection noted in the liter-
ature on EF. However, we cannot rule out the possibility that
improvements in self-regulation might also result from age-improvements
in childrens ability to translate the results of their monitoring evaluations
into effective self-corrective adjustments.
A third literature investigating the development of self-regulation is
metacognition, or the study of how individuals monitor their ongoing
mental activity and use the results of these evaluations to guide their
subsequent cognitive or behavioral responses (Flavell, 1979; Lyons &
Ghetti, 2010; Nelson & Narens, 1990). The notion that individuals have
the capacity to evaluate their ongoing mental activity (i.e., introspection)
has a long history in psychology (as noted by James, 1890, a characteristic
quality of the mature, adult mind is that it knows what it knows).
Piaget proposed that introspective awareness of onesthoughts is an
aspect of cognitive development that appears to emerge around age 7
(Fox & Riconscente, 2008). Notably, this is approximately the same age
that Flavell and colleagues established as the age at which children
become aware of their thoughts in stream of consciousness (Flavell,
Green, & Flavell, 1995, 2000). Similarly, Vygotsky noted that childrens
awareness of their cognitions, including attention and memory, follow a
rather protracted time course (Fox & Riconscente, 2008), consistent with
the results of later research investigating childrens explicit understanding
of aspects of memory functioning. For example, children gradually come
to understand that to forget something, one must have already
remembered it, and that some types of material (such as lists organized
around a theme) are easier to remember than others (such as lists of ran-
dom items) (Kreutzer, Leonard, & Flavell, 1975).
Contemporary conceptualizations of metacognition typically distinguish
between two levels of function. The rst is the cognitive level, where basic
cognitive functions (e.g., memory, attention, learning) occur. The second
is the metacognitive level which monitors the operations occurring at the
cognitive level (i.e., metacognitive monitoring) and controls the oper-
ations occurring at the cognitive level in a top-down manner (i.e.,
metacognitive control; Nelson & Narens, 1990; Pasquali, Timmermans,
&Cleermans, 2010; Plude, Nelson, & Scholnick, 1998). Research on
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metacognition thus generally focuses on the extent to which children
maintain ongoing explicit awareness of their cognitive activities and the
role of explicit awareness of ongoing cognitive activity in guiding behav-
ioral adjustments (in contrast to the more implicit or mixed levels of mon-
itoring that are emphasized in the EF and error monitoring literatures).
1. Metacogntive Monitoring
Typically, metacognitive research involves collecting introspective
reports from individuals, for example, asking individuals to report how
certain they are about the accuracy of their response on a particular trial
or how well they have learned the items on a list of words. Metacognitive
insight is assessed by examining the degree to which participantsintro-
spective judgments correspond with their performance on the task (i.e.,
response accuracy or reaction time).
Metacognitive monitoring may take many forms depending upon the
task at hand and the individualsprogress on a task (Lyons & Ghetti,
2010). For example, a student who is studying for an exam might evaluate
how well she has mastered different aspects of the test material (i.e., a
judgment of learning;Metcalfe, 2009; e.g., How well have I learned this
material?) to decide how to allot her remaining study time. Alternatively,
a person might experience a tip of the tongue phenomenon when trying to
remember the name of a restaurant to recommend to a friend (i.e., a
feeling-of-knowing that one possesses a given piece of knowledge
although it is not immediately recallable; Hart, 1965; e.g., I know that
I know this information, but I cannot bring it to mind.). Or, a witness
to a crime might be asked how certain she is that the individual on trial
was the perpetrator that she saw commit a robbery (i.e., a condence judg-
ment;Ghetti, Lyons, Lazzarin, & Cornoldi, 2008; e.g., How sure am I that
my memory is correct?).
There is some debate concerning the source of metacognitive
judgments, namely whether they are achieved via direct access to the
actual contents of mental activity (e.g., whether condence judgments
about learning or response accuracy stem from reective evaluations of
ones knowledge) or whether metacognitive judgments correspond to
inferences based on heuristic cues concerning qualities of the cognitive
experience (Koriat, 2000; Scott & Dienes, 2010). Agrowing body of
research supports the latter point of view. For example, there is evidence
that judgments of learning are based on how uently one processes the
material being learned (Benjamin, Bjork, & Schwartz, 1998; Koriat &
Maayan, 2005; Koriat, Maayan, & Nussinson, 2006; Matvey, Dunlosky,
& Guttentag, 2001). Indeed, adultsfeeling-of-knowing judgments appear
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to be driven by the familiarity of the question being asked, rather than the
amount of information that is actually retrieved (e.g., Schwartz, 2002).
Developmental research indicates that, like adults, children base their
metacognitive judgments on heuristic cues (e.g., latency to retrieve a
response), although the magnitude of their reliance on such cues may
increase with age (Koriat & Ackerman, 2010,see also Lockl & Schneider,
2002). Hence, metacognitive judgments may be characterized as intuitive
feelings(Price & Norman, 2008) arising from subjective features of the
decision-making experience. Following William James, some researchers
have speculated that while these eeting metacognitive experiences are
clearly consciously accessible, they represent a fringe consciousness, as
the individual is implicitly aware of what they know, which gives rise to
the subjective feelings, of which they are aware. However, the individual
is not consciously aware of the knowledge that generates these feelings
(Norman, Price, & Duf, 2010). From this perspective, metacognitive
judgments may actually reect content knowledge even if the judgments
are arrived at indirectly. Consistent with this proposal, experimental stud-
ies using implicit learning paradigms suggest that differences in fringe
experiences, such as hunches about the correct response, do not simply
arise from differences in heuristic cues (e.g., familiarity). Rather, they
appear to be inuenced by individualscontent knowledge, even though
individuals cannot consciously reect upon this content (e.g., Dienes,
Altmann, Kwan, & Goode, 1995). Moreover, experiences that arise in
fringe consciousness may lead to efforts by the individual to bring the
source of these feelings into full conscious awareness, resulting in a more
analytical, rather than intuitive, form of self-reection (Norman et al.,
2010). Thus, while debate concerning the source of metacognitive
judgments is typically framed in terms of an either-or question, monitoring
of ongoing cognitive performance likely arises from evaluations at multi-
ple levels of conscious access, similar to EF and error monitoring.
Neuroimaging research with adults has begun to investigate the neural
substrates of interoception, or individualssubjective awareness of their
physiological, cognitive, or emotional states (e.g., Craig, 2002; Khalsa,
Rudrauf,Feinstein, & Tranel, 2009). This work has implicated the insula
and ACC as critical structures supporting conscious awareness of these
states. Individual differences in the size of the ACC are correlated with
introspective accuracy (Fleming, Weil, Nagy, Dolan, & Rees, 2010), and
ACC and insula activity are correlated with the strength of feeling-of-
knowing judgments (Craig, 2009). Thus, like error monitoring, inter-
oception appears to be supported by structures in medial PFC, including
the ACC.
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What neural mechanisms might underlie interoception and
metacognitive monitoring more generally? Computational modeling
suggests that by evaluating the coherence of a neural signal in response
to a query, such as a question about whether an item on a memory test
is old or new, neural systems may be able to know when they know
(Pasquali et al., 2010). One can easily see how such a mechanism may
underlie the ndings that uency and familiarity are associated with high
degrees of condence, feelings-of-knowing, and judgments of learning.
Alternatively, Craig (2002, 2009) has argued that by integrating neural
signals from all of the inputs that the body receives at a given moment,
including physiological sensations (e.g., hunger, satiation, pain), emotional
experiences (e.g., empathic concern), motor and proprioceptive
experiences (e.g., body movement), motivational sensations (e.g., reward
signals), as well as environmental input (e.g., cues concerning social or
physical risk), the insula generates a meta-representation of the global
emotional moment’” (Craig, 2009, p. 67), giving rise to a personal sense
of agency and subjective sense of knowing oneself.
Developmental research indicates that metacognitive monitoring
follows a protracted developmental time course (see Schneider & Lockl,
2002 for a review). The capacity to monitor ones cognitive operations
appears to emerge during the preschool years (Lyons & Ghetti, 2010).
Between the ages of 3 and 5 years, children begin to be able to provide
feeling-of-knowing judgments that predict their subsequent memory per-
formance (Cultice, Somerville, & Wellman, 1983) and to show conscious
awareness of comprehension failures (e.g., comprehension monitoring;
e.g., Revelle, Wellman, & Karabenick, 1985). During this period, children
also begin to be able to provide crude verbal reports of their mental activ-
ity. For example, preschoolers as young as 4 years refer to mental imagery
when describing how they make their decisions on a mental rotation task
(Estes, 1998). However, it is not until the elementary school years that
children become adept at describing the contents of their thoughts in
stream of consciousness (Flavell et al., 1995, 2000).
Throughout childhood and into early adolescence, the accuracy of
metacognitive judgments improves substantially (e.g., Roebers, 2002;
Schneider & Lockl, 2008), with childrens metacognitive reports becoming
increasingly concordant with their actual performance. This developmen-
tal improvement likely results from a number of factors, including age-
related reductions in the inuence of wishful thinking on metacognitive
reports (Schneider, 1998) and age-related increases in childrens content
knowledge that provide a more accurate foundation for assessing the qual-
ity of their performance (Kruger & Dunning, 1999). The accuracy of
metacognitive judgments also likely improves as a result of age-related
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improvements in individualsability to psychologically distance them-
selves from their ongoing mental activity, affording them with a broader
perspective of their cognitive activity and its likely outcomes (Zelazo,
2004; Zelazo et al., 2007).
2. Metacognitive Control
Of course, metacognitive insight is only useful to the extent that it can
be used to inform the control of behavior. Accordingly, much research
has investigated the mechanisms through which individuals adjust their
responses based on the self-insight gleaned via metacognitive monitoring
(Pasquali et al., 2010).
Like monitoring, metacognitive control may take many forms, depending
upon the task at hand and the resources available to the individual. Even
very young children engage in rudimentary forms of metacognitive control,
for example, by seeking information from knowledgeable adults (e.g., Cho-
uinard, 2007; Koenig & Harris, 2005) or by spending additional time playing
with toys when one cannot quickly identify their causal properties (e.g.,
Schulz & Bonawitz, 2007). With age, children become increasingly able to
engage in more advanced forms of metacognitive control, such as slowing
down their response times to avoid committing errors (Davidson et al.,
2006), refraining from answering questions that they are likely to answer
incorrectly (e.g., Koriat, Goldsmith, Schneider, & Nakash-Dura, 2001), or
providing more general rather than more specic answers to questions,
increasing the likelihood of providing the correct answer (Goldsmith,
Koriat, & Weinberg-Eliezer, 2002). Older children and adults may also
selectively allocate more attention to more difcult or relevant tasks (e.g.,
Miller, 1990) or strategically allot their remaining study time to maximize
learning (e.g., Metcalfe, 2009).
While these behaviors differ signicantly supercially, at their core, they
represent means by which individuals may strategically adjust their behavior
in order to achieve higher levels of performance accuracy. Models of meta-
cognition posit that when monitoring operations indicate that individuals
current cognitive or behavioral activity is insufcient for achieving ones
aims, control operations are engaged to ensure that goals are achieved more
effectively or efciently (e.g., Nelson & Narens, 1990). For example,
research with adults indicates that judgments of learning guide the allocation
of study time, with individuals discontinuing the study of already mastered
material and focusing their attention on the material that is most likely to
be learned in the remaining time period, such as the material that is the most
well learned but not yet mastered (Metcalfe, 2009).
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However, it has been noted that under some conditions, control can
occur in the absence of conscious monitoring (Moulin, Perfect, & Fitch,
2002). Indeed, in daily life, it is often the case that individuals seem to
automatically regulate their actions with little conscious deliberation.
Recall, however, that fringe consciousness affords individuals with implicit
awareness of their cognition, and hence the ability to selectively respond
in a manner consistent with their intuitive assessment of their ongoing
cognitive operations (Norman et al., 2010). In this manner, as in error cor-
rection, metacognitive monitoring operations might guide metacognitive
control at a relatively implicit level.
Metacognitive control develops gradually over the course of childhood.
During the preschool years, children begin to evince rudimentary control
strategies (e.g., beginning to selectively seek information from reliable
sources (Koenig & Harris, 2005)and withholding incorrect responses on
memory tests (Balcomb & Gerken, 2008)). With increasing age, children
become more adept at selectively directing their attention and study time
to the more advantageous to-be-studied materials (Metcalfe, 2009; Miller,
1990), as well as becoming increasingly well calibrated in their ability
selectively to withhold responses that are unlikely to be correct (Balcomb
& Gerken, 2008; Koriat et al., 2001).
Although little research has directly investigated the relation between
monitoring and control operations in children, it has been hypothesized
that one reason children may evince poor metacognitive control
skills is that they are challenged in translating their monitoring
evaluations into appropriate adjustments in behavior (Metcalfe, 2009;
Schneider & Lockl, 2002). In addition, age-related improvements in
metacognitive control likely arise as a function of age-related increases
in metacognitive insight as children become increasingly equipped with
the necessary self-insight to facilitate accurate and appropriate
adjustments in behavior.
3. Summary
The metacognitive approach to the study of self-control emphasizes
the role of self-reection on ones current mental activity as a motivator
for the initiation of appropriate performance adjustments. From this
perspective, age-related improvements in individualsability accurately
assess their current cognitive performance and, to adaptively alter
their subsequent cognitive or behavioral responses in accordance
with these evaluations, play a critical role in the development of
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A spin-off from the metacognitive literature with connections to
research on risk-taking and the development of reasoning, research on
uncertainty monitoring concerns individualscapacity to evaluate their
subjective sense of certainty about the likely accuracy of a response or
decision (Lyons & Ghetti, in press; Roebers, 2002). Uncertainty monitor-
ing is a core aspect of metacognition (Ghetti, Qin, & Goodman, 2002;
Howie & Roebers, 2007), but given that uncertainty is such a pervasive
feature of human existence, and because the topic has generated such a
large literature with its own paradigms and theoretical frameworks (e.g.,
Berenbaum, Bredemeier, & Thompson, 2008; Hsu, Bhatt, Adolphs,
Tranel, & Camerer, 2005; Osman, 2010), we consider this topic separately.
Uncertainty monitoring has been investigated under a number of
rubrics, including research on infantsdeveloping ability to detect
differences in the statistical regularity of events in the environment (e.g.,
Xu & Garcia, 2008)and childrens developing ability to evaluate the
conditions under which various degrees of certainty may reasonably be
inferred (e.g., Deak & Narasimham, 2003; Fay & Klahr, 1996; Pillow &
Anderson, 2006). Here, we focus on research about the development of
subjective uncertainty monitoring from a perspective that emphasizes
self-reection (e.g., Fleming et al., 2010). Stemming from the eyewitness
memory literature, the main approach used in this line of research is to
examine whether individualscondence judgments differ systematically
as a function of the accuracy of their responses (e.g., Bornstein &
Zickafoose, 1999). Although research on eyewitness memory tends to
underscore dissociations between condence and accuracy, mainstream
cognitive research with adults consistently nds that the two indices are
correlated with one another, with individuals reporting higher condence
in their accurate responses than their inaccurate responses (e.g.,
Robinson, Johnson, & Herndon, 1997). Thus, like judgments of learning
or feelings of knowing, condence judgments appear to provide a rea-
sonably accurate representation of the individualsknowledge, although
these judgments may be arrived at indirectly via monitoring of uency
or familiarity (Robinson & Johnson, 1996).
Developmental research indicates that uncertainty monitoring begins to
emergeduring the preschool years with children as young as 3 years
reporting higher condence in accurate versus inaccurate responses on
perceptual identication tasks (Lyons & Ghetti, in press;see also
Ruffman, Garnham, Import, & Connolly, 2001). By age 5 years, children
report higher condence in their responses on memory tests for words
studied with a picture (which ought to result in stronger memories) than
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for words studied without a picture (Ghetti et al., 2002). By age 5, children
also report higher condence in responses on memory tests for repeatedly
experienced versus singularly experienced events (Roberts & Powell,
2005). Throughout middle childhood, children become increasingly able
to provide condence judgments that differentiate ne-grained distinct-
ions in the strength of their memory representations (e.g., for events imag-
ined once vs. twice; Ghetti et al., 2008) and they become increasingly able
accurately to monitor their certainty under more challenging conditions,
such as when they are asked misleading questions (e.g., Howie &
Roebers, 2007; Roebers, 2002).
Recent ndings suggest that developmental changes in the ability to
monitor uncertainty may stem from age-related differences in the avail-
ability of reliable heuristic cues. For example, Koriat and colleagues
(Koriat & Ackerman, 2010)documented age-related increases between
second and fth grade in childrens reliance on response latency as a heu-
ristic for condence judgments. Response latency became an increasingly
reliable predictor of the actual accuracy of responses with increasing age,
consistent with the trend that the speed-accuracy trade-off becomes more
pronounced with age. Thus, with increasing age, children may receive
increasingly reliable signals, via fringe consciousness, as to the likely accu-
racy of their responses, perhaps as a result of age-related increases in
childrens ability iteratively to reprocess information (Zelazo, 2004;
Zelazo et al., 2007).
Developmental improvement in uncertainty monitoring may also arise
as afunction of differences in the way children of different ages respond
to and reason about the experience of subjective uncertainty. For exam-
ple, when children initially begin to experience subjective feelings of
uncertainty, they may not interpret them as such (Flavell, 2003), and thus
may not appreciate that when they feel this way, they are more likely to
provide an incorrect response. However, as children come to associate
their subjective feelings of uncertainty with higher levels of risk for the
production of incorrect responses (perhaps via the maturation of the
insula and/or age-related increases in childrens ability to concurrently
represent and reason about both subjective experiences and outcomes),
they may come to identify their feelings as indicating uncertainty, and
adjust their actions accordingly (in order to alleviate their uncertainty),
contributing to age-related improvements in self-regulation.
Awareness of subjective uncertainty (the sensation that one cannot
quickly and easily decide how to proceed) may be a highly effective self-
regulation tool. As the counterpart to uency, which is inherently pleasing
(Reber, Schwartz, & Winkielman, 2004), uncertainty is arguably an affec-
tively negative experience. As such, subjective uncertainty may serve as a
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fundamental inhibitory control mechanism, preventing individuals from
engaging in behaviors that are likely to result in negative outcomes.
Moreover, the experience associated with resolving uncertainty (e.g.,
suddenly gaining insight about the answer to a crossword clue or reading
the nal chapters of a mystery novel as the criminals are exposed)
involves a rush of clarity and uency, resulting in highly positive
sensations (Topolinski & Reber, 2010). Thus, subjective awareness of
uncertainty may not simply motivate response inhibition but may also
motivate the exible shifting of ones thoughts or actions to clarify the
uncertainty, resulting in enhanced performance accuracy (e.g., Platt &
Huettel, 2008).
1. Summary
Research on uncertainty monitoring suggests that age-related
improvements in childrens subjective awareness of their own feelings of
uncertainty have a profound impact on the development of self-regulation,
helping children to detect instances when they should proceed with caution
and providing them with the motivation to adjust their actions as necessary
to ensure adequate performance in changing contexts.
III. Integrating Disparate Literatures
Although these four lines of research have progressed relatively inde-
pendently of one another, research on EF, error monitoring, metacogni-
tion, and uncertainty monitoring (summarized in Table I)shares several
common grounds. The processes of interest appear to be supported by
overlapping neural substrates in medial PFC, including ACC and insula
(Fernandez-Duque et al., 2000; Holroyd & Coles, 2002; Lahat, Todd,
Mahy, & Zelazo, 2010; Lamm, Zelazo, & Lewis, 2006; Shimamura,
2000). Investigations rely on overlapping methodological techniques. For
example, error monitoring studies often entail recording ERPs while par-
ticipants complete anker or go/no-go (i.e., EF) tasks, and uncertainty
monitoring, error monitoring, and metacognitive investigations often col-
lect self-monitoring reports from participants. Generally, similar patterns
of development are observed across the four literatures, with substantial
developmental improvement being observed in early childhood (in EF,
metacognition, and uncertainty monitoring) and more gradual develop-
ment continuing well into adolescence (in all four arenas).
Most critically, however, all four lines of research suggest that age-
relatedimprovements in self-regulation are critically dependent upon
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age-related increase in self-reection. In the EF literature, it has been
suggested that improved self-control results from age- and experience-
related increases in childrens ability to iteratively reprocess information
at lower levels of consciousness, with increased psychological distance
affording children with the ability to select their responses exibly, rather
than being limited to stimulusresponse patterns of responding. In the
error-monitoring literature, age-increases in self-control are attributed to
the maturation of neural monitoring systems that evaluate response accu-
racy and age-related increases in connectivity between regions supporting
error detection and PFC regions supporting response selection. In the
metacognitive literature, there is evidence that self-regulation improves
as children become increasingly aware of their ongoing cognitive activity,
and increasingly able to control their thoughts and actions, based on the
results of metacognitive monitoring assessments. Finally, research on
uncertainty monitoring suggests that with age, children become increas-
ingly able to evaluate the likely outcomes of their responses, via increased
awareness of their subjective feelings of certainty, with corresponding
changes in behavior aimed at alleviating uncertainty (via inhibitory con-
trol or adjustments in responding).
IV. The Role of Self-Reection in the Development
of Self-Regulation
Taken together, these literatures suggest that developmental improvement
in self-regulation arises from two sources: (a) age-related improvements in
self-reective awareness, and (b) age-related improvements in the ability to
translate information gleaned from self-reection into appropriate behavioral
adjustments. Both of these are likely multifaceted processes occurring at
various levels of conscious awareness.
There is some evidence to suggest that, like regulation, monitoring may
shift from being externally guided (e.g., performance monitoring based on
feedback), to internally guided (e.g., based on endemic signals) (Pasquali
et al., 2010). For example, childrens learning of response contingencies is
much more disrupted by intermittently incorrect feedback than is adults
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(Eppinger, Mock, & Kray, 2009). This nding suggests that with age,
childrens neural monitoring systems may become better calibrated, per-
haps as a result of improvements in connectivity among brain regions
feeding into monitoring evaluations.
Developmental research stemming from the somatic marker hypothesis
(Damasio, 1996)is consistent with this notion. This hypothesis posits that
ventromedial PFC associates facts (i.e., environmental cues, previous
responses in a given context) with corresponding internal physiological
and emotional sensations. When the same cues are encountered at a dif-
ferent time point, the internal emotional and physiological sensations
are automatically reactivated, supporting learning about which behaviors
are advantageous and which behaviors are disadvantageous in a given
context. Research indicates that between middle childhood and adoles-
cence, skin conductance responses preceding previously punished choices
increase signicantly (as does the ability to learn about which response
options are advantageous vs. disadvantageous; Crone & Van Der Molen,
2007). Hence, with age, children may receive increasingly reliable and
potent somatic signals concerning their performance accuracy.
Such improvements in signal quality are likely also accompanied by age-
relatedimprovements in childrens ability or propensity to readthese
signals. Conceptualizations of EF in terms of increasing levels of con-
sciousness and iterative reprocessing (Zelazo, 2004; Zelazo &
Cunningham, 2007) as well as metacognition (Dienes & Perner, 2002)
posit that with age, children become increasingly able to take as the con-
tents of their mental activity the contents of lower levels of mental activity.
Hence, with increasing age, children may gain better access to information
concerning their own performance.
Of course, increased awareness may not directly translate into improved
regulation as childrens ability to use their subjective knowledge to guide
their responding also likely improves with age. In part, this may stem from
age differences in childrens understanding of the meaning of their subjec-
tive feelings. For example, as children come to appreciate the relations
between subjective feelings of uncertainty and the likelihood of commit-
ting an error, they may be more likely to adjust their behavior in the face
of uncertainty, resulting in improvements in self-regulation. From this per-
spective, age-related improvements in self-regulation may arise from
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improvements in childrens ability to reason about the appropriate way to
respond, given their current status.
Relatedly, age-related improvements in self-regulation may arise from
increases in the motivational power of self-monitoring evaluations. That
is to say, as monitoring signals become increasingly reliable, they may also
become increasingly salient, persistent forces inuencing childrens behav-
ior, directing children to adjust their behavior in order to reduce the neg-
ative affective experience associated with erroneous responses.
Finally, as children practice using self-reection to adjust their behavior
to achieve more optimal outcomes, connectivity between regions
supporting monitoring and control operations is likely to strengthen and
become more efcient, leading to an increased automatization of appro-
priate control adjustments in response to different monitoring signals.
1. Summary
Developmental differences in self-regulation likely arise as a conse-
quence of age-related changes in childrens self-reective awareness of
their ongoing task performance, and their ability to use self-insight to
implement appropriate behavioral or cognitive adjustments. This appears
to be a multifaceted process, with changes in both automatic and con-
trolled functions contributing to improvements in childrens ability to stra-
tegically regulate their own behavior.
V. Dynamic Interactions Between Automatic and
Controlled Processes in Self-Regulation
In addition to striking developmental differences in self-regulation, lon-
gitudinal research suggests that individual differences in EF and aspects of
temperament related to self-regulation are relatively stable over child-
hood (e.g., Carlson et al., 2004, Kochanska et al., 2000), raising the
intriguing question of why some individuals are better at controlling them-
selves than are others. In part, this may arise from relatively stable
differences in childrens environments. For example, recent ndings sug-
gest that parents who are generally more sensitive to their childrens
needs, providing scaffolding, appropriate pacing, and helpful feedback
that helps children to succeed on tasks, tend to have children who exhibit
better EF (Bernier, Carlson, & Whipple, 2010). From this perspective,
individuals may differ in their self-regulation ability as a result of
differences in the quality of training that self-regulatory systems receive.
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Alternatively, differences in self-regulation may arise from relatively
endemic differences in the extent to which individuals are (neurophysio-
logically and behaviorally) sensitive to errors (Rueda, Rothbart,
McCandliss, Saccomanno, & Posner, 2005). Research from the social
psychological literature indicates that tolerance of uncertainty varies
signicantly between individuals (e.g., Weary & Jacobson, 1997), and
error-monitoring research indicates that individual differences in ERN
amplitude are associated with personality in children and adolescents,
with a reduced ERN being observed in children who are poorly socialized
and adolescents who are high in risk-taking (Santesso et al., 2005). On
the opposite end of the anxiety spectrum, individuals with
obsessivecompulsive disorder and anxiety disorder, who are highly
concerned about negative outcomes, show higher ERN amplitudes than
control participants (Santesso, Segalowitz, & Schmidt, 2006). Thus, it
seems reasonable to speculate that differences in self-regulation may stem
(at least in part) from individual differences in the degree to which low-
level monitoring operations signal to the individual the need for caution.
That is to say, some individuals may simply care less about making mis-
takes, acting rather impulsively without much concern for the potentially
negative outcomes that may result from their behavior because their neu-
ral responses to risk and ambiguity may be generally dampened.
An informative new direction for future research would thus be to col-
lect an independent measure of concern for accurate performance as well
as estimates of monitoring and control ability. Results could provide
insight into the factors contributing to individual differences in self-regula-
tion, as well as how the relative contribution of these factors to self-regu-
lation changes over the course of development. For example, the
emergence of the speed-accuracy trade-off during childhood may be
attributable to age-related increases in childrens concern about commit-
ting errors.
There is a growing recognition that self-regulation always results from
dynamic interactions between top-down inuences (e.g., EF) and bot-
tom-up inuences (e.g., physiological arousal, stress, anxiety, motivation)
(Blair & Dennis, 2010; Zelazo & Cunningham, 2007). However, the inu-
ence of automatic processes on childrens self-regulation remains poorly
understood. Future research elucidating the nature of this interaction
and how it changes over the course of development will provide invalu-
able new insight into the development of self-regulation.
Finally, future research is necessary to elucidate the complex
interactions between automaticity and conscious self-monitoring. While
increases in task automaticity ought to free up resources that could be
dedicated to self-monitoring (and thus, increases in automaticity may
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generally be correlated with increased self-monitoring), if automaticity
surpasses a certain threshold, individuals may become less able or prone
to monitor themselves on the task. Thus, automaticity and monitoring
may interact in a nonlinear manner, and this relation may change
with age.
VI. Conclusions
Over the course of childhood and adolescence, individuals become
increasingly responsible for, and increasingly capable of, regulating their
own thoughts, emotions, and actions. Converging evidence from diverse
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... It is facilitating or optimizing change spontaneous thinking processes. So that they become more creative: more likely to lead to new conclusions and realizations, correcting the imagery of the mind, emphasizing spontaneous thoughts and bringing more valuable attention, relating to individual perceptions and as an important center for observing emotional awareness of the state of the body and controlling cognitive activities [56], [57]. ...
... First, the cognitive level consists of memory, attention, and learning. Second, the metacognitive level observes processes that control processes and occur at the cognitive level, awareness according to behavior [57], which can strengthen and change cognitive processes resulting from the feedback process [78], can see subjective conclusions and concrete. Also, there is a process of working levels from time to time and self-evaluation [57], [82]. ...
... Second, the metacognitive level observes processes that control processes and occur at the cognitive level, awareness according to behavior [57], which can strengthen and change cognitive processes resulting from the feedback process [78], can see subjective conclusions and concrete. Also, there is a process of working levels from time to time and self-evaluation [57], [82]. ...
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span lang="EN-US">This study aimed to observe student learning activities in terms of number material metacognition. The method is a case study qualitative research. The research subjects were 30 students of the fifth-grade elementary school in Malang. Data collection techniques use tests and interviews by carrying out three stages: planning, monitoring, and evaluation. The results showed that internal and external factors caused 75% of moderate learning difficulties. Internal factors arise due to a lack of understanding of mathematical concepts, lack of thoroughness, and interest in literacy. Meanwhile, the external media used by the teacher was deemed less supportive, and the class conditions were not conducive. Thus, there is a conclusion that internal and external factors cause students’ metacognition analysis.</span
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The BRIEF-2 ( Gioia et al., 2015 ) is a widely used questionnaire to measure daily behavior related to executive function behaviors in the home and school environment of children between 5 and 18 years old. The current study was conducted to investigate the psychometric properties of the Dutch version of the BRIEF-2 in a representative Dutch-speaking norm sample. Using methods from classical test theory and network theory, we examined the reliability and validity of the BRIEF-2. The results indicated that the BRIEF-2 can be considered as a valid and reliable questionnaire that provides information on the role of executive function in the child’s and adolescent’s functioning in the home and school environment.
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Humans have been developing and playing musical instruments for millennia. With technological advancements, instruments were becoming ever more sophisticated. In recent decades computer-supported innovations have also been introduced in hardware design, usability, and aesthetics. One of the most commonly digitally augmented instruments is the piano. Besides electronic keyboards, several prototypes augmenting pianos with different projections providing various levels of interactivity on and around the keyboard have been implemented in order to support piano players. However, it is still unclear whether these solutions support the learning process. In this paper, we present a systematic review of augmented piano prototypes focusing on instrument learning based on the four themes derived from interviews with piano experts to understand better the problems of teaching the piano. These themes are (i) synchronised movement and body posture, (ii) sight-reading, (iii) ensuring motivation, and (iv) encouraging improvisation. We found that prototypes are saturated on the synchronisation themes, and there are opportunities for sight-reading, motivation, and improvisation themes. We conclude by presenting recommendations on augmenting piano systems towards enriching the piano learning experience as well as on possible directions to expand knowledge in the area.
How does cognition develop in infants, children and adolescents? This handbook presents a cutting-edge overview of the field of cognitive development, spanning basic methodology, key domain-based findings and applications. Part One covers the neurobiological constraints and laws of brain development, while Part Two covers the fundamentals of cognitive development from birth to adulthood: object, number, categorization, reasoning, decision-making and socioemotional cognition. The final Part Three covers educational and school-learning domains, including numeracy, literacy, scientific reasoning skills, working memory and executive skills, metacognition, curiosity-driven active learning and more. Featuring chapters written by the world's leading scholars in experimental and developmental psychology, as well as in basic neurobiology, cognitive neuroscience, computational modelling and developmental robotics, this collection is the most comprehensive reference work to date on cognitive development of the twenty-first century. It will be a vital resource for scholars and graduate students in developmental psychology, neuroeducation and the cognitive sciences.
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During stressful events, we are all trying to cope. We may not be equal depending on our emotional, psychological, and mental states. During the COVID-19 pandemic, we could try to avoid negative information processing and anxiogenics content to prevent unhealthy thinking processes. One of the processes we can observe regarding our way of thinking and its impact on our psychological well-being is Metacognition. Methods: We recruited 104 outpatients in 2018. In 2020, during the pandemic, we recruited 216 outpatients and 176 healthy controls. We assessed their level of metacognition with the MCQ30 scale together with Suicidal risk and Hopelessness. Results: All three groups showed significant differences, with the nonclinical sample having higher scores in MCQ30. Regression revealed the different profiles where Hopelessness was the only predictor for the clinical sample, whereas metacognition was an adjunctive predictor of suicidal risk for the nonclinical sample. Conclusion: Our results showed that the COVID-19 crisis influenced metacognitive levels for the nonclinical sample but not for the clinical population. Moreover, Hopelessness predicted suicide risk for both populations, but Metacognition was also a predictive factor for the nonclinical sample. We conclude with the possible impact of preventive measures based on Metacognitive work that can be created out of these results.
Executive dysfunction occurs in many clinical conditions and has significant impact on multiple facets of life. This book summarizes executive function and dysfunction for practitioners, researchers and educators, covering lifespan development, assessment, impact and interventions. Drawing together clinical, neurobiological and developmental viewpoints, the authors summarize the latest research findings in practical and applied terms, and review conceptual approaches to assessing and identifying executive function and dysfunction. Several chapters are devoted to practical aspects of executive dysfunction, including research-based treatment strategies, educational implications, forensic cautions and intervention resources. Executive dysfunction in ADHD, LD, MR, autism, mood disorders, epilepsy, cancer and TBI is covered, with test performance, neuroimaging and clinical presentation for these clinical conditions. The book concludes with anticipation of future work in the field. This is a key reference for medical, psychological and educational professionals who work with children, adolescents and young adults in clinical and educational settings.
Executive dysfunction occurs in many clinical conditions and has significant impact on multiple facets of life. This book summarizes executive function and dysfunction for practitioners, researchers and educators, covering lifespan development, assessment, impact and interventions. Drawing together clinical, neurobiological and developmental viewpoints, the authors summarize the latest research findings in practical and applied terms, and review conceptual approaches to assessing and identifying executive function and dysfunction. Several chapters are devoted to practical aspects of executive dysfunction, including research-based treatment strategies, educational implications, forensic cautions and intervention resources. Executive dysfunction in ADHD, LD, MR, autism, mood disorders, epilepsy, cancer and TBI is covered, with test performance, neuroimaging and clinical presentation for these clinical conditions. The book concludes with anticipation of future work in the field. This is a key reference for medical, psychological and educational professionals who work with children, adolescents and young adults in clinical and educational settings.
Executive dysfunction occurs in many clinical conditions and has significant impact on multiple facets of life. This book summarizes executive function and dysfunction for practitioners, researchers and educators, covering lifespan development, assessment, impact and interventions. Drawing together clinical, neurobiological and developmental viewpoints, the authors summarize the latest research findings in practical and applied terms, and review conceptual approaches to assessing and identifying executive function and dysfunction. Several chapters are devoted to practical aspects of executive dysfunction, including research-based treatment strategies, educational implications, forensic cautions and intervention resources. Executive dysfunction in ADHD, LD, MR, autism, mood disorders, epilepsy, cancer and TBI is covered, with test performance, neuroimaging and clinical presentation for these clinical conditions. The book concludes with anticipation of future work in the field. This is a key reference for medical, psychological and educational professionals who work with children, adolescents and young adults in clinical and educational settings.
Executive dysfunction occurs in many clinical conditions and has significant impact on multiple facets of life. This book summarizes executive function and dysfunction for practitioners, researchers and educators, covering lifespan development, assessment, impact and interventions. Drawing together clinical, neurobiological and developmental viewpoints, the authors summarize the latest research findings in practical and applied terms, and review conceptual approaches to assessing and identifying executive function and dysfunction. Several chapters are devoted to practical aspects of executive dysfunction, including research-based treatment strategies, educational implications, forensic cautions and intervention resources. Executive dysfunction in ADHD, LD, MR, autism, mood disorders, epilepsy, cancer and TBI is covered, with test performance, neuroimaging and clinical presentation for these clinical conditions. The book concludes with anticipation of future work in the field. This is a key reference for medical, psychological and educational professionals who work with children, adolescents and young adults in clinical and educational settings.
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The course, antecedents, and implications for social development of effortful control were examined in this comprehensive longitudinal study. Behavioral multitask batteries and parental ratings assessed effortful control at 22 and 33 months (N = 106). Effortful control functions encompassed delaying, slowing down motor activity, suppressing/initiating activity to signal, effortful attention, and lowering voice. Between 22 and 33 months, effortful control improved considerably, its coherence increased, it was stable, and it was higher for girls. Behavioral and parent-rated measures converged. Children's focused attention at 9 months, mothers' responsiveness at 22 months, and mothers' self-reported socialization level all predicted children's greater effortful control. Effortful control had implications for concurrent social development. Greater effortful control at 22 months was linked to more regulated anger, and at 33 months, to more regulated anger and joy and to stronger restraint.
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The experiments address the degree to which retrieval fluency—the ease with which information is accessed from long-term memory—guides and occasionally misleads metamnemonic judgments. In each of 3 experiments, participants' predictions of their own future recall performance were examined under conditions in which probability or speed of retrieval at one time or on one task is known to be negatively related to retrieval probability on a later task. Participants' predictions reflected retrieval fluency on the initial task in each case, which led to striking mismatches between their predicted and actual performance on the later tasks. The results suggest that retrieval fluency is a potent but not necessarily reliable source of information for metacognitive judgments. Aspects of the results suggest that a basis on which better and poorer rememberers differ is the degree to which certain memory dynamics are understood, such as the fleeting nature of recency effects and the consequences of an initial retrieval. The results have pedagogical as well as theoretical implications, particularly with respect to the education of subjective assessments of ongoing learning.
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The authors investigate reaction time, subjective assessments of memory processing, and confidence as predictors of memory for the details of a crime. The authors also examine the mediation of a previously identified difference between recognition tasks and recall tasks in the correlation between confidence and accuracy. College undergraduates (n = 111) answered either recognition or recall questions. Reaction time and subjective assessments of cognitive effort were both negatively related to confidence and accuracy. Subjective assessments, however, were superior predictors of confidence, whereas reaction time was a unique predictor of accuracy. The reaction time–confidence and reaction time–accuracy correlations were stronger under recall conditions than under recognition conditions. Multiple regression results suggested a possible explanation for the superior insight of recall participants into memory accuracy.
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The stop-signal procedure was used to examine the development of inhibitory control. A group of 275 participants, 6 to 81 years of age, performed a visual choice reaction time (go) task and attempted to inhibit their responses to the go task when they heard a stop signal. Reaction times to the stop and go signals were used to assess performance in inhibition and response execution, respectively. Results indicated the speed of stopping becomes faster with increasing age throughout childhood, with limited evidence of slowing across adulthood. By contrast, strong evidence was obtained for age-related speeding of go-signal reaction time throughout childhood, followed by marked slowing throughout adulthood. Hierarchical regression confirmed that the age-related change in inhibitory control could not be explained by general speeding or slowing of responses. Findings are discussed in regard to the contrast between the development of inhibition and response execution and the utility of the stop-signal procedure.
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The criteria by which incidentally acquired knowledge of an artificial grammar (A. S. Reber, 1967) could be unconscious was explored in 5 experiments. Participants trained on an artificial grammar lacked metaknowledge of their knowledge: Participants classified substantially above chance even when they believed that they were literally guessing, and, under some conditions, participants’ confidence in incorrect decisions was just as great as their confidence in correct decisions. However, participants had a large degree of strategic control over their knowledge: Participants trained on 2 grammars could decide which grammar to apply in a test phase, and there was no detectable tendency for participants to apply the other grammar.
There is a growing theoretical and practical interest in the topic of metacognition; how we monitor and control our mental processes. Applied Metacognition provides a coherent and up-to-date overview of the relation between theories in metacognition and their application in real-world situations. As well as a theoretical overview, there are substantive chapters covering metacognition in three areas of application: metacognition in education, metacognition in everyday life memory and metacognition in different populations. A diverse range of topics are covered such as how we judge our own learning, why we create false beliefs about our past, how children learn to monitor and control their memory, how well eyewitnesses can judge the accuracy of their own memories and how memory judgements change across the lifespan. The book has contributions from many of the leading researchers in metacognition from around the world.
Researchers aiming to explain the episodic memory deficit in Alzheimer’s disease have occasionally adopted a metacognitive framework to examine the role of memory monitoring as a possible contributory factor. In this chapter we briefly review the results of research into metacognition in Alzheimer’s disease — with particular focus on item repetition. Here we consider what the study of Alzheimer’s disease (AD) can contribute to our understanding of the bases on which metacognitive judgements are made. In particular, we concentrate on the cue utilisation approach (Koriat, 1997), describing work that suggests a dissociation between the mnemonic bases of metamemory control and metamemory monitoring during encoding. We present novel empirical data that examines the nature of metamemory monitoring at encoding for repeated items using a Judgement of Learning procedure (JOL). We find that a) in an AD group we can dissociate metamemory monitoring and control for repeatedly presented items and b) there is evidence that the ability to make JOLs that are sensitive to repetition of items is related to the awareness of repetition.