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Despite tremendous recent progress, extant artificial intelligence (AI) still falls short of matching human learning in effectiveness and efficiency. One fundamental disparity is that humans possess a wealth of prior knowledge, while AI lacks the essential commonsense knowledge required for learning tasks. Guided by schema theory, we employ the design science research methodology to introduce a novel knowledge-aware learning framework to harness the knowledge-based processes in human learning. Unlike existing pre-trained large language models (LLMs) and knowledge-aware approaches that treat knowledge in considerably different ways from humans, our theoretically grounded framework closely mimics how humans acquire, represent, activate, and utilize knowledge. The extensive evaluations in the context of text analytics tasks demonstrate that our design achieves comparable performance to the state-of-the-art LLMs and enhances model generalizability and learning efficiency. This study takes a step forward by bringing cognitive science into building cognitively plausible AI and human-AI collaboration research. [ABSTRACT FROM AUTHOR]

This article delves into the examination of the similarities and disparities between education and enhancement, with a particular focus on enhancement within the realm of NBIC (Nano-Bio-Information Technology, Cognitive Science). After scrutinizing how proponents of enhancement have delineated the concept of education, our investigation unfolds along two primary dimensions: the anthropological underpinnings of education and enhancement discourse and their respective objectives. Through this analysis, we assert that education and enhancement exhibit distinct characteristics and objectives, defying easy comparison for determining which approach is more conducive to human improvement, notwithstanding their superficially analogous theoretical frameworks and objectives. Furthermore, we aim to highlight the perceptual illusions that blur the demarcation lines between education and enhancement, in order to establish a clear and distinctive role for education amid the plethora of enhancement discourses. [ABSTRACT FROM AUTHOR]

This article aims to delve into the theoretical perspective on imagination in education, focusing specifically on Imaginative Education theory. The approach involves a dual objective: critically analyzing the limitations and specific potentials of Imaginative Education to stimulate contemporary discourse on imagination in education and using it as a foundation to frame current research in philosophy and psychology within an educational context. Key elements of this theoretical operation include a critical examination of philosophical taxonomies on the concept of imagination and its reinterpretation in relation to Predictive Coding and Embodied Cognition theories. The fundamental goal of this conceptual clarification goes beyond the theoretical realm. The article aspires to contribute to the growing interest in imagination, fantasy, and creativity as essential elements of curriculum design and teacher education, serving both as educational objectives and resources to create meaningful learning environments and experiences. Hence, the focus on the IE theory aims to bridge the gap between theoretical reflections on imagination and learning and their practical implications in curriculum design and teacher education or professional development. [ABSTRACT FROM AUTHOR]

Video presentation has become ubiquitous in paradigms investigating the neural and behavioral responses to observed actions. In spite of the great interest in uncovering the processing of observed bodily movements and actions in neuroscience and cognitive science, at present, no standardized set of video stimuli for action observation research in neuroimaging settings exists. To facilitate future action observation research, we developed an open-access database of 135 high-definition videos of a male actor performing object-oriented actions. Actions from 3 categories: kinematically natural and goal-intact (Normal), kinematically unnatural and goal-intact (How), or kinematically natural and goal-violating (What), directed toward 15 different objects were filmed from 3 angles. Psychometric evaluation of the database revealed high video recognition accuracy (Mean accuracy = 88.61 %) and substantial inter-rater agreement (Fleiss' Kappa = 0.702), establishing excellent validity and reliability. Videos' exact timing of motion onset was identified using a custom motion detection frame-differencing procedure. Based on its outcome, the videos were edited to assure that motion begins at the second frame of each video. The videos' timing of category recognition was also identified using a novel behavioral up-down staircase procedure. The identified timings can be incorporated in future experimental designs to counteract jittered stimulus onsets, thus vastly improving the sensitivity of neuroimaging experiments. All videos, their psychometric evaluations, and the timing of their frame of category recognition, as well as our custom programs for performing these evaluations on our, or on other similar video databases, are available at the Open Science Framework (https://osf.io/zexc4/). [ABSTRACT FROM AUTHOR]

Researchers increasingly explore deploying brain–computer interfaces (BCIs) for able-bodied users, with the motivation of accessing mental states more directly than allowed by existing body-mediated interaction. This motivation seems to contradict the long-standing HCI emphasis on embodiment, namely the general claim that the body is crucial for cognition. This paper addresses this apparent contradiction through a review of insights from embodied cognition and interaction. We first critically examine the recent interest in BCIs and identify the extent cognition in the brain is integrated with the wider body as a central concern for research. We then define the implications of an integrated view of cognition for interface design and evaluation. A counterintuitive conclusion we draw is that embodiment per se should not imply a preference for body-mediated interaction over BCIs. It can instead guide research by 1) providing body-grounded explanations for BCI performance, 2) proposing evaluation considerations that are neglected in modular views of cognition, and 3) through the direct transfer of its design insights to BCIs. We finally reflect on HCI's understanding of embodiment and identify the neural dimension of embodiment as hitherto overlooked. [ABSTRACT FROM AUTHOR]

Research Summary: External representations, particularly visuals, are important in strategic decision‐making. However, their pervasiveness and impact are not well understood in the strategy literature. Based on cognitive science research, we identify four cognitive functions crucial to strategic decision‐making that benefit from using external representations. We also propose a conceptual model and propositions that explain how the quality of strategic decision‐making depends on the interactions among task environment, external representations, and managers. We show that external representations influence in predictable ways the boundedly rational process of searching for new strategies. Key determinants include the manager's representational capability and the usability and malleability of the external representation. We discuss implications for users, designers, and teachers of external representations in strategy, as well as suggest avenues for future research. Managerial Summary: This research points to the pivotal role of external representations, especially visuals, in strategic decision‐making. Drawing from cognitive science, this study identifies four critical cognitive functions that benefit from these external representations—working memory, long‐term memory, pattern recognition, and knowledge transfer. Further, the study highlights that external representations significantly influence the process of strategic decision‐making in predictable ways. Finally, we show that not all external representations are alike in their ease of use and a managers' ability to operate on an external representation, referred to as representational capability, greatly affects the decision‐making quality. The implications extend to users, designers, and educators of external representations, urging attention to the design and use of external representations for improved decision outcomes. [ABSTRACT FROM AUTHOR]

Cognitive science has demonstrated that we construct knowledge about the world by abstracting patterns from routinely encountered experiences and storing them as semantic memories. This preregistered study tested the hypothesis that caregiving‐related early adversities (crEAs) shape affective semantic memories to reflect the content of those adverse interpersonal‐affective experiences. We also tested the hypothesis that because affective semantic memories may continue to evolve in response to later‐occurring positive experiences, child‐perceived attachment security will inform their content. The sample comprised 160 children (ages 6–12 at Visit 1; 87F/73 M), 66% of whom experienced crEAs (n = 105). At Visit 1, crEA exposure prior to study enrollment was operationalized as parental‐reports endorsing a history of crEAs (abuse/neglect, permanent/significant parent‐child separation); while child‐reports assessed concurrent attachment security. A false memory task was administered online ∼2.5 years later (Visit 2) to probe the content of affective semantic memories–specifically attachment schemas. Results showed that crEA exposure (vs. no exposure) was associated with a higher likelihood of falsely endorsing insecure (vs. secure) schema scenes. Attachment security moderated the association between crEA exposure and insecure schema‐based false recognition. Findings suggest that interpersonal‐affective semantic schemas include representations of parent‐child interactions that may capture the quality of one's own attachment experiences and that these representations shape how children remember attachment‐relevant narrative events. Findings are also consistent with the hypothesis that these affective semantic memories can be modified by later experiences. Moving forward, the approach taken in this study provides a means of operationalizing Bowlby's notion of internal working models within a cognitive neuroscience framework. Research Highlights: Affective semantic memories representing insecure schema knowledge (child needs + needs‐not‐met) may be more salient, elaborated, and persistent among youths exposed to early caregiving adversity.All youths, irrespective of early caregiving adversity exposure, may possess affective semantic memories that represent knowledge of secure schemas (child needs + needs‐met).Establishing secure relationships with parents following early‐occurring caregiving adversity may attenuate the expression of insecure semantic memories, suggesting potential malleability.Affective semantic memories include schema representations of parent‐child interactions that may capture the quality of one's own attachment experiences and shape how youths remember attachment‐relevant events. [ABSTRACT FROM AUTHOR]

One reason for the widespread use of the energy concept across the sciences is that energy analysis can be used to interpret the behavior of systems even if one does not know the particular mechanisms that underlie the observed behavior. By providing an approach to interpreting unfamiliar phenomena, energy provides a lens on phenomena that can set the stage for deeper learning about how and why phenomena occur. However, not all energy ideas are equally productive in setting the stage for new learning. In particular, researchers have debated the value of teaching students to interpret phenomena in terms of energy forms and transformations. In this study, we investigated how two different approaches to middle school energy instruction—one emphasizing energy transformations between forms and one emphasizing energy transfers between systems—prepared students to use their existing energy knowledge to engage in new learning about a novel energy‐related phenomenon. To do this, we designed a new assessment instrument to elicit student initial ideas about the phenomenon and to compare how effectively students from each approach learned from authentic learning resources. Our results indicate that students who learned to interpret phenomenon in terms of energy transfers between systems learned more effectively from available learning resources than did students who learned to interpret phenomena in terms of energy forms and transformations. This study informs the design of introductory energy instruction and approaches for assessing how students existing knowledge guides new learning about phenomena. [ABSTRACT FROM AUTHOR]

This paper stresses the importance of biases in the field of artificial intelligence (AI). To foster efficient algorithmic decision-making in complex, unstable, and uncertain real-world environments, we argue for the implementation of human cognitive biases in learning algorithms. We use insights from cognitive science and apply them to the AI field, combining theoretical considerations with tangible examples depicting promising bias implementation scenarios. Ultimately, this paper is the first tentative step to explicitly putting the idea forth to implement cognitive biases into machines. [ABSTRACT FROM AUTHOR]

Since the 18th century, one of the key features of diagnosed psychopaths has been "moral colorblindness" or an inability to form moral judgments. However, attempts at experimentally verifying this moral incapacity have been largely unsuccessful. After reviewing the centrality of "moral colorblindness" to the study and diagnosis of psychopathy, I argue that the reason that researchers have been unable to verify that diagnosed psychopaths have an inability to make moral judgments is because their research is premised on the assumption that there is a specific moral faculty of the brain, or specific "moral" emotions, and that this faculty or set of emotions can become "impaired". I review recent research and argue that we have good reason to think that there is no such distinct capacity for moral judgment, and that, as a result, it is impossible for someone's "moral judgment faculty" to become selectively disabled. I then discuss the implications of such a position on psychopathy research, the coherence of the disorder, and the moral responsibility of psychopaths. [ABSTRACT FROM AUTHOR]

To account for the explanatory role representations play in cognitive science, Egan's deflationary account introduces a distinction between cognitive and mathematical contents. According to that account, only the latter are genuine explanatory posits of cognitive-scientific theories, as they represent the arguments and values cognitive devices need to represent to compute. Here, I argue that the deflationary account suffers from two important problems, whose roots trace back to the introduction of mathematical contents. First, I will argue that mathematical contents do not satisfy important and widely accepted desiderata all theories of content are called to satisfy, such as content determinacy and naturalism. Secondly, I will claim that there are cases in which mathematical contents cannot play the explanatory role the deflationary account claims they play, proposing an empirical counterexample. Lastly, I will conclude the paper highlighting two important implications of my arguments, concerning recent theoretical proposals to naturalize representations via physical computation, and the popular predictive processing theory of cognition. [ABSTRACT FROM AUTHOR]

Some argue that emotions represent so-called core relational themes. A core relational theme describes a relation between a particular event and an organism's well-being. For instance, the core relational theme of anger is 'a demeaning offense against me and mine'. I argue that a core relational theme is a summary or generalization of a more complex mental content. Defenders of the Simple Core Relational Theme View reject the idea that emotional content is complex. Instead, they argue that the content of emotion simply consists of a core relational theme. I argue that this view commits the linguistic fallacy: it confuses a theory of emotion categorization with a theory of emotional content. [ABSTRACT FROM AUTHOR]

This study explores the relationship between humor, creativity, rationality, intuitiveness, and decision-making quality, all of which are vital in organizational management and success. Despite the importance attached to decision-making, prior research has not fully addressed how humor and creativity interact with rationality. Drawing from psychology, cognitive science, and management studies, we investigate how humor and creativity jointly influence cognitive reflection and decision quality. Using a sample of 998 participants and employing a mediating-moderation PROCESS model, our findings indicate that rational individuals tend to make higher-quality decisions, with affiliative humor mediating this relationship. Furthermore, we observed that employees' creativity levels moderated this relationship, especially among rational employees with high creativity, who made higher-quality decisions. These findings highlight the interconnectedness of humor, creativity, and rationality in decision-making processes, offering practical implications for organizational behavior and management practices. Understanding this interplay can provide a nuanced approach to enhancing decision-making processes in management, emphasizing the value of humor in organizational contexts. [ABSTRACT FROM AUTHOR]

Dual-process theories play a central role in both psychology and neuroscience, figuring prominently in domains ranging from executive control to reward-based learning to judgment and decision making. In each of these domains, two mechanisms appear to operate concurrently, one relatively high in computational complexity, the other relatively simple. Why is neural information processing organized in this way? We propose an answer to this question based on the notion of compression. The key insight is that dual-process structure can enhance adaptive behavior by allowing an agent to minimize the description length of its own behavior. We apply a single model based on this observation to findings from research on executive control, reward-based learning, and judgment and decision making, showing that seemingly diverse dual-process phenomena can be understood as domain-specific consequences of a single underlying set of computational principles. Author summary: Since the founding of psychology as a scientific discipline, scientists have recognized that much of human and animal behavior falls into two separate categories: slow, effortful deliberation (e.g., solving math problems) and fast, automatic habitual action selection (e.g., signing your name). Such "dual process" theories of cognition have since been developed to explain a number of phenomena from across psychology and neuroscience. Despite all of these experimental results, understanding why this pattern in behavior exists has proven elusive. In this work, we develop a model of dual process cognition which can be derived independently from experimental observations about the brain. Our theory proposes that the division between effortful and automatic behavior emerges as a natural result of the need to balance mastery of the tasks we have to complete every day and flexibility to adapt to new circumstances. In a large number of computer simulations, our model captures many behavioral phenomena associated with "dual process" cognition across multiple subfields of cognitive science. [ABSTRACT FROM AUTHOR]

Video presentation has become ubiquitous in paradigms investigating the neural and behavioral responses to observed actions. In spite of the great interest in uncovering the processing of observed bodily movements and actions in neuroscience and cognitive science, at present, no standardized set of video stimuli for action observation research in neuroimaging settings exists. To facilitate future action observation research, we developed an open-access database of 135 high-definition videos of a male actor performing object-oriented actions. Actions from 3 categories: kinematically natural and goal-intact (Normal), kinematically unnatural and goal-intact (How), or kinematically natural and goal-violating (What), directed toward 15 different objects were filmed from 3 angles. Psychometric evaluation of the database revealed high video recognition accuracy (Mean accuracy = 88.61 %) and substantial inter-rater agreement (Fleiss' Kappa = 0.702), establishing excellent validity and reliability. Videos' exact timing of motion onset was identified using a custom motion detection frame-differencing procedure. Based on its outcome, the videos were edited to assure that motion begins at the second frame of each video. The videos' timing of category recognition was also identified using a novel behavioral up-down staircase procedure. The identified timings can be incorporated in future experimental designs to counteract jittered stimulus onsets, thus vastly improving the sensitivity of neuroimaging experiments. All videos, their psychometric evaluations, and the timing of their frame of category recognition, as well as our custom programs for performing these evaluations on our, or on other similar video databases, are available at the Open Science Framework (https://osf.io/zexc4/). [ABSTRACT FROM AUTHOR]

Video presentation has become ubiquitous in paradigms investigating the neural and behavioral responses to observed actions. In spite of the great interest in uncovering the processing of observed bodily movements and actions in neuroscience and cognitive science, at present, no standardized set of video stimuli for action observation research in neuroimaging settings exists. To facilitate future action observation research, we developed an open-access database of 135 high-definition videos of a male actor performing object-oriented actions. Actions from 3 categories: kinematically natural and goal-intact (Normal), kinematically unnatural and goal-intact (How), or kinematically natural and goal-violating (What), directed toward 15 dierent objects were filmed from 3 angles. Psychometric evaluation of the database revealed high video recognition accuracy (Mean accuracy = 88.61 %) and substantial inter-rater agreement (Fleiss’ Kappa = 0.702), establishing excellent validity and reliability. Videos’ exact timing of motion onset was identified using a custom motion detection frame-dierencing procedure. Based on its outcome, the videos were edited to assure that motion begins at the second frame of each video. The videos’ timing of category recognition was also identified using a novel behavioral up-down staircase procedure. The identified timings can be incorporated in future experimental designs to counteract jittered stimulus onsets, thus vastly improving the sensitivity of neuroimaging experiments. All videos, their psychometric evaluations, and the timing of their frame of category recognition, as well as our custom programs for performing these evaluations on our, or on other similar video databases, are available at the Open Science Framewo. [ABSTRACT FROM AUTHOR]

The widespread adoption of large language models (LLMs) makes it important to recognize their strengths and limitations. We argue that to develop a holistic understanding of these systems, we must consider the problem that they were trained to solve: next-word prediction over Internet text. By recognizing the pressures that this task exerts, we can make predictions about the strategies that LLMs will adopt, allowing us to reason about when they will succeed or fail. Using this approach--which we call the teleological approach--we identify three factors that we hypothesize will influence LLM accuracy: the probability of the task to be performed, the probability of the target output, and the probability of the provided input. To test our predictions, we evaluate five LLMs (GPT-3.5, GPT-4, Claude 3, Llama 3, and Gemini 1.0) on 11 tasks, and we find robust evidence that LLMs are influenced by probability in the hypothesized ways. Many of the experiments reveal surprising failure modes. For instance, GPT-4's accuracy at decoding a simple cipher is 51% when the output is a high-probability sentence but only 13% when it is low-probability, even though this task is a deterministic one for which probability should not matter. These results show that AI practitioners should be careful about using LLMs in low-probability situations. More broadly, we conclude that we should not evaluate LLMs as if they are humans but should instead treat them as a distinct type of system--one that has been shaped by its own particular set of pressures. [ABSTRACT FROM AUTHOR]

This theme issue brings together researchers from diverse fields to assess the current status and future prospects of embodied cognition in the age of generative artificial intelligence. In this introduction, we first clarify our view of embodiment as a potentially unifying concept in the study of cognition, characterizing this as a perspective that questions mind–body dualism and recognizes a profound continuity between sensorimotor action in the world and more abstract forms of cognition. We then consider how this unifying concept is developed and elaborated by the other contributions to this issue, identifying the following two key themes: (i) the role of language in cognition and its entanglement with the body and (ii) bodily mechanisms of interpersonal perception and alignment across the domains of social affiliation, teaching and learning. On balance, we consider that embodied approaches to the study of cognition, culture and evolution remain promising, but will require greater integration across disciplines to fully realize their potential. We conclude by suggesting that researchers will need to be ready and able to meet the various methodological, theoretical and practical challenges this will entail and remain open to encountering markedly different viewpoints about how and why embodiment matters. This article is the part of this theme issue 'Minds in movement: embodied cognition in the age of artificial intelligence'. [ABSTRACT FROM AUTHOR]

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Nostalgia is a common emotional phenomenon, but its complexity has resulted in a limited understanding and interpretation. This study, grounded in emotional cognitive science, develops a cognitive processing model of nostalgia, encompassing its triggering mechanism, cognitive processes, and effects. The analysis indicates that nostalgia functions as an adaptive mechanism for individuals with deficiencies in belongingness and low-avoidance tendencies, helping them cope with disruptions in self-continuity by forging symbolic social bonds in a distant and idealized timespace. Essentially, nostalgia allows individuals to reconstruct alternate systems of meaning and value, which serve as references for defining self-worth and identity. This study advances the understanding of the complex cognitive processing involved in nostalgia and also provides an important reference for the study of complex emotions. [ABSTRACT FROM AUTHOR]

Women's empowerment is a critical topic included in a wide range of programs and policies of various institutions worldwide. Despite this, research in cognitive sciences, particularly regarding cognition and cognitive abilities, has often been overlooked in many of these policies. This research aims to bridge this gap by providing a framework for empowering women in governance based on cognitive science studies. It employs a two-step method comprising a scoping review and content analysis. The study's findings include 18 key elements of women's empowerment derived from cognitive studies and a conceptual framework. These results can guide experts, researchers, and policymakers interested in empowerment, governance, and women's issues in their decision-making processes. Additionally, this research advocates for the creation of a network of related concepts, facilitating collaboration and knowledge sharing. The significance of this study extends to applied research, aiming to connect different fields of governance and cognitive science. It highlights the importance of interdisciplinary approaches in addressing complex issues and identifies conceptual gaps that can inspire further research. By doing so, it opens new pathways for those interested in interdisciplinary studies, offering a comprehensive understanding of the interplay between cognitive sciences and women's empowerment. This comprehensive approach not only enriches the academic discourse but also has practical implications for policy and governance, ultimately contributing to more effective and inclusive empowerment strategies. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Beijing University of Traditional Chinese Medicine is the property of Journal of Beijing University of Traditional Chinese Medicine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Determining the compositional structure and dimensionality of psychological constructs lies at the heart of many research questions in developmental science. Structural equation modeling (SEM) provides a versatile framework for formalizing and estimating the relationships among multiple latent constructs. While the flexibility of SEM can accommodate many complex assumptions on the underlying structure of psychological constructs, it makes a priori estimation of statistical power and required sample size challenging. This difficulty is magnified when comparing non-nested SEMs, which prevents the use of traditional likelihood-ratio tests. Sample size estimates for SEM model fit comparisons typically rely on generic rules of thumb. Such heuristics can be misleading because statistical power in SEM depends on a variety of model properties. Here, we demonstrate a Monte Carlo simulation approach for estimating a priori statistical power for model selection when comparing non-nested models in an SEM framework. We provide a step-by-step guide to this approach based on an example from our memory development research in children. [ABSTRACT FROM AUTHOR]

Perceiving an armchair prepares us to sit. Reading the first line in a text prepares us to read it. This article proposes that the affordance construct used to explain reactive potentiation of behavior similarly applies to reactive potentiation of cognitive actions. It defends furthermore that, in both cases, affordance-sensings do not only apply to selective (dis)engagement, but also to the revision and the termination of actions. In the first section, characteristics of environmental affordance-sensings such as directness, stability, action potentiation, valence, and phenomenology are reexamined in light of contemporary cognitive science. In the second section, it is proposed that cognitive affordance-sensings can also be characterized along these dimensions. Called "metacognitive feelings" in the metacognitive literature, their function is to select, engage, revise and post-evaluate cognitive actions. A third section discusses alternative views, and responds to objections. [ABSTRACT FROM AUTHOR]

Cognitive science has well-established the correlation between faces and voices because neuro-cognitive pathways of both information share the same structure. Recently, the task has come to the attention of the computer vision community with the introduction of large-scale face-voice data. To this end, our work aims to leverage the structure of faces and voices along with the availability of large-scale face-voice information to improve speaker recognition tasks including identification and verification. To achieve this task, we propose novel multimodal systems to leverage the structure of face and voice, one with weight sharing and another without weight sharing, to learn joint representations of multiple modalities establishing the Face-voice association. Afterwards, features are extracted from the trained multimodal networks capturing face-voice association to perform speaker recognition tasks. We evaluated our proposed multimodal networks for speaker recognition along with Face-voice association tasks on challenging benchmark datasets including VoxCeleb1 and MAV-Celeb. Our results show that adding facial information improved speaker recognition tasks' performance. [ABSTRACT FROM AUTHOR]

Trends and developments in recent behavioural and cognitive sciences demonstrate the need for a well-developed theoretical and empirical framework for examining the ecology of human behaviour. The increasing recognition of the role of the environment and interaction with the environment in the organization of behaviour within the cognitive sciences has not been met with an equally disciplined and systematic account of that environment (Heft 2018 Ecol. Psychol. 30, 99–123 (doi:10.1080/10407413.2018.1410045); McGann 2014 Synth. Philos.29, 217–233). Several bodies of work in behavioural ecology, anthropology and ecological psychology provide some frameworks for such an account. At present, however, the most systematic and theoretically disciplined account of the human behavioural ecosystem is that of behaviour settings, as developed by the researchers of the Midwest Psychological Field Station (see Barker 1968 Ecological psychology: concepts and methods for studying the environment of human behavior). The articles in this theme issue provide a critical examination of these theoretical and methodological resources. The collection addresses their theoretical value in connecting with contemporary issues in cognitive science and research practice in psychology, as well as the importance of the methodological specifics of behaviour settings research. Additionally, articles diagnose limitations and identify points of potential extension of both theory and methods, particularly with regard to changes owing to the advance of technology, and the complex relationship between the individual and the collective in behaviour settings work. This article is part of the theme issue 'People, places, things, and communities: expanding behaviour settings theory in the twenty-first century'. [ABSTRACT FROM AUTHOR]

At the intersection of computation and cognitive science, graph theory is utilized as a formalized description of complex relationships description of complex relationships and structures, but traditional graph models are static, lack the dynamic and autonomous behaviors of biological neural networks, rely on algorithms with a global view. This study introduces a multi-agent system (MAS) model based on the graph theory, each agent equipped with adaptive learning and decision-making capabilities, thereby facilitating decentralized dynamic information memory, modeling and simulation of the brain's memory process. This decentralized approach transforms memory storage into the management of MAS paths, with each agent utilizing localized information for the dynamic formation and modification of these paths, different path refers to different memory instance. The model's unique memory algorithm avoids a global view, instead relying on neighborhood-based interactions to enhance resource utilization. Emulating neuron electrophysiology, each agent's adaptive learning behavior is represented through a microcircuit centered around a variable resistor. Using principles of Ohm's and Kirchhoff's laws, we validated the model's efficacy in memorizing and retrieving data through computer simulations. This approach offers a plausible neurobiological explanation for memory realization and validates the memory trace theory at a system level. [ABSTRACT FROM AUTHOR]

Research on brain function in natural environments has become a new interest in cognitive science. In this study, we aim to advance mobile electroencephalography (EEG) participant and device mobility. We investigated the feasibility of measuring human brain activity using mobile EEG during a full-body motion task as swimming, by the example of cognitive-motor interference (CMI). Eleven participants were given an auditory oddball task while sitting and swimming, with mobile EEG recording ongoing brain activity. Measures of interest were event-related potentials (ERPs) elicited by experimental stimuli. While the auditory N100 was measured to verify signal quality, the P300 to task-relevant stimuli served as a marker of CMI effects. Analyzes were first performed within subjects, while binomial tests assessed the proportion of significant effects. Event-related changes in the time-frequency domain around turns during swimming were analyzed in an exploratory fashion. The successful recording of the N100 in all conditions shows that the setup was functional throughout the experiment. Regarding CMI, we did not find reliable changes in P300 amplitude in different motor settings in all subjects. However, we found plausible modulations in the alpha/mu and beta bands before and after turns. This study shows that it is generally feasible to measure mobile EEG in the time and time-frequency domain in an aquatic environment while subjects are freely moving. We see promising potential in the use of mobile EEG in extreme settings, advancing toward the application of mobile EEG in more real-life situations. [ABSTRACT FROM AUTHOR]

Since the birth of cognitive science, researchers have used reaction time and accuracy to measure cognitive ability. Although recognition of these two measures is often based on empirical observations, the underlying consensus is that most cognitive behaviors may be along two fundamental dimensions: cognitive processing speed (CPS) and cognitive processing accuracy (CPA). In this study, we used genomic-wide association studies (GWAS) data from 14 cognitive traits to show the presence of those two factors and revealed the specific neurobiological basis underlying them. We identified that CPS and CPA had distinct brain phenotypes (e.g. white matter microstructure), neurobiological bases (e.g. postsynaptic membrane), and developmental periods (i.e. late infancy). Moreover, those two factors showed differential associations with other health-related traits such as screen exposure and sleep status, and a significant causal relationship with psychiatric disorders such as major depressive disorder and schizophrenia. Utilizing an independent cohort from the Adolescent Brain Cognitive Development (ABCD) study, we also uncovered the distinct contributions of those two factors on the cognitive development of young adolescents. These findings reveal two fundamental factors underlying various cognitive abilities, elucidate the distinct brain structural fingerprint and genetic architecture of CPS and CPA, and hint at the complex interrelationship between cognitive ability, lifestyle, and mental health. Here, the authors investigate the genetic architecture and neuroimaging signatures of cognitive processing speed and accuracy, two fundamental dimensions underlying cognitive abilities. They also identify links between these two factors and lifestyle, mental health and cognitive development. [ABSTRACT FROM AUTHOR]

Authors of the NCTE policy brief on translanguaging discuss possibilities for the field of English language arts by sharing examples from their expansive work on translanguaging in teacher education. [ABSTRACT FROM AUTHOR]

This article continues an overview of the "science of reading" story, focusing on media misrepresentations of balanced literacy and whole language, the National Reading Panel, teacher education and the LETRS program, grade retention, cognitive science, and dyslexia. [ABSTRACT FROM AUTHOR]

The current prevailing embodied cognitive science is essentially the result of the pragmatic turn of cognitive science, and enactivism is the epitome of this turn. For a long time, most advocates of enactivism have consciously regarded phenomenology as their important source of thought but ignored its pragmatic roots. In fact, there are many similarities between enactivism and pragmatism, and pragmatism has foreshadowed some core ideas and principles of enactivism. In particular, enactivism contains a pragmatic assumption that there is interaction between organisms and their environment, and cognitive ability is evolved and developed by organisms in the history of interactions with their environment. Their interpretations of cognition both rely on the theoretical support of biology and emphasize the basic role of organisms' active capacities and environment in the formation of cognition. They hold a neutral monism position ontologically. Undoubtedly, pragmatism is the precursor of cognitive enactivism. Pragmatism not only provides rich conceptual resources for the development of enactivism, but also provides a unique perspective and method to solve some problems in its theory. Pragmatism is a rich mine for enactivists to further explore. [ABSTRACT FROM AUTHOR]

"Cognitive Plausibility in Natural Language Processing" by Beinborn and Hollenstein explores the concept of cognitive plausibility in the field of Natural Language Processing (NLP). The book highlights the importance of evaluating NLP models based on characteristics such as fairness, interpretability, and efficiency, in addition to accuracy. It focuses on the cognitive plausibility of models, examining how "human-like" they are. The book provides examples, discusses theoretical and methodological issues, and explores ethical considerations. It is aimed at NLP researchers, cognitive scientists, psycholinguists, and students with basic knowledge of NLP. The book emphasizes the complexity of cognitive plausibility and suggests ways to design more cognitively plausible models. [Extracted from the article]

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There are increasingly frequent calls for school mathematics curricula to be informed by robust research evidence. One approach to achieving this is designing evidence‐informed learning and teaching resources for the classroom. In this paper, we reflect on our experiences of designing a free and fully resourced complete set of secondary mathematics curriculum materials. We explore in detail the challenges we have encountered in our attempts to apply principles from the cognitive theory of multimedia learning. We focus on tensions we have experienced when simultaneously applying multiple principles and balancing these with other educational considerations. Specifically, we consider trade‐offs between redundancy versus clarity, seductive details versus richness, personalisation and emotional design versus abstraction, spatial contiguity and signalling versus parsimony, and pre‐training and worked examples versus exploration. We examine the choices and dilemmas we faced, and illustrate our emerging attempts to resolve these tensions through presenting multiple examples from our design work. We conclude with recommendations about how tensions among these design principles might be navigated in curriculum design and we suggest possible avenues for further research in this area. [ABSTRACT FROM AUTHOR]

Copyright of Beytulhikme: An International Journal of Philosophy is the property of Beytulhikme: An International Journal of Philosophy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This document is an editorial introduction to a special issue commemorating the centenary of Evald Ilyenkov, a prominent Soviet philosopher. Ilyenkov was known for his contributions to Marxist philosophy and his work on dialectical logic, the theory of the ideal, and the philosophy of mind. The special issue includes essays from various scholars discussing Ilyenkov's influence and ideas, as well as his relationship with other philosophers such as Vygotsky and Spinoza. The issue aims to highlight the contemporary relevance of Ilyenkov's thought and its potential for interdisciplinary research in fields such as education, continental philosophy, and cognitive science. [Extracted from the article]

Neuroscience has largely conceptualized inner speech, sometimes called covert speech, as being a part of the language system, namely, a precursor to overt speech and/or speech without the motor component (impoverished motor speech). Yet interdisciplinary work has strongly suggested that inner speech is multidimensional and situated within the language system as well as in more domain general systems. By leveraging evidence from philosophy, linguistics, neuroscience and cognitive science, we argue that neuroscience can gain a more comprehensive understanding of inner speech processes. We will summarize the existing knowledge on the traditional approach to understanding the neuroscience of inner speech, which is squarely through the language system, before discussing interdisciplinary approaches to understanding the cognitive, linguistic and neural substrates/mechanisms that may be involved in inner speech. Given our own interests in inner speech after brain injury, we finish by discussing the theoretical and clinical benefits of researching inner speech in aphasia through an interdisciplinary lens. [ABSTRACT FROM AUTHOR]

This study used a cluster randomized controlled trial to investigate the effectiveness of two approaches to increasing middle school students' science learning when using an inquiry‐based science curriculum. Eighty‐nine schools, with 253 teachers and 20,591 students, were randomly assigned into one of three conditions: (a) a treatment condition in which the textbook curriculum was modified based on three principles of cognitive science coupled with teacher professional development (PD), (b) a second treatment condition in which teachers received PD designed to improve their knowledge of the science content, and (c) a business‐as‐usual control group. The cognitive science treatment had a small but statistically significant positive effect on content learning, with a stronger impact on students of higher prior achievement. Compared to business‐as‐usual, the intervention to increase teacher content knowledge had no impact. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Planning Education & Research is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

How does the act of explaining influence learning? Prior work has studied effects of explaining through a predominantly proximal lens, measuring short‐term outcomes or manipulations within lab settings. Here, we ask whether the benefits of explaining extend to academic performance over time. Specifically, does the quality and frequency of student explanations predict students' later performance on standardized tests of math and English? In Study 1 (N = 127 5th−6th graders), participants completed a causal learning activity during which their explanation quality was evaluated. Controlling for prior test scores, explanation quality directly predicted both math and English standardized test scores the following year. In Study 2 (N = 20,384 10th graders), participants reported aspects of teachers' explanations and their own. Controlling for prior test scores, students' own explanations predicted both math and English state standardized test scores, and teacher explanations were linked to test performance through students' own explanations. Taken together, these findings suggest that benefits of explaining may result in part from the development of a metacognitive explanatory skill that transfers across domains and over time. Implications for cognitive science, pedagogy, and education are discussed. [ABSTRACT FROM AUTHOR]

Code summarization is the task of creating short, natural language descriptions of source code. It is an important part of code comprehension and a powerful method of documentation. Previous work has made progress in identifying where programmers focus in code as they write their own summaries (i.e., Writing). However, there is currently a gap in studying programmers' attention as they read code with pre-written summaries (i.e., Reading). As a result, it is currently unknown how these two forms of code comprehension compare: Reading and Writing. Also, there is a limited understanding of programmer attention with respect to program semantics. We address these shortcomings with a human eye-tracking study (n = 27) comparing Reading and Writing. We examined programmers' attention with respect to fine-grained program semantics, including their attention sequences (i.e., scan paths). We find distinctions in programmer attention across the comprehension tasks, similarities in reading patterns between them, and differences mediated by demographic factors. This can help guide code comprehension in both computer science education and automated code summarization. Furthermore, we mapped programmers' gaze data onto the Abstract Syntax Tree to explore another representation of human attention. We find that visual behavior on this structure is not always consistent with that on source code. [ABSTRACT FROM AUTHOR]

This article explores the evolving nature of Computer-Supported Collaborative Learning (CSCL) and the need for a unified language in the field. It discusses four changes that have occurred in CSCL research, including the adoption of collaborative pedagogies, a shift towards focusing on group organization rather than software characteristics, recognition of large learning collectives, and changes in the scale of collaboration. The article also suggests the possibility of a broader field called Collaboration Sciences, which combines CSCL and Learning Sciences perspectives. It concludes by discussing the benefits of formalizing theories in CSCL using the Bayesian framework and highlights the practical value of Bayesian Networks in designing group and learning support systems. [Extracted from the article]

The cognitive science of religion (CSR) seeks to find causal explanations for the origin, dissemination and transmission of theistic beliefs. One of the beliefs related to the field of religion is counterintuitive concepts: ideas and concepts that violate the automatic and non-reflective expectations of our mental tools. According to the researchers of CSR, counterintuitive concepts, if they are used in their minimal sense and do not weaken the conceptual coherence, cause the permanence and transmission of religious beliefs in comparison with other beliefs. Therefore, counter intuitiveness plays an important role in understanding religion. Despite the positive points of counterintuitive concepts, we believe that these concepts have ambiguities and problems that, if not properly explained and corrected, will cause problems in the acceptance and fixation of theistic beliefs: First, metare presentation's inability to solve the problem of distinguishing between counterintuitive religious beliefs and other counterintuitive concepts. Second, ambiguity in the explanatory role of counterintuitive concepts. Third, emphasis on cognitive architecture and not paying attention to the role of upbringing and culture in identifying counterintuitive concepts. Fourth, the inconsistency in the analysis of some counterintuitive concepts such as God with the official doctrine of religions. Fifth, not paying attention to conscious intuitions. Sixth, it seems that with the naturalization of beliefs in the cognitive system, human agents will take the place of supernatural agents, but the statistics show something else. [ABSTRACT FROM AUTHOR]

Comparative cognitive science often involves asking questions like 'Do nonhumans have C?' where C is a capacity we take humans to have. These questions frequently generate unproductive disagreements, in which one party affirms and the other denies that nonhumans have the relevant capacity on the basis of the same evidence. I argue that these questions can be productively understood as questions about natural kinds: do nonhuman capacities fall into the same natural kinds as our own? Understanding such questions in this way has several advantages: it preserves the intuition that these are substantive empirical questions worth asking; it helps us to understand why they so frequently give rise to disagreements of the kind described; and it provides clues about how to diagnose and resolve them. [ABSTRACT FROM AUTHOR]

Modes of presentation (MOPs) are often said to have to be transparent, usually in the sense that thinkers can know solely via introspection whether or not they are deploying the same one. While there has been much discussion of threats to transparency stemming from externalism, another threat to transparency has garnered less attention. This novel threat arises if MOPs are robust, as I argue they should be according to internalist views of MOPs which identify them with representational vehicles, such as mental files. I explain how identifying MOPs with vehicles/files threatens transparency, provide empirical illustrations, and critically examine some attempts to dispel the threat. Rather than abandoning transparency, I outline a way of reconciling it with a robust view of mental files which takes seriously the idea that they are targets for investigation in cognitive science. Transparency does not require introspective access, and rather than as an incontrovertible principle for individuating MOPs, we can view it more modestly, as an open empirical hypothesis. [ABSTRACT FROM AUTHOR]

How good a research scientist is ChatGPT? We systematically probed the capabilities of GPT-3.5 and GPT-4 across four central components of the scientific process: as a Research Librarian, Research Ethicist, Data Generator, and Novel Data Predictor, using psychological science as a testing field. In Study 1 (Research Librarian), unlike human researchers, GPT-3.5 and GPT-4 hallucinated, authoritatively generating fictional references 36.0% and 5.4% of the time, respectively, although GPT-4 exhibited an evolving capacity to acknowledge its fictions. In Study 2 (Research Ethicist), GPT-4 (though not GPT-3.5) proved capable of detecting violations like p-hacking in fictional research protocols, correcting 88.6% of blatantly presented issues, and 72.6% of subtly presented issues. In Study 3 (Data Generator), both models consistently replicated patterns of cultural bias previously discovered in large language corpora, indicating that ChatGPT can simulate known results, an antecedent to usefulness for both data generation and skills like hypothesis generation. Contrastingly, in Study 4 (Novel Data Predictor), neither model was successful at predicting new results absent in their training data, and neither appeared to leverage substantially new information when predicting more vs. less novel outcomes. Together, these results suggest that GPT is a flawed but rapidly improving librarian, a decent research ethicist already, capable of data generation in simple domains with known characteristics but poor at predicting novel patterns of empirical data to aid future experimentation. [ABSTRACT FROM AUTHOR]