the role of metacognition in critical thinking and problem solving

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• Published: 08 June 2021

Metacognition: ideas and insights from neuro- and educational sciences

• Damien S. Fleur   ORCID: orcid.org/0000-0003-4836-5255 1 , 2 ,
• Bert Bredeweg   ORCID: orcid.org/0000-0002-5281-2786 1 , 3 &
• Wouter van den Bos 2 , 4  

npj Science of Learning volume  6 , Article number:  13 ( 2021 ) Cite this article

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Metacognition comprises both the ability to be aware of one’s cognitive processes (metacognitive knowledge) and to regulate them (metacognitive control). Research in educational sciences has amassed a large body of evidence on the importance of metacognition in learning and academic achievement. More recently, metacognition has been studied from experimental and cognitive neuroscience perspectives. This research has started to identify brain regions that encode metacognitive processes. However, the educational and neuroscience disciplines have largely developed separately with little exchange and communication. In this article, we review the literature on metacognition in educational and cognitive neuroscience and identify entry points for synthesis. We argue that to improve our understanding of metacognition, future research needs to (i) investigate the degree to which different protocols relate to the similar or different metacognitive constructs and processes, (ii) implement experiments to identify neural substrates necessary for metacognition based on protocols used in educational sciences, (iii) study the effects of training metacognitive knowledge in the brain, and (iv) perform developmental research in the metacognitive brain and compare it with the existing developmental literature from educational sciences regarding the domain-generality of metacognition.

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Introduction

Metacognition is defined as “thinking about thinking” or the ability to monitor and control one’s cognitive processes 1 and plays an important role in learning and education 2 , 3 , 4 . For instance, high performers tend to present better metacognitive abilities (especially control) than low performers in diverse educational activities 5 , 6 , 7 , 8 , 9 . Recently, there has been a lot of progress in studying the neural mechanisms of metacognition 10 , 11 , yet it is unclear at this point how these results may inform educational sciences or interventions. Given the potential benefits of metacognition, it is important to get a better understanding of how metacognition works and of how training can be useful.

The interest in bridging cognitive neuroscience and educational practices has increased in the past two decades, spanning a large number of studies grouped under the umbrella term of educational neuroscience 12 , 13 , 14 . With it, researchers have brought forward issues that are viewed as critical for the discipline to improve education. Recurring issues that may impede the relevance of neural insights for educational practices concern external validity 15 , 16 , theoretical discrepancies 17 and differences in terms of the domains of (meta)cognition operationalised (specific or general) 15 . This is important because, in recent years, brain research is starting to orient itself towards training metacognitive abilities that would translate into real-life benefits. However, direct links between metacognition in the brain and metacognition in domains such as education have still to be made. As for educational sciences, a large body of literature on metacognitive training is available, yet we still need clear insights about what works and why. While studies suggest that training metacognitive abilities results in higher academic achievement 18 , other interventions show mixed results 19 , 20 . Moreover, little is known about the long-term effects of, or transfer effects, of these interventions. A better understanding of the cognitive processes involved in metacognition and how they are expressed in the brain may provide insights in these regards.

Within cognitive neuroscience, there has been a long tradition of studying executive functions (EF), which are closely related to metacognitive processes 21 . Similar to metacognition, EF shows a positive relationship with learning at school. For instance, performance in laboratory tasks involving error monitoring, inhibition and working memory (i.e. processes that monitor and regulate cognition) are associated with academic achievement in pre-school children 22 . More recently, researchers have studied metacognition in terms of introspective judgements about performance in a task 10 . Although the neural correlates of such behaviour are being revealed 10 , 11 , little is known about how behaviour during such tasks relates to academic achievement.

Educational and cognitive neuroscientists study metacognition in different contexts using different methods. Indeed, while the latter investigate metacognition via behavioural task, the former mainly rely on introspective questionnaires. The extent to which these different operationalisations of metacognition match and reflect the same processes is unclear. As a result, the external validity of methodologies used in cognitive neuroscience is also unclear 16 . We argue that neurocognitive research on metacognition has a lot of potential to provide insights in mechanisms relevant in educational contexts, and that theoretical and methodological exchange between the two disciplines can benefit neuroscientific research in terms of ecological validity.

For these reasons, we investigate the literature through the lenses of external validity, theoretical discrepancies, domain generality and metacognitive training. Research on metacognition in cognitive neuroscience and educational sciences are reviewed separately. First, we investigate how metacognition is operationalised with respect to the common framework introduced by Nelson and Narens 23 (see Fig. 1 ). We then discuss the existing body of evidence regarding metacognitive training. Finally, we compare findings in both fields, highlight gaps and shortcomings, and propose avenues for research relying on crossovers of the two disciplines.

Meta-knowledge is characterised as the upward flow from object-level to meta-level. Meta-control is characterised as the downward flow from meta-level to object-level. Metacognition is therefore conceptualised as the bottom-up monitoring and top-down control of object-level processes. Adapted from Nelson and Narens’ cognitive psychology model of metacognition 23 .

In cognitive neuroscience, metacognition is divided into two main components 5 , 24 , which originate from the seminal works of Flavell on metamemory 25 , 26 . First, metacognitive knowledge (henceforth, meta-knowledge) is defined as the knowledge individuals have of their own cognitive processes and their ability to monitor and reflect on them. Second, metacognitive control (henceforth, meta-control) consists of someone’s self-regulatory mechanisms, such as planning and adapting behaviour based on outcomes 5 , 27 . Following Nelson and Narens’ definition 23 , meta-knowledge is characterised as the flow and processing of information from the object level to the meta-level, and meta-control as the flow from the meta-level to the object level 28 , 29 , 30 (Fig. 1 ). The object-level encompasses cognitive functions such as recognition and discrimination of objects, decision-making, semantic encoding, and spatial representation. On the meta-level, information originating from the object level is processed and top-down regulation on object-level functions is imposed 28 , 29 , 30 .

Educational researchers have mainly investigated metacognition through the lens of Self-Regulated Learning theory (SRL) 3 , 4 , which shares common conceptual roots with the theoretical framework used in cognitive neuroscience but varies from it in several ways 31 . First, SRL is constrained to learning activities, usually within educational settings. Second, metacognition is merely one of three components, with “motivation to learn” and “behavioural processes”, that enable individuals to learn in a self-directed manner 3 . In SRL, metacognition is defined as setting goals, planning, organising, self-monitoring and self-evaluating “at various points during the acquisition” 3 . The distinction between meta-knowledge and meta-control is not formally laid down although reference is often made to a “self-oriented feedback loop” describing the relationship between reflecting and regulating processes that resembles Nelson and Narens’ model (Fig. 1 ) 3 , 23 . In order to facilitate the comparison of operational definitions, we will refer to meta-knowledge in educational sciences when protocols operationalise self-awareness and knowledge of strategies, and to meta-control when they operationalise the selection and use of learning strategies and planning. For an in-depth discussion on metacognition and SRL, we refer to Dinsmore et al. 31 .

Metacognition in cognitive neuroscience

Operational definitions.

In cognitive neuroscience, research in metacognition is split into two tracks 32 . One track mainly studies meta-knowledge by investigating the neural basis of introspective judgements about one’s own cognition (i.e., metacognitive judgements), and meta-control with experiments involving cognitive offloading. In these experiments, subjects can perform actions such as set reminders, making notes and delegating tasks 33 , 34 , or report their desire for them 35 . Some research has investigated how metacognitive judgements can influence subsequent cognitive behaviour (i.e., a downward stream from the meta-level to the object level), but only one study so far has explored how this relationship is mapped in the brain 35 . In the other track, researchers investigate EF, also referred to as cognitive control 30 , 36 , which is closely related to metacognition. Note however that EF are often not framed in metacognitive terms in the literature 37 (but see ref. 30 ). For the sake of concision, we limit our review to operational definitions that have been used in neuroscientific studies.

Metacognitive judgements

Cognitive neuroscientists have been using paradigms in which subjects make judgements on how confident they are with regards to their learning of some given material 10 . These judgements are commonly referred to as metacognitive judgements , which can be viewed as a form of meta-knowledge (for reviews see Schwartz 38 and Nelson 39 ). Historically, researchers mostly resorted to paradigms known as Feelings of Knowing (FOK) 40 and Judgements of Learning (JOL) 41 . FOK reflect the belief of a subject to knowing the answer to a question or a problem and being able to recognise it from a list of alternatives, despite being unable to explicitly recall it 40 . Here, metacognitive judgement is thus made after retrieval attempt. In contrast, JOL are prospective judgements during learning of one’s ability to successfully recall an item on subsequent testing 41 .

More recently, cognitive neuroscientists have used paradigms in which subjects make retrospective metacognitive judgements on their performance in a two-alternative Forced Choice task (2-AFC) 42 . In 2-AFCs, subjects are asked to choose which of two presented options has the highest criterion value. Different domains can be involved, such as perception (e.g., visual or auditory) and memory. For example, subjects may be instructed to visually discriminate which one of two boxes contains more dots 43 , identify higher contrast Gabor patches 44 , or recognise novel words from words that were previously learned 45 (Fig. 2 ). The subjects engage in metacognitive judgements by rating how confident they are relative to their decision in the task. Based on their responses, one can evaluate a subject’s metacognitive sensitivity (the ability to discriminate one’s own correct and incorrect judgements), metacognitive bias (the overall level of confidence during a task), and metacognitive efficiency (the level of metacognitive sensitivity when controlling for task performance 46 ; Fig. 3 ). Note that sensitivity and bias are independent aspects of metacognition, meaning that two subjects may display the same levels of metacognitive sensitivity, but one may be biased towards high confidence while the other is biased towards low confidence. Because metacognitive sensitivity is affected by the difficulty of the task (one subject tends to display greater metacognitive sensitivity in easy tasks than difficult ones and different subjects may find a task more or less easy), metacognitive efficiency is an important measure as it allows researchers to compare metacognitive abilities between subjects and between domains. The most commonly used methods to assess metacognitive sensitivity during retrospective judgements are the receiver operating curve (ROC) and meta- d ′. 46 Both derive from signal detection theory (SDT) 47 which allows Type 1 sensitivity, or d’ ′ (how a subject can discriminate between stimulus alternatives, i.e. object-level processes) to be differentiated from metacognitive sensitivity (a judgement on the correctness of this decision) 48 . Importantly, only comparing meta- d ′ to d ′ seems to give reliable assessments metacognitive efficiency 49 . A ratio of 1 between meta- d’ ′ and d’ ′, indicates that a subject was perfectly able to discriminate between their correct and incorrect judgements. A ratio of 0.8 suggests that 80% of the task-related sensory evidence was available for the metacognitive judgements. Table 1 provides an overview of the different types of tasks and protocols with regards to the type of metacognitive process they operationalise. These operationalisations of meta-knowledge are used in combination with brain imaging methods (functional and structural magnetic resonance imaging; fMRI; MRI) to identify brain regions associated with metacognitive activity and metacognitive abilities 10 , 50 . Alternatively, transcranial magnetic stimulation (TMS) can be used to temporarily deactivate chosen brain regions and test whether this affects metacognitive abilities in given tasks 51 , 52 .

a Visual perception task: subjects choose the box containing the most (randomly generated) dots. Subjects then rate their confidence in their decision. b Memory task: subjects learn a list of words. In the next screen, they have to identify which of two words shown was present on the list. The subjects then rate their confidence in their decision.

The red and blue curves represent the distribution of confidence ratings for incorrect and correct trials, respectively. A larger distance between the two curves denotes higher sensitivity. Displacement to the left and right denote biases towards low confidence (low metacognitive bias) and high confidence (high metacognitive bias), respectively (retrieved from Fig. 1 in Fleming and Lau 46 ). We repeat the disclaimer of the original authors that this figure is not a statistically accurate description of correct and incorrect responses, which are typically not normally distributed 46 , 47 .

A recent meta-analysis analysed 47 neuroimaging studies on metacognition and identified a domain-general network associated with high vs. low confidence ratings in both decision-making tasks (perception 2-AFC) and memory tasks (JOL, FOK) 11 . This network includes the medial and lateral prefrontal cortex (mPFC and lPFC, respectively), precuneus and insula. In contrast, the right anterior dorsolateral PFC (dlPFC) was specifically involved in decision-making tasks, and the bilateral parahippocampal cortex was specific to memory tasks. In addition, prospective judgements were associated with the posterior mPFC, left dlPFC and right insula, whereas retrospective judgements were associated with bilateral parahippocampal cortex and left inferior frontal gyrus. Finally, emerging evidence suggests a role of the right rostrolateral PFC (rlPFC) 53 , 54 , anterior PFC (aPFC) 44 , 45 , 55 , 56 , dorsal anterior cingulate cortex (dACC) 54 , 55 and precuneus 45 , 55 in metacognitive sensitivity (meta- d ′, ROC). In addition, several studies suggest that the aPFC relates to metacognition specifically in perception-related 2-AFC tasks, whereas the precuneus is engaged specifically in memory-related 2-AFC tasks 45 , 55 , 56 . This may suggest that metacognitive processes engage some regions in a domain-specific manner, while other regions are domain-general. For educational scientists, this could mean that some domains of metacognition may be more relevant for learning and, granted sufficient plasticity of the associated brain regions, that targeting them during interventions may show more substantial benefits. Note that rating one’s confidence and metacognitive sensitivity likely involve additional, peripheral cognitive processes instead of purely metacognitive ones. These regions are therefore associated with metacognition but not uniquely per se. Notably, a recent meta-analysis 50 suggests that domain-specific and domain-general signals may rather share common circuitry, but that their neural signature varies depending on the type of task or activity, showing that domain-generality in metacognition is complex and still needs to be better understood.

In terms of the role of metacognitive judgements on future behaviour, one study found that brain patterns associated with the desire for cognitive offloading (i.e., meta-control) partially overlap with those associated with meta-knowledge (metacognitive judgements of confidence), suggesting that meta-control is driven by either non-metacognitive, in addition to metacognitive, processes or by a combination of different domain-specific meta-knowledge processes 35 .

Executive function

In EF, processes such as error detection/monitoring and effort monitoring can be related to meta-knowledge while error correction, inhibitory control, and resource allocation can be related to meta-control 36 . To activate these processes, participants are asked to perform tasks in laboratory settings such as Flanker tasks, Stroop tasks, Demand Selection tasks and Motion Discrimination tasks (Fig. 4 ). Neural correlates of EF are investigated by having subjects perform such tasks while their brain activity is recorded with fMRI or electroencephalography (EEG). Additionally, patients with brain lesions can be tested against healthy participants to evaluate the functional role of the impaired regions 57 .

a Flanker task: subjects indicate the direction to which the arrow in the middle points. b Stroop task: subjects are presented with the name of colour printed in a colour that either matches or mismatches the name. Subjects are asked to give the name of the written colour or the printed colour. c Motion Discrimination task: subjects have to determine in which direction the dots are going with variating levels of noise. d Example of a Demand Selection task: in both options subjects have to switch between two tasks. Task one, subjects determine whether the number shown is higher or lower than 5. Task two, subjects determine whether the number is odd or even. The two options (low and high demand) differ in their degree of task switching, meaning the effort required. Subjects are allowed to switch between the two options. Note, the type of task is solely indicated by the colour of the number and that the subjects are not explicitly told about the difference in effort between the two options (retrieved from Fig. 1c in Froböse et al. 58 ).

In a review article on the neural basis of EF (in which they are defined as meta-control), Shimamura argues that a network of regions composed of the aPFC, ACC, ventrolateral PFC (vlPFC) and dlPFC is involved in the regulations of cognition 30 . These regions are not only interconnected but are also intricately connected to cortical and subcortical regions outside of the PFC. The vlPFC was shown to play an important role in “selecting and maintaining information in working memory”, whereas the dlPFC is involved in “manipulating and updating information in working memory” 30 . The ACC has been proposed to monitor cognitive conflict (e.g. in a Stroop task or a Flanker task), and the dlPFC to regulate it 58 , 59 . In particular, activity in the ACC in conflict monitoring (meta-knowledge) seems to contribute to control of cognition (meta-control) in the dlPFC 60 , 61 and to “bias behavioural decision-making toward cognitively efficient tasks and strategies” (p. 356) 62 . In a recent fMRI study, subjects performed a motion discrimination task (Fig. 4c ) 63 . After deciding on the direction of the motion, they were presented additional motion (i.e. post-decisional evidence) and then were asked to rate their confidence in their initial choice. The post-decisional evidence was encoded in the activity of the posterior medial frontal cortex (pMFC; meta-knowledge), while lateral aPFC (meta-control) modulated the impact of this evidence on subsequent confidence rating 63 . Finally, results from a meta-analysis study on cognitive control identified functional connectivity between the pMFC, associated with monitoring and informing other regions about the need for regulation, and the lPFC that would effectively regulate cognition 64 .

Online vs. offline metacognition

While the processes engaged during tasks such as those used in EF research can be considered as metacognitive in the sense that they are higher-order functions that monitor and control lower cognitive processes, scientists have argued that they are not functionally equivalent to metacognitive judgements 10 , 11 , 65 , 66 . Indeed, engaging in metacognitive judgements requires subjects to reflect on past or future activities. As such, metacognitive judgements can be considered as offline metacognitive processes. In contrast, high-order processes involved in decision-making tasks such as used in EF research are arguably largely made on the fly, or online , at a rapid pace and subjects do not need to reflect on their actions to perform them. Hence, we propose to explicitly distinguish online and offline processes. Other researchers have shared a similar view and some have proposed models for metacognition that make similar distinctions 65 , 66 , 67 , 68 . The functional difference between online and offline metacognition is supported by some evidence. For instance, event-related brain potential (ERP) studies suggest that error negativities are associated with error detection in general, whereas an increased error positivity specifically encodes error that subjects could report upon 69 , 70 . Furthermore, brain-imaging studies suggest that the MFC and ACC are involved in online meta-knowledge, while the aPFC and lPFC seem to be activated when subjects engage in more offline meta-knowledge and meta-control, respectively 63 , 71 , 72 . An overview of the different tasks can be found in Table 1 and a list of different studies on metacognition can be found in Supplementary Table 1 (organised in terms of the type of processes investigated, the protocols and brain measures used, along with the brain regions identified). Figure 5 illustrates the different brain regions associated with meta-knowledge and meta-control, distinguishing between what we consider to be online and offline processes. This distinction is often not made explicitly but it will be specifically helpful when building bridges between cognitive neuroscience and educational sciences.

The regions are divided into online meta-knowledge and meta-control, and offline meta-knowledge and meta-control following the distinctions introduced earlier. Some regions have been reported to be related to both offline and online processes and are therefore given a striped pattern.

Training metacognition

There are extensive accounts in the literature of efforts to improve EF components such as inhibitory control, attention shifting and working memory 22 . While working memory does not directly reflect metacognitive abilities, its training is often hypothesised to improve general cognitive abilities and academic achievement. However, most meta-analyses found that training methods lead only to weak, non-lasting effects on cognitive control 73 , 74 , 75 . One meta-analysis did find evidence of near-transfer following EF training in children (in particular working memory, inhibitory control and cognitive flexibility), but found no evidence of far-transfer 20 . According to this study, training on one component leads to improved abilities in that same component but not in other EF components. Regarding adults, however, one meta-analysis suggests that EF training in general and working memory training specifically may both lead to significant near- and far-transfer effects 76 . On a neural level, a meta-analysis showed that cognitive training resulted in decreased brain activity in brain regions associated with EF 77 . According to the authors, this indicates that “training interventions reduce demands on externally focused attention” (p. 193) 77 .

With regards to meta-knowledge, several studies have reported increased task-related metacognitive abilities after training. For example, researchers found that subjects who received feedback on their metacognitive judgements regarding a perceptual decision-making task displayed better metacognitive accuracy, not only in the trained task but also in an untrained memory task 78 . Related, Baird and colleagues 79 found that a two-week mindfulness meditation training lead to enhanced meta-knowledge in the memory domain, but not the perceptual domain. The authors link these results to evidence of increased grey matter density in the aPFC in meditation practitioners.

Research on metacognition in cognitive science has mainly been studied through the lens of metacognitive judgements and EF (specifically performance monitoring and cognitive control). Meta-knowledge is commonly activated in subjects by asking them to rate their confidence in having successfully performed a task. A distinction is made between metacognitive sensitivity, metacognitive bias and metacognitive efficacy. Monitoring and regulating processes in EF are mainly operationalised with behavioural tasks such as Flanker tasks, Stroop tasks, Motion Discrimination tasks and Demand Selection tasks. In addition, metacognitive judgements can be viewed as offline processes in that they require the subject to reflect on her cognition and develop meta-representations. In contrast, EF can be considered as mostly online metacognitive processes because monitoring and regulation mostly happen rapidly without the need for reflective thinking.

Although there is some evidence for domain specificity, other studies have suggested that there is a single network of regions involved in all meta-cognitive tasks, but differentially activated in different task contexts. Comparing research on meta-knowledge and meta-control also suggest that some regions play a crucial role in both knowledge and regulation (Fig. 5 ). We have also identified a specific set of regions that are involved in either offline or online meta-knowledge. The evidence in favour of metacognitive training, while mixed, is interesting. In particular, research on offline meta-knowledge training involving self-reflection and metacognitive accuracy has shown some promising results. The regions that show structural changes after training, were those that we earlier identified as being part of the metacognition network. EF training does seem to show far-transfer effects at least in adults, but the relevance for everyday life activity is still unclear.

One major limitation of current research in metacognition is ecological validity. It is unclear to what extent the operationalisations reviewed above reflect real-life metacognition. For instance, are people who can accurately judge their performance on a behavioural task also able to accurately assess how they performed during an exam? Are people with high levels of error regulation and inhibitory control able to learn more efficiently? Note that criticism on the ecological validity of neurocognitive operationalisations extends beyond metacognition research 16 . A solution for improving validity may be to compare operationalisations of metacognition in cognitive neuroscience with the ones in educational sciences, which have shown clear links with learning in formal education. This also applies to metacognitive training.

Metacognition in educational sciences

The most popular protocols used to measure metacognition in educational sciences are self-report questionnaires or interviews, learning journals and thinking-aloud protocols 31 , 80 . During interviews, subjects are asked to answer questions regarding hypothetical situations 81 . In learning journals, students write about their learning experience and their thoughts on learning 82 , 83 . In thinking-aloud protocols, subjects are asked to verbalise their thoughts while performing a problem-solving task 80 . Each of these instruments can be used to study meta-knowledge and meta-control. For instance, one of the most widely used questionnaires, the Metacognitive Awareness Inventory (MAI) 42 , operationalises “Flavellian” metacognition and has dedicated scales for meta-knowledge and meta-control (also popular are the MSLQ 84 and LASSI 85 which operate under SRL). The meta-knowledge scale of the MAI operationalises knowledge of strategies (e.g., “ I am aware of what strategies I use when I study ”) and self-awareness (e.g., “ I am a good judge of how well I understand something ”); the meta-control scale operationalises planning (e.g., “ I set a goal before I begin a task ”) and use of learning strategies (e.g., “ I summarize what I’ve learned after I finish ”). Learning journals, self-report questionnaires and interviews involve offline metacognition. Thinking aloud, though not engaging the same degree self-reflection, also involves offline metacognition in the sense that online processes are verbalised, which necessitate offline processing (see Table 1 for an overview and Supplementary Table 2 for more details).

More recently, methodologies borrowed from cognitive neuroscience have been introduced to study EF in educational settings 22 , 86 . In particular, researchers used classic cognitive control tasks such as the Stroop task (for a meta-analysis 86 ). Most of the studied components are related to meta-control and not meta-knowledge. For instance, the BRIEF 87 is a questionnaire completed by parents and teachers which assesses different subdomains of EF: (1) inhibition, shifting, and emotional control which can be viewed as online metacognitive control, and (2) planning, organisation of materials, and monitoring, which can be viewed as offline meta-control 87 .

Assessment of metacognition is usually compared against metrics of academic performance such as grades or scores on designated tasks. A recent meta-analysis reported a weak correlation of self-report questionnaires and interviews with academic performance whereas think-aloud protocols correlated highly 88 . Offline meta-knowledge processes operationalised by learning journals were found to be positively associated with academic achievement when related to reflection on learning activities but negatively associated when related to reflection on learning materials, indicating that the type of reflection is important 89 . EF have been associated with abilities in mathematics (mainly) and reading comprehension 86 . However, the literature points towards contrary directions as to what specific EF component is involved in academic achievement. This may be due to the different groups that were studied, to different operationalisations or to different theoretical underpinnings for EF 86 . For instance, online and offline metacognitive processes, which are not systematically distinguished in the literature, may play different roles in academic achievement. Moreover, the bulk of research focussed on young children with few studies on adolescents 86 and EF may play a role at varying extents at different stages of life.

A critical question in educational sciences is that of the nature of the relationship between metacognition and academic achievement to understand whether learning at school can be enhanced by training metacognitive abilities. Does higher metacognition lead to higher academic achievement? Do these features evolve in parallel? Developmental research provides valuable insights into the formation of metacognitive abilities that can inform training designs in terms of what aspect of metacognition should be supported and the age at which interventions may yield the best results. First, meta-knowledge seems to emerge around the age of 5, meta-control around 8, and both develop over the years 90 , with evidence for the development of meta-knowledge into adolescence 91 . Furthermore, current theories propose that meta-knowledge abilities are initially highly domain-dependent and gradually become more domain-independent as knowledge and experience are acquired and linked between domains 32 . Meta-control is believed to evolve in a similar fashion 90 , 92 .

Common methods used to train offline metacognition are direct instruction of metacognition, metacognitive prompts and learning journals. In addition, research has been done on the use of (self-directed) feedback as a means to induce self-reflection in students, mainly in computer-supported settings 93 . Interestingly, learning journals appear to be used for both assessing and fostering metacognition. Metacognitive instruction consists of teaching learners’ strategies to “activate” their metacognition. Metacognitive prompts most often consist of text pieces that are sent at specific times and that trigger reflection (offline meta-knowledge) on learning behaviour in the form of a question, hint or reminder.

Meta-analyses have investigated the effects of direct metacognitive instruction on students’ use of learning strategies and academic outcomes 18 , 94 , 95 . Their findings show that metacognitive instruction can have a positive effect on learning abilities and achievement within a population ranging from primary schoolers to university students. In particular, interventions lead to the highest effect sizes when they both (i) instructed a combination of metacognitive strategies with an emphasis on planning strategies (offline meta-control) and (ii) “provided students with knowledge about strategies” (offline meta-knowledge) and “illustrated the benefits of applying the trained strategies, or even stimulated metacognitive reasoning” (p.114) 18 . The longer the duration of the intervention, the more effective they were. The strongest effects on academic performance were observed in the context of mathematics, followed by reading and writing.

While metacognitive prompts and learning journals make up the larger part of the literature on metacognitive training 96 , meta-analyses that specifically investigate their effectiveness have yet to be performed. Nonetheless, evidence suggests that such interventions can be successful. Researchers found that metacognitive prompts fostered the use of metacognitive strategies (offline meta-control) and that the combination of cognitive and metacognitive prompts improved learning outcomes 97 . Another experiment showed that students who received metacognitive prompts performed more metacognitive activities inside the learning environment and displayed better transfer performance immediately after the intervention 98 . A similar study using self-directed prompts showed enhanced transfer performance that was still observable 3 weeks after the intervention 99 .

Several studies suggest that learning journals can positively enhance metacognition. Subjects who kept a learning journal displayed stronger high meta-control and meta-knowledge on learning tasks and tended to reach higher academic outcomes 100 , 101 , 102 . However, how the learning journal is used seems to be critical; good instructions are crucial 97 , 103 , and subjects who simply summarise their learning activity benefit less from the intervention than subjects who reflect about their knowledge, learning and learning goals 104 . An overview of studies using learning journals and metacognitive prompts to train metacognition can be found in Supplementary Table 3 .

In recent years, educational neuroscience researchers have tried to determine whether training and improvements in EF can lead to learning facilitation and higher academic achievement. Training may consist of having students continually perform behavioural tasks either in the lab, at home, or at school. Current evidence in favour of training EF is mixed, with only anecdotal evidence for positive effects 105 . A meta-analysis did not show evidence for a causal relationship between EF and academic achievement 19 , but suggested that the relationship is bidirectional, meaning that the two are “mutually supportive” 106 .

A recent review article has identified several gaps and shortcoming in the literature on metacognitive training 96 . Overall, research in metacognitive training has been mainly invested in developing learners’ meta-control rather than meta-knowledge. Furthermore, most of the interventions were done in the context of science learning. Critically, there appears to be a lack of studies that employed randomised control designs, such that the effects of metacognitive training intervention are often difficult to evaluate. In addition, research overwhelmingly investigated metacognitive prompts and learning journals in adults 96 , while interventions on EF mainly focused on young children 22 . Lastly, meta-analyses evaluating the effectiveness of metacognitive training have so far focused on metacognitive instruction on children. There is thus a clear disbalance between the meta-analyses performed and the scope of the literature available.

An important caveat of educational sciences research is that metacognition is not typically framed in terms of online and offline metacognition. Therefore, it can be unclear whether protocols operationalise online or offline processes and whether interventions tend to benefit more online or offline metacognition. There is also confusion in terms of what processes qualify as EF and definitions of it vary substantially 86 . For instance, Clements and colleagues mention work on SRL to illustrate research in EF in relation to academic achievement but the two spawn from different lines of research, one rooted in metacognition and socio-cognitive theory 31 and the other in the cognitive (neuro)science of decision-making. In addition, the MSLQ, as discussed above, assesses offline metacognition along with other components relevant to SRL, whereas EF can be mainly understood as online metacognition (see Table 1 ), which on the neural level may rely on different circuitry.

Investigating offline metacognition tends to be carried out in school settings whereas evaluating EF (e.g., Stroop task, and BRIEF) is performed in the lab. Common to all protocols for offline metacognition is that they consist of a form of self-report from the learner, either during the learning activity (thinking-aloud protocols) or after the learning activity (questionnaires, interviews and learning journals). Questionnaires are popular protocols due to how easy they are to administer but have been criticised to provide biased evaluations of metacognitive abilities. In contrast, learning journals evaluate the degree to which learners engage in reflective thinking and may therefore be less prone to bias. Lastly, it is unclear to what extent thinking-aloud protocols are sensitive to online metacognitive processes, such as on-the-fly error correction and effort regulation. The strength of the relationship between metacognitive abilities and academic achievement varies depending on how metacognition is operationalised. Self-report questionnaires and interviews are weakly related to achievement whereas thinking-aloud protocols and EF are strongly related to it.

Based on the well-documented relationship between metacognition and academic achievement, educational scientists hypothesised that fostering metacognition may improve learning and academic achievement, and thus performed metacognitive training interventions. The most prevalent training protocols are direct metacognitive instruction, learning journals, and metacognitive prompts, which aim to induce and foster offline metacognitive processes such as self-reflection, planning and selecting learning strategies. In addition, researchers have investigated whether training EF, either through tasks or embedded in the curriculum, results in higher academic proficiency and achievement. While a large body of evidence suggests that metacognitive instruction, learning journals and metacognitive prompts can successfully improve academic achievement, interventions designed around EF training show mixed results. Future research investigating EF training in different age categories may clarify this situation. These various degrees of success of interventions may indicate that offline metacognition is more easily trainable than online metacognition and plays a more important role in educational settings. Investigating the effects of different methods, offline and online, on the neural level, may provide researchers with insights into the trainability of different metacognitive processes.

In this article, we reviewed the literature on metacognition in educational sciences and cognitive neuroscience with the aim to investigate gaps in current research and propose ways to address them through the exchange of insights between the two disciplines and interdisciplinary approaches. The main aspects analysed were operational definitions of metacognition and metacognitive training, through the lens of metacognitive knowledge and metacognitive control. Our review also highlighted an additional construct in the form of the distinction between online metacognition (on the fly and largely automatic) and offline metacognition (slower, reflective and requiring meta-representations). In cognitive neuroscience, research has focused on metacognitive judgements (mainly offline) and EF (mainly online). Metacognition is operationalised with tasks carried out in the lab and are mapped onto brain functions. In contrast, research in educational sciences typically measures metacognition in the context of learning activities, mostly in schools and universities. More recently, EF has been studied in educational settings to investigate its role in academic achievement and whether training it may benefit learning. Evidence on the latter is however mixed. Regarding metacognitive training in general, evidence from both disciplines suggests that interventions fostering learners’ self-reflection and knowledge of their learning behaviour (i.e., offline meta-knowledge) may best benefit them and increase academic achievement.

We focused on four aspects of research that could benefit from an interdisciplinary approach between the two areas: (i) validity and reliability of research protocols, (ii) under-researched dimensions of metacognition, (iii) metacognitive training, and (iv) domain-specificity vs. domain generality of metacognitive abilities. To tackle these issue, we propose four avenues for integrated research: (i) investigate the degree to which different protocols relate to similar or different metacognitive constructs, (ii) implement designs and perform experiments to identify neural substrates necessary for offline meta-control by for example borrowing protocols used in educational sciences, (iii) study the effects of (offline) meta-knowledge training on the brain, and (iv) perform developmental research in the metacognitive brain and compare it with the existing developmental literature in educational sciences regarding the domain-generality of metacognitive processes and metacognitive abilities.

First, neurocognitive research on metacognitive judgements has developed robust operationalisations of offline meta-knowledge. However, these operationalisations often consist of specific tasks (e.g., 2-AFC) carried out in the lab. These tasks are often very narrow and do not resemble the challenges and complexities of behaviours associated with learning in schools and universities. Thus, one may question to what extent they reflect real-life metacognition, and to what extent protocols developed in educational sciences and cognitive neuroscience actually operationalise the same components of metacognition. We propose that comparing different protocols from both disciplines that are, a priori, operationalising the same types of metacognitive processes can help evaluate the ecological validity of protocols used in cognitive neuroscience, and allow for more holistic assessments of metacognition, provided that it is clear which protocol assesses which construct. Degrees of correlation between different protocols, within and between disciplines, may allow researchers to assess to what extent they reflect the same metacognitive constructs and also identify what protocols are most appropriate to study a specific construct. For example, a relation between meta- d ′ metacognitive sensitivity in a 2-AFC task and the meta-knowledge subscale of the MAI, would provide external validity to the former. Moreover, educational scientists would be provided with bias-free tools to assess metacognition. These tools may enable researchers to further investigate to what extent metacognitive bias, sensitivity and efficiency each play a role in education settings. In contrast, a low correlation may highlight a difference in domain between the two measures of metacognition. For instance, metacognitive judgements in brain research are made in isolated behaviour, and meta-d’ can thus be viewed to reflect “local” metacognitive sensitivity. It is also unclear to what extent processes involved in these decision-making tasks cover those taking place in a learning environment. When answering self-reported questionnaires, however, subjects make metacognitive judgements on a large set of (learning) activities, and the measures may thus resemble more “global” or domain-general metacognitive sensitivity. In addition, learners in educational settings tend to receive feedback — immediate or delayed — on their learning activities and performance, which is generally not the case for cognitive neuroscience protocols. Therefore, investigating metacognitive judgements in the presence of performance or social feedback may allow researchers to better understand the metacognitive processes at play in educational settings. Devising a global measure of metacognition in the lab by aggregating subjects’ metacognitive abilities in different domains or investigating to what extent local metacognition may affect global metacognition could improve ecological validity significantly. By investigating the neural correlates of educational measures of metacognition, researchers may be able to better understand to what extent the constructs studied in the two disciplines are related. It is indeed possible that, though weakly correlated, the meta-knowledge scale of the MAI and meta-d’ share a common neural basis.

Second, our review highlights gaps in the literature of both disciplines regarding the research of certain types of metacognitive processes. There is a lack of research in offline meta-control (or strategic regulation of cognition) in neuroscience, whereas this construct is widely studied in educational sciences. More specifically, while there exists research on EF related to planning (e.g. 107 ), common experimental designs make it hard to disentangle online from offline metacognitive processes. A few studies have implemented subject reports (e.g., awareness of error or desire for reminders) to pin-point the neural substrates specifically involved in offline meta-control and the current evidence points at a role of the lPFC. More research implementing similar designs may clarify this construct. Alternatively, researchers may exploit educational sciences protocols, such as self-report questionnaires, learning journals, metacognitive prompts and feedback to investigate offline meta-control processes in the brain and their relation to academic proficiency and achievement.

Third, there is only one study known to us on the training of meta-knowledge in the lab 78 . In contrast, meta-knowledge training in educational sciences have been widely studied, in particular with metacognitive prompts and learning journals, although a systematic review would be needed to identify the benefits for learning. Relative to cognitive neuroscience, studies suggest that offline meta-knowledge trained in and outside the lab (i.e., metacognitive judgements and meditation, respectively) transfer to meta-knowledge in other lab tasks. The case of meditation is particularly interesting since meditation has been demonstrated to beneficiate varied aspects of everyday life 108 . Given its importance for efficient regulation of cognition, training (offline) meta-knowledge may present the largest benefits to academic achievement. Hence, it is important to investigate development in the brain relative to meta-knowledge training. Evidence on metacognitive training in educational sciences tends to suggest that offline metacognition is more “plastic” and may therefore benefit learning more than online metacognition. Furthermore, it is important to have a good understanding of the developmental trajectory of metacognitive abilities — not only on a behavioural level but also on a neural level — to identify critical periods for successful training. Doing so would also allow researchers to investigate the potential differences in terms of plasticity that we mention above. Currently, the developmental trajectory of metacognition is under-studied in cognitive neuroscience with only one study that found an overlap between the neural correlates of metacognition in adults and children 109 . On a side note, future research could explore the potential role of genetic factors in metacognitive abilities to better understand to what extent and under what constraints they can be trained.

Fourth, domain-specific and domain-general aspects of metacognitive processes should be further investigated. Educational scientists have studied the development of metacognition in learners and have concluded that metacognitive abilities are domain-specific at the beginning (meaning that their quality depends on the type of learning activity, like mathematics vs. writing) and progressively evolve towards domain-general abilities as knowledge and expertise increase. Similarly, neurocognitive evidence points towards a common network for (offline) metacognitive knowledge which engages the different regions at varying degrees depending on the domain of the activity (i.e., perception, memory, etc.). Investigating this network from a developmental perspective and comparing findings with the existing behavioural literature may improve our understanding of the metacognitive brain and link the two bodies of evidence. It may also enable researchers to identify stages of life more suitable for certain types of metacognitive intervention.

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Acknowledgements

We would like to thank the University of Amsterdam for supporting this research through the Interdisciplinary Doctorate Agreement grant. W.v.d.B. is further supported by the Jacobs Foundation, European Research Council (grant no. ERC-2018-StG-803338), the European Union Horizon 2020 research and innovation programme (grant no. DiGYMATEX-870578), and the Netherlands Organization for Scientific Research (grant no. NWO-VIDI 016.Vidi.185.068).

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Fleur, D.S., Bredeweg, B. & van den Bos, W. Metacognition: ideas and insights from neuro- and educational sciences. npj Sci. Learn. 6 , 13 (2021). https://doi.org/10.1038/s41539-021-00089-5

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Metacognition’s Role in Decision Making

Metacognition can help us to think outside the box..

Posted February 14, 2024 | Reviewed by Hara Estroff Marano

• Research tells us that making creative decisions is not necessarily related to intelligence.
• We can use metacognition to draw from a wide range of problem-solving strategies.
• Metacognition is a cognitive skill that can be taught and nurtured.

We make decisions all day long. Some of them are based on careful consideration, some are based on past experiences, and some just seem to come without much thought. Decisions come in all forms. Results can be good, bad, or unclear.

Research tells us that our decision-making ability is not necessarily linked to intelligence but rather to personality , motivation , and willingness to learn. We all have goals and we want to find a way to reach them.

More complex decisions require problem-solving, strategies, re-framing, creative thinking , and possibly seeking advice from others. In addition, there often is the matter of evaluating the difficulty of the task. Is it within or beyond a person’s perceived capabilities?

There is another key player in the mix when it comes to making effective decisions and following up with appropriate actions. It has to do with being able to reflect on one’s thinking and make adjustments that bring about the desired outcome.

The intricacies of how we make decisions are directly related to our facility of metacognition . Metacognition is often referred to as the ability to “think about our thinking.” It includes knowledge about oneself and the ability to select effective strategies, as well as being able to evaluate task performance. Importantly, it includes knowledge about oneself as a learner. Can the person trust their abilities to evaluate all phases of the decision-making process?

An everyday example

Let’s bring this down to what this can look like when making daily decisions that may affect health and well-being,

There is a person whose goal is to eat healthier and lose weight. He/she has decided that there is a specific number on the scale that matters, and a restrictive diet has been chosen. Let’s say that person is then confronted with making choices at a dinner buffet. They can select a small plate of items that are part of the program or a large plate filled with favorites as well as a plan to go back for dessert. It’s decision time!

The person can say to themselves, “Well, just this once, I am going to go for it. I will be better with my eating tomorrow.” Or they may say, “OK, I am going to garner all my willpower and do the right thing here.”

Alternatively, using metacognition would look like this: The person says, “Uh oh, this is a situation that is challenging for me. I can reframe this and come up with a creative solution. I do not have to think about this as my last chance to pig out. I can be more selective and choose what will please me most, using reasonable portion size as a guide. That way, I can enjoy the experience and still reach my goals.” This person is evaluating and shifting their thoughts in order to achieve their goal, rather than trying to following some rules.

This is a fairly simplistic example, but it describes a scenario that is fairly common.

Learning about metacognition

Why don’t people take advantage of metacognition more often, in this context and others?

In spite of that simplistic example, there are some complexities here. Metacognition is a vital part of being able to think creatively, as seen in the example. Research by Akcaoglu, Mor and Kulekci (2023) indicates that, “As a skill, metacognitive awareness is one of the core components of self-regulated learning.” The example above shows how metacognition links to self-regulated learning via creative thinking, curiosity, and willingness to learn.

Notice that the expression is metacognitive awareness. Not everyone has that awareness. This came to the attention of John Flavell in the 1970s when he was first formulating the concept of metacognition. His focus at the time was educational psychology.

Broadly speaking, metacognition is a skill like other cognitive skills in that some people have more of it than others. For many people, developing the skill comes from having been exposed to the concept and learning how to use it.

Flavell envisioned an educational system that describes metacognition, and supports development of it. He indicated that metacognition includes awareness that a person’s beliefs about themselves affect their learning process. Additionally, metacognitions may not be correct. Being able to evaluate the thought process and results is important. According to Flavell, these features can become part of the educational process.

Stimulating metacognition

In line with Flavell’s observations, there are ways to encourage metacognition by asking certain questions. Here are some examples:

• Are you aware that we all have habits around how we think?
• What are your beliefs about how difficult this task is going to be?
• Have you used some creative strategies for this challenge in the past? What were they?
• Sometimes, we evaluate our mistakes so that we can learn from them. Could you do that with this process?

The point here is to stimulate new thoughts that are outside the usual box. Also to see the potential to do so, and the benefits. Ultimately, the goal is nurture metacognition skills when devising solutions to a problem, whether it is healthier eating or something else.

Flavell, J. (1979) Theories of Learning in Educational Psychology. American Psychologist. 34: 906-911.

Akcaoglu, M.O.. Mor, E., Kulekci, E. (2023). The mediating role of metacognitive awareness in the relationship between critical thinking and self-regulation. Thinking Skills and Creativity. 47:101187.

Basu, S & Dixit, S. (2022). Role of metacognition in explaining decision-making styles: A study of knowledge about cognition and regulation of cognition. Personality and Individual Differences. 185:111318.

Kristen Carter, M.S., is an exercise physiologist and the author of The End of Try Try Again: Overcome Your Weight Loss and Exercise Struggles for Good.

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The Role of Metacognition in Learning and Achievement

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Excerpted from " Four-Dimensional Education:
 The Competencies Learners Need to Succeed ," by Charles Fadel, Bernie Trilling and Maya Bialik. The following is from the section, "Metacognition—Reflecting on Learning Goals, Strategies, and Results."

Metacognition, simply put, is the process of thinking about thinking . It is important in every aspect of school and life, since it involves self-reflection on one’s current position, future goals, potential actions and strategies, and results. At its core, it is a basic survival strategy, and has been shown to be present even in rats.

Perhaps the most important reason for developing metacognition is that it can improve the application of knowledge, skills, and character qualities in realms beyond the immediate context in which they were learned. This can result in the transfer of competencies across disciplines—important for students preparing for real-life situations where clear-cut divisions of disciplines fall away and one must select competencies from the entire gamut of their experience to effectively apply them to the challenges at hand. Even within academic settings, it is valuable—and often necessary—to apply principles and methods across disciplinary lines.

Transfer can also be necessary within a discipline, such as when a particular idea or skill was learned with one example, but students must know how to apply it to another task to complete their homework or exams, or to a different context. Transfer is the ultimate goal of all education, as students are expected to internalize what they learn in school and apply it to life.

To illustrate the value of metacognition and how it actually plays a role in learning, we can consider an example from mathematics, where it has been shown that metacognition plays a central role in learning and achievement. Specifically, when novice students were compared to seasoned mathematicians, the students selected a seemingly useful strategy and continued to apply it without checking to see if the strategy of choice was actually working well. Thus, a significant amount of time was wasted in fruitless pursuits. The more experienced mathematicians on the other hand, exercised metacognition, monitoring their approach all along the way to see if it was actually leading to a solution or merely to a dead end.   Being aware of how one is engaging with the process of learning influences how the student interprets the task at hand, and what strategies are selected and employed in service of achieving learning goals. It can help optimize the problem-solving experience at a very high level, and is thus applicable across a large range of contexts. These metacognitive strategies are powerful tools for any discipline, inter-discipline or for learning in general.

It is important to note that since metacognition involves higher-level thinking overseeing lower-level thoughts, there is actually a range of mental processes that fall under its definition. Effects of metacognitive training vary based on what kind of lower-level thoughts are being overseen, and how they are being overseen. Research has identified three levels of reporting on metacognitive processes:

1. Verbalization of knowledge that is already in a verbal state (such as recalling what happened in a story).

2. Verbalization of nonverbal knowledge (such as recalling how one solved a Rubik’s Cube).

3. Verbalization of explanations of verbal or nonverbal knowledge (such as explaining how one makes use of the rhetorical structures of a story as one reads).

Only this third level of metacognitive process has been linked to improved results in problem solving.

Metacognition can be developed in students in the context of their current goals and can enhance their learning of competencies   as well as transfer of learning, no matter their starting achievement level. In fact, it may be most useful for lower-achieving students, as the higher-achieving students are already employing strategies that have proven successful for them. For learning disabled and low - achieving students, metacognitive training has been shown to improve behavior more effectively than traditional attention-control training.

Students who have higher levels of self-efficacy (more confidence in their ability to achieve their goals) are more likely to engage in metacognition and, in turn, are more likely to perform at higher levels. This strongly indicates a positive feedback loop for high-achieving students—they are more successful by using metacognitive strategies, which increases their confidence and in turn leads them to continue to increase their performance. Metacognition is an integral part of this virtuous learning cycle, and one that is amenable to further improvement through instruction.

Charles Fadel is founder of the Center for Curriculum Redesign, Bernie Trilling is founder of 21st Century Learning Advisors and Maya Bialik is researcher at CCR. 

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Metacognition & Critical Thinking: Differences and Similarities

Two terms we usually confuse with each other are Critical Thinking and Metacognition. Even though they both describe the skill of being aware of thinking processes and their possible outcomes, metacognition is a bit more complicated. To fully understand both terms properly, we need to examine their similarities and differences.

Critical Thinking

Critical thinking mostly means putting into practice theoretical frameworks and concepts. This skill is quite necessary because of its ability to allow us to face real-life issues better. When we learn how to critically think and process information, we immediately become smarter consumers, civilians, and people. We are also able to comprehend hidden meanings and to criticize better and more constructively.

Also, when our critical thinking skills are used we can engage in conflict with well-reasoned arguments (in favor; against a party involved).

Overall, critical thinking works as a way of perceiving reality, while it provides us with more ways of dealing with daily life issues.

Critical thinking skills though, need to be practiced, learned, and constantly improved. As critical thinking is not a set of skills that we acquire when we are born, we need to learn it, and how to practice it. This is often achieved through school-college and real-life events that challenge us and require some special treatment that urges us to think differently, and from another perspective.

Also, as our life changes, we need to be “equipped with” the appropriate critical thinking skills that will help us face any kind of situation. This usually occurs by having many challenging experiences, that offer us many new characteristics.

Taking into consideration the fact that a lot of us learn how to “critically think” at school, the educational field should be able to promote such skills and make sure that critical thinking is taught during every class/lesson.

Unfortunately, this is not what occurs. Conventional teaching and learning methods are still used, and they do not support critical thinking at all. In fact, they promote “rigid” learning and most of the time, too theoretical that can’t be applied in real-life situations. That results in students not being able to remember what they have learned, let alone apply all that information in various situations.

When defining this term, we need to take into account four traits.

• Foundation skills:  This category of skills consists of basic skills that also fall under the umbrella of critical thinking skills. For example, proper speculations about an issue, constructing an argument with facts, and doubting the credibility of a piece of information, are all independent skills that, in this case, constitute a foundation base for critical thinking.
• Knowledge base : This includes the context that allows us to apply our skills. For example, academic knowledge is a good part of this category as real-life events that require critical thinking from the participants, are.
• Willingness to question : This category describes the personal attitude of a person towards critical thinking, and towards practices that demand critical thinking. For example, some people avoid events that require critical thinking because they perceive it as difficult or too challenging.
• Self-reflection : This category means Metacognition, which we are going to examine below.

Metacognition

Metacognition, or the “Self-reflection” dimension of Critical Thinking, is a more theoretical and personal concept. It describes our perspective and reflection on our thinking processes. That is why it is also called “Self-reflection”. Because, with Metacognition we can evaluate the efficacy of our thinking procedures before, during, and after an issue.

Basically, Metacognition is the level after critical thinking. It allows us to examine our critical thinking abilities a bit more clearly, and to reflect on their usefulness. It is a slower procedure, and it requires good observation skills, regarding our critical thinking attitude.

In addition, we can control Metacognition, since it is our reflection. Metacognition is a rather new concept and somewhat difficult to examine since it heavily relies on personal thoughts and reflections that are not caused by external factors ( educational field).

Differences

When it comes to the differences these concepts have, there are 4 points to consider:

• When using critical thinking, we usually know our goal and expected result ( resolving an issue, reaching a conclusion). However, when we use Metacognition, we are aware of the efficiency of our thinking processes and methods, rather than the outcome of our critical thinking.
• In general, Critical thinking is more supported, in comparison with Metacognition. For example, educational institutions recognize Creative thinking as a useful tool, when Metacognition is not discussed ( very rarely).
• Overall, Critical Thinking is more directly applicable to real-life situations than Metacognition. Thus, critical thinking is much easier and less complicated.
• Metacognition is more personal than critical thinking. Critical thinking- as mentioned above- is also highly affected by interaction with other people and with external factors. Metacognition is purely personal, as it is a reflection.

Similarities: Metacognition and critical-thinking

Regarding the similarities between these two concepts, three points need to be considered:

• Critical thinking and metacognition need a lot of practice. They both include skills that work better when practiced frequently. However, critical thinking comes first, as Metacognition is a reflection of it (hence, it makes sense for Metacognition to come second).
• Both Critical thinking and metacognition are very much needed. They might have different goals, but they complete each other as concepts.
• Also, they both “require awareness of the relevant procedures”. That means that during both procedures, we learn more when we are conscious of the skills and tools we are using.

On An Ending Note

To sum up, the concept of Critical Thinking and the concept of Metacognition share some elements, but they are also very different from each other. Even though they both are necessary, Critical thinking (as the first level) needs to be more promoted and supported, when Metacognition (the second level) needs to be a concept that people raise awareness of, especially in the educational and academic domain.

Two forms of ‘thinking about thinking’: metacognition and critical thinking

https://www.encyclopedia.com/education/applied-and-social-sciences-magazines/critical-thinking-metacognition-and-problem-based-learningC

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The role of metacognitive skills in developing critical thinking

• Published: 31 March 2010
• Volume 5 , pages 137–156, ( 2010 )

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The study investigated the influence of metacognition on critical thinking skills. It is hypothesized in the study that critical thinking occurs when individuals use their underlying metacognitive skills and strategies that increase the probability of a desirable outcome. The Metacognitive Assessment Inventory (MAI) by Schraw and Dennison (Contemporary Educational Psychology 19:460–475, 1994 ), which measures regulation of cognition and knowledge of cognition, and the Watson-Glaser Critical Thinking Appraisal (WGCTA) with the factors inference, recognition of assumptions, deduction, interpretations, and evaluation of arguments were administered to 240 college students from different universities in the National Capital Region in the Philippines. The Structural Equations Modeling (SEM) was used to determine the effect of metacognition on critical thinking as latent variables. Two models were tested: (1) In the first model, metacognition is composed of two factors while (2) in the second model, metacognition has eight factors as they affect critical thinking. The results indicated that in both models, metacognition has a significant path to critical thinking, p  < .05. The analysis also showed that for both metacognition and critical thinking, all underlying factors are significant. The second model had a better goodness of fit as compared with the first as shown by the RMSEA value and other fit indices.

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Special thanks to my students who participated in the study and helped me gather and encode the data.

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Sample Critical Thinking Items

These sample items were patterned from the WGCTA

Recognition of Assumption

Interpretation

Evaluation of Arguments

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Magno, C. The role of metacognitive skills in developing critical thinking. Metacognition Learning 5 , 137–156 (2010). https://doi.org/10.1007/s11409-010-9054-4

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Received : 08 January 2009

Accepted : 18 March 2010

Published : 31 March 2010

Issue Date : August 2010

DOI : https://doi.org/10.1007/s11409-010-9054-4

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• v.81(4); 2017 May

Strategies for Improving Learner Metacognition in Health Professional Education

Melissa s. medina.

a University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma

Ashley N. Castleberry

b University of Arkansas for Medical Sciences College of Pharmacy, Little Rock, Arkansas

Adam M. Persky

c Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina

Metacognition is an essential skill in critical thinking and self-regulated, lifelong learning. It is important for learners to have skills in metacognition because they are used to monitor and regulate reasoning, comprehension, and problem-solving, which are fundamental components/outcomes of pharmacy curricula. Instructors can help learners develop metacognitive skills within the classroom and experiential setting by carefully designing learning activities within courses and the curriculum. These skills are developed through intentional questioning, modeling techniques, and reflection. This article discusses key background literature on metacognition and identifies specific methods and strategies to develop learners’ metacognitive skills in both the classroom and experiential settings.

INTRODUCTION

Imagine the following situation: You ask your class to find and review a journal article. One of your learners, Morgan, begins the assignment the night before the assignment due date. She is unsure where to search for primary literature. Once she finds an article, she underestimates the review time. She spends several hours reviewing and finishes the assignment in the early morning. When the instructor graded the assignment, she receives a poor grade because most questions were not directly and concisely answered. Morgan is surprised by her grade because she spent several hours working on the assignment, which was more than she thought would be necessary.

While many things could explain Morgan’s behavior, at the foundation Morgan may have trouble with metacognition. She failed to plan. She did not know where to look for information. She misjudged time. She did not check her work for accuracy. She was overconfident in her predicted grade. All these elements point to poor metacognitive skills.

What is Metacognition?

We can define metacognition as the “thinking about thinking.” Because it refers to a person’s “knowledge and cognition about cognitive phenomena.” 1,2 This type of cognition regulates thinking and learning and consists of three self-assessment skills: planning, monitoring, and evaluating. In the case of Morgan, she failed to lay out a plan for her article review; during the process, did not monitor whether she was accomplishing the goal; and once done, did not evaluate her work for correctness.

Researchers have investigated three aspects of metacognition: metacognitive knowledge, metacognitive monitoring, and metacognitive control. 3 Metacognitive knowledge is the information you consult when thinking about an idea; it includes the basic facts and concepts. Metacognitive monitoring is the ability to assess cognitive activity whereas metacognitive control is the ability to regulate cognitive activity. In the example above, Morgan may have lacked the knowledge of where to look for an article or how to review an article (metacognitive knowledge). She may have lacked the ability to assess whether she was answering the relevant questions (metacognitive monitoring). She also may be deficient in the control of metacognition by allowing insufficient time for this activity (metacognitive control).

Importance of Metacognition

Metacognition is important to every profession. There are many reasons why metacognition is important in the health sciences, including from being a better learner to becoming a better clinician. During the learning process, metacognition guides our learning strategies. If learners know what they know and do not know, they can focus on acquiring the knowledge they are lacking. Metacognitive skills also have a role in critical thinking and problem solving. If you know what you know and do not know, your metacognitive skills help drive you to obtain the missing information, which we refer to as self-directed or self-regulated learning. Finally, being mindful or metacognitively aware can prevent medication errors in clinical settings because of increases in awareness of our thought process leading to better critical thinking and monitoring of actions. As an example, self-assessment errors routinely occur among physicians, nurses, pharmacists and other health care providers. 4

Metacognition in Medical Errors

Medical errors are one of the leading causes of death in many countries. 5 Researchers have argued that medical error is partly a cognitive issue. 6 Medication order entry errors were the fourth leading cause of medication errors in 2003. 7 These types of errors can occur because the pharmacist did not ask “do the orders make sense for the indication?” (ie, metacognitive monitoring) or “did I check to ensure I entered things correctly?” (ie, evaluation of medical orders or evaluation of entered data). One study cited that most medication errors occur at the prescription and found 40% of errors were related to prescribing the wrong dose and 18% from omitted information. 8

In addition, physicians, pharmacists, and other health care providers can be overconfident in their assessments leading to medical errors which can lead to hindsight bias which may further hinder learning. Hindsight bias is the “knew it all along” effect and is the belief that an event is more predictable after it becomes known than it was before it became known. During hindsight bias, we lose the ability to recollect the feeling of uncertainty that preceded an event. This bias hinders our appraisal of past events.

Part of the cause of hindsight bias is the subjective feeling of ease associated when we make judgments – a metacognitive function. When people find it easy to come to a conclusion about a particular outcome, they will show greater hindsight bias, particularly regarding foreseeability (“I knew that would happen.”). One reason is that people attribute the subjective ease of the judgment to the certainty of being correct – the answer came easily and thus must be correct. In one study, physicians were asked to guess the likelihood that they would get the correct diagnosis in the future (prospective or foresight) and in the past (retrospectively or hindsight). 9 The less experienced physicians gave significantly higher estimates in hindsight than in foresight. For easier cases, the more experienced physicians demonstrated hindsight bias; however, for more difficult cases they did not give higher estimates than in foresight. In another study, physicians were asked their confidence and accuracy during right heart catheterization. 10 Physicians were confident of their estimates, but there was no relationship between confidence and accuracy. Experienced physicians were no more accurate than less experienced ones, although they were significantly more confident. These are two examples of how metacognitive skills may affect clinical judgments.

Metacognition and Study Skills

Metacognition is crucial in controlling and guiding thinking. 1 Dunlosky proposed a model of how metacognitive control impacts study time. 11 This model included study preparation (self-efficacy evaluation, task appraisal, and initial strategy selection) followed by monitoring and assessing whether the to-be-learned items has been learned and feeding back into the cycle to re-study unlearned material. Several investigators found that learners are unaware of effective study strategies which impact performance. 12-14

College learners have displayed overconfidence in self-chosen study strategies about academic performance and have demonstrated low correlations between self-predicted and actual performance on learning assessments. 15,16 This pattern of overconfidence may be more apparent in low-performing learners. 17,18 The issue of selecting study strategies is complicated because a requirement for selecting a learning strategy is metacognitive knowledge about which learning strategies are beneficial for long-term memory. Several studies report learners using low-impact study strategies such as rereading or highlighting notes. 12,19,20 In one study, 80% of undergraduates reported that the study skills they use were learned on their own and not taught to them in a formal manner by teachers. 16 These findings are consistent with the health science literature that also found rereading a prominent learning strategy. 20,21 The selection of poor study strategies raises questions of whether those improvised strategies, presumably based on intuition or metacognitive feedback, are consistent with the evidence. This hypothesis raises a second question whether instruction on learning and memory topics could improve metacognitive awareness of successful learning strategies. Recently it was documented that learners who have engaged in their study skills development use better strategies, but low impact strategies still predominate. 20 As a result, faculty members are advised to teach study skills formally to learners. 22

Metacognition and Self-Directed Learning

Most health-professional organizations and accrediting bodies encourage lifelong learning because of the ever-changing biomedical landscape. Lifelong learning requires self-direction and self-regulation. Self-directed learning is the result of allowing learners to make decisions about the information they want to experience or learn. 23 In a realistic learning situation, self-directed learning is difficult and in a formal education setting, information selection is limited and governed by the instructor. 24 While this is limiting, instructors need to set learning objectives for novice learners because these learners are not in a position to be self-directed. They do not know the skills and knowledge needed to become a health professional; also, limiting resources to find information may be appropriate early on to help build efficiency into the learning process (ie, learners do not have to spend large amounts of time searching for relevant information).

Providing guidance can lead to a “passive learning environment.” However, within a passive learning environment, learners selectively attend to different environmental cues. 25 As an example of a passive environment, learners actively evaluate what has been said, or engage in self-explanation to decide what other information is required. 24 Self-directed learning differs from self-regulation. For example, if the article Morgan found was interesting, she could be self-directed in learning more about the topic. However, she would be self-regulated when balancing this additional learning with her required course learning.

Self-regulation is how individuals guide their goal-directed activities over time. It is designed to maximize the long-term best interests of an individual, resulting in learners controlling their impulses and looking out for their well-being. 26 Self-regulated learning modulates various processes (eg, cognitive, behavioral) to reach the desired goal. These regulatory mechanisms are the essentials of self-regulated learning because they are under the control of the learners and would be the basis for future professional development (ie, continual professional development). The self-regulated behaviors include planning, monitoring, attention, and effort.

Both planning and monitoring are components of metacognition. When learners engage in planning activities, they think through what they need to learn and set task-specific goals. 27,28 Once they plan, they need to monitor. Monitoring refers to paying attention to one’s performance and understanding of the course material. 29 Monitoring is a critical component of self-regulation because it provides awareness of one’s knowledge level, which then leads to changes in one’s affect, cognition, and behavior. 27 Accurate monitoring enhances the regulation of learning because it provides feedback to what trainees already know and where they need to focus their resources. 28,30

Metacognition and Critical Thinking

Critical thinking involves cognitive, dispositional and metacognitive components. The cognitive component represents the abilities to comprehend a problem and apply cognitive skills to make sound judgments. The disposition component influences the patterns of intellectual activity; these can include the enjoyment of thinking, an open attitude, a careful approach and a mindset for truth seeking. 31,32 Metacognitive strategies enable learners to supervise and control their thinking processes. At its core, a critical thinker is one in charge of their thinking processes, while metacognitive strategies enable such control to take place. The metacognitive aspects interact with a variety of internal and external factors like type of instruction, motivation, and socio-economic status ( Figure 1 ).

Influence of Internal and External Factors in Cognition

Metacognition is the ability to monitor thinking to use skills and strategies appropriately to achieve a desirable outcome. We discussed this regarding learning strategies and parallels can be made for critical thinking skills. Halpern defines a critical thinker as one who applies appropriate skills and strategies to achieve a desirable outcome. 33 As such, critical thinkers strategically use cognitive skills that are best suited to a particular situation. They are aware of their thinking and thus control their thinking processes. Metacognitive strategies are an important variable during thinking processes. 33 These skills need to be made explicit and public to develop critical thinking skills. 33

Metacognition and the Accreditation Process

Accreditation standards for pharmacy (ACPE) and medicine (AAMC) emphasize metacognitive skills as a critical part of health professional training. For pharmacy education, the college or school provides an environment and culture that promotes self-awareness, self-directed lifelong learning, professional behavior, leadership, collegial relationships, and collaboration within and across academic units, disciplines, and professions. (Standards 4 and 9). The experiential curriculum should provide an inculcation of habits of self-directed lifelong learning (Standard 12). Standard 4 explicitly states self-awareness as a key factor and that learners use metacognitive practice to regulate their learning. The appendices further emphasize self-directed and lifelong learning including continuous professional development. Similarly, in medicine we see an emphasis on self-directed learning. The faculty of a medical school should ensure that the medical curriculum includes self-directed learning experiences and time for independent study to allow medical learners to develop the skills of lifelong learning. Self-directed learning involves medical learners’ self-assessment of learning needs; independent identification, analysis, and synthesis of relevant information; and appraisal of the credibility of information sources (Standard 6.3).

Overview of Instructional Approaches to Teach Metacognition

Metacognitive processes are best taught in conjunction and alignment with cognitive processes and separating the two processes is challenging. 34 One key instructional strategy in developing metacognition is cognitive apprenticeship. Cognitive apprenticeship is “learning through guided experience.” In this model, the expert’s cognitive and metacognitive processes and skills used when performing a task are explicit and public and are the focus of teaching activities. 35 There are four dimensions to this model that reflect the three dimensions of metacognition.

The first dimension includes content knowledge (concepts, facts, procedures) and strategic knowledge (heuristic, metacognitive, learning). To think through a process, one must have the content knowledge to think about something. One also needs to have a heuristic (short-cut) or algorithm (formula) to follow to develop the skill. Thus, instruction should have a content component and direct instruction on how to work through a process.

The second dimension of cognitive apprenticeship has a method to demonstrate metacognition. The expert or instructor should model the process – externalizing the thought process. The concept of coaching is appropriate as the expert should help demonstrate and coach learners through the process. Within this procedure, learners reflect on their thoughts, verbalizing their motives and assumptions. 34 The process should be scaffolded, ie, offering early examples or demonstrations in a more supportive model leading to a level of independence.

The third dimension of cognitive apprenticeship is an extension of scaffolding, and this concept is the importance of sequencing: increasing task complexity, diversity of problems, and migrating from global to local skills. Task complexity starts with straightforward problems and building complexity with experience. The diversity of problems helps learners build more generalizable knowledge and skills. When we use a diversity of problems, we are approaching similar problems from different contexts to help build context-independent knowledge and skills. When we learn, we form a memory trace for that information. This memory is dependent on the cues available during the learning context. 36 We can recall this information only if we receive the correct cues. If we see the content or skill (or thought process) with a wide array of problems, we can retrieve the information from a variety of cues and contexts and start to make generalities. Finally, after faculty scaffold and sequence appropriately, they move the learners from global skills to local skills. At this point, learners should have a clear conceptual model of the task or process before executing its parts. Developing global skills reflects the idea that seeing the overall structure of the problem or content helps in understanding the individual parts because we can draw on relationships to help reinforce the learning. 37

The fourth dimension of cognitive apprenticeship is the sociology of learning and includes situated learning, a community of practice, intrinsic motivation, and exploiting cooperation. This idea is consistent with factors of motivation especially relatedness – we are more motivated to learn or perform when we can relate to the situation or the person. The authenticity of the learning environment (experiential vs. classroom) or the problem (patient case vs. foundational science) helps frame the real-world context which increases motivation. Therefore, situated learning (environment reflects the real-world) increases motivation. 38-40 The last components are social in nature but also consistent with effective learning strategies: a community of practice (engaging in a community to achieve goals) and cooperation (cooperation between learners in problem solving). These methods are real-world since health care is a team process and the research consistently show that learners teaching other learners is an effective strategy (effect sizes above 0.70). 41 Cooperative learning allows for a variety of positive attributes including feedback and communication which help in the metacognitive process.

Strategies to Enhance Metacognition in the Classroom

Several methods can be used to enhance learners’ metacognition in the classroom. Methods used during any part of normal instructional approaches include lecture, active learning exercises, or pre-planned activities outside of the classroom. Example methods can be modified based on the knowledge level of the learner and number of learners in the classroom in combination with scaffolding. To note, developing metacognition within learners is not an easy task. 34 Appendix 1 contains some sample metacognitive learning objectives.

General Planning

Learners plan better and learn when their attention focuses on learning objectives established by the instructor. The explicit discussion of the learning objectives starts the metacognitive process by prioritizing the importance of thinking about the learning process over the content. To activate prior knowledge, prompt the learners to think about what they already know that is related to the content of that day and what relevant knowledge they lack. 42 Next, lead the learners to analyze the distinctions between contrasting information and focus more on these differences rather than the similarity between concepts. 43,44 Have learners assess the time it will take to complete this activity and where they will find the resources for successful completion of the task to help them think about the process of studying. Additional self-questions to promote learner metacognition about learning can be found in Table 1 . 45

Sample Self-Questions to Promote Learner Metacognition About Learning 45,66-68

General Monitoring

Learners benefit from monitoring their understanding (ie, metacognitive awareness) during teaching activities. 46-48 By checking learning behavior throughout the lecture or teaching activity, learners are reminded of the importance of the learning process. Learners can accomplish this by noting important concepts and writing down questions during the lecture or activity. 45 Jotting down questions can be facilitated by dividing content into 10-15 minute segments and offering activities to refocus attention to the learning objectives and reflecting on their comprehension of the material. The instructor can help learners learn strategies for retaining information such as chunking, connecting, and elaborating and assist them in organizing the material in ways to recognize patterns and associations. They may regulate the difficulty of the material by breaking down the problem into simpler steps for learners to clearly see the thought process of problem-solving. 43 After some practice with simpler questions, incrementally increase the difficulty of the problem. Another way to assist learners in monitoring their thought processes is to provide half-done examples and have learners solve them then discuss possible conclusions. By monitoring smaller pieces of an assignment, the instructor and learners are better able to identify and correct errors in thinking. ( Table 1 ).

General Evaluating

By evaluating metacognitive skills, learners become more aware of this process and its impact on learning. Creating checklists, rating scales, and rubrics for distribution before the assignment can help learners monitor and evaluate their thinking as they are working. Additionally, administering a metacognitive questionnaire during an exam can help learners evaluate their thinking during the exam and make corrections accordingly ( Appendix 2 provides an example). 49 Reviewing this questionnaire after the exam along with individual results can also be helpful to identify patterns of incorrect thinking or gaps in preparation and study time. Having learners evaluate their learning is powerful and can lead to change for future learning ( Table 1 ).

Other Strategies Examination Reviews

Examinations themselves can be a metacognitive method. 50,51 Reviewing an examination with learners after grades are released can be a powerful way to help them start thinking about their thought process during the examination. Examination reviews occur in a group setting with the entire class or during a one-on-one or small group interaction with learners. During this session, have learners reflect on their answer choice and the actual correct answer. Ask them to reflect on why they got the item incorrect and specifically why this occurred. Ask prompting questions such as: What were your assumptions about this item? What are some alternative ways to approach this question? What piece of knowledge were you missing? By forcing learners to identify the problem in their thought process for each item, you might be able to discern a pattern in behaviors and offer strategies to remedy this. In addition, the small delay in feedback also can enhance learning. 52

In addition to reviewing the exam after administration and scoring, a review before the exam can help learners assess their learning strategies and adjust accordingly before the exam. Doing an exam review a couple of days before the exam still gives learners time to change their studying and enhance weak areas. By using questions similar to the format of an examination question, learners familiarize themselves with the examination requirements. Using active learning strategies paired with a group discussion on questions that require critical thinking can be a powerful review tool for learners. A review before and after an examination can benefit learner learning.

Thinking out Loud

A form of modeling is thinking out loud, and this occurs in the classroom. 43 For example, provide learners with a complex question or case scenario and let them think about their approach to solving the issue. Then think out loud to model your thought process for how you would solve this issue as a content expert. Have learners compare their thought process to yours to identify gaps, errors, or alignment to improve their thinking. This method also benefits learners in experiential training such as clinical rotations or shadowing experiences. Expert thinking is often internal and not portrayed to learner learners who can negatively reinforce wrong thinking. For example, when experts are problem-solving, they silently sort relevant and irrelevant information before generating a solution. To a novice learner, all of the information can appear important, which can hinder their problem solving. Experts should instead think out loud so novices can better understand what is irrelevant in certain problem-solving situations. By thinking out loud, you show learners how to approach situations and model the process of monitoring your behaviors in professional practice.

Reflection is simply the intentional and dynamic process that allows improvement in one’s actions, abilities, and knowledge by learning from past experiences. 53 To reflect, think back on an experience and analyze the situation. By getting learners to reflect, they think about their actions, abilities, and knowledge and assess improvement in these areas moving forward. Reflection assignments following learning activities (whether in the classroom, simulation, or practice) can help learners think about their thinking and develop plans to grow in these areas. Reflective writing assignments can include responses to three questions: What worked well when preparing for this exam/quiz/assignment? What did not work well when preparing for this exam/quiz/assignment? What will I change before my next exam/quiz/assignment? 45

Reflection using the “Muddiest Point” allows learners to identify confusion during a lecture or learning activity. 45 Have learners write down what part of the material remains confusing to them. Then have the learners investigate the issue further to encourage exploration of knowledge and self-directed learning. This quick exercise can have a high yield for metacognitive practice.

Another reflective method is self-explanation. When learners use self-explanation, they are asking themselves to explain their process and what they can do next time. This technique has been used to facilitate the transfer of learning and problem solving. 54

Adding Judgments of Understanding

Asking learners to prospectively make judgments (eg, I predict my score on this exam to be…) or retrospectively make judgments (eg, for the test question I just completed, my confidence in my answer is…) can help learners monitor or evaluate their learning. These types of judgments have been used within higher education and courses in pharmacy. 17,18,55 When asked these questions, learner accuracy in predicting grades improves and moves from being overconfident to underconfident with reductions in bias. 18,49 See Appendix 3 for an example of a weekly monitoring exercise with judgments of understanding.

Strategies to Enhance Metacognition in the Experiential Setting

In addition to classroom instruction, raising learners’ metacognition is important in the experiential setting. To date, there is less research in this educational setting, but opportunities exist to develop and research metacognitive development.

Mastery Goal Setting

Artino and colleagues in 2012 found that learners’ metacognitive skills (planning, goal setting, monitoring comprehension, and evaluating learning) correlated positively with mastery goal structures, which are environments that emphasize developing competence, mastering new skills and learning to understand. 56 Mastery goal structures contrast with performance-approach goal structures that focus on demonstrating proficiency and peer comparison and performance-avoid goal structures that encourage avoiding looking incompetent. 56 Both performance-approach and avoidance structures are associated with procrastination, avoidance of help-seeking, and poor grades, which are goal orientations that become predominant in the experiential setting. 56 Learners in the experiential setting may resort to these goal orientations because it is a time when the bulk of learners’ grades are derived directly from observation instead of tests, and they may adapt behaviors to avoid looking incompetent. 56 Based on these findings, preceptors should consider encouraging learners to adapt mastery-oriented goals and seek help when needed. One way preceptors support mastery goal structures is to offer formative assessments paired with feedback that emphasizes progress and mastery of knowledge, skills, and attitudes. 56 These formative assessments can take a variety of forms from case discussions, journal clubs, or presentations – typically practices that normally occur during experiential rotations. These should regularly occur to help the learner develop. These feedback sessions may be an opportunity to use the verbalization strategies found in Appendix 4 .

Questioning and Feedback

Another way preceptors can help their learners on rotation is to emphasize metacognitive skills from the beginning of training coupled with immediate feedback regarding technique. This method was shown to help novice medical learners on a surgery rotation learn laparoscopic surgery skills using simulation software. 57 There are questions that preceptors regularly can ask learners to promote metacognitive awareness, including questions related to planning, monitoring, and evaluating. Research with elementary school learners showed that when teachers asked learners two questions, “what did you learn about yourself today regarding the subject area?” and “What did you learn that you can consistently replicate well?” their metacognitive awareness increased. 58 Based on these results, preceptors could ask learners questions found in Table 2 .

Questions to Ask During Experiential Settings

Another important aspect of experiential education is the purpose of asking questions. Often we might hear of preceptors “pimping” learners – that is to ask questions under the guise of educating them but the real purpose is to determine hierarchy. Questioning should be Socratic and developmental compared to evaluative and demeaning ( Table 3 ). 59-62

Comparison of the Socratic Teaching Method vs Clinical “Pimping”

To effectively ask questions, preceptors should do the following: 59 diagnose the learners (ie, what level are they at) and teach to that level; avoid asking questions for questions’ sake (for eg, questions about trivia, historical facts, non-meaningful eponyms, and impossible, guess-what-I’m-thinking questions); tell learners your goal in asking questions; emphasize important learning points; and do not attempt to embarrass intentionally or humiliate the learners.

Clinical Documentation with Explanation

Written and verbal communication require an explanation of the thought process. For example, if you are making a recommendation to a physician for a specific drug, you should explain why you chose that drug (drug allergy to another drug, lab levels, adverse effects, other disease states). By explicitly documenting reasoning, metacognition is modeled and could lead to better communication and patient outcomes. As an example, SOAP notes may include an additional page that documents the rationalization and resources used to arrive at the plan. SOAP notes have been used to improve reflection and learning in medical physiology in medical learners and help faculty reflect on learning in dental hygiene education. 63 The use of clinical documentation may be especially impactful when novices can compare their documents to experienced clinicians and when clinicians verbalize their process as they develop the document.

Experiential Rotation Structure

Finally, the overall structure of experiential education should be scaffolded – both between and within a rotation. Learners should be started with a more supportive environment and moved toward more independence; this can support their metacognitive development. This scaffolding or progressive problem-solving approach is a critical part of developing expertise. It is the gaining of experience for both content but process that is important. Experts are more metacognitively aware than novices because the progression of problem solving requires the cognitive and metacognitive processes. 64

Metacognition refers to a person’s ability to regulate their thinking and learning and consists of the self-assessment skills: planning, monitoring, and evaluating. These important skills reduce self-assessment errors, such as hindsight bias, among health care providers. The new pharmacy, medical, and nursing education accreditation standards emphasize metacognitive skills and the related skills in critical thinking and self-directed learning. Studies reporting formal teaching of these skills are often lacking which further emphasizes the need to teach health care learners explicitly metacognitive skills during their training. Suggestions for teaching metacognitive skills in the didactic setting include cognitive apprenticeships, exam reviews, modeling of metacognitive skills, thinking out loud protocols, reflection assignments, self-explanation methods, and judgment of understanding assignments. In the experiential setting, faculty members can emphasize mastery goal setting, use questioning techniques that promote metacognitive awareness coupled with feedback about learner efforts in this area, request clinical documentation with an explanation, and scaffold learners during the rotation. Overall, using these teaching strategies regardless of setting can raise learners’ self-awareness and help metacognitive thinking to occur more automatically. Metacognition’s role in clinical decision making is important as it is a means to address “what to learn,” “when to learn,” and “how to learn.” 65

ACKNOWLEDGMENTS

The authors thank Cindy Stowe and John Dunlosky for their input during manuscript preparation, and Kayley Lyons, Shelby Hudson, and Tom Angelo for their help during the editing process.

Appendix 1. Outcome/Objective Statements

By the end of this course, you should be able to:

Comprehend the limits of your memory for a particular task and create a means of external support.

Self-monitor your learning strategies and then adapt the strategies if they are effective.

Notice whether you comprehend something you just read and then modify your approach if you did not comprehend it.

Skim subheadings of unimportant information to get to the information you need.

Rehearse a skill to gain proficiency.

Self-test to see how well you learned something.

Verbalize your thought process for a particular task.

Appendix 2. Exam Item Assessment

Appendix 3. Example Weekly Monitoring Exercise

Appendix 4. Example of Verbalization Techniques to Develop Metacognition

• Study Guides
• Homework Questions

The Role of Education in Fostering Critical Thinking Skills