Metacognition in Animals and Humans: A Comparative Perspective

Metacognition refers to the capacity to monitor and evaluate one's own knowledge, confidence, and cognitive processes. This article examines how researchers study metacognition across species, what the evidence shows about metacognitive abilities in nonhuman animals, and how these findings inform our understanding of consciousness, self-awareness, and the evolution of cognition. The content is intended for students, researchers, life-science professionals, and informed general readers seeking a rigorous comparison of metacognitive abilities across species and a summary of key experimental approaches.

Defining Metacognition and Its Core Components

Metacognition is commonly described as knowledge about knowledge, often expressed through confidence judgments about what one knows. In humans, this capacity is typically studied through verbal reports, where individuals state how certain they are about a decision or memory. The concept encompasses several related abilities, including the monitoring of one's own uncertainty, the evaluation of one's confidence in a response, and the regulation of cognitive effort based on perceived difficulty.

The study of metacognition requires distinguishing between first-order cognitive processes and second-order monitoring. A first-order process might be recognizing a visual stimulus or recalling a fact. A second-order process involves assessing whether that recognition or recall is likely to be correct. This distinction is central to comparative research because animals cannot provide verbal reports, so researchers must design behavioral tasks that reveal whether an animal is tracking its own accuracy.

Visual confidence research demonstrates that the ability to judge the accuracy of perceptual decisions has been recorded since the early days of psychophysics, but only recently has it been recognized as essential for understanding visual perception. Investigators have developed different experimental paradigms to study visual confidence in both humans and nonhuman animals, with competing theoretical frameworks based on signal detection theory and evidence accumulation models. These frameworks differ in their ability to account for response times and the sometimes paradoxical dissociation between performance and confidence.

Historical Foundations of Comparative Metacognition Research

Comparative psychologists have investigated whether animals possess precursors to metacognition for several decades. The core question is whether nonhuman animals can monitor their own mental states or cognitive processes, instead of simply responding to external stimuli based on learned associations. Researchers have tested a range of species including apes, monkeys, rats, pigeons, and a dolphin using perceptual, memory, foraging, and information-seeking paradigms. The consensus among many researchers is that some species demonstrate a functional analog to human metacognition.

The historical trajectory of this field shows a progression from simple demonstrations of uncertainty responses to more sophisticated experimental designs. Early work focused on whether animals could learn to decline difficult trials, while later research has examined the neural substrates underlying these abilities and the computational mechanisms that support confidence judgments. The field has also generated significant debate about whether observed behaviors truly reflect metacognitive processes or can be explained by simpler associative mechanisms.

One important development has been the recognition that metacognition may take different forms. Some researchers distinguish between model-based metacognition, which involves a simplified model of one's own mind, and model-free metacognition, which represents mental states without requiring such a model. This distinction has important implications for interpreting animal behavior and for understanding the evolutionary origins of metacognitive abilities.

Nonverbal Methods for Studying Animal Metacognition

Because animals cannot report their confidence verbally, researchers have developed nonverbal techniques to investigate metacognition. Two primary methods have emerged in the comparative literature. In the first method, subjects are given the option to escape from difficult trials. If an animal chooses to decline a trial when it is uncertain about the correct response, this suggests that it is monitoring its own knowledge state. In the second method, subjects are trained to place bets about the accuracy of their most recent response, wagering more when they are confident and less when they are uncertain.

These nonverbal techniques require careful controls to rule out noncognitive interpretations. Researchers must ensure that escape responses do not increase the overall density of reinforcement and that they do not occur in the presence of the stimuli on which the subject was trained. These controls are essential because animals might learn to escape difficult trials simply because doing so leads to rewards, without any genuine monitoring of their own uncertainty.

The development of these methods has enabled two important lines of research. First, investigators can examine the contribution of language and explicit instruction in establishing metacognition by comparing humans who have verbal abilities with animals that do not. Second, researchers can investigate the neural substrates of metacognition by recording brain activity while animals perform metacognitive tasks. These approaches have opened new avenues for understanding the mechanisms underlying confidence judgments.

Post-Decision Wagering and Confidence Measurement

Post-decision wagering has emerged as a particularly useful method for studying confidence in animals. In this paradigm, an animal makes a decision and then places a wager on the accuracy of that decision. The size of the wager reflects the animal's confidence, with larger wagers indicating higher confidence. This approach provides a continuous measure of confidence instead of a simple binary choice between accepting or declining a trial.

A computational framework for studying confidence in humans and animals suggests that post-decision wagering tasks with continuous measures of confidence offer the best available metrics of confidence. This framework emphasizes that behavioral reports alone provide a limited window into mechanism, and progress requires measuring neural representations and identifying the computations underlying confidence reports. Research using this approach has shown that confidence assessments may be considered higher order but can be generated using elementary neural computations available to a wide range of species.

The computational approach has been applied to study the neural correlates of decision confidence in rats. This work demonstrates that confidence judgments can be studied using overt behavioral measures in animals trained in decision-making tasks with perceptual or mnemonic uncertainty. The findings suggest that confidence assessments rely on neural computations that are not unique to humans, supporting the idea that metacognitive abilities have deep evolutionary roots.

Uncertainty Monitoring and Information-Seeking Paradigms

Uncertainty monitoring paradigms present animals with tasks where they must discriminate between stimuli of varying difficulty. Animals that can monitor their own uncertainty should be more likely to decline or escape difficult trials than easy ones. This pattern has been observed in several species, suggesting that they can track the reliability of their own perceptual or memory processes.

Information-seeking paradigms offer another window into animal metacognition. In these tasks, animals can choose whether to seek additional information before making a decision. If an animal seeks information when it is uncertain but not when it is confident, this suggests that it is monitoring its own knowledge state. This paradigm has been used with various species to examine whether animals know when they do not know.

However, some researchers have raised concerns about the interpretation of these behaviors. One critique argues that comparative psychologists have been too quick to jump to metacognitive interpretations of their data. Uncertainty monitoring behavior may be better explained in terms of first-order estimates of risk, where the animal learns that certain stimuli are associated with lower reward probabilities. Similarly, informational search may be better explained by a first-order curiosity-like motivation that directs questions at the environment instead of by genuine metacognitive monitoring.

The Debate Over Associative Explanations

A significant debate in comparative metacognition research concerns whether observed behaviors can be explained by associative learning instead of genuine metacognitive processes. Associative modelers have used formal mathematical models to describe animals' metacognitive performances in associative-behaviorist ways. These models attempt to show that animals could produce the observed behaviors without any genuine monitoring of their own mental states.

Critics of this approach argue that these attempts to reify formal models as proof of particular explanations misunderstand the content and proper application of models. They contend that such models embody mistakes of scientific reasoning, blur fundamental distinctions in understanding animal cognition, and impede theoretical development. Instead, they advocate for careful empirical work that can describe the psychology underlying animals' metacognitive performances.

This debate highlights the difficulty of studying internal mental states in nonhuman animals. Because we cannot directly observe an animal's subjective experience, we must rely on behavioral evidence and theoretical inference. The challenge is to determine when behavioral patterns are best explained by metacognitive processes and when they can be accounted for by simpler mechanisms. This question remains actively debated in the field, with different research groups favoring different interpretations of the available evidence.

Model-Based and Model-Free Metacognition

Recent theoretical work has proposed a distinction between two forms of metacognition. Model-based metacognition implicates at least a simplified model of the thinker's own mind, allowing the individual to reason about their own cognitive processes. Model-free metacognition represents some mental state or process in oneself without requiring such a model. This distinction has important implications for interpreting animal behavior.

Research on human metacognitive judgments has focused primarily on the model-based variety, as have most attempts to discover metacognition in animals. However, some researchers argue that the behavioral tests employed with animals fail to provide evidence of even simplified forms of model-based metacognition. This conclusion is based on studies suggesting that there are no resources shared between human metacognitive judgments and the sorts of behavioral tests employed with animals.

The question of model-free metacognition in animals has received more positive answers. Two forms of model-free metacognition have been defended. First, epistemic emotions like curiosity and interest, as well as the signals involved in failed memory searches, implicate representations whose content is unknown. Second, decisions to deploy attentional or mental effort, which many animals besides humans can make, depend on appraisals of an analog-magnitude signal representing the extent to which executive resources are engaged. These forms of metacognition do not require a model of the mind but still involve monitoring and regulating cognitive processes.

At a Glance: Metacognitive Abilities Across Species

The following table summarizes the evidence for metacognitive abilities across different species groups, based on the experimental paradigms discussed in this article.

Neural Substrates of Confidence and Metacognition

Understanding the neural mechanisms underlying confidence judgments is essential for determining whether animals share metacognitive processes with humans. Research using computational approaches has identified neural correlates of decision confidence in rats, showing that confidence assessments can be generated using elementary neural computations available to a wide range of species. This finding suggests that the neural building blocks of metacognition are not unique to humans.

The investigation of neural substrates has been advanced by the development of behavioral tasks that can be used with animals while neural activity is recorded. These tasks allow researchers to identify when and where confidence signals are computed in the brain. The results indicate that confidence information is represented in neural circuits that are also involved in decision-making more broadly, suggesting that metacognitive monitoring is integrated with first-order cognitive processes.

The neural evidence has important implications for understanding the evolution of metacognition. If confidence computations rely on basic neural mechanisms that are widely conserved across species, then metacognition may have evolved early in animal evolution instead of being a uniquely human capacity. This perspective is consistent with the view that metacognition is not a single ability but a family of related processes that vary in complexity across species.

Consciousness, Self-Awareness, and the Mirror Test

The study of metacognition is closely related to questions about consciousness and self-awareness. Consciousness is a state of subjective experience or awareness, such as awareness of an emotion, the self, or external objects. In humans, this awareness is underpinned by a suite of cognitive functions, from attention to metacognition. To understand the evolution of consciousness, the study of these cognitive functions across a variety of animal taxa is critical.

The mirror test is a well-known paradigm for assessing self-awareness in animals. In this test, an animal is marked with a visible dye or sticker and then placed in front of a mirror. If the animal touches or investigates the mark on its own body instead of on the mirror image, this is taken as evidence of self-recognition. While the mirror test has been used with many species, its relationship to metacognition is complex. Self-recognition may require some form of self-monitoring, but it is not identical to the confidence judgments studied in metacognition research.

Insects have emerged as useful organisms for studying the building blocks of consciousness because researchers have a sophisticated understanding of their cognition from over a century of study, and modern tools are revealing the intricacies of insect brains with increasing clarity. Research on insects has focused on emotions, the distinction of self and other, prediction, attention, and active sleep. While there can still be no formal certainty about consciousness in insects, evidence from these lines of investigation builds toward an increasing probability that insects might possess some form of subjective experience.

Comparative Evidence Across Taxonomic Groups

The comparative evidence for metacognition spans multiple taxonomic groups, each providing unique insights into the evolution of metacognitive abilities. Primates have been the most extensively studied, with multiple paradigms providing convergent evidence for metacognitive abilities. Monkeys and apes can learn to decline difficult trials, place bets on their accuracy, and seek information when uncertain. These findings are consistent with the view that primates possess a functional analog to human metacognition.

Rodents have become increasingly important in metacognition research because they offer opportunities for neural recording and manipulation that are not feasible in primates. Studies with rats have demonstrated that they can report confidence in perceptual decisions and that confidence signals are represented in their neural activity. The computational framework developed for studying confidence in rats has provided a model for how confidence judgments can be generated using elementary neural computations.

Birds, particularly pigeons, have been studied in metacognition paradigms with mixed results. Some studies have found evidence for uncertainty monitoring, while others have suggested that associative explanations can account for the observed behavior. The debate over pigeon metacognition illustrates the broader challenge of distinguishing genuine metacognitive monitoring from learned associations.

Dolphins have been studied in auditory discrimination tasks, with early research suggesting that they can monitor their own uncertainty. However, the limited number of studies and the practical challenges of working with marine mammals mean that the evidence base is smaller than for other species.

Practical Assessment Steps for Evaluating Metacognitive Claims

When evaluating claims about metacognition in animals, researchers and students should follow a systematic approach to assess the quality of the evidence. The following steps provide a framework for critically evaluating comparative metacognition research.

First, identify the specific paradigm used and determine whether it includes appropriate controls. The key controls are ensuring that escape responses do not increase the overall density of reinforcement and that they do not occur in the presence of the stimuli on which the subject was trained. Without these controls, apparent metacognitive behavior may reflect simpler learning processes.

Second, examine whether the results are consistent across multiple paradigms. Convergent evidence from uncertainty monitoring, post-decision wagering, and information-seeking tasks provides stronger support for metacognitive interpretations than evidence from a single paradigm. Researchers should be cautious about drawing strong conclusions from studies that rely on only one type of task.

Third, consider whether associative explanations can account for the observed behavior. Formal models that describe how animals could produce metacognitive-like behavior through associative learning should be evaluated alongside metacognitive interpretations. The existence of a plausible associative account does not necessarily disprove metacognition, but it does require careful consideration.

Fourth, assess whether the study includes neural evidence when available. Studies that identify neural correlates of confidence provide stronger evidence for metacognitive processes than behavioral studies alone. The identification of confidence signals in neural activity supports the interpretation that animals are genuinely tracking their own accuracy.

Records and Measurements in Metacognition Research

Systematic record-keeping is essential for metacognition research. Researchers should maintain detailed records of trial-by-trial performance, including accuracy, response times, confidence ratings or wagers, and escape or information-seeking choices. These records allow for the calculation of metacognitive sensitivity, which measures how well confidence tracks accuracy, and metacognitive efficiency, which accounts for the difficulty of the task.

Standard measurements in metacognition research include the calibration between confidence and accuracy, which examines whether high-confidence responses are more accurate than low-confidence responses. Researchers also measure the resolution of confidence judgments, which indicates how well an individual can distinguish between correct and incorrect responses. These measurements can be compared across species to assess whether animals show similar patterns of confidence to humans.

The comparison of metacognitive sensitivity and efficiency across species requires careful attention to task design. Tasks that are too easy or too difficult may not provide meaningful measures of metacognitive ability. Researchers must also consider whether animals have had sufficient training to understand the task requirements and whether performance reflects genuine metacognitive monitoring or learned response strategies.

Common Failure Patterns in Comparative Metacognition Research

Several common failure patterns can undermine the validity of comparative metacognition research. The most significant is the failure to include adequate controls for associative learning. When animals can learn to escape difficult trials because doing so leads to rewards, their behavior may not reflect genuine uncertainty monitoring. Researchers must ensure that escape responses do not increase the overall density of reinforcement.

Another common failure is the overinterpretation of results from a single paradigm. Studies that rely on only one type of task may produce results that are specific to that task instead of reflecting general metacognitive abilities. Convergent evidence from multiple paradigms provides stronger support for metacognitive interpretations.

A third failure pattern involves the use of tasks that are too complex for the species being studied. If an animal cannot understand the task requirements, its performance may not provide meaningful information about metacognitive abilities. Researchers must ensure that animals have sufficient training and that task demands are appropriate for the species.

A fourth failure pattern is the neglect of individual differences. Animals within a species may vary in their metacognitive abilities, and averaging across individuals can obscure important patterns. Researchers should examine individual performance and consider whether variability in metacognitive abilities is related to other cognitive or behavioral characteristics.

Limitations and Open Questions

The study of metacognition in animals faces several fundamental limitations. The most basic limitation is that we cannot directly access the subjective experience of nonhuman animals. All evidence for animal metacognition is indirect, based on behavioral observations and neural recordings. This limitation means that interpretations of animal behavior are always subject to debate.

A related limitation is the difficulty of distinguishing genuine metacognitive monitoring from simpler cognitive processes. The debate over associative explanations illustrates this challenge. While many researchers are convinced that some animals possess metacognitive abilities, others argue that the observed behaviors can be explained without invoking metacognition.

The relationship between metacognition and consciousness remains poorly understood. While metacognition is often considered a component of consciousness, the exact relationship between these constructs is unclear. Some researchers argue that metacognition can exist without consciousness, while others view metacognitive monitoring as a form of conscious awareness.

Open questions in the field include whether metacognition is a single ability or a family of related processes, how metacognitive abilities vary across species, and what neural mechanisms support confidence judgments. The development of new experimental paradigms and computational models continues to advance our understanding of these questions.

Welfare and Safety Context

The study of metacognition in animals raises important welfare considerations. Researchers must ensure that experimental procedures do not cause unnecessary distress to animal subjects. Tasks that involve difficult discriminations or the withholding of rewards should be designed to minimize stress and provide adequate opportunities for animals to obtain reinforcement.

The welfare of animals in metacognition research is governed by institutional animal care and use committees, which review experimental protocols to ensure compliance with ethical standards. Researchers must justify the use of animals, minimize the number of subjects, and refine procedures to reduce pain and distress. These requirements are consistent with the broader principles of ethical animal research.

The safety context for metacognition research primarily concerns the use of neural recording and manipulation techniques in animal subjects. These procedures require appropriate anesthesia, analgesia, and postoperative care to ensure animal welfare. Researchers must follow established protocols for surgical procedures and monitor animals closely during recovery.

Professional Escalation Criteria

Researchers and students who encounter concerns about the interpretation of metacognition research should escalate their questions to appropriate experts. When evaluating whether a particular behavioral result reflects genuine metacognition, consultation with researchers who have expertise in both comparative cognition and associative learning can provide valuable perspective.

If concerns arise about the welfare of animals in metacognition research, these should be reported to the institutional animal care and use committee. Concerns about the ethical treatment of animals should be addressed promptly to ensure compliance with institutional policies and legal requirements.

When interpreting metacognition research for educational or clinical purposes, professionals should be aware of the limitations of the evidence and avoid overstating conclusions. The distinction between evidence for metacognitive abilities and evidence for simpler cognitive processes should be maintained in all communications.

Applications in Education and Clinical Contexts

Metacognition research has important applications in education and clinical practice. In educational settings, metacognitive skills such as self-assessment and confidence calibration are associated with improved learning outcomes. Research on open-ended problems in mathematics education has shown that students who develop their own problem-solving strategies improve their abilities and are better equipped to face unpredictable challenges.

Studies of metacognition in clinical populations have revealed that metacognitive deficits are associated with various psychiatric disorders. Research comparing metacognition and meta-emotion in schizophrenia, bipolar I disorder, and obsessive-compulsive disorder has found distinct patterns of metacognitive functioning across these conditions. Individuals with schizophrenia showed the lowest scores on cognitive self-consciousness and cognitive confidence, while individuals with obsessive-compulsive disorder showed the highest cognitive self-consciousness.

The assessment of metacognition in clinical settings can inform treatment approaches. For example, research on social anxiety disorder in adolescents has found that impairments in metacognitive beliefs and working memory may help distinguish affected adolescents from their typically developing peers. Incorporating these domains into clinical assessment and intervention strategies could enhance early detection and treatment outcomes.

Metacognition in Artificial Systems

The study of metacognition has recently extended to artificial intelligence systems, particularly large language models. Research comparing humans and GPT-4 across multiple task formats has examined how confidence relates to performance. While GPT-4 consistently outperformed humans in task accuracy, this advantage was not accompanied by human-like confidence behavior. Human confidence closely tracked variations in accuracy, while GPT-4 confidence did not.

These findings reveal a dissociation between task-level performance and metacognitive behavior in GPT-4, suggesting that its confidence reflects structural properties of its outputs instead of genuine internal uncertainty monitoring. This research indicates that GPT-4 lacks robust metacognitive abilities compared to humans, or at least that its metacognitive processes differ significantly from those of humans.

The study of metacognition in artificial systems has implications for AI alignment and safety. If AI systems cannot accurately monitor their own uncertainty, they may produce confident but incorrect outputs. Understanding the differences between human and artificial metacognition is essential for developing AI systems that can appropriately communicate their confidence and limitations.

Frequently Asked Questions

What is the difference between metacognition and consciousness?

Metacognition refers specifically to the monitoring and evaluation of one's own cognitive processes, such as knowing when you are uncertain about a decision. Consciousness is a broader concept that refers to subjective experience or awareness of oneself and the external world. In humans, metacognition is one of several cognitive functions that underpin consciousness, but the two concepts are not identical. An organism could potentially have metacognitive abilities without possessing the full range of conscious experiences that humans have.

How do researchers study metacognition in animals that cannot speak?

Researchers use nonverbal behavioral paradigms to study metacognition in animals. The two primary methods are uncertainty monitoring, where animals can escape or decline difficult trials, and post-decision wagering, where animals place bets on the accuracy of their responses. These methods require careful controls to rule out simpler explanations, such as learned associations between stimuli and rewards. Researchers also use information-seeking paradigms where animals can choose whether to obtain additional information before making a decision.

What species have shown evidence of metacognitive abilities?

Evidence for metacognitive abilities has been reported in several species, including apes, monkeys, rats, pigeons, and dolphins. The strength of evidence varies across species, with primates showing the most consistent results across multiple paradigms. Rats have provided important neural evidence for confidence computations. The interpretation of evidence in some species, particularly pigeons, remains debated, with some researchers arguing that associative explanations can account for the observed behavior.

Does passing the mirror test mean an animal has metacognition?

The mirror test assesses self-recognition, which is related to but not identical with metacognition. Self-recognition involves the ability to recognize oneself in a mirror, which may require some form of self-monitoring. However, metacognition specifically involves monitoring one's own knowledge and confidence, which is a different capacity. An animal could potentially pass the mirror test without demonstrating metacognitive abilities, and vice versa.

Can insects have metacognitive abilities?

Research on insects has focused on the building blocks of consciousness, including emotions, the distinction of self and other, prediction, attention, and active sleep. While there is no formal certainty about consciousness in insects, evidence from these lines of investigation suggests that insects might possess some form of subjective experience. Whether insects have metacognitive abilities in the same sense as humans or other mammals remains an open question that requires further investigation.

Why is the study of animal metacognition controversial?

The study of animal metacognition is controversial because researchers cannot directly access the subjective experience of nonhuman animals. All evidence is indirect, based on behavioral observations and neural recordings. Some researchers argue that observed behaviors can be explained by simpler associative learning processes instead of genuine metacognitive monitoring. This debate reflects fundamental questions about how to interpret animal behavior and what counts as evidence for internal mental states.

How is metacognition measured in humans?

In humans, metacognition is typically measured through verbal reports, where individuals state how confident they are about a decision or memory. Researchers also use behavioral measures such as post-decision wagering and response time patterns. Computational models can be used to quantify metacognitive sensitivity, which measures how well confidence tracks accuracy, and metacognitive efficiency, which accounts for task difficulty. These measures can be compared across individuals and populations.

What are the practical applications of metacognition research?

Metacognition research has applications in education, where metacognitive skills are associated with improved learning outcomes, and in clinical psychology, where metacognitive deficits are associated with various psychiatric disorders. Understanding metacognition can inform the development of educational interventions and clinical treatments. Research on metacognition in artificial systems has implications for AI alignment and safety, particularly for developing systems that can accurately communicate their confidence and limitations.

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References and Further Reading

• NCBI Literature Resources. National Center for Biotechnology Information.
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• Obsessive-Compulsive Disorder: Puzzles and Prospects.. Neuron, 2019.
• The exploration of consciousness in insects.. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2025.
• Visual Confidence.. Annual review of vision science, 2016.
• Comparative metacognition.. Current opinion in neurobiology, 2009.
• A computational framework for the study of confidence in humans and animals.. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2012.
• Model-free metacognition.. Cognition, 2022.
• Immuno-epileptology.. Expert review of clinical immunology, 2017.
• Formal models in animal-metacognition research: the problem of interpreting animals' behavior.. Psychonomic bulletin & review, 2016.
• A Special Issue Introduction: Educational Applications of Cognitive Psychology.. 2026.
• Metacognition of ChatGPT in confidence judgements.. 2026.
• Attribution of consciousness to non-human animals: insights from AI and multidimensional frameworks.. 2026.
• Metacognitive profiling of PDO goat cheese consumers based on self-perceived sensory evaluation difficulty.. 2026.
• Effectiveness of virtual simulation-based pre-learning and the mediating role of metacognition in pharmacokinetics laboratory education.. 2026.
• The interplay of self-efficacy, grit, and metacognition in shaping work engagement among EFL teachers: a comparative study of Mainland China and Hong Kong. BMC Psychology, 2025.
• Enhancing metacognition and nursing competency in undergraduate students utilizing multi-user virtual environment simulations: A multi-site multi-group comparative study.. Nurse Education Today, 2025.
• Metacognition and meta-emotion in schizophrenia, bipolar I disorder, and obsessive-compulsive disorder: A cross-sectional comparative study.. Acta Psychologica, 2025.
• Theory of mind, metacognition, and executive functions in adolescents with social anxiety disorder: a comparative study. Child and Adolescent Psychiatry and Mental Health, 2025.
• Comparative metacognition. Animal Behavior and Cognition, 2019.
• 1 Comparative metacognition. 2019.
• Exploring the Role of Metacognition in Measuring Students’ Critical Thinking and Knowledge in Mathematics: A Comparative Study of Regression and Neural Networks. Knowledge, 2023.
• Comparative Approaches to the Natural Ecology of Metacognition. Comparative Cognition &amp, Behavior Reviews, 2023.
• Metacognition and Metamemory in Non-Human Animals. Encyclopedia of Animal Behavior Volume Three Set, 2010.
• Metacognition and Metamemory in Non-Human Animals. Encyclopedia of Animal Behavior Second Edition Volume 1 5, 2019.

This article is educational and does not replace institutional policy, professional advice, or applicable safety and regulatory requirements.