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Fostering Metacognition to Support Student Learning and Performance

• Julie Dangremond Stanton
• Amanda J. Sebesta
• John Dunlosky

*Address correspondence to: Julie Dangremond Stanton ( E-mail Address: [email protected] ).

Department of Cellular Biology, University of Georgia, Athens, GA 30602

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Department of Biology, Saint Louis University, St. Louis, MO 63103

Department of Psychological Sciences, Kent State University, Kent, OH 44240

Metacognition is awareness and control of thinking for learning. Strong metacognitive skills have the power to impact student learning and performance. While metacognition can develop over time with practice, many students struggle to meaningfully engage in metacognitive processes. In an evidence-based teaching guide associated with this paper ( https://lse.ascb.org/evidence-based-teaching-guides/student-metacognition ), we outline the reasons metacognition is critical for learning and summarize relevant research on this topic. We focus on three main areas in which faculty can foster students’ metacognition: supporting student learning strategies (i.e., study skills), encouraging monitoring and control of learning, and promoting social metacognition during group work. We distill insights from key papers into general recommendations for instruction, as well as a special list of four recommendations that instructors can implement in any course. We encourage both instructors and researchers to target metacognition to help students improve their learning and performance.

INTRODUCTION

Supporting the development of metacognition is a powerful way to promote student success in college. Students with strong metacognitive skills are positioned to learn more and perform better than peers who are still developing their metacognition (e.g., Wang et al. , 1990 ). Students with well-developed metacognition can identify concepts they do not understand and select appropriate strategies for learning those concepts. They know how to implement strategies they have selected and carry out their overall study plans. They can evaluate their strategies and adjust their plans based on outcomes. Metacognition allows students to be more expert-like in their thinking and more effective and efficient in their learning. While collaborating in small groups, students can also stimulate metacognition in one another, leading to improved outcomes. Ever since metacognition was first described ( Flavell, 1979 ), enthusiasm for its potential impact on student learning has remained high. In fact, as of today, the most highly cited paper in CBE—Life Sciences Education is an essay on “Promoting Student Metacognition” ( Tanner, 2012 ).

Despite this enthusiasm, instructors face several challenges when attempting to harness metacognition to improve their students’ learning and performance. First, metacognition is a term that has been used so broadly that its meaning may not be clear ( Veenman et al. , 2006 ). We define metacognition as awareness and control of thinking for learning ( Cross and Paris, 1988 ). Metacognition includes metacognitive knowledge , which is your awareness of your own thinking and approaches for learning. Metacognition also includes metacognitive regulation , which is how you control your thinking for learning ( Figure 1 ). Second, metacognition includes multiple processes and skills that are named and emphasized differently in the literature from various disciplines. Yet upon examination, the metacognitive processes and skills from different fields are closely related, and they often overlap (see Supplemental Figure 1). Third, metacognition consists of a person’s thoughts, which may be challenging for that person to describe. The tacit nature of metacognitive processes makes it difficult for instructors to observe metacognition in their students, and it also makes metacognition difficult for researchers to measure. As a result, classroom intervention studies of metacognition—those that are necessary for making the most confident recommendations for promoting student metacognition—have lagged behind foundational and laboratory research on metacognitive processes and skills.

FIGURE 1. Metacognition framework commonly used in biology education research (modified from Schraw and Moshman, 1995 ). This theoretical framework divides metacognition into two components: metacognitive knowledge and metacognitive regulation. Metacognitive knowledge includes what you know about your own thinking and what you know about strategies for learning. Declarative knowledge involves knowing about yourself as a learner, the demands of the task, and what learning strategies exist. Procedural knowledge involves knowing how to use learning strategies. Conditional knowledge involves knowing when and why to use particular learning strategies. Metacognitive regulation involves the actions you take in order to learn. Planning involves deciding what strategies to use for a future learning task and when you will use them. Monitoring involves assessing your understanding of concepts and the effectiveness of your strategies while learning. Evaluating involves appraising your prior plan and adjusting it for future learning.

How do undergraduate students develop metacognitive skills?

To what extent do active learning and generative work 1 promote metacognition?

To what extent do increases in metacognition correspond to increases in achievement in science courses?

FIGURE 2. (A) Landing page for the Student Metacognition guide. The landing page provides a map with sections an instructor can click on to learn more about how to support students’ metacognition. (B) Example paper summary showing instructor recommendations. At the end of each summary in our guide, we used italicized text to point out what instructors should know based on the paper’s results.

The organization of this essay reflects the organization of our evidence-based teaching guide. In the guide, we first define terms and provide important background from papers that highlight the underpinnings and benefits of metacognition ( https://lse.ascb.org/evidence-based-teaching-guides/student-metacognition/benefits-definitions-underpinnings ). We then explore metacognition research by summarizing both classic and recent papers in the field and providing links for readers who want to examine the original studies. We consider three main areas related to metacognition: 1) student strategies for learning, 2) monitoring and control of learning, and 3) social metacognition during group work.

SUPPORTING STUDENTS TO USE EFFECTIVE LEARNING STRATEGIES

What strategies do students use for learning.

First our teaching guide examines metacognition in the context of independent study ( https://lse.ascb.org/evidence-based-teaching-guides/student-metacognition/supporting-student
-learning-strategies ). When students transition to college, they have increased responsibility for directing their learning, which includes making important decisions about how and when to study. Students rely on their metacognition to make those decisions, and they also use metacognitive processes and skills while studying on their own. Empirical work has confirmed what instructors observe about their own students’ studying—many students rely on passive strategies for learning. Students focus on reviewing material as it is written or presented, as opposed to connecting concepts and synthesizing information to make meaning. Some students use approaches that engage their metacognition, but they often do so without a full understanding of the benefits of these approaches ( Karpicke et al. , 2009 ). Students also tend to study based on exam dates and deadlines, rather than planning out when to study ( Hartwig and Dunlosky, 2012 ). As a result, they tend to cram, which is also known in the literature as massing their study. Students continue to cram because this approach is often effective for boosting short-term performance, although it does not promote long-term retention of information.

Which Strategies Should Students Use for Learning?

Here, we make recommendations about what students should do to learn, as opposed to what they typically do. In our teaching guide, we highlight three of the most effective strategies for learning: 1) self-testing, 2) spacing, and 3) interleaving ( https://lse.ascb.org/evidence-based-teaching-guides/student
-metacognition/supporting-student-learning-strategies/
#whatstudentsshould ). These strategies are not yet part of many students’ metacognitive knowledge, but they should know about them and be encouraged to use them while metacognitively regulating their learning. Students self-test when they use flash cards and answer practice questions in an attempt to recall information. Self-testing provides students with opportunities to monitor their understanding of material and identify gaps in their understanding. Self-testing also allows students to activate relevant knowledge and encode prompted information so it can be more easily accessed from their memory in the future ( Dunlosky et al. , 2013 ).

Students space their studying when they spread their learning of the same material over multiple sessions. This approach requires students to intentionally plan their learning instead of focusing only on what is “due” next. Spacing can be combined with retrieval practice , which involves recalling information from memory. For example, self-testing is a form of retrieval practice. Retrieval practice with spacing encourages students to actively recall the same content across several study sessions, which is essential for consolidating information from prior study periods ( Dunlosky et al. , 2013 ). Importantly, when students spread their learning over multiple sessions, they are less susceptible to superficial familiarity with concepts, which can mislead them into thinking they have learned concepts based on recognition alone ( Kornell and Bjork, 2008 ).

Students interleave when they alternate studying of information from one category with studying of information from another category. For example, when students learn categories of amino acid side groups, they should alternate studying nonpolar amino acids with polar amino acids. This allows students to discriminate across categories, which is often critical for correctly solving problems ( Rohrer et al. , 2020 ). Interleaving between categories also supports student learning because it usually results in spacing of study.

How are students enacting specific learning strategies, and do different students enact them in different ways?

To what extent do self-testing, spacing, and interleaving support achievement in the context of undergraduate science courses?

What can instructors do to increase students’ use of effective learning strategies?

What Factors Affect the Strategies Students Should Use to Learn?

Next, we examined the factors that affect what students should do to learn. Although we recommend three well-established strategies for learning, other appropriate strategies can vary based on the learning context. For example, the nature of the material, the type of assessment, the learning objectives, and the instructional methods can render some strategies more effective than others ( Scouller, 1998 ; Sebesta and Bray Speth, 2017 ). Strategies for learning can be characterized as deep if they involve extending and connecting ideas or applying knowledge and skills in new ways ( Baeten et al. , 2010 ). Strategies can be characterized as surface if they involve recalling and reproducing content. While surface strategies are often viewed negatively, there are times when these approaches can be effective for learning ( Hattie and Donoghue, 2016 ). For example, when students have not yet gained background knowledge in an area, they can use surface strategies to acquire the necessary background knowledge. They can then incorporate deep strategies to extend, connect, and apply this knowledge. Importantly, surface and deep strategies can be used simultaneously for effective learning. The use of surface and deep strategies ultimately depends on what students are expected to know and be able to do, and these expectations are set by instructors. Openly discussing these expectations with students can enable them to more readily select effective strategies for learning.

What Challenges Do Students Face in Using Their Metacognition to Enact Effective Strategies?

How can students address challenges they will face when using effective—but effortful—strategies for learning?

What approaches can instructors take to help students overcome these challenges?

ENCOURAGING STUDENTS TO MONITOR AND CONTROL THEIR LEARNING FOR EXAMS

Metacognition can be investigated in the context of any learning task, but in the sciences, metacognitive processes and skills are most often investigated in the context of high-stakes exams. Because exams are a form of assessment common to nearly every science course, in the next part of our teaching guide, we summarized some of the vast research focused on monitoring and control before, during, and after an exam ( https://lse.ascb.org/evidence-based-teaching-guides/student-metacognition/encouraging-students-monitor-control-learning ). In the following section, we demonstrate the kinds of monitoring and control decisions learners make by using an example of introductory biology students studying for an exam on cell division. The students’ instructor has explained that the exam will focus on the stages of mitosis and cytokinesis, and the exam will include both multiple-choice and short-answer questions.

How Should Students Use Metacognition while Preparing for and Taking an Exam?

As students prepare for an exam, they can use metacognition to inform their learning. Students can consider how they will be tested, set goals for their learning, and make a plan to meet their goals. It is expected that students who set specific goals while planning for an exam will be more effective in their studying than students who do not make specific goals. For example, a student who sets a specific goal to identify areas of confusion each week by answering end-of-chapter questions each weekend is expected to do better than a student who sets a more general goal of staying up-to-date on the material. Although some studies include goal setting and planning as one of many metacognitive strategies introduced to students, the influence of task-specific goal setting on academic achievement has not been well studied on its own in the context of science courses.

As students study, it is critical that they monitor both their use of learning strategies and their understanding of concepts. Yet many students struggle to accurately monitor their own understanding ( de Carvalho Filho, 2009 ). In the example we are considering, students may believe they have already learned mitosis because they recognize the terms “prophase,” “metaphase,” “anaphase,” and “telophase” from high school biology. When students read about mitosis in the textbook, processes involving the mitotic spindle may seem familiar because of their exposure to these concepts in class. As a result, students may inaccurately predict that they will perform well on exam questions focused on the mitotic spindle, and their overconfidence may cause them to stop studying the mitotic spindle and related processes ( Thiede et al. , 2003 ). Students often rate their confidence in their learning based on their ability to recognize, rather than recall, concepts.

Instead of focusing on familiarity, students should rate their confidence based on how well they can retrieve relevant information to correctly answer questions. Opportunities for practicing retrieval, such as self-testing, can improve monitoring accuracy. Instructors can help students monitor their understanding more accurately by encouraging students to complete practice exams and giving students feedback on their answers, perhaps in the form of a key or a class discussion ( Rawson and Dunlosky, 2007 ). Returning to the example, if students find they can easily recall the information needed to correctly answer questions about cytokinesis, they may wisely decide to spend their study time on other concepts. In contrast, if students struggle to remember information needed to answer questions about the mitotic spindle, and they answer these questions incorrectly, then they can use this feedback to direct their efforts toward mastering the structure and function of the mitotic spindle.

While taking a high-stakes exam, students can again monitor their performance on a single question, a set of questions, or an entire exam. Their monitoring informs whether they change an answer, with students tending to change answers they judge as incorrect. Accordingly, the accuracy of their monitoring will influence whether their changes result in increased performance ( Koriat and Goldsmith, 1996 ). In some studies, changing answers on an exam has been shown to increase student performance, in contrast to the common belief that a student’s first answer is usually right ( Stylianou-Georgiou and Papanastasiou, 2017 ). Changing answers on an exam can be beneficial if students return to questions they had low confidence in answering and make a judgment on their answers based on the ability to retrieve the information from memory, rather than a sense of familiarity with the concepts. Two important open questions are:

What techniques can students use to improve the accuracy of their monitoring, while preparing for an exam and while taking an exam?

How often do students monitor their understanding when studying on their own?

How Should Students Use Metacognition after Taking an Exam?

How do students develop metacognitive regulation skills such as evaluation?

To what extent does the ability to evaluate affect student learning and performance?

When students evaluate the outcome of their studying and believe their preparation was lacking, to what degree do they adopt more effective strategies for the next exam?

PROMOTING SOCIAL METACOGNITION DURING GROUP WORK

Next, our teaching guide covers a relatively new area of inquiry in the field of metacognition called social metacognition , which is also known as socially shared metacognition ( https://lse.ascb.org/evidence-based-teaching-guides/student
-metacognition/promoting-social-metacognition
-group-work ). Science students are expected to learn not only on their own, but also in the context of small groups. Understanding social metacognition is important because it can support effective student learning during collaborations both inside and outside the classroom. While individual metacognition involves awareness and control of one’s own thinking, social metacognition involves awareness and control of others’ thinking. For example, social metacognition happens when students share ideas with peers, invite peers to evaluate their ideas, and evaluate ideas shared by peers ( Goos et al. , 2002 ). Students also use social metacognition when they assess, modify, and enact one another’s strategies for solving problems ( Van De Bogart et al. , 2017 ). While enacting problem-solving strategies, students can evaluate their peers’ hypotheses, predictions, explanations, and interpretations. Importantly, metacognition and social metacognition are expected to positively affect one another ( Chiu and Kuo, 2009 ).

How do social metacognition and individual metacognition affect one another?

How can science instructors help students to effectively use social metacognition during group work?

CONCLUSIONS

We encourage instructors to support students’ success by helping them develop their metacognition. Our teaching guide ends with an Instructor Checklist of actions instructors can take to include opportunities for metacognitive practice in their courses ( https://lse.ascb.org/wp-content/uploads/sites/10/2020/12/Student-Metacognition-Instructor-Checklist.pdf ). We also provide a list of the most promising approaches instructors can take, called Four Strategies to Implement in Any Course ( https://lse.ascb.org/wp-content/uploads/sites/10/2020/12/Four
-Strategies-to-Foster-Student-Metacognition.pdf ). We not only encourage instructors to consider using these strategies, but given that more evidence for their efficacy is needed from classroom investigations, we also encourage instructors to evaluate and report how well these strategies are improving their students’ achievement. By exploring and supporting students’ metacognitive development, we can help them learn more and perform better in our courses, which will enable them to develop into lifelong learners.

1 Generative work “involves students working individually or collaboratively to generate ideas and products that go beyond what has been presented to them” ( Andrews et al. , 2019 , p2). Generative work is often stimulated by active-learning approaches.

ACKNOWLEDGMENTS

We are grateful to Cynthia Brame, Kristy Wilson, and Adele Wolfson for their insightful feedback on this paper and the guide. This material is based upon work supported in part by the National Science Foundation under grant number 1942318 (to J.D.S.). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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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  

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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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Making Metacognition Part of Student Writing

When students are encouraged to think deeply about their writing processes, they become better writers.

Writing conferences are a staple in many English language arts classrooms today. Teachers recognize the benefit of conversational feedback, allowing students to feel more agency over their own writing, and the power of building rapport that comes with conferences.

In my own classroom, I’ve been on the journey of incorporating writing conferences for over a decade, and they have changed drastically from when I first began. I’ve transitioned from doing most of the talking to students doing more and more sharing. Recently, my thinking on writing conferences has shifted again. After realizing that our conferences were primarily centered on a piece with little to no reflection on the thought process of writing, I added a new layer of complexity. 

Metacognitive Reflection

Metacognition is a term that describes thinking about one’s thinking as a means of reflection. The goal is for students to think more about the process—how they approach writing, barriers to good writing, and strategies that help them write successfully—instead of focusing only on content or rubric requirements. Metacognitive reflection can awaken students to be more aware of their thinking during writing, resulting in a deeper understanding of who they are as writers and of how to transfer their knowledge to any genre of writing. 

So what exactly does metacognitive thinking on writing look like, and how can teachers build this type of reflection into writing conferences?

A whole-class conversation about the importance of metacognition is a good starting place, since students are often focused on assignments rather than their thinking while completing them. These strategies can help students become aware of their thinking while writing and are easy to incorporate in assignments, providing students with opportunities to pause and think about their thinking while writing. Observations from these activities will enable students to talk about metacognition during conferences. 

6 Activities to Encourage Metacognition

1. Keeping a journal. Encourage students to take metacognitive breaks of two to three minutes during writing to record their thoughts. Describe your process to this point . What was a barrier to your writing? How did you overcome this? What do you think you could do to prevent this from occurring next time? These breaks can and should occur at different points in the writing process. 

2. Recording troubleshooting ideas. Encourage students to keep a list of strategies and ideas they have found successful in the past that they can use during writing to help them push through when they’re experiencing difficulty.

3. Writing collaboratively. Provide opportunities for students to work on writing assignments together. The students can discuss why they are making the choices they make along the way. Thoughts can be addressed in comments in a Google Doc or on sticky notes placed on the student’s paper. 

4. Using graphic organizers. Graphic organizers can also serve as tools to guide students to think about their thinking while writing and to identify successful strategies. The object is not to fill the entire graphic organizer but to provide multiple entry points to think about their thinking while writing. 

5. Highlighting papers. I often have students highlight papers for claims, evidence, and analysis, but this can be modified for any focus. This strategy adds a visual component to reflection and opens opportunities for students to think about what leads to strong components of a piece and why other components are weaker.

6. Recording post-writing thoughts. Writing a paragraph on the thought process during an assignment can be particularly helpful for the big-picture process. What would you do differently if writing again? Why? What would you keep the same? Why? What strategies did you employ that worked well that you can use for future writing?

The insights gathered from these metacognitive tools can carry over into writing conversations. In your next writing conferences, try adding some of the italicized questions to questions already commonly asked to gather insight and give input into the thought process behind the writing. 

• What do you like best about this writing? Why do you think this section is strong? What did you notice as you were writing this section? 
• Where did you struggle with this piece? Why did you struggle with this section? How did you feel while you were writing this section? What could have helped you while writing this particular section? Let’s review your list of troubleshooting ideas and strategies. What can you add to these?
• Where is an area you took a risk or experimented with something new? Why did you decide to do something different here? Was it successful? Why or why not? If so, how could you incorporate this into other writing? 
• How do you feel about the piece overall? How did you feel about the overall process? How do you see yourself growing as a writer? Are there particular things in your learning environment or mindset that contribute to successful writing? Identify one or two concrete strategies to use moving forward. 

Metacognition is an important step in writing instruction and where the real magic happens in learning. Students do need feedback on specific pieces of writing but should be given the opportunity to think beyond the product. Providing students with opportunities for metacognitive reflection and the opportunity to discuss their thinking strengthens their writing not only in class but for years to come.

Center for Teaching Innovation

Metacognitive strategies (how people learn).

Metacognitive strategies are techniques to help students develop an awareness of their thinking processes as they learn. These techniques help students focus with greater intention, reflect on their existing knowledge versus information they still need to learn, recognize errors in their thinking, and develop practices for effective learning.

Some metacognitive strategies are easy to implement:

• ask students to submit a reflection on a topic before reading a text and then revisit that reflection after the reading to consider how it informed their thinking
• introduce a problem and have students participate in a think-pair-share on the strategy they would use to solve it; then share your strategy too
• ask students to write a reflection on how they figured out an answer to a question (Bransford, Brown, & Cocking, 2000)
• Pre-Assessment of Knowledge: Use a pre-class survey, homework assignment, polling questions in class, or a short reflective writing piece as a way for students to explore their existing knowledge about a topic. Asking how the topic relates to students’ experiences or interests can highlight pre-existing knowledge and boost engagement. Comment on the reflections or share some themes with the class.
• Debrief with the class and share a list of common strategies
• Preview your reading (title, abstract, headings, charts, diagrams, questions, terms highlighted in bold text, italicized words, etc.)
• Based on your preview, develop some questions that you think the text will answer
• Write down any questions you have
• Read a paragraph, paraphrase it, and check to see if it answered any of your questions
• Repeat this process with the entire document to ensure you understand the material and can answer your questions
• After you finish reading, test yourself on your questions
• Make a note of what is still unclear
• What is one question you still have about the reading?
• What is one thing you are curious about?
• How can you best prepare for class?
• What can you do in class to help yourself learn?
• Explain two ideas in the reading that you found confusing.
• Did working with your group help you learn? Why or why not?
• What advice would you give yourself now if you were to start this project again?
• What went well?
• What could have gone better?
• What could you do to improve things in the future?

These strategies offer a great opportunity to teach students about metacognition. Explaining that this reflection process can help them integrate new knowledge and take control of their learning experience.

For more information on using metacognitive strategies, please contact CTI for a consultation.

Selected Resources

• Assessing Prior Knowledge
• Classroom Assessment Techniques
• Bransford, J., National Research Council (U.S.)., & National Research Council (U.S.). (2000).  How people learn: Brain, mind, experience, and school . Washington, D.C: National Academy Press.
• Brown, P. C., Roediger, H. L., & McDaniel, M. A. (2014). Make it stick: The science of successful learning.
• Lang, J. M. (2016). Small teaching: Everyday lessons from the science of learning.
• Khosa, D. K., & Volet, S. E. (2014). Productive group engagement in cognitive activity and metacognitive regulation during collaborative learning: Can it explain differences in students’ conceptual understanding? Metacognition and Learning, 9, 287–307.
• McGuire, S. Y., & McGuire, S. (2015). Teach students how to learn: Strategies you can incorporate into any course to improve student metacognition, study skills, and motivation.

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Metacognitive strategies improve learning

Metacognition refers to thinking about one's thinking and is a skill students can use as part of a broader collection of skills known as self-regulated learning. Metacognitive strategies for learning include planning and goal setting, monitoring, and reflecting on learning. Students can be instructed in the use of metacognitive strategies. Classroom interventions designed to improve students’ metacognitive approaches are associated with improved learning (Cogliano, 2021; Theobald, 2021).

Strategies to encourage students to use metacognitive techniques

• Prompt students to develop study plans and to evaluate their approaches to planning for, monitoring, and evaluating their learning. Early in the term, advise and support students in making a study plan. After receiving feedback on the first and subsequent assessments, ask students to reflect on their performance and determine which study strategies worked and which did not. Encourage them to revise their study plans if needed. One way to support this is to ask students to identify their personal learning environment .  This is an activity where students identify the various resources and support available to them.
• Offer practice tests. Explain to students the benefits of practice testing for improving retention and performance on exams. Create practice tests with an answer key to help students prepare for exams. Use practice questions for in-class formative feedback throughout the term. Consider creating a bank of practice questions from previous exams to share with students (Stanton, 2021).
• Call attention to strategies students can adopt to space their practice. This can include explaining the benefits of spaced practice and encouraging students to map out weekly study sessions for your course on their calendar. These study sessions should include the most recent material and revisit older material, perhaps in the form of practice tests (Stanton, 2021).
• Model your metacognitive processes with students. Show students the thinking process behind your approach to solving problems (Ambrose, 2010). This can take the form of a think-aloud where you talk through the steps you would take to plan, monitor, and reflect on your problem-solving approach.
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Metacognitive Study Strategies

Do you spend a lot of time studying but feel like your hard work doesn’t help your performance on exams? You may not realize that your study techniques, which may have worked in high school, don’t necessarily translate to how you’re expected to learn in college. But don’t worry—we’ll show you how to analyze your current strategies, see what’s working and what isn’t, and come up with new, more effective study techniques. To do this, we’ll introduce you to the idea of “metacognition,” tell you why metacognition helps you learn better, and introduce some strategies for incorporating metacognition into your studying.

What is metacognition and why should I care?

Metacognition is thinking about how you think and learn. The key to metacognition is asking yourself self-reflective questions, which are powerful because they allow us to take inventory of where we currently are (thinking about what we already know), how we learn (what is working and what is not), and where we want to be (accurately gauging if we’ve mastered the material). Metacognition helps you to be a self-aware problem solver and take control of your learning. By using metacognition when you study, you can be strategic about your approach. You will be able to take stock of what you already know, what you need to work on, and how best to approach learning new material.

Strategies for using metacognition when you study

Below are some ideas for how to engage in metacognition when you are studying. Think about which of these resonate with you and plan to incorporate them into your study routine on a regular basis.

Use your syllabus as a roadmap

Look at your syllabus. Your professor probably included a course schedule, reading list, learning objectives or something similar to give you a sense of how the course is structured. Use this as your roadmap for the course. For example, for a reading-based course, think about why your professor might have assigned the readings in this particular order. How do they connect? What are the key themes that you notice? What prior knowledge do you have that could inform your reading of this new material? You can do this at multiple points throughout the semester, as you gain additional knowledge that you can piece together.

Summon your prior knowledge

Before you read your textbook or attend a lecture, look at the topic that is covered and ask yourself what you know about it already. What questions do you have? What do you hope to learn? Answering these questions will give context to what you are learning and help you start building a framework for new knowledge. It may also help you engage more deeply with the material.

Think aloud

Talk through your material. You can talk to your classmates, your friends, a tutor, or even a pet. Just verbalizing your thoughts can help you make more sense of the material and internalize it more deeply. Talking aloud is a great way to test yourself on how well you really know the material. In courses that require problem solving, explaining the steps aloud will ensure you really understand them and expose any gaps in knowledge that you might have. Ask yourself questions about what you are doing and why.

Ask yourself questions

Asking self-reflective questions is key to metacognition. Take the time to be introspective and honest with yourself about your comprehension. Below are some suggestions for metacognitive questions you can ask yourself.

• Does this answer make sense given the information provided?
• What strategy did I use to solve this problem that was helpful?
• How does this information conflict with my prior understanding?
• How does this information relate to what we learned last week?
• What questions will I ask myself next time I’m working these types of problems?
• What is confusing about this topic?
• What are the relationships between these two concepts?
• What conclusions can I make?

Try brainstorming some of your own questions as well.

Use writing

Writing can help you organize your thoughts and assess what you know. Just like thinking aloud, writing can help you identify what you do and don’t know, and how you are thinking about the concepts that you’re learning. Write out what you know and what questions you have about the learning objectives for each topic you are learning.

Organize your thoughts

Using concept maps or graphic organizers is another great way to visualize material and see the connections between the various concepts you are learning. Creating your concept map from memory is also a great study strategy because it is a form of self-testing.

Take notes from memory

Many students take notes as they are reading. Often this can turn notetaking into a passive activity, since it can be easy to fall into just copying directly from the book without thinking about the material and putting your notes in your own words. Instead, try reading short sections at a time and pausing periodically to summarize what you read from memory. This technique ensures that you are actively engaging with the material as you are reading and taking notes, and it helps you better gauge how much you’re actually remembering from what you read; it also engages your recall, which makes it more likely you’ll be able to remember and understand the material when you’re done.

Review your exams

Reviewing an exam that you’ve recently taken is a great time to use metacognition. Look at what you knew and what you missed. Try using this handout to analyze your preparation for the exam and track the items you missed, along with the reasons that you missed them. Then take the time to fill in the areas you still have gaps and make a plan for how you might change your preparation next time.

Take a timeout

When you’re learning, it’s important to periodically take a time out to make sure you’re engaging in metacognitive strategies. We often can get so absorbed in “doing” that we don’t always think about the why behind what we are doing. For example, if you are working through a math problem, it’s helpful to pause as you go and think about why you are doing each step, and how you knew that it followed from the previous step. Throughout the semester, you should continue to take timeouts before, during or after assignments to see how what you’re doing relates to the course as a whole and to the learning objectives that your professor has set.

Test yourself

You don’t want your exam to be the first time you accurately assess how well you know the material. Self-testing should be an integral part of your study sessions so that have a clear understanding of what you do and don’t know. Many of the methods described are about self-testing (e.g., thinking aloud, using writing, taking notes from memory) because they help you discern what you do and don’t actually know. Other common methods include practice tests and flash cards—anything that asks you to summon your knowledge and check if it’s correct.

Figure out how you learn

It is important to figure out what learning strategies work best for you. It will probably vary depending on what type of material you are trying to learn (e.g. chemistry vs. history), but it will be helpful to be open to trying new things and paying attention to what is effective for you. If flash cards never help you, stop using them and try something else instead. Making an appointment with an academic coach at the Learning Center is a great chance to reflect on what you have been doing and figuring out what works best for you.

Works consulted

McGuire, S.Y. and McGuire, S. (2016). Teach Students How to Learn: Strategies You Can Incorporate in Any Course to Improve Student Metacognition, Study Skills, and Motivation. Sterling, Virginia: Stylus Publishing, LLC.

Centre for Innovation and Excellence in Learning. Ten Metacognitive Teaching Strategies. Vancouver Island University. Retrieved from https://ciel.viu.ca/sites/default/files/ten_metacognitive_teaching_strategies.docx

Anderson, J. (2017, May 09). A Stanford researcher’s 15-minute study hack lifts B+ students into the As. Quartz. Retrieved from https://qz.com/978273/a-stanford-professors-15-minute-study-hack-improves-test-grades-by-a-third-of-a-grade/

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What Is Metacognition? How Does It Help Us Think?

Metacognitive strategies like self-reflection empower students for a lifetime..

Posted October 9, 2020 | Reviewed by Abigail Fagan

Metacognition is a high order thinking skill that is emerging from the shadows of academia to take its rightful place in classrooms around the world. As online classrooms extend into homes, this is an important time for parents and teachers to understand metacognition and how metacognitive strategies affect learning. These skills enable children to become better thinkers and decision-makers.

Metacognition: The Neglected Skill Set for Empowering Students is a new research-based book by educational consultants Dr. Robin Fogarty and Brian Pete that not only gets to the heart of why metacognition is important but gives teachers and parents insightful strategies for teaching metacognition to children from kindergarten through high school. This article summarizes several concepts from their book and shares three of their thirty strategies to strengthen metacognition.

What Is Metacognition?

Metacognition is the practice of being aware of one’s own thinking. Some scholars refer to it as “thinking about thinking.” Fogarty and Pete give a great everyday example of metacognition:

Think about the last time you reached the bottom of a page and thought to yourself, “I’m not sure what I just read.” Your brain just became aware of something you did not know, so instinctively you might reread the last sentence or rescan the paragraphs of the page. Maybe you will read the page again. In whatever ways you decide to capture the missing information, this momentary awareness of knowing what you know or do not know is called metacognition.

When we notice ourselves having an inner dialogue about our thinking and it prompts us to evaluate our learning or problem-solving processes, we are experiencing metacognition at work. This skill helps us think better, make sound decisions, and solve problems more effectively. In fact, research suggests that as a young person’s metacognitive abilities increase, they achieve at higher levels.

Fogarty and Pete outline three aspects of metacognition that are vital for children to learn: planning, monitoring, and evaluation. They convincingly argue that metacognition is best when it is infused in teaching strategies rather than taught directly. The key is to encourage students to explore and question their own metacognitive strategies in ways that become spontaneous and seemingly unconscious .

Metacognitive skills provide a basis for broader, psychological self-awareness , including how children gain a deeper understanding of themselves and the world around them.

Metacognitive Strategies to Use at Home or School

Fogarty and Pete successfully demystify metacognition and provide simple ways teachers and parents can strengthen children’s abilities to use these higher-order thinking skills. Below is a summary of metacognitive strategies from the three areas of planning, monitoring, and evaluation.

1. Planning Strategies

As students learn to plan, they learn to anticipate the strengths and weaknesses of their ideas. Planning strategies used to strengthen metacognition help students scrutinize plans at a time when they can most easily be changed.

One of ten metacognitive strategies outlined in the book is called “Inking Your Thinking.” It is a simple writing log that requires students to reflect on a lesson they are about to begin. Sample starters may include: “I predict…” “A question I have is…” or “A picture I have of this is…”

Writing logs are also helpful in the middle or end of assignments. For example, “The homework problem that puzzles me is…” “The way I will solve this problem is to…” or “I’m choosing this strategy because…”

2. Monitoring Strategies

Monitoring strategies used to strengthen metacognition help students check their progress and review their thinking at various stages. Different from scrutinizing, this strategy is reflective in nature. It also allows for adjustments while the plan, activity, or assignment is in motion. Monitoring strategies encourage recovery of learning, as in the example cited above when we are reading a book and notice that we forgot what we just read. We can recover our memory by scanning or re-reading.

One of many metacognitive strategies shared by Fogarty and Pete, called the “Alarm Clock,” is used to recover or rethink an idea once the student realizes something is amiss. The idea is to develop internal signals that sound an alarm. This signal prompts the student to recover a thought, rework a math problem, or capture an idea in a chart or picture. Metacognitive reflection involves thinking about “What I did,” then reviewing the pluses and minuses of one’s action. Finally, it means asking, “What other thoughts do I have” moving forward?

Teachers can easily build monitoring strategies into student assignments. Parents can reinforce these strategies too. Remember, the idea is not to tell children what they did correctly or incorrectly. Rather, help children monitor and think about their own learning. These are formative skills that last a lifetime.

3. Evaluation Strategies

According to Fogarty and Pete, the evaluation strategies of metacognition “are much like the mirror in a powder compact. Both serve to magnify the image, allow for careful scrutiny, and provide an up-close and personal view. When one opens the compact and looks in the mirror, only a small portion of the face is reflected back, but that particular part is magnified so that every nuance, every flaw, and every bump is blatantly in view.” Having this enlarged view makes inspection much easier.

When students inspect parts of their work, they learn about the nuances of their thinking processes. They learn to refine their work. They grow in their ability to apply their learning to new situations. “Connecting Elephants” is one of many metacognitive strategies to help students self-evaluate and apply their learning.

In this exercise, the metaphor of three imaginary elephants is used. The elephants are walking together in a circle, connected by the trunk and tail of another elephant. The three elephants represent three vital questions: 1) What is the big idea? 2) How does this connect to other big ideas? 3) How can I use this big idea? Using the image of a “big idea” helps students magnify and synthesize their learning. It encourages them to think about big ways their learning can be applied to new situations.

Metacognition and Self-Reflection

Reflective thinking is at the heart of metacognition. In today’s world of constant chatter, technology and reflective thinking can be at odds. In fact, mobile devices can prevent young people from seeing what is right before their eyes.

John Dewey, a renowned psychologist and education reformer, claimed that experiences alone were not enough. What is critical is an ability to perceive and then weave meaning from the threads of our experiences.

The function of metacognition and self-reflection is to make meaning. The creation of meaning is at the heart of what it means to be human.

Everyone can help foster self-reflection in young people.

Marilyn Price-Mitchell, Ph.D., is an Institute for Social Innovation Fellow at Fielding Graduate University and author of Tomorrow’s Change Makers.

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Metacognitive writing strategies, critical thinking skills, and academic writing performance: A structural equation modeling approach

• Published: 24 November 2022
• Volume 18 , pages 237–260, ( 2023 )

Cite this article

• Mark Feng Teng   ORCID: orcid.org/0000-0002-5134-8504 1 &
• Mei Yue   ORCID: orcid.org/0000-0003-0688-1040 2  

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The present study adopted the structural equation modeling approach to examine Chinese university students’ metacognition, critical thinking skills, and academic writing. In particular, this research explored whether awareness in metacognition can foster critical thinking and, thus, lead to enhancement in academic writing. The measure for exploring metacognitive writing strategies covered metacognitive knowledge and regulation in academic writing. The measure for understanding learners’ critical thinking encompassed the following five skills: inference, recognition of assumptions, deduction, interpretations, and evaluation of arguments. The academic writing assessment was based on an internal test. The participants consisted of 644 third-year students from a Chinese university. Three models tested: (1) the role of metacognition in academic writing; (2) the role of metacognition in critical thinking; and (3) correlations between metacognition, critical thinking skills, and academic writing. The results indicated significant relationships between the three variables, and the implications based on these findings were discussed.

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The study was supported by the Project from the Education Department of Hainan Province (Project number: Hnky2020ZD-9). We appreciate Professor Chuang Wang’ help in proofreading this article.

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Teng, M.F., Yue, M. Metacognitive writing strategies, critical thinking skills, and academic writing performance: A structural equation modeling approach. Metacognition Learning 18 , 237–260 (2023). https://doi.org/10.1007/s11409-022-09328-5

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13 Examples of Metacognitive Strategies

Metacognition is the ability to think about your own thinking. ‘Meta’ means beyond and ‘Cognition’ means thinking . So, metacognitive strategies involve reflecting on and regulating how you think.

Having this skill is essential for improving your own productivity and effectiveness at school or work. 

When we apply metacognitive strategies, we become better learners. We can control not only our thoughts but also our actions much more effectively.

The following meta cognitive strategies are used regularly as teaching strategies to help people learn better.

Examples of Metacognitive Strategies

Read Also: What is Flavell’s Metacognitive Theory?

1. Self-Questioning

Self-questioning involves pausing throughout a task to consciously check your own actions.

Without self-questioning, we may lack humility and awareness of our own faults.

Most importantly, we would not be able to improve because we never took the time to ask ourselves important questions like:

• Is this the best way to carry out this task?
• Did I miss something? Maybe I should check again.
• Did I follow the right procedure there?
• How could I do better next time?
• Am I looking at this task the right way?
• How can I do a better job at thinking about what I’m doing?

Good students question their actions both while they’re completing the task and after finishing it (see also: ‘reflection’).

2. Meditation

Meditation involves clearing your mind. We could consider it to be a metacognitive strategy because meditators aim to:

• Clear out the chatter that goes on in our heads.
• Reach a calm and focused state that can prime us for learning.
• Be more aware of our own inner speech.

Meditation for children is becoming increasingly popular in schools because educators can see the value of this task for helping students achieve greater self-awareness in the classroom.

3. Reflection

Reflection involves pausing to think about a task. It is usually a cyclical process where we reflect, think of ways to improve, try again then go back to reflection.

Reflection is metacognitive only if you consciously reflect on what your thought processes were and how to improve upon them next time .

There are many models of reflection with varying steps. Most reflective cycles have at least the following phases:

• A task is planned.
• You attempt the task.
• You look at how you did the task.
• You come up with things you did well and areas for improvement.
• You plan the next task, with a focus on improving on your weaknesses.
• You try again …
• You reflect again …

Once you become skilled at reflection, you may also reflect while doing a task so that you can make adjustments to your thinking processes as you go. We call this sort of reflection reflection in action (as opposed to reflection on action).

4. Awareness of Strengths and Weaknesses

Central to metacognition is a person’s capacity to see their own strengths and weaknesses. Only through looking at yourself and making a genuine assessment of your weaknesses can you achieve self-improvement.

One way to start looking at your strengths and weaknesses is to use a SWOT chart.

A SWOT chart is a chart with four sections:

• Strengths : write down what you perceive to be your strengths as a learner.
• Weaknesses : write down what you perceive to be your weaknesses as a learner.
• Opportunities : identify opportunities you may have to improve your cognitive skills in the coming weeks or months.
• Threats : identify potential threats that may prevent you from improving your cognitive skills in the coming weeks or months.

5. Awareness of Learning Styles

Learning styles theories such as Gardner’s Multiple Intelligences and Learning Modalities theories argue that different people learn in different ways.

For example, you may feel you are better at learning through images than reading.

Some common learning styles include:

• Visual: A visual learner learns best through images, graphics, TV documentaries and graphs. They are good at identifying patterns and matching complementary colours.
• Auditory: A visual learner learns best through listening rather than watching or reading. They enjoy being read stories and listening to podcasts.
• Kinesthetic: A kinesthetic learner learns best through movement. They like to learn by doing things rather than reading or listening. They are active rather than passive learners .
• Logical-Mathematical: People who are logical-mathematical learners are good at using reasoning to find answers. They are good with numbers but may struggle with subjective issues in the humanities .
• Interpersonal: An Interpersonal learner loves learning through social interaction. They’re good at group work, have high emotional intelligence , and can compromise to get their job done.
• Intrapersonal: An intrapersonal learner is someone who likes to mull things over in their own heads. They’re happy to learn in silence and isolation and may find working with others to be a distraction (see: intrapersonal communication skills ).

If you are aware of how you learn (i.e. the way your brain processes information!) you may be able to use your strengths and work on your weaknesses more efficiently.

6. Mnemonic aids

Mnemonic aids are strategies you can use to improve your information retention. They involve using rhymes, patterns, and associations to remember.

They work by adding context (additional or surrounding information) to a fact to help you to recall it.

My favorite example of using mnemonic aids is for remembering names.

You might remember a name in one of the following ways:

• Rhyme: You meet a singer named Tom. You tell yourself “Tom would sing a song before long.” Now, next time you meet Tom the singer, you might be able to recall your rhyme to remember both his name and profession!
• Association: I have a sister named Vanessa. I always remember people named Vanessa because my head says “Oh, she has the same name as my sister!” every time I meet a Vanessa.

7. Writing Down your Working

Most people will recall in high school math classes their teacher saying: “I want to see your working so I know how you got to your answer.”

This teacher is ensuring you are employing the right thinking processes and can show others how you went about thinking about the task.

When you become an expert at a topic you tend not to think about your thinking. We sometimes call this “unconscious competence”, which is the fourth stage of learning in the learner competence model.

8. Thinking Aloud

Lev Vygotsky (a central figure in the sociocultural theory of education ) argues beginner learners tend to think aloud before learning to think inside their heads.

The benefit of sociocultural theory ‘s strategy of thinking aloud is that it makes you really think. You have to talk through what your brain is doing, making those thinking processes explicit.

Teachers will often ask students to speak out loud about what they’re thinking. It not only helps the student be more conscious of their cognitive processes, it also helps the teacher identify areas where the student is going astray.

9. Graphic Organizers

Graphic organizers, also sometimes called cognitive tools , help us to consciously improve our thinking processes. They assist us in:

• Organizing our thoughts.
• Creating connections between things we know.
• Thinking more deeply about something.
• Visualizing processes and procedures.

Examples of graphic organizers include:

• Flow charts.
• Spider diagrams.

The ideal graphic organizer will allow us to spill our thinking out onto a sheet or screen and shuffle and sort our thoughts to help us organize our minds better. By using a graphic organizer, we are more effectively thinking about our thinking.

10. Regulation Checklists

A regulation checklist can either be task-based or generalized.

A task-based regulation checklist is usually created before a task begins. It will:

• List the thought processes required to succeed in the task.
• List the observable outcomes of higher order thinking linked to the task.
• List the checkpoints during the task where people should pause to reflect on their thinking.

A general regulation checklist provides regulation strategies that can be used across any normal task, such as:

• Reminders to pause and reflect-in-practice at regular intervals.
• Prompts to remind students to think about what strategies they are using and whether they are appropriate for the task.
• Self-questioning prompts to remind students to question their choices.
• Quick charts and questionnaires to help people focus on their developments such as KWL charts.

11. Active Reading Strategies

Active reading strategies are strategies that ensure you are concentrating while you read and actually comprehend the information.

Examples of active reading strategies include:

• Underlining text: Underline key or important bits of information to highlight their importance in your mind.
• Using a ruler to read: place a ruler under the sentence you’re reading to help you focus on that line.
• Scan for the main ideas: In informational texts , you can scan for the information you need. Pay close attention to subheadings that give you a clue about where you will find the key information.

My favorite approach to active reading is the reciprocal teaching approach. This approach emphasizes four more strategies:

• Questioning: Ask yourself questions or ask your friends questions to check comprehension.
• Summarizing: Try to sum up the page you just read in one or two sentences to check for comprehension before moving on.
• Predicting: Try to predict how a story will go by looking at the pictures on the cover.
• Clarifying: Ask for clarification from friends or a teacher when you don’t understand rather than just moving on.

12. Active Listening Strategies

Active listening strategies are strategies students use to ensure they are listening attentively.

Some examples of active listening strategies include:

• Turning your body to directly face the speaker.
• Making eye contact.
• Asking questions.
• Nodding when appropriate.
• Repeating what was said to you.

Teachers can directly teach and model active listening strategies to help students develop these metacognitive skills and internalize them for future use.

13. Planning Ahead

When we plan ahead, we often have to think about how we’ll go about a task. We might call it our “plan of attack”.

Planning ahead involves thinking about what we’re going to do in order to complete a task. During your planning phase, you might make decisions such as:

• Deciding what strategies you’ll use when your task, competition or activity begins.
• Tossing up a range of different thinking skills you might use when approaching a task.
• Reminding yourself not to make the same mistakes you made last time.
• Preparing some tools that will help you keep your thinking on track, such as preparing graphic organizers.

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Final Thoughts

When learners “think about their thinking” they are more capable of self-improvement. Metacognitive strategies can be learned, practiced, and made into habits in order to improve learning, studying, and thinking skills into the future.

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A questionnaire-based validation of metacognitive strategies in writing and their predictive effects on the writing performance of English as foreign language student writers

Ruru Zhang, https://orcid.org/0000-0002-5654-2402

Yanling Xiao, https://orcid.org/0000-0003-0025-2024

Associated Data

The original contributions presented in the study are included in the article/ Supplementary material , further inquiries can be directed to the corresponding author.

Introduction

This study—drawing upon data from a questionnaire—examined 503 Chinese university students’ metacognitive strategies in writing (MSW). The focus was on Chinese student writers who are learning English as a foreign language (EFL).

The examination was conducted through a survey on MSW and a writing test administered at the end of the semester. We employed exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) for data analysis. Multiple regression analysis was also adopted for understanding the predictive effects of strategies on writing performance.

The findings provided validity to MSW, including person, task, strategies, planning, monitoring, and evaluating. The different components of MSW were reported to significantly affect the participants’ writing performance. The findings highlight that EFL student writers were aware of metacognitive writing strategies. The MSW survey could be used to assess EFL students’ metacognitive writing strategies and develop curricula in writing strategy training.

Writing instruction can direct learners’ ability to acquire metacognitive writing strategies, particularly those of planning, monitoring, and evaluating, to build their awareness as agents in EFL writing. Relevant pedagogical implications are discussed.

Metacognitive strategies are essential to the process of learning to write when learning English as a foreign language (EFL; Nguyen and Gu, 2013 ; Teng, 2016 , 2019 ; Teng and Yue,2022 ). However, in the Chinese EFL context, for which English writing instruction typically emphasizes grammatical correctness rather than idea development, learners may find it difficult to build an awareness of using metacognitive writing strategies ( Ruan, 2014 ). Through a mixed-methods study, Amani (2014) found that explicit metacognitive strategy instruction had a positive impact on the writing competence of L2 writing students. However, in terms of EFL writing, university EFL students may find it challenging because of their lack of awareness of metacognitive writing strategies ( Teng, 2019 ). In addition, EFL learners in the Chinese context receive limited English language input, making it more challenging to learn to write. Student writers are expected to have repertoires of strategies when learning to write ( Raimes, 1987 ). In particular, they need to build an advanced level of “self-initiated thoughts, feelings, and actions” for them to “attain various literary goals” ( Zimmerman and Risemberg, 1997 , p.76). Hence, metacognitive writing strategies are essential to possible improvements in EFL writing.

Nevertheless, even though students are taught how to plan, monitor, and evaluate their own writing, students may know little about themselves as writers ( Leung and Hicks, 2014 ). They may also not recognize their own writing strengths or weaknesses, tending to overemphasize the latter and overlook any progress they have made or can make in their writing ( Teng, 2016 ). Wenden (1998) argued that metacognitive knowledge is a prerequisite for self-regulation, and metacognitive knowledge is essential to learner autonomy because it “informs planning decisions taken at the outset of learning and the monitoring processes that regulate the completion of a learning task and decisions to remediate; it also provides the criteria for evaluation made once a learning task is completed” (p. 528). Teng and Zhang (2021) argued that there is a dynamic and longitudinal relationship between metacognitive knowledge and reading and writing in a foreign language context. However, teachers may not recognize the importance of metacognitive knowledge in Chinese EFL writing contexts, wherein teaching academic writing is product oriented ( Teng and Zhang, 2016 ). The student writers were passive and found it difficult to keep positive beliefs in writing ( Bruning and Horn, 2000 ). This may be related to learners’ lack of awareness of self-regulation in writing. They may exert more effort learning vocabulary knowledge and grammar for writing, rather than being an agent for writing ( Graham and Harris, 2000 ). Student writers need self-awareness, motivation, and positive behavioral skills for writing ( Zimmerman, 2002 , p.65–66). Metacognitive writing strategies are thus essential to EFL students’ writing performance.

Self-regulation principles, measurements, and practices have a solid ground for enriching second and foreign language learning and teaching ( Teng and Zhang, 2022 ). Through a socio-cognitive approach to writing, Nishino and Atkinson (2015) argued that writing is primarily a cognitive activity and that cognition plays a vital role in writing and its development. To help students become competent English writers and autonomous learners, instructors need to support their development of metacognitive strategies. However, scarce attention was paid to writing strategies from the perspective of metacognition, particularly for low-achieving students in the EFL context. The present study examined Chinese university EFL students’ metacognitive strategies in EFL writing. We aim for the following purposes: (a) to assess the reliability of a new scale, which we named it as metacognitive strategies in writing (MSW) and (b) to explore how different components of MSW predict EFL students’ writing performance. The findings are insightful in helping researchers and classroom practitioners to diagnose the needs of metacognitive strategies in writing and develop guidelines for instructing writing courses for university EFL students. The findings shed lights on how to teach EFL writing and deliver more effective program for writing teacher preparation.

Literature review

Language learning strategies.

Oxford (1990) classified a list of language learning strategies based on cognitive learning theory. These strategies include memory, cognitive, compensatory, affective, social, and metacognitive strategies. Past studies have documented differences in strategy use between more and less successful learners. For example, successful learners use these strategies in larger numbers and at higher frequencies ( Magogwe and Oliver, 2007 ). Most importantly, cognitive and metacognitive strategies are associated with a higher level of language proficiency ( Peacock and Ho, 2003 ). However, contradictory findings were also reported, showing that less successful learners used more strategies than more successful learners did because the former automatized their language learning process ( Oxford and Cohen, 1992 ). Another point worth noting is that unsuccessful learners may adopt a large number of strategies frequently, but it does not necessarily mean that they are able to identify appropriate strategy use. In fact, it was reported that successful learners were able to identify appropriate strategies depending on the task requirements, but unsuccessful learners failed to choose the most appropriate and efficient strategies during the task ( Chamot and El-Dinary, 1999 ).

Although ample research has been reported relating to learners’ proficiency level and strategy use, learner variables, such as cultural background and national origin, could have a strong influence on learners’ strategy use ( Oxford and Nyikos, 1989 ). Therefore, their findings might not be generalizable to learners with completely different cultural backgrounds. In light of this, Lai (2009) conducted a questionnaire survey that investigated the relationships between the language learning strategies used by 418 EFL learners in Taiwan based on learners’ language proficiency and their use of strategies. While the more proficient learners used metacognitive strategies and cognitive strategies most frequently and memory strategies least frequently, the less proficient learners preferred social and memory strategies to cognitive and metacognitive strategies. This finding partially echoes Wu (2008) , who reported that higher-proficiency EFL students in Taiwan used learning strategies more often than lower-proficiency EFL students did, especially the cognitive, metacognitive and social strategies.

Although research documented in the literature examines general language learning strategy use, it is possible that these summarized findings could serve as a reference for the specific examination of metacognitive strategy use during English writing.

Understanding metacognition

Metacognition is multidimensional and domain-general. When we talk about metacognition, we may need to mention the theory of mind ( Flavell, 1979 ). Such theory is the foundation of understanding metacognition. Generally, metacognition is related to self-regulatory capacity because metacognition provides individuals with domain knowledge and regulatory skills that are essential to become an agentive learner in relevant domains ( Schraw, 2001 , p. 7). Metacognition refers to how learners build an awareness of their own thinking processes and executive processes ( Flavell, 1979 ). Metacognition is essential to helping learners regulate their cognitive processes, and finally, becoming an independent thinker and learner. Zhang and Zhang (2019) applied metacognition in second and foreign language learning, and posited that EFL learners need to plan, monitor, and evaluate their cognitive processes for better language learning performance.

Metacognition includes metacognitive knowledge and metacognitive regulation. Flavell (1985) suggested that person, task, and strategy knowledge are three key elements of metacognitive knowledge. Wenden (1998) explained the three elements. For example, person knowledge is the knowledge for the learners to control their cognitive processes. Task knowledge is the knowledge that can be helpful for the learners to understand the purpose, nature, and demands of different task conditions. Strategy knowledge is the knowledge of different important strategies that are helpful for realizing the pre-determined goals. Metacognitive regulation entails three skills: planning, monitoring, and evaluating ( Schraw, 1998 ). Planning refers to the ability to appropriately select the strategies and adequately allocate the resources for completing tasks. Monitoring refers to learners’ capacity to observe their task performance. Evaluating means learners’ capacity to reflect on their learning outcome and the use of different strategies for self-regulation.

Teng et al. (2022) summarized the procedures of understanding metacognition. First, monitoring function and control of cognition are two important functions of metacognition. In order to realize the functions, individuals need to process three major stages, i.e., acquisition, retention, and retrieval. Second, learners need metacognitive knowledge and metacognitive experiences to process the monitoring function. In contrast, they need metacognitive strategies or metacognitive skills to fulfill the needs of control of cognition. Third, metacognitive knowledge, metacognitive experiences, and metacognitive skills are interconnected with each other. Metacognitive knowledge includes person, task, and strategies. Metacognitive experiences include feelings and judgments. Metacognitive skills are important for their metacognitive regulation, which needs learners to plan, monitor, and evaluate their learning process. Finally, reflection is the outcome of the interconnected process of planning, monitoring, and evaluating ( Figure 1 ).

The multifaceted elements of metacognition ( Teng et al., 2022 , p. 171).

Metacognitive strategies in EFL writing

Macaro (2010) maintains that strategic behavior plays a vital role in second language learning success and proposes that strategic behavior should be essential to linguistic knowledge resources. Dornyei (2010) emphasizes that students need a repertoire of appropriate task-related plans, scripts, and self-regulatory strategies that are activated by their ideal L2 selves; that is, learners’ aptitude, motivation, goals, and self-regulatory strategies all interact and affect one another in the SLA process. Writing strategies include rhetorical strategies, metacognitive strategies, cognitive strategies, and social/affective strategies ( Wenden, 1991 ; Riazi, 1997 ). Writers explore rhetorical strategies to organize and present their ideas based on the writing conventions of the target language. Metacognitive strategies are used to monitor the writing process consciously and evaluate the effectiveness of writing actions. Cognitive strategies are used to implement actual writing actions. Social/affective strategies are employed to interact with others and to regulate emotions, motivation, and attitudes in writing.

Wenden (1991) classifies writing strategies based on metacognitive and cognitive frameworks. She distinguishes general executive metacognitive strategies of planning, self-monitoring, and self-evaluating from more specific cognitive strategies, such as clarification, retrieval, resourcing, avoidance, and verification. Each of these metacognitive strategies is discussed below.

Planning for writing involves thinking and self-questioning strategies such as identifying one’s purpose, activating background knowledge, and organizing ideas. Planning is not limited to a specific stage of writing but rather appears recursively throughout the writing process. Flower and Hayes (1981) identified three different types of planning strategies based on the focus of the goal: (1) generating ideas; (2) setting procedural goals; and (3) organizing. Generating ideas includes retrieving information from long-term memory, revising old ideas to incorporate new information, drawing inferences, making connections, and looking for examples, contradictions, and objections. Setting procedural goals includes content goals (e.g., plans for content, text structure and audience, and criteria for evaluation) and process goals (how to proceed, generated by the writer, done at any time during the composing process, followed or preceded by generating ideas, revising strategies, etc.). The third strategy (organizing) includes selecting the most useful materials produced during the generating process and organizing them in the writing plan. Organizing strategies include grouping and sequencing ideas, deciding on the presentation of the text, planning the introduction and conclusions, and structuring the text based on a particular genre. Furthermore, in using these strategies, it is essential to consider the audience, topic, and rhetorical knowledge. Planning in EFL writing determines how writers write in subsequent stages. It engages them in metacognitive activities that allow them to consider the purpose and goals for writing, identify their audience, decide upon voice, and generate a framework for their essays.

Monitoring involves conscious control and regulation of the writing process. Hayes and Flower (1980) include self-monitoring in their model of the cognitive processes of writing, noting that the ability to self-monitor the composing process is an important part of writing strategies. Charles (1990) claims that self-monitoring makes it easier for L2 students to avoid uncertainty about any part of their text, to find direct answers to their queries and to encourage them “to look critically and analytically at their writing and to place themselves in the position of readers” (p. 289). The more important functions of self-monitoring are controlling, directing, and sequencing the composing processes and one’s progress in the task. Monitoring allows the writer to decide whether something needs to be retrieved, whether new ideas need to be further generated, or whether a given subprocess has ended. Monitoring allows L2 writers to evaluate the effectiveness of writing strategies and how and when to check the outcomes of problem-solving processes and strategically regulate the processes according to cognitive goals ( Mayer, 1999 ).

Self-evaluating—experiencing the quality of one’s writing in relation to one’s goals—is crucial for developing an individual’s perception of writing. In self-evaluation, students can recognize weaknesses, identify needs, and make changes ( Zimmerman, 2002 ). In cognitive research, evaluation has been characterized as a strategy for considering the outcome of the undertaken task, an essential metacognitive strategy that successful learners need to execute and control.

Empirical studies on the use of metacognitive writing strategies

Various studies have been conducted on EFL students’ use of metacognitive writing strategies. Employing think-aloud protocols and immediate retrospective interviews, Chien (2012) investigated the differences in writing strategies and English writing achievements of 20 low-achieving and 20 high-achieving student writers in Taiwan. Chien found that high-achieving student writers were more aware of and focused more on, formulating their position statements when planning, generating, revising, and editing their essays and focused more on correcting grammatical and spelling errors. Teng and Zhang (2016) validated questionnaire-based self-regulated strategies in EFL writing and highlighted planning, monitoring, and evaluating in EFL writing. Teng and Huang (2019) also suggested that learners’ self-regulated strategies in writing, as well as their English proficiency and language learning experiences, and significantly influenced their EFL writing. In a recent publication ( Teng et al., 2022 ), two experimental studies were reported. Study 1 adopted a factorial design using exploratory and confirmatory factor analysis to validate a self-regulatory writing strategy questionnaire. Study 2 assessed the predictive effects of the different components of the scale on students’ writing performance. The results supported the construct validity for the six strategy factors, i.e., writing planning, goal-oriented monitoring, goal-oriented evaluation, emotional control, memorization, and metacognitive judgment. The factors also predicted writing performance. Zhang and Qin (2018) also validated the newly developed scale on metacognitive strategies in a multimedia writing context. The results provided evidence for the validation of planning, monitoring, and evaluating strategies. In an early empirical study on the importance of planning in EFL writing, Graham et al. (1995) examined differences between expert and less-skilled L2 writers. They found that expert L2 writers spent considerable time planning and appeared to have higher-level plans and self-conscious control of their planning. In contrast, less-skilled EFL writers were less likely to use knowledge of textual structure in planning, to use heuristic strategies in searching their memory for content, or to establish goals to direct the writing process and were more likely to engage in “knowledge telling” (i.e., writing everything they knew about a topic and stopping when they felt that they had written down everything they knew). Less-skilled writers did not write with goals or plans in mind; rather, they tended to generate ideas through free writing and usually did not organize those ideas. As shown in a longitudinal study ( Teng and Zhang, 2021 ), learners’ L2 writing development was dependent on their initial level of metacognitive knowledge. This is evidence for the strong correlation between metacognitive knowledge and writing.

Nguyen and Gu (2013) explored the impact of strategy-based instruction on promoting learner autonomy (operationally defined as learner self-initiation and learner self-regulation) of students at a Vietnamese university; 37 students were in an experimental group, and 54 students were in two control groups. After an 8-week metacognition training intervention, students in the experimental group were found to have improved their planning, monitoring, and evaluating of a writing task more than those in the two control groups. The findings suggest that strategy-based instruction on task-specific metacognitive self-regulation improves learner autonomy and writing performance. Teng (2020) also incorporated training of metacognitive strategies for EFL learners. There were two groups of learners, i.e., those with group feedback guidance and those with self-explanation guidance. The results supported the positive effects of group metacognitive support on EFL students’ writing. EFL students need to build a certain level of metacognitive awareness to manage themselves as writers.

Bai et al. (2014) conducted a questionnaire survey to explore the relationship between 1,618 Singapore primary school pupils’ reported use of strategies in learning to write and the correlation with their English language proficiency. They found that participants used a wide range of writing strategies at medium frequency. They also reported a significant correlation between the participants’ English language proficiency and the use of writing strategies such as planning, text-generating, revising, monitoring and evaluating, and resourcing. Similar results were also found in Bai and Guo (2021) , wherein high achievers reported higher levels of motivation (i.e., growth mindset, self-efficacy, and interest) and self-regulated learning strategy use than the average achievers, and average achievers reported more strategy use than the low achievers, Ma and Teng (2021) collected qualitative data from two undergraduate university students learning English as L2 in Hong Kong to explore their use of writing strategies. They reported that both students realized the importance of self-evaluation and revision. It seems that the students perceived affordances in the kind of writing that enabled them to play an active role in seeking, interpreting, and using teacher feedback to perform the evaluation and modification of their own work. However, variations in engagement in the process of learning to write and their metacognitive knowledge development were also detected. For example, students’ varying degrees of engagement may result in various degrees of developing metacognitive awareness. Teng et al. (2022) validated a new instrument, i.e., the Metacognitive Academic Writing Strategies Questionnaire (MAWSQ). Analyses were conducted through a series of Confirmatory factor analyses (CFA). Results supported two hypothesized models, i.e., an eight-factor correlated model and a one-factor second-order model. Model comparisons supported the role of metacognition as a higher-order construct. Metacognition also explains the eight metacognitive strategies, including declarative knowledge, procedural knowledge, conditional knowledge, planning, monitoring, evaluating, information management, and debugging strategies. Those strategies also significantly influenced EFL writing performance.

Overall, the studies on metacognition development reviewed in this section highlight the importance of the high-level cognitive processes involved in composing, the development of the autonomous and self-regulated use of effective writing strategies, and the formation of positive attitudes about writing. Metacognitively oriented learners are aware of both their own learner characteristics and the writing task and are able to select, employ, monitor, and evaluate their use of metacognitive strategies.

The present study

Metacognition functions as an important predictor in EFL writing performance. We aim for two purposes in the present study. First, we attempted to validate a questionnaire on metacognitive strategies in writing. Second, we assessed the predictive effects of different metacognitive strategies in the outcome EFL writing. The present study sheds light on learners’ awareness and use of metacognitive writing strategies. The present study includes two questions:

• What is the evidence to support the validity and reliability of metacognitive strategies in writing?
• What is the evidence for the predictive effects of metacognitive strategies on EFL writing proficiency?

Materials and methods

Participants.

The present study included 503 participants. They were undergraduate students at a university in China. They were first-year students with Chinese as their first language and English as a foreign language. They had received at least 6 years of formal English instruction. Writing is a subject to be taught in college English and a compulsory course for all the participants. We selected the participants because they were all enrolled in a university English course. The first author was teaching the participants, and the sample of participants was a convenient sample. Among the 503 students, 351 were men and 152 were women. An unequal gender balance may be because most of the students were from science and engineering majors. Originally, there were 700 students who responded to the questionnaire. We finally selected data from 503 students for data analysis. Some participants’ data were excluded because of missing values or because some were unable to take the writing test. They attended the study voluntarily by signing the consent form.

Questionnaire development

The questionnaire, which was named Metacognitive Strategies in Writing (MSW), was developed through item generation, reference consultation, initial piloting, psychometric evaluation, and exploratory factor analysis (EFA) in a pilot study. We first invited 10 students to reflect on their writing practices and strategies. The students were mainly interviewed about the strategies they adopted for writing. We generated approximately 50 items based on analyzing the transcriptions of learners’ interviews. In the next stage, we consulted relevant literature on metacognition, self-regulation, and language learning strategies ( Schraw and Dennison, 1994 ; Oxford, 2013 ; Teng et al., 2022 ). We selected the items that fit with metacognition theories. In the third stage, we invited the 10 students to check the items. In the fourth stage, which was psychometric evaluation, we invited two researchers in L2 writing to assess the items. Based on the comments, we finally removed 10 items. In the final stage, we ran an EFA with a sample of 360 students with similar backgrounds. We deleted 10 items with unsatisfactory factor loading values. The final questionnaire includes 30 items, which are in the Appendix .

This questionnaire was a novel one as it was based on metacognition theory, through which the focus was on understanding metacognitive knowledge and regulation in learning to write. We adopted a seven-point Likert scale (i.e., from 1, Strongly disagree to 7, Strongly agree). MSW focuses on metacognitive knowledge and metacognitive regulation. Metacognitive knowledge includes three factors, i.e., person, task, and strategies. Metacognitive regulation includes three factors: planning, monitoring, and evaluating. Cronbach’s alpha, which ranged from 0.81 to 0.90 for the six factors, ensured the internal consistency of responses to the items. The questionnaires were administered to the participants in Chinese. The author translated into Chinese while a research assistant was invited to check the translated items through back translation.

Writing test

A writing test from IELTS (writing task 2) was adopted to measure learners’ writing proficiency. Students were required to write at least 250 words within 1 h. Students were asked to respond to the topic provided by giving and justifying an opinion, discussing the topic, summarizing details, outlining problems, identifying possible solutions and supporting what they wrote with reasons, arguments and relevant examples. The topic proposed the possible influence of social media sites on personal relationships.

The marking scheme was consistent with the writing rubrics in IELTS. However, we adjusted it to fit with our school assessment needs. Each learner was awarded with six marks for task response, coherence and cohesion, lexical resource, and grammatical range and accuracy. The maximum possible score was 24 points. A total of 40 English teachers were paid to rate the writing. The teachers did not know the participants’ identities. They also joined a training session on the marking scheme. Disagreements on marking were subject to further discussion. The Cronbach’s alpha for the test was.85, indicating acceptable reliability.

We invited 20 EFL teachers to help us distribute a QR code to the students through WeChat group. The students spent an average of 6 min completing the questionnaire. The writing test was administered as an exercise for all students during class. They needed to complete it within 1 h. The format for the writing test was a paper-and-pencil format. All participants received the same format for the questionnaire and the writing test.

Data analysis

The final dataset was run through a series of confirmatory factor analyses (CFAs). STATA was used for data analysis. CFA is used to test a theoretical model by confirming factors, correlations, covariance patterns, and residual or error values within a data matrix ( Byrne, 2016 ). We used the maximum likelihood (ML) estimation method. The model fit was evaluated through the following statistics: a chi-square statistic, the degrees of freedom (df), p value, the ratio of chi-square χ 2 divided by the df, the root mean square error of approximation (RMSEA), the standardized root mean square residual (SRMR), the comparative fit index (CFI), and the Tucker–Lewis Index (TLI; DiStefano and Hess, 2005 ). The following criteria are a relatively good fit between the hypothesized model and the observed data: the value of RMSEA should be close to 0.06, the value of SRMR should be close to 0.08, and the values for CFI and TLI should be close to 0.95 ( Hu and Bentler, 1999 ). Finally, multiple regression analysis was adopted to evaluate the predictive effects of MSW on students’ writing proficiency.

Descriptive statistics

The kurtosis and skewness values for the metacognitive strategies in writing, as well as the mean and standard deviation, are shown in Table 1 . The means of the six factors ranged from 3.346 to 4.079, with the two factors, monitoring and evaluating, greater than 4. There were no noticeable variations based on the standard deviation values.

Means, standard deviations. and normality test.

Exploratory factor analysis in the pilot study

Exploratory factor analysis was conducted on a sample of 360 learners from similar background in the pilot study. We examined the adequacy of the sample. The Kaiser-Meyer-Olkin value was 0.914, which appropriate for EFA ( Tabachnick and Fidell, 2001 ). Bartlett’s test of sphericity was significant, p < 0 .001; thus, the matrix was adequate for factor analysis. We adopted principal component analysis as a factor extraction method. We finally extracted six factors that explained 57.411% of the variance ( Table 2 ). The scree plot showed a considerable drop after the sixth factor, for which we excluded other possible factors. Based on key theories in metacognition, we named the six factors as following: person, task, strategies, planning, monitoring, and evaluating.

Extraction results for the six factors.

The six factors’ eigenvalues exceeded 1. The next step was to examine the factor loadings. We deleted 10 items with factor loadings lower than 0.4. The final version included 30 items across six factors ( Table 3 ). Items’ factor loadings ranged from 0.534 to 0.772, while communality ranged from 0.531 to 0.754. The items hence fit their respective factors well.

Results on factor loadings and the communality.

Construct validity of metacognitive strategies in writing through CFA

The data fitness metrics for metacognitive strategies in writing are displayed in Table 4 . Table 4 shows that the RMSEA was 0.073, less than 0.08, indicating a good fit; CFI, TLI, CNFI, IFI, and GFI all exceeded 0.9, which was ideal for adaptability. Although the χ 2 /df was 7.916, larger than 3, the scale on metacognitive strategies in writing still showed reliability when taken as a whole.

Model fit indices for metacognitive writing strategies.

According to Figure 2 and Table 5 , the factor loadings for Person, Task, Strategy, Planning and Evaluating were all greater than 0.5, while Monitoring was 0.41. Additionally, the average variance extracted (AVE) for each variable was 0.47, and the model’s convergent validity was good, as evidenced by the composite reliability (CR) being 0.84, indicating that the model had satisfactory convergent validity.

A first-order model of metacognitive strategies in writing. Prs, Person; Tsk, Task; Str, Strategy; Pln, Planning; Mnt, Monitoring; and Evl, Evaluating.

Convergent validity of the model.

Predictive effect of metacognitive strategies in writing on EFL writing

Figure 3 presents the correlations between metacognitive strategies in writing and L2 learners’ writing proficiency in English. The findings indicated that each of the six metacognitive strategies was significantly correlated with learners’ English writing performance. Writing performance (WP) was correlated with Person ( r  = 0.264), Task ( r  = 0.500), Planning ( r  = 0.584), and Monitoring ( r  = 0.408). Strategy ( r  = 0.470) and Evaluating ( r  = 0.470) were significantly correlated with WP.

Spearman correlation for metacognitive writing strategies and L2 learners’ proficiency in English. Persontotal, Person; Tasktotal, Task; Strategytotal, Strategy; Planningtotal, Planning; Monitoringtotal, Monitoring; and Evaluatingtotal, Evaluating.

Moreover, we adopted a structural equation model to investigate the degree to which metacognitive strategies in writing predicted learners’ L2 writing proficiency. Table 6 presents the model fitness indices. For our model, seven indices (i.e., χ 2 /df, RMSEA, CFI, TLI, NFI, WIFI, and GFI) indicated acceptable model fit ( Table 6 ). Figure 4 shows a structural equation model of the relationship between metacognitive strategies in writing and writing proficiency. The six variables on the left side of the model represent the six factors of metacognitive strategies in writing. The only rectangular variable on the right side of the model was EFL learners’ writing proficiency. The findings demonstrated that metacognitive strategies in writing had a predictive power of 0.65 for L2 learners’ writing proficiency, indicating that it could account for 65% of the variances in writing performance.

Model fit indices for metacognitive writing strategies on writing performance.

The structural equation model of metacognitive strategies in writing proficiency.

Regression analysis was employed in the study to show the extent to which each factor impacts writing performance. The results presented in Table 7 demonstrate that all factors significantly predicted writing competence ( p  < 0.001), with the exception of Strategy ( p  = 0.344). Planning had the greatest effect on writing abilities, and Task had the least effect. Notably, monitoring and evaluating also had a great effect on EFL learners’ writing proficiency. According to the findings, there was no multicollinearity among the strategies, as indicated by the variance inflation factor (VIF), which was less than 3. In addition, the residuals adhered to a normal distribution, as shown in Figure 5 . This offered a trustworthy foundation for the regression analysis results.

Linear regression results.

Normal P–P plot of regression standardized residual.

Discussion and conclusion

Overall, the present study aims to answer two research questions. The first research question entails the validation of a newly developed scale, which we named Metacognitive Strategies in Writing (MSW). The scale was developed based on metacognition theory. The findings supported the factorial structure of the scale. The second research question aims to answer the predictive effects of different factors of MSW in writing performance. Overall, the findings provided evidence for the factorial structure of MSW. The findings also suggested the predictive effects of different factors on writing performance.

Validation of MSW

First, MSW is with satisfactory psychometric properties. The six factors were reliable in terms of conceptual and empirical evidence. The six factors were distinct but correlated with each other. Consistent with previous studies ( Teng et al., 2022 ), metacognition is an important construct that can explain the significant correlations of different lower-order metacognitive dimensions in writing. In line with Schraw and Moshman (1995) , metacognition is a domain that can explain self-regulatory capacity. The present study thus provides insights into metacognition theory, which can entail person, task, strategies, planning, monitoring, and evaluating ( Schraw and Dennison, 1994 ). These strategies are interconnected and reflect the metacognitive process in writing. To build metacognitive awareness, learners need to be engaged in self-reflection and controlling of cognition ( Paris and Winograd, 1990 ). In terms of writing, student writers need to assess their knowledge states and executive abilities to orchestrate different dimensions of metacognitive awareness. Overall, the sum of the six strategies in writing indicates EFL student writers’ overall level of metacognitive awareness in writing.

The six factors were interpreted through metacognitive knowledge and regulation. The two paradigms were also conceptualized in early studies ( Flavell, 1979 ; Schraw, 1998 ; Wenden, 1998 ). In the present study, the two paradigms can represent key elements of metacognition. Person, task, and strategies represent learners’ beliefs and knowledge about themselves. Planning, monitoring, and evaluating reflect the process of cultivating one’ self-regulatory capacity for learning to write ( Teng and Zhang, 2016 ; Teng et al., 2022 ). The findings showed a positive and significant relationship between metacognitive knowledge and regulation ( Pugalee, 2001 ; Teng, 2016 ). We may need to reconsider the strong connection between metacognitive knowledge and regulation. The positive correlation may reflect the need of both knowledge and regulation in learning to write. For example, EFL students may need cognitive, metacognitive, and regulatory skills and strategies for writing ( Teng, 2020 ). The importance of metacognitive knowledge and regulation may reflect the argument by Wolters (1999) that learners’ engagement, effort, and achievement are influenced by their metacognitive knowledge and regulation. Hence, metacognition is essential to the development of self-regulated capacity ( Efklides, 2008 ), build identity as a student writer ( Zimmerman and Risemberg, 1997 , p.76), and develop self-awareness in processing their second and foreign language learning ( Zhang and Zhang, 2019 ).

Overall, the MSW data suggest that the student writers adopted metacognitive knowledge, i.e., person, task, and strategies, to understand their strengths and weakness in writing, demands in writing, and solutions for solving problems in writing. The data also suggest that the planning strategy should be used. In the planning stage, the student writers directed their attention to fulfilling the goal of the task, planning thoroughly, evaluating the relevance and effectiveness of ideas, and eliminating inappropriate examples. Data regarding the second subscale (monitoring) reflected that students tended to use some metacognitive monitoring strategies. During the monitoring stage, the student writers focused on the overall essay development, concentrating on expanding and developing their initial ideas, evaluating their essay for clear development and focus/unity, and ignoring interruptions posed by language constraints, such as grammar and vocabulary. For the third subscale (self-evaluating), student writers tended to use certain metacognitive strategies. Student writers prioritized their attention to evaluating the unity and effectiveness of their writing before editing local errors, such as grammar, vocabulary, mechanics, and sentence variation.

Predictive effects of metacognitive strategies in writing

The findings suggest the predictive effects of metacognitive strategies in writing. The results confirmed that the metacognitive strategies significantly predicted learners’ writing performance, which was consistent with previous studies ( Teng and Huang, 2019 ; Teng et al., 2022 ). One reason is that student writers’ meager metacognitive knowledge base could result in unsatisfactory cognitive monitoring of production and progress toward the writing task goal, which, in turn, may also affect their writing performance ( Teng et al., 2022 ). For example, lower-level writers tended to be bound to the local areas of writing, focusing on language correctness, while higher-level writers tended to focus on developing ideas and revising at the discourse level, saving editing until later ( Teng and Huang, 2019 ). As supported in previous studies ( Chien, 2012 ; Bai et al., 2014 ), higher level student writers were more aware of metacognitive strategies and used them more frequently in writing.

The argument revealed, at least for this particular sample and the chosen test, a strong and significant link between the writing abilities of EFL students and the factors of person, task, strategy, planning, monitoring, and evaluation. The EFL learners’ writing performance variations were accounted for by the six metacognitive components. The findings complement cognitive writing model of Flower and Hayes (1981) , which recognizes the abilities in process writing such as planning, monitoring, and reviewing. Writing necessitates the adaptive use of emotional strategies, performance strategies, and cognitive strategies ( Teng et al., 2022 ). The effectiveness of the strategies highlights the personal, behavioral, and environmental impacts on the regulatory capacity in learning to write ( Zimmerman and Risemberg, 1997 ).

In our study, person and task significantly predicted writing performance with a large effect size. According to earlier research ( Brown, 1987 ; Schraw, 2001 ), learners who have declarative, procedural, and conditional knowledge are more likely to become strategic learners. These results provide evidence for the idea that to master writing, EFL learners need to be able to distinguish among the various strategies, employ the appropriate strategies, and apply these strategies in their writing. The results also support earlier research that metacognitive knowledge is crucial for encouraging active involvement in applying their understanding of the writing process, recognizing the kinds of strategies useful in the growth of writing, and improving students’ writing outputs ( Ruan, 2014 ).

In terms of metacognitive regulation, planning, monitoring, and evaluating are also important for writing performance. The effect size was quite large in the current study, for which we can detect similar results in previous studies ( Teng, 2019 ; Teng et al., 2022 ). The writing abilities of students who were more self-controlled in their writing were higher in terms of goal setting, time management, and planning for writing resources ( Teng and Zhang, 2016 ). We argue that Chinese EFL students need an awareness of planning ahead and monitoring and evaluating their planning tactics to produce successful written essays. The success of EFL academic writing depends heavily on this method. Academic writing development may be seen as a complex process for student writers because it depends on how strategically they seek information and modify their planning techniques. Students who have prepared well for academic writing are typically those who have a high level of metacognitive awareness of their writing-related objectives ( Zhang and Qin, 2018 ). When composing their essays, lower-level writers often experienced difficulty in transferring ideas to paper during the planning, monitoring, and self-evaluating stages. The constraints in the lower-level writers’ knowledge system, including their limited linguistic competence (grammar and vocabulary), their confusion about their role as writers, their lack of knowledge strategies for overcoming writing difficulties, and their lack of knowledge of how and when to apply those strategies, impeded their composition of a meaningful essay. Consequently, many students tended to simultaneously engage in a few different stages of writing—planning, composing, revising, and editing—without any extra attention resources to monitor the overall unity and coherence of the essay, thus making the essay messy and confusing.

Limitations and implications

Despite the positive findings, we still need to acknowledge some limitations of this study. First, the strategies described in the questionnaire were still scarce, although we showed excellent content validity. Due to the limited amount of time the learners could invest in data collection, we did not assess metacognitive experiences, another crucial component of metacognition. Interview data with students were not conducted to yield adequate methods connected to metacognitive experiences. Second, a self-report questionnaire served as the foundation for this study. Because they are dependent on the use of self-reported information, surveys may not fully reflect learners’ actual metacognitive awareness and activities. The quantitative data in future studies should be triangulated with interview data. Third, the writing test should include additional activity categories that can gauge various writing abilities. We only used one writing performance indicator. The performance of student writers may also be impacted by individual characteristics, including their language learning experiences and English proficiency level ( Teng and Huang, 2019 ). Future studies might look at learners’ individual differences and their use of different metacognitive strategies.

However, there are also some implications based on the findings. Our findings suggest directions for pedagogy as well as future research. Considerations include issues of focus on form, development of metacognitive awareness to support metacognitive knowledge and strategies, and appreciation of the many aspects of metacognitive awareness that good L2 writing entails.

Data collected from the surveys suggest a strong connection between EFL student writers’ metacognitive knowledge and the regulation strategies they employ. Helping students become more aware of themselves as writers and the metacognitive resources upon which they can draw during the writing process may help them develop their writing competence. Language teachers and instructors should clearly instruct the importance of metacognitive strategies for EFL student writers. Related to this, metacognitive training should help students develop such awareness in learning to write. However, an important step in developing productive pedagogy for metacognitive training is assessing learners’ needs and understandings of their metacognitive strategies. The MSW might potentially contribute to EFL writing assessment in China. The MSW monitoring subscale identified the important first step in writing—planning—as a potential problem. So far as these Chinese EFL non-English major student writers were concerned, regardless of their level of English class or their majors, it seems that many of them may need to faster a metacognitive awareness. As a result, it might be helpful to provide these students with additional lessons on metacognitive strategies to address their concerns and the problems evident in their English writing. While dealing with grammatical errors is essential to writing instruction, the students should focus not only on identifying the errors and fixing them but also on finding out why they make those mistakes and how to avoid making them again. In other words, instead of correcting the errors, they should also develop their awareness of metacognitive strategies to improve their overall language competence. The instructors may also explicitly teach and demonstrate effective strategies to enhance vocabulary acquisition, such as making learners aware of lexical morphology (including word roots and suffixes), synonyms, antonyms, word categories, and similar spellings.

Clearly, it should not be assumed that learners who do not score high on norm-referenced assessments of their L2 writing need to focus exclusively on their metacognitive strategies, even though that is where they may think they need to work. Rather, these learners need to consider not only metacognitive strategies but also discourse organization and considerations of audience, voice, and genre ( Hyland, 2007 ). It is only through an approach raising their awareness of the various aspects that contribute to good writing and through work on writing and revision strategies that they will progress optimally. Additionally, to implement these recommendations for pedagogy, teachers themselves must have substantial knowledge, professional development, and practice regarding approaches to support L2 writing. In the Chinese context, knowledge must be processed and understood in light of the metacognition and experiences of students, colleagues, and the community.

Data availability statement

Ethics statement.

The studies involving human participants were reviewed and approved by Hainan University. The patients/participants provided their written informed consent to participate in this study.

Author contributions

CQ: Coordinated the study, drafted, and revised the manuscript. RZ: Data collection, drafted literature review. YX: Participated in the design of the study, revised the manuscript and performed the statistical analysis and data interpretation. All authors proofread and approved the final manuscript.

This article is supported by the Project from the Education Department of Hainan Province, Project number: Hnky2020ZD-9.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2022.1071907/full#supplementary-material

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Teaching Connections

Advancing discussions about teaching, integrating reflections on assignments to develop metacognitive awareness.

Leslie LEE Department of English, Linguistics and Theatre Studies, Faculty of Arts and Social Sciences (FASS)

Leslie shares his experience of adapting Tanner (2012)’s approach to promoting metacognition amongst undergraduates, i.e. administrating self-questions to raise students’ metacognition in his undergraduate linguistic morphology course.

Image by ijeab on Freepik

Metacognition refers to the knowledge that we have about our own cognitive processes (Flavell, 1979). It is recognised as an important aspect of learning (National Research Council, 2000, 97).

Tanner (2012) discusses ways to promote metacognition amongst undergraduate students of biology, including administrating self-questions for learners to ask “in the process of planning, monitoring, and evaluating their learning”. Adapting Tanner’s self-questions to linguistics, Vallejos and Rodríguez-González (2021) explored the impact of employing self-questions to raise undergraduates’ metacognition as they did their assignments, and found that these helped students to:

• Notice learning concerns and self-capabilities;
• Raise awareness about learning strategies and develop self-efficacy;
• Better communicate needs and challenges when completing a task;
• Highlight the importance of time management and teamwork;
• Recognise that asking for help is key to monitor their understanding and learning;
• Reflect upon research skills and persona growth

Inspired, I adapted a subset of the questions (see Table 1, organised according to the metacognitive processes of planning, monitoring , and evaluating ) to three iterations of an undergraduate linguistic morphology course I offered between 2021 and 2023. These were implemented as reflection questions 1 that accompanied an assignment, and accounted for a nominal percentage of the continuous assessment marks, graded on a “Complete/Incomplete” basis. There were no word-count restrictions and I emphasised to the students that there were no “correct” or “wrong” responses.   

Table 1 Reflection questions

Unlike Vallejos and Rodríguez-González (2021), who administered their survey only once in their courses, I was curious if the repeated administration of the survey over a semester would have any additional benefit to the students. Hence, I administered my survey four times over the semester: once accompanying each of the three homework assignments, and once with the final term project. In the 2022 and 2023 iterations, the final survey included two additional questions:

• Do you agree with this statement? “The reflection questions have benefited me in my learning and self-growth.”  
• What (positive or negative) impact has responding to these reflection questions over the semester had on your learning and self-growth?

Due to space constraints, I will not discuss the students’ responses to the questions in Table 1 here, and focus instead on responses to these latter two questions.

A small minority (<9%) who read the course in 2022 and 2023 felt that they did not benefit from the reflections. The reasons provided suggested that these students either already possessed a high degree of self-awareness or were not invested in reflecting:

• “I expected myself to face these challenges and I know my strengths especially since this is my last semester of uni.”
• “(…) maybe because I don’t really put too much effort into it (…) But I think it helped me reflect on the journey that I had in this module, which might have helped in my learning and self-growth, but I’m not introspective enough to know.”

Other negative impacts of responding to reflection questions were along the lines of:

• “(…) sometimes it’s really hard to come up with an answer, maybe I am just not self-aware at all… But maybe that is what this is for??”
• “I think a negative impact may just be worrying whether I answered the reflection question uniquely enough from the last time I did it or wrote long enough.”

Nonetheless, an overwhelming majority (91%) agreed that they benefited. Positive impacts identified by the students included the following:

• “The reflection questions did help me to think back on how I approached each assignment and allowed me to use what worked and discard what didn’t in previous assignments.”
• “Thinking about the instructor’s goal helped me reflect on the purpose of the assignments and to illuminate how they were reinforcing my learning no matter the stress and suffering of going through them. I understood how they were helping me to apply what I learnt as knowledge progressed.”
• “it provides a feedback channel for me to convey my learning concerns to [the instructor] and I saw my concern being addressed in one of the assignment feedbacks.”
• “I think that they helped me to more or less process my thought processes (…) figure out what exactly I had struggles with (…) it also helped me to process my disappointments in my work, but allowed me to consider how I can perhaps do better in other modules or what good strategies there could possibly be.”

Students also saw benefits in completing multiple reflections over the semester:

• “I was able to reflect on my own growth throughout the module as well as work on improving my own personal workflow and productivity habits.”
• “The fact that the questions are the same caused me to compare myself in relation to the periods I did each survey (…) this allowed me to improve myself…”
• “I became more aware of how I learn. I made changes and adopted new strategies in order to improve. I will try to keep those in mind and reflect on my future work as well.”

Overall, while a small minority did not see any benefits to the reflections, an overwhelming majority of students did and appreciated the exercises. There is evidence that implementing regular reflections on assignments over the semester can help develop students’ metacognitive awareness, and that this effect is not simply limited to the assignment or course at hand, but has the potential to be more long-term and benefit students’ learning elsewhere, more globally. This is consistent with previous studies that have studied the effect of reflection on understanding and transfer of learning (see e.g. Lin & Lehman, 1999 and references therein).

• One can conceive of many different types of “reflections”. The questions used here did not require students to reflect on the content of what they were learning, but on their learning process .

Flavell, J. H. (1979). Metacognition and cognitive monitoring. A new area of cognitive-developmental inquiry. American Psychologist , 34 (10), 906-11. https://psycnet.apa.org/doi/10.1037/0003-066X.34.10.906

Lin X., & Lehman, J. D. (1999). Supporting learning of variable control in a computer-based biology environment: Effects of prompting college students to reflect on their own thinking. Journal of Research in Science Teaching , 36 (7), 837-58. https://doi.org/10.1002/(SICI)1098-2736(199909)36:7%3C837::AID-TEA6%3E3.0.CO;2-U

National Research Council. (2000). How People Learn: Brain, Mind, Experience, and School: Expanded Edition. The National Academies Press. https://doi.org/10.17226/9853 .

Tanner, K. D. (2012). Promoting student metacognition. CBE–Life Sciences Education , 11 (2), 113-20. https://doi.org/10.1187/cbe.12-03-0033 .

Vallejos, R., & Rodríguez-González, E. (2021). The impact of metacognition in linguistics courses . [Poster Presentation, organized session on Scholarly Teaching in Linguistics in the Age of Covid-19 and Beyond]. 2021 Annual Meeting of the Linguistics Society of America. https://lingscholarlyteaching.org/2021/01/05/poster-b7/ .

• Open access
• Published: 09 October 2023

Writing metacognitive strategy-based instruction through flipped classroom: an investigation of writing performance, anxiety, and self-efficacy

• Rahele Khosravi 1 ,
• Adel Dastgoshadeh 2 &
• Kaveh Jalilzadeh   ORCID: orcid.org/0000-0003-3113-512X 3  

Smart Learning Environments volume  10 , Article number:  48 ( 2023 ) Cite this article

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This study aimed at exploring the effect of implementing writing metacognitive strategies via flipped classrooms on the Iranian EFL learners' achievement, anxiety, and self-efficacy in writing. The study involved 45 intermediate learners of both genders, selected using a random convenience sampling method. The participants' English proficiency was measured by the Preliminary English Test, and they were placed in two groups: experimental group (23 learners) and control group (22 learners). In the former group, the students were exposed to 5 distinct types of metacognitive strategies over the course of 10 flipped classroom sessions, while the latter group received writing metacognitive strategy-based instruction in a traditional classroom setting. The data collection process involved administering the Second Language Writing Self-Efficacy Scale, two intermediate writing tasks, and the Second Language Writing Anxiety Scale. The collected data were analyzed using a one-way ANCOVA. The findings evidenced considerable enhancement in the writing performance of the students who underwent instruction through flipped classrooms in comparison to those in the traditional classroom refsetting. Furthermore, the results demonstrated that the utilization of writing metacognitive strategies in flipped classrooms resulted in a substantial rise in students' writing self-efficacy, while simultaneously leading to a decrease in their writing anxiety.

Introduction

In recent decades, the field of education has experienced substantial and transformative changes in its landscape, with writing gaining increased attention as a vital mode of communication and a marker of academic success in higher education. Scholars such as Kellogg ( 1999 ) have emphasized the role of cognitive processes and strategies in shaping the success of writers. A writer's ability to effectively employ strategies, procedures, and cognitive frameworks within the confines of their working memory plays a pivotal role in the writing process. As a result, students aiming to become proficient writers need to not only choose appropriate strategies but also execute them effectively. (Bai et al. ( 2014 ) and Chien ( 2012 ) in their studies emphasized on a positive association between the application of writing strategies and the development of writing proficiency.

Traditionally, writing instruction has often focused on the end product, the written text itself. However, a shift has been advocated towards a more process-oriented approach in educational settings (Chien, 2012 ; Silva & Brice, 2004 ). This shift aligns with the recognition that the strategies employed during the writing process greatly influence the outcome. An effective approach to teaching these strategies is Strategy-Based Instruction (SBI), which has been shown to significantly impact learners' strategy utilization, both in terms of quality and quantity (Hu, 2005 ; Ong & Zhang, 2013 ; De Silva, 2015 ; Stavropoulou, 2023 ).

Among the array of strategies, metacognitive strategies are particularly notable as advanced cognitive abilities, as underscored by O'Malley and Chamot ( 1990 ). These tactics encompass tasks like devising plans, overseeing progress, and making assessments. Regarding writing, metacognitive strategies assume a vital role. Individuals possessing adept metacognitive skills exhibit self-reliance, self-governance, and adeptness in strategizing, overseeing, and assessing their writing undertakings (LV & Chen, 2010 ).

However, teaching metacognitive strategies demands substantial time investment. Traditional classroom setups often allocate significant time to elaborate on these strategies, leaving students to grapple with the writing process independently outside of class (Muldrow, 2013 ). To address this challenge, educators are seeking innovative instructional methodologies that not only foster learning but also motivate students towards excellence (Johnson et al., 2014 ). An influential educational direction that tackles this issue is student-focused learning, where the flipped model has garnered significant attention. This approach is a distinct form of blended learning (Strayer, 2012 ; Namaziandost, et al., 2020 ), recognized as one of the most prevalent and effective methods (Tucker, 2012 ).

Flipped learning, introduced by Bergmann and Sams ( 2012 ), represents a departure from conventional teaching approaches. This model restructures the roles of homework and classroom activities. In the conventional method, new material is presented in lectures, while students engage in practice at home. Flipped classrooms contribute to students' engagement with new content at home through teacher-provided resources, such as videos, and engage in skill practice and application in the classroom. This approach aligns well with learner-centered principles and offers a dynamic and interactive learning environment that optimizes classroom time for engagement and active learning (Knowles, 1975 ).

While the notion of the flipped classroom has garnered acknowledgment across diverse academic domains, its utilization in second language (L2) education has not been extensively investigated (Lee & Wallace, 2018 ; Chung et al., 2019 ). Several studies have highlighted its favorable influence on academic performance, student engagement, and the acquisition of skills (Lee & Wallace, 2018 ; O'Flaherty & Phillips, 2015 ). Moreover, several research endeavors have provided empirical support for the advantages of integrating the flipped model into blended learning settings. Noteworthy benefits include students' self-paced ability to learn (Altemueller & Lindquist, 2017 ; Andujar & Nadif, 2020 ; Namaziandost et al., 2020 ; van Alten et al., 2020 ), while according to Altemueller and Lindquist ( 2017 ) and Andujar and Nadif ( 2020 ), educators can effectively address students' learning challenges as students come prepared with study materials prior to class participation. The outcomes of implementing a flipped classroom approach were investigated in Turan and Akdag-Cimen's ( 2019 ) study in an ELT domain which was an extensive systematic review. Their findings indicated that the utilization of the flipped classroom model in the context of ELT has the potential to not only enhance students' engagement, English language proficiency, interactions, and academic accomplishments but also to elevate motivation, higher-order cognitive skills, adoption of profound learning strategies, and competence in information and communication technology (ICT) skills. However, there is still little research, especially on L2 writing and the application of metacognitive strategies.

Therefore, the current study attempts to explore whether the flipped classroom model can increase EFL learners' awareness of writing metacognitive strategies and contribute to their writing performance and self-efficacy. By exploring this novel approach, the study contributes to both the flipped learning discourse and the pedagogy of L2 writing, shedding light on its efficacy and implications for language educators and learners in the twenty-first century.

Review of the related literature

• Flipped classroom

The concept of the flip model, denoted by the acronym F-L-I-P, derives its principles from the notions of a flexible learning environment, an adaptive learning culture, deliberate instructional content, and proficient educators (Marshall & Kostka, 2020 ). This innovative pedagogical approach redefines the traditional classroom setup, positioning students at the forefront of learning while diminishing the centrality of the teacher within the physical classroom (Marshall & Kostka, 2020 ). By emphasizing a shift from teacher-centric to student-centric instruction, the flip model underscores the paramount importance of fostering active engagement in the learning process (Marshall & Kostka, 2020 ).

Within this framework, Marshall and Kostka, ( 2020 ) state that the significance of intentional content creation by educators comes to the fore, as they assume a crucial role in steering the learning journey and producing pertinent resources to facilitate learning outside the traditional classroom setting. Additionally, the work of Egbert et al. ( 2015 ) provides a thorough elucidation of the components of flipped classroom content, which include the emphasis on meaningful tasks over mere busywork, the teacher's transformation into a supportive mentor rather than a mere director, heightened interactions centered around the instructional content, an overarching focus on holistic learning as opposed to conforming to traditional scholastic behavior, prompt feedback mechanisms to aid students' procedural and incremental growth, seamless incorporation of technology to amplify learning, and the provision of just-in-time instruction to cater to immediate learning needs.

In a practical sense, the core essence of the flipped classroom model revolves around offering pre-recorded instructional lectures through online platforms, allowing students' self-paced access to and internalization of content before the scheduled class sessions (Marshall & Kostka, 2020 ). As a result, students can independently consume the lecture material prior to attending class, enabling classroom time to be repurposed for dynamic interactive activities, including discussions which are carried out in group, student-centered lectures, as well as problem-solving tasks which are done collaboratively (Yilmaz & Baydas, 2017 ).

The notion of the flipped classroom paradigm is frequently viewed as a type of blended learning, which is characterized by amalgamation of two or more instructional approaches (Caner, 2012 ). Within this context, the conventional delivery of direct instruction within the classroom is transformed into a personalized learning experience in individualized settings, mediated by a variety of technological tools (Caner, 2012 ). Educators typically provide online resources such as video lectures or supplementary materials for independent study, which in turn liberates classroom time for meaningful interactions and higher-order cognitive activities (Yilmaz & Baydas, 2017 ).

In academic literature, Lage et al. ( 2000 ) refers to the flipped classroom as an inverted classroom to signify the inversion of traditional classroom activities with those occurring outside the class and vice versa. A more refined definition is offered by Bishop and Verleger ( 2013 ) that stipulates two essential elements for a flipped classroom: computer-assisted teaching for independent learning beyond the classroom and interactive group engagements within the classroom. Research indicates that adopting the flipped model yields several advantages. Firstly, Kim et al. ( 2014 ) indicated that it empowers students through self-directed and self-regulated learning, granting them access to instructional content beyond the classroom boundaries. In contrast to conventional pedagogies, the flipped classroom allows learners greater flexibility and agency in customizing their learning environments and self-managing their learning journey (Bruff et al., 2013 ).

Secondly, the interactive dynamics within the classroom are enriched, fostering dynamic teacher-student and peer-to-peer engagements (Adnan, 2017 ; Bergmann & Sams, 2012 ). Baldwin et al. ( 2019 ) claimed that implementing flipped online learning model has resulted in significantly higher scores among graduate students in Korea. Assessment was conducted through online quizzes and individual assignments linked to course video lectures. Similarly, in an Indonesian university setting, the flipped classroom model demonstrated efficacy in enhancing students' higher-order cognitive skills while actively participating in in-class activities (Riza & Setyarini, 2020 ).

Examining a case with sophomore English major students, Hsieh et al. ( 2017 ) employed the flipped approach to teach English idioms. Leveraging technology, learners interacted with idiomatic content via a smartphone app, contrasting with traditional in-person instruction. Mixed-method research encompassing pretest and post-tests, questionnaires, in-class observations, and interviews revealed that the flipped model, centered on theory-based online interaction, amplified motivation and engagement, effectively enhancing participants' idiomatic knowledge.

Huang and Hong`s ( 2016 ) study, on the effect of flipping the classrooms in high schools in Taiwan, realized that the treatment group exhibited enhanced skills in English reading comprehension and proficiency in information and communication technology (ICT). The flipped approach offered opportunities for skill practice, optimized time utilization, and garnered positive feedback from students in a distance learning context.

Kostka and Lockwood ( 2015 ) underscore three key insights regarding the flipped classroom: its potential to cultivate autonomous language learning, its capacity to elevate higher-order cognitive skills, and its accommodation of diverse learning paces. This perspective is corroborated by Husnawadi ( 2021 ) that examined the effectiveness of flipped classroom for fostering learners` autonomy and flexibility. His study indicated that flipping the classrooms fosters learners` autonomy and flexibility. Additionally, a study by Qader and Arslan ( 2018 ) pinpoints the effective role of flipped classrooms on students` performance and higher-order thinking skills compared to conventional methodologies.

To conclude, the notion of the flipped classroom, stemming from the F-L-I-P framework, involves establishing a versatile, learner-centered educational setting facilitated by purposeful content delivery and skilled educators. The model's impact spans improved autonomy, enhanced interactions, and increased performance, while concurrently promoting higher-order cognitive skills. Research across various educational settings underscores its efficacy in promoting engaged and effective learning experiences.

Strategies and writing

Learning strategies are categorized into two groups, as outlined by Oxford ( 1990 ): direct strategies and indirect strategies. According to Oxford ( 1990 ), strategies such as affective, social, and metacognitive do not have an impact on the target language directly are called indirect strategies. In addition, others classifications such as cognitive, memory, and compensation strategies that can influence the target language directly are referred to as direct strategies. Abdollahzadeh ( 2010 ) refers to cognitive strategies as the actual mental processes at work while writing a text. Metacognitive strategies, as described by Brown and Walker ( 1983 ), O'Malley and Chamot ( 1990 ), and Cohen et al. ( 1998 ), pertain to techniques employed for managing the learning process by students. These strategies serve to supervise, strategize, and assess their own learning journey.

Likewise, a research endeavor undertaken by De Silve ( 2015 ) illuminated the influence of writing strategies on Second Language (SL) writing. The study involved 72 undergraduate science program students who were instructed to employ specific strategies, including planning, formulating, self-monitoring, evaluation, and revision. Writing performance was found to be better in the treatment group than in the control group. Furthermore, it was observed that imparting strategy instruction positively impacted students' writing accomplishments. As a result, it is advisable that educators train the learners to use writing strategies effectively while writing.

Metacognitive strategies

Flavell ( 1979 ), recognized as an early advocate in introducing the metacognition concept, proposed that metacognition encompasses two elements: metacognitive knowledge and metacognitive experience. As outlined by Xing et al. ( 2008 ), metacognitive strategies are characterized as cognitive techniques that are employed to guide cognitive processes with the intention of achieving specific cognitive goals. Mu ( 2005 ) and Diaz ( 2013 ) classified metacognitive writing strategies into diverse categories, notably including Planning, Monitoring, and Evaluating taxonomies. Thus, employing metacognitive writing strategies prompts learners to deliberate on the writing process, encompassing its planning, monitoring, and self-evaluation. Furthermore, by implementing practices like planning, monitoring, and evaluating a composition, learners can effectively oversee, steer, regulate, and shape their writing output.

In addition, King ( 2004 ) defines metacognition in brief as “the way learners think about thinking”. And regarding writing skills, metacognition involves the way learners understand their writing processes, also the way they adapt their processes to evolving demands. The effect of strategies on learners` writing performance and skills has also been studied previously. The writing was considered a product-based task which is simple. However, writing is nowadays viewed as process-based activity. Also, writing tasks as a process deals with cognitive, linguistic, affective, behavioral, and physical parts (Manchon et al., 2007 ). Additionally, Flavell ( 1979 ) defines metacognition as an umbrella term for metacognitive knowledge, experience, and strategies the assists us in understanding of the knowledge and cognition concerning cognitive phenomena. And also, Cohen ( 2011 ) defines metacognitive strategies as the deliberate actions that learners undertake to improve their learning process. Wenden ( 1998 ) states that learners can employ these strategies to “manage, direct, regulate, or guide their learning”.

Overall, using metacognitive strategies for writing proficiency development has remained under-researched. Recently, several studies have haven carried out with focus on the effect of metacognitive strategies on teaching writing skills. A study was done by Surat et al. ( 2014 ) in which 18 learners attending secondary school took part as participants in Malaysia. In this research, the participants were instructed to engage in metacognitive reflection concerning the essays they composed. The findings showed that the learners had minimal comprehension of how the process of writing should be structured. These findings hold relevance for education and future research. During past decades, Williams ( 2012 ) and other studies have reported the facilitative role of writing skills in language development. In contrast to other skills, the improvement of writing performance often comes through rigorous practice. Hence, considering its characteristics, the flipped model offers teachers the chance to allocate their in-class time specifically for writing practice (Kormos, 2012 ).A study done by Cutumisu and Schwartz ( 2018 ) concluded that feedback plays a crucial role in a writing course. For example, Wigglesworth and Storch ( 2012 ) in their study reported that receiving feedback as well as working in pairs writing tasks amplifies learners' chances to support each other's advancement through scaffolding.

Another study, involving 102 Iranian TEFL undergraduate students, employed Structural Equation Modeling (SEM) to investigate the relationships between collaborative digital writing, online knowledge sharing, and metacognitive knowledge in writing. The findings supported the structural model and confirmed that online knowledge sharing mediates the connection between collaborative digital writing and metacognitive knowledge in writing. These results have important implications for improving knowledge sharing practices, attitudes toward collaborative digital writing, and the development of metacognitive skills in TEFL education (Farahian and Ebadi ( 2023 ). Moreover, two significant studies focused on the role of metacognition in EFL writing. Sun et al. ( 2023 ) conducted a mixed-methods investigation, revealing that metacognitive experiences in writing vary among students of differing proficiency levels and serve as predictors of overall writing quality. In a similar vein, Yousef et al. ( 2023 ) explored the impact of integrating metacognitive techniques on EFL learners' writing performance in the UAE, finding a significant improvement in the writing performance of the experimental group that received metacognitive-based writing training. These findings collectively underscore the significance of metacognitive strategies in enhancing EFL writing proficiency, with implications for both theory and pedagogy in EFL writing instruction. Also, Teng ( 2023 ) used structural equation modeling to explore how metacognition, critical thinking, and academic writing relate in Chinese university students. The study involved 644 third-year students, assessing metacognitive writing strategies, critical thinking skills, and academic writing proficiency. Significant connections between these factors were found, offering valuable educational insights.

• Writing anxiety

Writing is a cognitive and emotional process where thoughts and feelings interplay. The investigation into first language (L1) writing anxiety was spurred by Daly and Miller ( 1975 ), who highlighted the prevalence and potential negative impacts of writing anxiety on American students. Their work led to the term "writing anxiety" describing the distressing unease many learners experience when confronted with writing tasks. They also introduced the Daly-Miller Writing Apprehension scale (WAT), which triggered numerous studies on the nature and consequences of writing anxiety.

Lin et al. ( 2009 ) suggested that anxiety, although uncomfortable, can have positive aspects. It helps us recognize potential threats and prepares us to address them effectively by paying close attention. They emphasized the need to critically consider important matters. Consequently, teachers should adopt effective methods to help students feel more at ease while composing. Anxiety, a natural response caused by various factors in different situations like exams, public speaking, or job interviews, has become a significant aspect of education, especially in language learning. Kara ( 2013 ) posits that anxiety impacts the learning process. Similarly, Lin ( 2009 ) views anxiety as a sensation that triggers productive attitudes. It heightens our awareness of potential threats and readies us to handle them thoughtfully.

Lots of studies have addressed the effect of writing anxiety on EFL learners` writing performance. Research by scholars like Woodrow ( 2011 ), Rezai et al., ( 2014 ), as well as Nausheen and Richardson ( 2010 ), has consistently demonstrated that elevated levels of anxiety detrimentally affect both the quality of writing performance and the motivation to participate in writing activities. Nonetheless, it is worth noting that a moderate level of anxiety can potentially function as a motivator (Daud & Kassim, 2016 ). Writing anxiety can arise from diverse origins, including limitations in time (Kirmizi & Kirmizi, 2015 ), apprehension about receiving inadequate evaluations (Zhang, 2011 ), test-related stress (Yan & Xiaoging, 2010 ), and the dynamics between educators and students (Karakaya & Ulper, 2011 ).

• Writing self-efficacy

The term 'self-efficacy', which denotes a social-learning and cognitive-behavioral perspective, was introduced by Bandura ( 1995 ) as the belief in one's ability to effectively manage future situations through planned actions. In simple terms, self-efficacy shows one's confidence in organizing and accomplishing tasks. For learners, high self-efficacy in writing can lead to increased effort, determination, and resilience when facing challenges in composing written tasks. Writing self-efficacy refers to learners' evaluation of their writing skills and their confidence in successfully accomplishing writing tasks. This belief often falls into three categories: high, medium, and low, each corresponding to varying levels of confidence. Those with high self-confidence show a higher level of writing efficacy, seeing complex activities as stimulating challenges that they can overcome through cognitive strategies.

Different studies have explored the impacts of writing self-efficacy on writing performance which have consistently found that self-efficacious learners are more motivated, experience less apprehension, invest greater effort, and ultimately perform better in writing tasks. For instance, Sun and Wang ( 2020 ) discovered that EFL college learners with high writing self-efficacy and self-regulated learning strategies performed better in their writing tasks.

Woodrow ( 2011 ) studied the effect of self-efficacy and anxiety levels on the writing performance of college students in China and found that they greatly influenced writing performance. Importantly, writing self-efficacy turned out to mediate the relationship between writing anxiety and performance. In simpler terms, previous instances of unsuccessful writing experiences could result in anxiety, subsequently diminishing self-efficacy and, consequently, impacting overall performance. Zabihi ( 2018 ) illustrated that fluency, accuracy, and complexity narrative writing were significantly influenced by writing self-efficacy in second language (L2) context. Additionally, it indirectly influences performance by interacting with writing anxiety.

Han and Hiver ( 2018 ) investigated distinct motivational profiles related to writing and discovered that writing self-efficacy and self-regulation acted as counterweights to the rise in writing anxiety throughout a course. They proposed that providing genre-based writing instruction enhances learners' confidence while accomplishing writing tasks. Sun and Wang ( 2020 ) further advanced this research by demonstrating that second language (L2) writing proficiency is significantly affected by self-efficacy and self-regulation. Notably, self-efficacy for grammar strongly influenced performance, and self-regulation strategies like text review and self-evaluation were associated with better performance. Also, Zhou's study ( 2022 ) addressed the impact of instructional efforts targeting self-efficacy in writing performance. The study involved 50 Chinese undergraduates in a 10-week EFL integrated course. Results showed significant improvements in performance, transformation, and language control, with stable self-regulatory strategy and motivation. Consistent correlations emerged among motivation, self-regulatory strategy, transformation, and language control, and performance was moderately correlated with posttest self-efficacy. These findings highlight the importance of transformative processes in EFL learning, shaping learners' beliefs and positively influencing language acquisition and writing and reading regulation.

Overall, the role of writing self-efficacy in writing proficiency is widely acknowledged in the literature. Also, it is noted that learners' beliefs in their writing skills play an essential role in their success.

To address these research lacunas, this study primarily sought to examine whether writing strategy-based instruction through the flipped classroom approach would facilitate two key aspects among second language (L2) learners: first, their writing performance, and second, their levels of anxiety and self-efficacy. These affective factors hold significance within the L2 learning context. Therefore, the following questions were investigated:

Does writing metacognitive strategy-based instruction through flipped classroom significantly affect intermediate learners’ writing performance?

Does writing metacognitive strategy-based instruction through flipped classroom significantly decrease intermediate EFL learner`s writing anxiety?

Does writing metacognitive strategy-based instruction through flipped classroom significantly develop intermediate EFL learners’ writing self-efficacy?

Participants

A sample of two intact classes with 45 students was selected by convenience sampling method (Dörnyei, 2007 ), from an English institute in Tehran, Iran as the participants of this study. The sample encompassed both male and female learners, with ages spanning from 17 to 24 years. The two intact classes chosen for the study were assigned randomly: one functioned as the control group (N = 22), in a non-flipped classroom setting, while the other served as the experimental group (N = 23), in a flipped classroom environment. All participants in both groups were assigned to successfully complete an intermediate writing strategy training course instructed by the same educator in the winter of the 2019 academic year. The instructor has previous experience in implementation of flipped classrooms for L2 learners. Prior to commencing the present course, certain learners had prior exposure to blended learning, yet none of them had encountered flipped classrooms in their educational experience. However, the participants received introductory explanations about flipped classrooms and their instructional design before the conduction of the flipped approach.

Instruments and materials

To collect the quantitative data and apply the treatment, the following instruments were used in this study.

Proficiency test

The participants` proficiency level was estimated using the Preliminary English Test (PET) which includes 200 items and measures learners' listening and reading comprehension and grammar and vocabulary. PET is considered as a reliable measure for placing language learners of intermediate levels.

Second language writing scale

Jacobs et al.'s ( 1981 ) writing scale was utilized to evaluate the students' essays, which follows an analytical scoring approach and encompasses five content criteria for evaluation of essays. These criteria include: communicative quality, organization, paragraphing, cohesion, and relevance and adequacy. Jacobs et al. ( 1981 ) outline five distinct subcategories within this scoring rubric, encompassing content criteria, organization criteria, vocabulary criteria, language criteria, and mechanics criteria. The scores provided by both raters and the graduate students were then subjected to Cohen’s Kappa inter-rater reliability test. This scoring rubric employed a 100-point system in which20 points for vocabulary utilization, 25 points for language usage (primarily syntax), 30 points were designated for the writing's content, 20 points for writing organization, and 5 points for mechanics. Also, two trained raters independently evaluated 40% of the essays to ensure the inter-rater reliability of the essay scores.

Self-efficacy in writing scale (SWS)

Yavuz-Erkan's ( 2004 ) self-efficacy scale was used to measure students' writing self-efficacy in this study. Aligned with Bandura's ( 1977 ) self-efficacy concept, this scale includes a 21-item writing self-efficacy scale to gauge the degree of subjects' confidence in their writing competence. The items on the scale were rated using a four-tier Likert scale: Strongly Disagree, Disagree, Agree, or Strongly Agree, with each statement beginning with the phrase "I can…”. The reliability and validity of the scale were estimated by Yavuz-Erkan ( 2004 ).

Second language writing anxiety inventory

Cheng’s ( 2004 ) Second Language Writing Anxiety Inventory (SLWAI) was used to estimate learners' writing anxiety. This inventory was developed to assess the levels and different aspects of anxiety that individuals experience when participating in second language writing tasks. This scale consists of 22 items and measures anxiety levels in English writing which includes three aspects: somatic anxiety, cognitive anxiety, and avoidance behavior. The questionnaire employs a Likert-type response format with 5 choices: 1 (strongly disagree), 2 (disagree), 3 (undecided), 4 (agree), and 5 (strongly agree). The items are distributed across three categories: (1). Somatic anxiety (items 2, 6, 8, 11, 13, 15, and 19), (2) Cognitive anxiety (items 1, 3, 7, 9, 14, 17, 20, and 21), and (3) Avoidance behavior (items 4, 5, 10, 12, 16, 18, and 22). As the participants were English major students, the questionnaire was administered in English. The reliability and validity of SLWAI was established through correlation and factor analysis. To measure internal consistency, the Cronbach's Alpha formula was employed for the scale.

In the experimental group, students were presented with video or PowerPoint sessions that covered various metacognitive strategies based on O’Malley and Chamot’s ( 1990 ) classification of writing metacognitive strategies. To reinforce comprehension and application, follow-up activities were assigned to ensure their grasp of these strategies. Subsequently, during class sessions, they practiced employing these metacognitive strategies while engaging in writing tasks. In contrast, the control group received lectures about writing metacognitive strategies, derived from O’Malley and Chamot’s ( 1990 ) classification, delivered by their instructors during class. Due to the lecture-focused approach, students in this group didn't have dedicated time for practice in the classroom. Instead, they were given a writing task to complete at home. Finally, both groups were tasked with writing an essay to evaluate their application of the metacognitive strategies they had learned.

The participants of this study were learners of two intermediate -writing classes at an English Institute in Tehran. First, a week before the commencement of the semester and the initiation of the intervention, the experimental and control groups underwent a PET assessment to ensure their homogeneity in language proficiency. The proficiency test was conducted because language proficiency is recognized as a potential factor influencing students' overall writing performance. Following the PET administration, the mean scores of both groups were compared to ensure that both groups had the same level of language proficiency before the start of the treatment. During the initial course session, students were assigned a pre-test writing task which involved composing a 45-min essay on the first topic. Subsequently, these essays were evaluated using Jacobs et al.’s ( 1981 ) scoring rubric. Meanwhile, both SWS (Second Language Writing Anxiety) and SLWAI (Second Language Writing Anxiety Inventory) were administered to gauge the initial levels of L2 writing anxiety and writing self-efficacy in both groups before the course commenced.

To achieve the study's objectives, the treatment group was taught the writing metacognitive strategies using a flipped classroom approach. This involved delivering three types of metacognitive strategies through PowerPoint presentations or videos across ten sessions. In addition, they were meant to do particular writing activities regarding the specific strategy which were presented to them. Furthermore, to ensure that students can implement the strategies, more activities were done in the classroom context. The other class, which served as a control group was provided by writing metacognitive strategies in the classroom, taught by the teacher. Consequently, the class time was partitioned into two segments: the first section for teaching strategies and the latter part dedicated to writing activities. The primary emphasis was on effectively applying writing metacognitive strategies. Over the course of these ten sessions, students were instructed in three categories of writing metacognitive strategies, namely planning, drafting, and monitoring, editing, and evaluating. Upon the conclusion of the intervention, the post-tests of the study were conducted, which included the writing task (topic b), as well as the administration of SWS (Second Language Writing Anxiety) and SLWAI (Second Language Writing Anxiety Inventory).

Learners in both groups participated in ten instructional sessions, each lasting one hour and fifteen minutes. In both groups, learners were exposed to the same three writing metacognitive strategies. However, the instructional methods differed: the treatment group experienced a flipped classroom approach, whereas the control group was taught following the traditional method, with the teacher delivering the writing metacognitive strategies within the classroom setting. In contrast, the treatment group was made familiar with the writing metacognitive strategies via flipped learning, utilizing videos and PowerPoint presentations. In the control group, students attended lectures in the classroom and practiced implementing the strategies at home. Conversely, learners in the treatment group not only learned the strategies but also immediately applied them to a writing task. Furthermore, they participated in supervised class sessions for additional practice, where teachers provided guidance and support.

Five writing metacognitive strategies were chosen following O’Malley and Chamot’s ( 1990 ) framework. These strategies encompassed: planning (Advance Organizers, Directed Attention, and Functional Planning), monitoring (Self-Monitoring), and self-evaluation.

In experimental group, each strategy was taught before attending the class through a video or PowerPoint. First, the strategy was described and explained completely and also it was exemplified by the teacher. Next, the learners were presented a model using the related strategy. Finally, learners were given a practical task to practice applying the strategy.

Then, learners attended the class in which they were presented with various tasks which could be done through implementing the chosen strategy. Additionally, learners were encouraged to share their perspectives on the utilization of these selected strategies with both their peers and the teacher. They were also prompted to evaluate the efficacy of these strategies based on their experiences. Then, the learners were engaged in composing various types of essays, including advantage and disadvantage, problem and solution, opinion essays, as well as compare and contrast essays, sourced from the "IELTS Advantage Writing Skills" book. In the subsequent sections, a detailed breakdown of the procedures carried out in both groups will be provided.

FLIPPED classroom

In this study, the Cognitive Academic Language Learning Approach (CALLA), developed by Chamot and O’Malley ( 1994 ), was employed to implement the writing metacognitive strategies. The metacognitive writing strategies employed in this study encompass planning (utilizing Advance Organizers, Directed Attention, Self-management, and Functional Planning), monitoring (through Self-Monitoring), and Self-Evaluation. Regarding Chamot and O’Malley’s ( 1994 ) CALLA, the five stages of preparation, presentation, practice, monitoring and evaluation, expansion, and teacher’s assessment were followed in the present study to apply the above strategies. The five stages were as follows. There might be some variations in the stages of strategy instruction due to implementing flipped classroom.

Guidance regarding “the how” of strategy instruction can be found in the work of Chamot and O’Malley ( 1994 ). The primary focus of their approach is represented in the “Framework for Strategic Instruction” (See Fig.  1 ).

Framework for Strategy Instruction

Following Tamer Mohammad Al-Jarrah et al. ( 2019 ) we added the last stage which was teacher`s assessment.

Teacher’s assessment teacher assesses learners` writing as well as their strategy use.

During these 10 sessions, Nguyen and Gu`s ( 2013 ) the instructional procedure was taken into account to teach writing metacognitive strategies (planning, monitoring, evaluation) to the learners. Consequently, learners were asked to write various essay types (advantage and disadvantage, problem and solution, opinion essay, compare and contrast) implementing these strategies. They practiced setting goals, selecting learning strategies, relate to their prior knowledge, reflecting on their strategy use, monitoring and evaluating their writing process. They were trained to compose topic sentences, introduction, body, and conclusion paragraphs. Further, they were trained to use proper witting mechanics. Also, they got familiar with a list of vocabulary and phrases relevant to each topic and essay type. Various chunks were introduced to them which helped them start or link ideas. Moreover, they gained the ability to observe and evaluate their writing performance and their strategy use (Figs. 2 and 3 ).

The five basic stages of Chamot and O’Malley’s ( 1994 ) CALLA conducted to implement the writing strategies in the flipped classroom

The ten-session metacognitive writing strategy instruction in the flipped WSBIWSBI classroom

Each session, learners worked on an essay topic from the IELTS Advantage Writing Skills book to apply what they have learned previously also they were supposed to do some after-class homework.

Non-FLIPPED classroom

Students in the non-flipped classroom covered the same course book, tasks, and materials. They followed the same instructional procedure except for the videos and power points which were given to be watched out of the classroom. Instead, the learners in the control group received teacher explanations about strategies. Simultaneously they were given various tasks to check their understanding of the strategies. They planned, monitored, and evaluated their writings in the class. They were provided by the planning strategy explanation, the aim of implementing this strategy. They learned the importance of setting a goal and the way to set achievable goals. Further, they were trained to identify the task requirements and also to brainstorm ideas, draw content maps, choose proper language writing mechanics both individually and collaboratively. Then, they were taught various ways to monitor their writing task and check the break downs and overcome their problems. In the end, they were given different types of evaluations and an explanation of the way it is done. Each session after the explanation of each strategy and providing them with a model, learners had few minutes to follow a writing task, but due to lack of time most of the tasks had to be done after class individually. Each session, they were given a task to do as homework. The whole instructional process of both flipped and non-flipped classrooms is presented below.

To insure the participants' homogeneity in general language proficiency, they took the Preliminary English Test (PET). The performance of both groups was compared using analysis of covariance (ANCOVA). As it can be seen in Table 1 , there was no significant disparity in the PET scores of the two groups (M = 61.26, SD = 13.36) and the control group (M = 62.98, SD = 12.83); t = -0.613, p  > 0.05). This suggests that both groups had a comparable level of general English proficiency before the commencement of the study's treatment.

Addressing the research questions

Table 2 below displays the descriptive statistics which show that the mean scores for both variables increased from the pre-test to the post-test. However, for a more conclusive understanding of these statistical changes, inferential statistics were used.

In order to test the assumption of normality, a one-sample Kolmogorov–Smirnov (K-S) test was executed on the scores obtained before and after the test. Within the context of the one-sample Kolmogorov–Smirnov (K-S) test, a significance level exceeding 0.05 suggests that the data conforms to a normal distribution. As illustrated in Fig.  4 , the outcomes of the one-sample Kolmogorov–Smirnov (K-S) test revealed that the data displayed a distribution that adhered to normality.

Flipped and non- flipped classroom instructional processes

Afterward, to answer the first research question and find out whether writing metacognitive strategy-based instruction through flipped classrooms significantly affected intermediate learners’ writing performance, ANCOVA was performed. As outlined by Pallant and Manual ( 2007 ), ANCOVA is suitable for pre-test/post-test designs. This includes scenarios such as comparing the effects of distinct interventions by measuring before and after outcomes for each group. In ANCOVA, pre-test scores are treated as covariates to account for any initial disparities between the groups. This helps to ensure that the observed effects are not solely attributed to pre-existing differences.

Table 2 shows that the mean score of treatment group`s pretest stood at 50.26. Remarkably, this score surged to 69.36 for the posttest writing performance. Similarly, the control group`s pretest mean score, which was 54.54 before the intervention, rose to 62.22 on the posttest. Consequently, it is evident that both instructional approaches improved writing proficiency in both groups (Fig. 5 ).

Normality of data

However, in order to identify which group has experienced a greater gain, ANCOVA was carried out. For this ANCOVA analysis, the independent variable was the type of instruction (flipped or traditional), while the dependent variable was the scores on the timed writing performance task conducted after the study's conclusion. The students' scores on the pretests were included as covariates in this analysis to account for their initial performance differences. Also, before conducting the ANCOVAs, the researchers employed several preliminary tests to ensure various assumptions of the covariate were not violated. These assumptions were as follows: normality, linearity, homogeneity of variances, homogeneity of regression slopes, and reliable measurement.

As it is shown in Table 3 , a statistically significant difference is observed in the two groups' writing performance on the posttest, F (1, 42) = 15.41, p  = 0.00, partial eta squared = 0.26). This finding indicates that the learners in the experimental group had a greater development in their writing performance compared to the learners in the control group. This strongly suggests that writing metacognitive strategy-based instruction through flipped classrooms significantly enhanced the intermediate learners` writing ability.

The second research question revolved around whether writing metacognitive strategy-based instruction through flipped classrooms effectively decreased EFL learners' writing anxiety. The descriptive statistics (see Table 2 ) reveal that in the experimental group, the participants` mean score for writing anxiety dropped from 19.84 in the pretest to 18.91 in the posttest. Conversely, writing anxiety mean score of the participants in the control group was 21 in the pretest, rising slightly to 21.88 in the posttest. Hence, it becomes evident that the implementation of flipped instruction led to a reduction in writing anxiety among the participants.

Moreover, inferential statistics were used to answer the second research question. Another One-Way ANCOVA was conducted on the writing anxiety scores to examine the effects of the two types of interventions on the participants' writing anxiety. As evidenced in Table 4 , the ANCOVA results based on the General Linear Modeling technique showed a significant difference between both groups' posttest scores related to writing anxiety in experimental and control group F (1, 42) = 5.00, p  = 0.031, partial eta squared = 0.10).This result underscores that the writing metacognitive strategy-based instruction through flipped classrooms played a substantial role in decreasing the writing anxiety of Iranian intermediate EFL learners.

The third research question explored whether writing strategy-based instruction through flipped classrooms led to a significant enhancement in intermediate learners' writing self-efficacy in an EFL context. The treatment group's average pretest score on writing self-efficacy was 20.34 (refer to Table 2 ). Notably, this score rose to 25.02 in the posttest. Similarly, the pretest mean score on writing self-efficacy for the control group was 20.04, increasing to 22.02 on the posttest. Hence, it is evident that both instructional approaches significantly played a role in fostering an improvement in writing self-efficacy among the participants in both groups.

To determine which group experienced a greater improvement, an ANCOVA was performed. In this analysis, the type of instruction (flipped or traditional) was independent variable, while the scores reflecting writing self-efficacy evaluated after the culmination of the study was the dependent variable, and students' initial scores (pretest) were utilized as covariates.

After adjusting for the writing self-efficacy scores on the pretest, a statistically significant difference became evident between the two groups' scores on the posttest, F (1, 42) = 7.54, p  = 0.09, partial eta squared = 0.15) (refer to Table 5 ). This outcome indicates that the participants in the treatment group exhibited a notably greater enhancement in their writing self-efficacy compared to those in the control group. This strongly indicates the effectiveness of the intervention in this study.

This study sought to examine the impact of writing metacognitive strategy-based instruction through flipped classrooms on learners' writing ability, writing anxiety, and writing self-efficacy. It was hypothesized that writing metacognitive strategy-based instruction through flipped classrooms would positively influence intermediate learners' writing performance.

The results showed that the treatment significantly enhanced writing ability of the relevant group. This finding is in line with the view of the researchers including Afrilyasanti et al., ( 2016 ), Güvenç ( 2018 ), Soltanpour and Valizadeh ( 2018 ) who carried out similar studies and claimed that there is a significant relationship between writing performance and flipped instruction.

Additionally, this discovery aligns with the previous research findings in this domain, including Wen's ( 2008 ) Output-driven/Input-enabled model. Wen asserted that the flipped classroom approach was more effective than traditional methods in enhancing EFL students' academic writing skills. One plausible explanation for these results could be attributed to the inverse structure of the flipped classroom, where EFL learners were exposed to course content before class through videos, notes, and lectures, thereby enhancing their engagement and understanding.

As Faulkner and Green ( 2015 ) point out, the flipped classroom format offers students the advantage of accessing content lessons prior to attending class. This facilitates repeated viewing and seamless integration of activities before and during class which facilitates students' self-paced and convenient learning. Conversely, Mehring ( 2016 ) highlights that, unlike flipped classrooms, students in the non-flipped classroom may not have equal opportunities for active interaction with peers, course content, and instructors.

Hsieh and Marek ( 2017 ) claimed that learners in the flipped classroom are capable of completing the class activities as a result of spending a great deal of time on before-class activities. Accordingly, students had a full engagement in a variety of class activities and were able to act effectively and efficiently. However, the students in the traditional classroom weren`t engaged in the class activities efficiently as they were exposed to different tasks after that class, not before the class and they didn`t attend the class well prepared. Besides, the class time was allocated to teaching the strategies. Therefore, there was no time for engaging activities to work on the high cognitive skills of the learners and the class activities were mostly teacher-centered.

The present study also aimed at comparing students' writing anxiety and writing self-efficacy across flipped and non-flipped classrooms. Therefore, in addressing the second and third research questions, this study aimed at comparing the two groups' post-test mean scores. This part of the study aimed to ascertain the extent to which the independent variable (our treatment: writing metacognitive strategy-based instruction through flipped classrooms) influenced the dependent variables (writing anxiety, writing self-efficacy). The outcomes invalidated the null hypotheses for both writing self-efficacy and writing anxiety, revealing a noteworthy disparity in performance between the experimental and control groups.

In relation to students' writing self-efficacy, the outcomes of this study demonstrated that the implementation of writing metacognitive strategy-based instruction through flipped classrooms led to an improvement in students' self-efficacy. These findings accord with previous research, such as Namaziandost and Çakmak ( 2020 ), Chigbu et.al. ( 2023 ), and Chen et al. ( 2020), which also substantiate the notion that technology-assisted learning diminishes learners' writing anxiety and elevates their writing self-efficacy.

Furthermore, with respect to students' writing anxiety, the study's findings unveiled a reduction in writing anxiety through flipped instruction. However, this outcome diverged from the conclusions drawn by Lakarnchua et al. ( 2020 ), whose study indicated that the learners' L2 writing anxiety was not significantly impacted by the flipped approach. Whereas, several researchers (e.g., Chang & Lin, 2019 ; Ho, 2020 ) have referred to the facilitative role of flipped approach in reducing learners` anxiety. The participants of flipped approach were able to cover the course lesson beforehand and watch the given videos as much as needed at their own pace and attend the class well prepared. We may argue that this inverted learning style helped learners to attend their classes which lead to a great deal of cooperation and collaboration which in turn reduced learners` anxiety.

This study underscores the efficacy of employing metacognitive strategy-based instruction to improve intermediate learners' writing performance within a flipped learning environment. By providing evidence that supports the superior results of writing metacognitive strategy instruction, this research adds to the existing literature on the benefits of flipped classrooms, indicating that teaching writing metacognitive strategies through flipped classrooms enhances learners' writing skills. When the flipped classroom is fully conducted, it facilitates learners' engagement and interaction in class as well as their independence and autonomy out of class. Additionally, flipped classroom provides learners with the opportunity for the self-paced study of the course content and review of the lessons as much as needed which ensures their prepared class attendance. They are ready to take part in various interactive activities involving high cognitive skills and implementing useful strategies as flipped learning is a promising technique for enhancing a student-centered classroom and enables the teacher to give advice and instruction as students write compositions and apply different metacognitive strategies during class time.

Furthermore, when the content lesson is covered before joining the class, it benefits learners` self-efficacy and decreases their anxiety. As learners study the lessons and watch the videos and read the materials at their own pace, and are assisted by teachers, they can recognize their style of learning and cope with the barriers efficiently. Consequently, their self-efficacy is increased and they experience less anxiety in doing the class activities in a friendlier environment interacting with their classmate, having enough time to practice what they already acquired.

While the positive outcomes of incorporating writing metacognitive strategy-based instruction within flipped classrooms are highlighted, it is important for researchers to acknowledge that diverse learning environments, cultural contexts, and participant characteristics can yield varying learning outcomes. Therefore, it is advisable for language educators to adapt a similar study design to different EFL scenarios to gather additional evidence endorsing the efficacy of strategy utilization within flipped classrooms.

Researchers are able to test different approaches and theories and gain experiences by carrying out carefully-organized and controlled studies. Also, they can easily ignore external factors which might influence their results. As an instance, before deciding that implementing flipped classroom can affect X, Y or Z, it is essential to ensure the provision of flipped approach and no other factors. By doing this, the researcher ensures that one of the variables is eliminated. To date, no researcher claims that ‘I controlled all variables in conducting a study’, due to the fact that all these studies are conducted on human beings and possibly there are uncontrolled variables that must be controlled, and practically it is impossible. Consequently, this study only focused on the writing skill of Iranian intermediate EFL students. Finally, a number of limitations are listed below in order to limit the effect of other variables.

The current study was restricted to intermediate EFL students of only one language center in Iran.

the current research was conducted on Iranian EFL learners whose mother tongue was Kurdish. Therefore, researchers can obtain different results by conducting this study on other languages.

In the present study, only writing metacognitive strategies were used.

This study only focused on two affective variables including: writing anxiety and writing self-efficacy; researchers can investigate the effect of flipped learning on the other affective variables. Pronunciation of the content words and other language skills and sub-skills were not paid attention to.

The participants of the study were between the ages17 to 24, thus the findings could not be generalized to learners with other ages.

Availability of data and materials

Data will be available on reasonable request.

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Khosravi, R., Dastgoshadeh, A. & Jalilzadeh, K. Writing metacognitive strategy-based instruction through flipped classroom: an investigation of writing performance, anxiety, and self-efficacy. Smart Learn. Environ. 10 , 48 (2023). https://doi.org/10.1186/s40561-023-00264-8

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Metacognitive Study Strategies

Do you spend a lot of time studying but feel like your hard work doesn’t help your performance on exams? You may not realize that your study techniques, which may have worked in high school, don’t necessarily translate to how you’re expected to learn in college. But don’t worry—we’ll show you how to analyze your current strategies, see what’s working and what isn’t, and come up with new, more effective study techniques. To do this, we’ll introduce you to the idea of “metacognition,” tell you why metacognition helps you learn better, and introduce some strategies for incorporating metacognition into your studying.

What is metacognition and why should I care?

Metacognition is thinking about how you think and learn. The key to metacognition is asking yourself self-reflective questions, which are powerful because they allow us to take inventory of where we currently are (thinking about what we already know), how we learn (what is working and what is not), and where we want to be (accurately gauging if we’ve mastered the material). Metacognition helps you to be a self-aware problem solver and take control of your learning.

By using metacognition when you study, you can be strategic about your approach. You will be able to take stock of what you already know, what you need to work on, and how best to approach learning new material.

Strategies for Using Metacognition When You Study

Below are some ideas for how to engage in metacognition when you are studying. Think about which of these resonate with you and plan to incorporate them into your study routine on a regular basis.

Use Your Syllabus as a Roadmap

Look at your syllabus. Your professor probably included a course schedule, reading list, learning objectives or something similar to give you a sense of how the course is structured. Use this as your roadmap for the course. For example, for a reading-based course, think about why your professor might have assigned the readings in this particular order. How do they connect? What are the key themes that you notice? What prior knowledge do you have that could inform your reading of this new material? You can do this at multiple points throughout the semester, as you gain additional knowledge that you can piece together.

Summon Your Prior Knowledge

Before you read your textbook or attend a lecture, look at the topic that is covered and ask yourself what you know about it already. What questions do you have? What do you hope to learn? Answering these questions will give context to what you are learning and help you start building a framework for new knowledge. It may also help you engage more deeply with the material.

Think Aloud

Talk through your material. You can talk to your classmates, your friends, a tutor, or even a pet. Just verbalizing your thoughts can help you make more sense of the material and internalize it more deeply. Talking aloud is a great way to test yourself on how well you really know the material. In courses that require problem solving, explaining the steps aloud will ensure you really understand them and expose any gaps in knowledge that you might have. Ask yourself questions about what you are doing and why.

Ask Yourself Questions

Asking self-reflective questions is key to metacognition. Take the time to be introspective and honest with yourself about your comprehension. Below are some suggestions for metacognitive questions you can ask yourself.

• Does this answer make sense given the information provided?
• What strategy did I use to solve this problem that was helpful?
• How does this information conflict with my prior understanding?
• How does this information relate to what we learned last week?
• What questions will I ask myself next time I’m working these types of problems?
• What is confusing about this topic?
• What are the relationships between these two concepts?
• What conclusions can I make?

Try brainstorming some of your own questions as well.

Use Writing

Writing can help you organize your thoughts and assess what you know. Just like thinking aloud, writing can help you identify what you do and don’t know, and how you are thinking about the concepts that you’re learning. Write out what you know and what questions you have about the learning objectives for each topic you are learning.

Organize Your Thoughts

Using concept maps or graphic organizers is another great way to visualize material and see the connections between the various concepts you are learning. Creating your concept map from memory is also a great study strategy because it is a form of self-testing.

Take Notes from Memory

Many students take notes as they are reading. Often this can turn notetaking into a passive activity, since it can be easy to fall into just copying directly from the book without thinking about the material and putting your notes in your own words. Instead, try reading short sections at a time and pausing periodically to summarize what you read from memory. This technique ensures that you are actively engaging with the material as you are reading and taking notes, and it helps you better gauge how much you’re actually remembering from what you read; it also engages your recall, which makes it more likely you’ll be able to remember and understand the material when you’re done.

Review Your Exams

Reviewing an exam that you’ve recently taken is a great time to use metacognition. Look at what you knew and what you missed. Try using this guide to  analyze your preparation for the exam and track the items you missed , along with the reasons that you missed them. Then take the time to fill in the areas you still have gaps and make a plan for how you might change your preparation next time.

Take a Timeout

When you’re learning, it’s important to periodically take a time out to make sure you’re engaging in metacognitive strategies. We often can get so absorbed in “doing” that we don’t always think about the why behind what we are doing. For example, if you are working through a math problem, it’s helpful to pause as you go and think about why you are doing each step, and how you knew that it followed from the previous step. Throughout the semester, you should continue to take timeouts before, during or after assignments to see how what you’re doing relates to the course as a whole and to the learning objectives that your professor has set.

Test Yourself

You don’t want your exam to be the first time you accurately assess how well you know the material. Self-testing should be an integral part of your study sessions so that have a clear understanding of what you do and don’t know. Many of the methods described are about self-testing (e.g., thinking aloud, using writing, taking notes from memory) because they help you discern what you do and don’t actually know. Other common methods include practice tests and flash cards—anything that asks you to summon your knowledge and check if it’s correct.

Figure Out How You Learn

It is important to figure out what learning strategies work best for you. It will probably vary depending on what type of material you are trying to learn (e.g. chemistry vs. history), but it will be helpful to be open to trying new things and paying attention to what is effective for you. If flash cards never help you, stop using them and try something else instead.

Works Consulted

McGuire, S.Y. & McGuire, S. (2016). Teach Students How to Learn: Strategies You Can Incorporate in Any Course to Improve Student Metacognition, Study Skills, and Motivation. Stylus Publishing, LLC.

Ten Metacognitive Teaching Strategies. Vancouver Island University. Centre for Innovation and Excellence in Learning.

Anderson, J. (2017, May 09). A Stanford researcher’s 15-minute study hack lifts B+ students into the As. Quartz.

Developed and shared by The Learning Center , University of North Carolina at Chapel Hill.

• Class Attendance
• Semester-At-A-Glance Calendar
• Semester Action Plan
• Using Calendars and Planners
• Studying 101

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