Search

Several deep learning models are presented: Ref. [[4]] designs a network intrusion detection model, DLNID, that combines an attention mechanism, a bidirectional long short-term memory (LSTM), and an adaptive synthetic sampling, and demonstrates improved performance for severely imbalanced data. In addition, there are a couple of papers on HPO: Ref. [[11]] introduces a greedy I k i -fold cross validation method that vastly reduces the average time required to find the best-performing model with or without a computational budget, and experimentally verifies its improved performance over existing methods. Since its inception as a branch of Artificial Intelligence, Machine Learning (ML) has flourished in recent years. [Extracted from the article]

Cognitive science-informed approaches have gained considerable influence in education in the UK and internationally, but not much is known about how teachers perceive cognitive science-informed strategies or enact them within the contexts of their everyday classrooms. In this paper, we discuss the perceptions and experiences of cognitive science-informed strategies of 13 teachers in England. The paper critically explores how the teachers understood and used cognitive science-informed strategies in their teaching, their views of the benefits and challenges for different subjects and groups of learners, and their reflections on supporting factors and barriers for adopting the strategies in their schools. The teachers' accounts illustrate some of the many complexities of adopting cognitive science-informed approaches in real-life educational settings. Drawing on their narratives, the paper emphasises the importance of acknowledging different contextual dimensions and the dynamic interactions between them to understand when and how teachers enact cognitive science-informed approaches in their classrooms. [ABSTRACT FROM AUTHOR]

[This paper is part of the Focused Collection on Curriculum Development: Theory into Design.] Research in physics education has contributed substantively to improvements in the learning and teaching of university physics by informing the development of research-based instructional materials for physics courses. Reports on the design of these materials have tended to focus on overall improvements in student performance, while the role of theory in informing the development, refinement, and assessment of the materials is often not clearly articulated. In this article, we illustrate how dual-process theories of reasoning and decision making have guided the ongoing development, testing, and analysis of an instructional intervention, implemented at three different institutions, designed to build consistency in student reasoning about the application of Newton's 2nd law to objects at rest. By employing constructs from cognitive science associated with dual-process theories of reasoning (such as mindware and cognitive reflection), we were able not only to examine the overall improvement in student performance but also to investigate the impact of the intervention on two aspects of productive reasoning--mindware and cognitive reflection. Our analysis showed that the intervention strengthened students' mindware such that students were able to apply it as a criterion while checking the validity of their intuitive responses. Moreover, logistic regression revealed that the success of our intervention was mediated by the students' cognitive reflection skills. Indeed, for students with comparable mindware, those who demonstrated a weaker tendency toward cognitive reflection were less likely to initiate conflict detection and therefore never had the opportunity to utilize their mindware. We believe that this kind of integrated, theory-driven approach to intervention design and testing represents an important first step in efforts to both account for and leverage domain-general reasoning phenomena in the learning and teaching of physics.

The challenge of detecting research topics in a specific research field has attracted attention from researchers in the bibliometrics community. In this study, to solve two problems of clustering papers, i.e., the influence of different distributions of citation links and involved textual features on similarity computation, the authors propose a hybrid self-optimized clustering model to detect research topics by extending the hybrid clustering model to identify “core documents”. First, the Amsler network, consisting of bibliographic coupling and co-citation links, is created to calculate the citation-based similarity based on the cosine angle of papers. Second, the cosine similarity is also used to compute the text-based similarity, which consists of the textual statistical and topological features. Then, the cosine angle of the linear combination of citation- and text-based similarity is considered as the hybrid similarity. Finally, the Louvain method is applied to cluster papers, and the terms based on term frequency are used to label clusters. To test the performance of the proposed model, a dataset related to the data envelopment analysis field is used for comparison and analysis of clustering results. Based on the benchmark built, different clustering methods with different citation links or textual features are compared according to evaluation measures. The results show that the proposed model can obtain reasonable and effective clustering results, and the research topics of data envelopment analysis field are also analyzed based on the proposed model. As different features are considered in the proposed model compared with previous hybrid clustering models, the proposed clustering model can provide inspiration for further studies on topic identification by other researchers. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue including the rationality of human cognition and the papers presented at the Cognitive Science Society Annual conference and the International Conference on Cognitive Modeling.

"Large-Scale Multimedia Retrieval" (LSMR) is the task to fast analyze a large amount of multimedia data like images or videos and accurately find the ones relevant to a certain semantic meaning. Although LSMR has been investigated for more than two decades in the fields of multimedia processing and computer vision, a more interdisciplinary approach is necessary to develop an LSMR system that is really meaningful for humans. To this end, this paper aims to stimulate attention to the LSMR problem from diverse research fields. By explaining basic terminologies in LSMR, we first survey several representative methods in chronological order. This reveals that due to prioritizing the generality and scalability for large-scale data, recent methods interpret semantic meanings with a completely different mechanism from humans, though such humanlike mechanisms were used in classical heuristic-based methods. Based on this, we discuss "human-machine cooperation," which incorporates knowledge about human interpretation into LSMR without sacrificing the generality and scalability. In particular, we present three approaches to human-machine cooperation ("cognitive," "ontological," and "adaptive"), which are attributed to cognitive science, ontology engineering, and metacognition, respectively. We hope that this paper will create a bridge to enable researchers in different fields to communicate about the LSMR problem and lead to a ground-breaking next generation of LSMR systems.

This special issue of "International Journal of Science Education" is based on the theme "Conceptual Metaphor and Embodied Cognition in Science Learning." The idea for this issue grew out of a symposium organized on this topic at the conference of the European Science Education Research Association (ESERA) in September 2013. The eight papers collected in this issue reflect the emergence of a critical mass of studies in science education applying ideas from the perspective of "embodied cognition" in cognitive science. It is hoped that by bringing together these papers and commentaries on conceptual metaphor and embodied cognition in science learning, others will be encouraged to further exploration, discussion, and debate regarding these issues.

Although a number of papers have already discussed the relevance of brain research for education, the fundamental concepts and discoveries connecting education and the brain have not been systematically reviewed yet. In this paper, four of these concepts are presented and evidence concerning each one is reviewed. First, the concept of neuroplasticity is proposed as a "sine qua non" for linking education and the brain. Then, the concepts of neuronal recycling and inhibition are presented as two fundamental mechanisms of school learning that emphasize the importance of knowing the initial brain structure of learners and, finally, the concept of attention is discussed as a central concept for linking teaching and the brain.

Background: Impairments in social cognition have been described in several psychiatric and neurological disorders. Given the importance of the relationship between social cognition and functioning and quality of life in these disorders, there is a growing interest in social cognition remediation interventions. The aim of this study was to carry out a systematic mapping review to describe the state of the art in social cognition training and remediation interventions. Methods: Publications from 2006 to 2016 on social cognition interventions were reviewed in four databases: Scopus, PsycINFO, PubMed and Embase. From the initial result set of 3229 publications, a final total of 241 publications were selected. Results: The study revealed an increasing interest in social cognition remediation interventions, especially in the fields of psychiatry and psychology, with a gradual growth in the number of publications. These were frequently published in high impact factor journals and underpinned by robust scientific evidence. Most studies were conducted on schizophrenia, followed by autism spectrum disorders. Theory of mind and emotional processing were the focus of most interventions, whilst a limited number of studies addressed attributional bias and social perception. Targeted interventions in social cognition were the most frequent practice in the selected papers, followed by non-specific treatment interventions and broad-based interventions. Conclusions: Research in social cognition remediation interventions is growing. Further studies are needed on attributional bias and social perception remediation programs, while the comparative efficacy of different interventions also remains unclear. [ABSTRACT FROM AUTHOR]

The role of artificial intelligence (AI) in the education sector has received considerable attention from scholars; however, its potency and application among tourism learners are yet to be discerned. Accordingly, this research note articulates the potential impact and limitations of the AI chatbot, ChatGPT, in tourism education practices. In particular, the paper aims to raise awareness among tourism educators regarding the disruptive potential of ChatGPT and its impact on academic integrity and ethics. This paper contributes to tourism education practices on AI and robotics by critically discussing ChatGPT from a cognitive science perspective and providing recommendations on how to minimise AI plagiarism in tourism education. This research argues for adapting novel pedagogies as technology evolves and raises the need for AI ethical use guidelines in tourism education. [ABSTRACT FROM AUTHOR]

This paper reports the results of a study of adult ethical development in Christian congregations. Using an empirical hermeneutic phenomenological methodology, this study examined how five pastors understand and encourage ethical development, creating an in-depth analysis and interpretation of their perceptions of the phenomenon of adult ethical development. Two primary themes emerged, with several significant sub-themes contributing to those primary themes: 1) the integrity of ethical and spiritual development; and 2) the relational nature of ethical development. Drawing on a theoretical background of neo-pragmatic appropriations of both value theory and cognitive science, the relational nature of adult ethical development that emerges from this study makes contributions to the field of adult education in its understanding of the richness of the concrete spiritual context, the importance of informal learning environments, and the breadth of intersubjective experience that serves to incubate adult ethical development.

This paper is concerned with fair and valid testing. It reports on a long-term project aimed at creating visual accessibility resources in mathematics computer-administered test items in a large-scale assessment system. We discuss our experience designing and developing pop-up illustration glossaries (IGs) for second language learners (SLLs) -- students who are not native users of the predominant language in the society in which they live, are typically schooled in that predominant language, and face the challenge of learning content and demonstrating knowledge in a language that is not their first language. An IG is a visual representation of a word/term identified as likely to be linguistically challenging to a substantial proportion of SLL test takers and which appears on the screen when the test taker clicks on that word/term. Because they interact with the user, IGs are more sensitive than other accessibility resources to students' individual needs -- a characteristic that addresses the linguistic heterogeneity of SLL populations. We discuss the extent to which IGs contribute to ensuring valid, fair assessment for SLL students, and the implications of the lessons learned for improving assessment systems.

Research at the intersection of cognitive science and education has major benefits for both researchers and education practitioners. Yet, a number of logistical and communication challenges must be carefully negotiated to maximize the benefits of these collaborations. In this article, we trace the investments and major publications that have sought to bridge cognitive science and education over the past 40 years to provide context for the papers in a special issue of the "Journal of Cognition and Development" "Found in Translation: Cognitive Development Meets Education. We use the Institute of Education Sciences' investments in research at the intersection of cognitive science and education as a case study for what the field has primarily focused on over the past two decades and, finally, we offer a broad overview of the themes that this special issue touches on and a commentary on how we believe the field can improve.

Purpose: The concept of a mental model has been described by theorists from diverse disciplines. The purpose of this paper is to offer a robust definition of an individual mental model for use in organisational management. Design/methodology/approach: The approach adopted involves an interdisciplinary literature review of disciplines, including system dynamics, psychology, cognitive science and organisational learning. Findings: Critical reflection on the published individual mental model definitions revealed similarities and shortcomings. It is argued that here the literature presents some consensus in the concept being internally held and having the capacity to affect how a person acts. The proposed definition of an individual mental model was found to be robust through a complexity based inquiry conducted in an organisation within the hospitality industry. Research limitations/implications: The application of the model has only been tested in one case study with a small staff sample in the hospitality industry. Thus generalisation is limited pending further testing. Practical implications: The pilot study demonstrated the usefulness of the definition of an individual mental model in making the conceptualisations of work practices explicit at various levels within organisations. Originality/value: This paper produces a definition that is lucid, inclusive, and specific for mental model research and knowledge management in organisations. The paper provides added value for academics and organisational practitioners interested in a robust definition for understanding the concept and the implications of mental models on an individual's actions.

Cognitive metaphor research is characterized by the diversity of rival theories. Starting from this observation, the paper focuses on the problem of how the unity and diversity of cognitive theories of metaphor can be accounted for. The first part of the paper outlines a suitable metascientific approach which emerges as a modification of B. von Eckardt's notion of "research framework." In the second part, by the help of this approach, some aspects of the sophisticated relationship between Lakoff and Johnson's, Glucksberg's, and Gentner's theories are discussed. The main finding is that the data, the problems, the heuristics and the hypotheses which have been partly shaped by the rivals contribute to the development of the particular theories to a considerable extent. (Contains 1 figure and 4 tables.)

Historically, cognitive researchers have largely ignored the domain of sport in their quest to understand how the mind works. This neglect is due, in part, to the limitations of the information processing paradigm that dominated cognitive psychology in its formative years. With the emergence of the embodiment approach to cognition, however, sport has become a dynamic natural laboratory in which to investigate the relationship between thinking and skilled action. Therefore, the purpose of this paper is to explore some insights into the relationship between thinking and action that have emerged from recent research on exceptional performance states (e.g., "flow" and "choking" in athletes. The paper begins by explaining why cognitive psychologists' traditional indifference to sport has been replaced by a more enthusiastic attitude in recent years. The next section provides some insights into the relationship between thinking and skilled action that have emerged from research on "flow" (or peak performance) and "choking" (or impaired performance) experiences in athletes. The third section of the paper explores some practical issues that arise when athletes seek to exert conscious control over their thoughts in competitive situations. The final part of the paper considers the implications of research on thinking in action in sport for practical attempts to improve thinking skills in domains such as business organizations and schools.

Over the past 10 to 15 years the twin fields of neuroscience and cognitive psychology have exploded. Through a number of new imaging technologies, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) scans, scientists have been able to look into the living brain in ways never before possible. What they have discovered, some of which is discussed in this paper, may help to inspire new approaches to the practice and teaching of drawing. The process of thinking through drawing shares characteristics common to many domains in the arts and sciences. Improvisation, analogy and metaphor, exploration and invention all have their place in a variety of creative pursuits. Yet the simplicity of marks on paper as a direct externalization of thought makes drawing a particularly good case study of the human imagination at work. The act of drawing can be understood as the creation of a physical space to play with one's thoughts outside the confines of one's minds, to see and manipulate one's ideas and perceptions in visible form. Drawing is exactly the kind of external cognitive support that can enhance metacognition. It is a powerful tool for nonverbal inquiry, for thinking through problems and analyzing experiences. Beginning to draw, one immediately discovers that he or she understands far less about what he or she sees than he or she had assumed and that there is much more there than he or she had imagined. Drawing enables the drawer to see and comprehend that which is beyond words. Training the brain to draw, to engage with eye and hand, is to learn to be open to surprise, to perceive underlying structures and make unexpected connections and discoveries. In moving beyond automatic, superficial, and stereotyped responses and developing metacognitive skills like constructive perception, it is possible for those who draw to become deeper and more creative thinkers who are better equipped to solve problems across disciplines. (Contains 49 notes.)

Cognitive science is an interdisciplinary field of researchers from psychology, neuroscience, linguistics, philosophy, computer science, and anthropology who seek to understand the mind. This paper considers findings from this field that are strong and clear enough to merit classroom application. Although many teachers and parents worry that high school students don't sleep enough, research shows that the impact of sleep deprivation on learning is not as dramatic as typically thought. Even so, research does show that teenagers can learn to get more shuteye, and that doing so can improve their mood and behavior. (Contains 51 endnotes.)

A large body of research in the conceptual change tradition has shown the difficulty of learning fundamental science concepts, yet conceptual change schemes have failed to convincingly demonstrate improvements in supporting significant student learning. Recent work in cognitive science has challenged this purely conceptual view of learning, emphasising the role of language, and the importance of personal and contextual aspects of understanding science. The research described in this paper is designed around the notion that learning involves the recognition and development of students' representational resources. In particular, we argue that conceptual difficulties with the concept of force are fundamentally representational in nature. This paper describes a classroom sequence in force that focuses on representations and their negotiation, and reports on the effectiveness of this perspective in guiding teaching, and in providing insight into student learning. Classroom sequences involving three teachers were videotaped using a combined focus on the teacher and groups of students. Video analysis software was used to capture the variety of representations used, and sequences of representational negotiation. Stimulated recall interviews were conducted with teachers and students. The paper reports on the nature of the pedagogies developed as part of this representational focus, its effectiveness in supporting student learning, and on the pedagogical and epistemological challenges negotiated by teachers in implementing this approach.

Purpose: The purpose of this paper is to argue that emotion has a central role to play in rational decision making based on recent research in the neuroanatomy of emotion. As a result, traditional rational decision-making theories, including Herbert Simon's modified model of satisficing that sharply demarcates emotions and values from rationality and rational decision making, need substantial revision. The paper concludes by outlining some central features of a theory of emotional decisions that is biologically more realistic than the traditional rationalist-cognitive model. Design/methodology/approach: The paper employs contemporary scientific as well as traditional philosophical criteria in its argumentation. Methodologically, it can be described as an example of applying naturalistic philosophy to a central issue of human thought and experience, and how humans are able to value things at all on the basis of their neuroanatomy. Findings: The paper presents some initial features of a new theory of emotional decisions that is biologically more realistic than the traditional rationalist-cognitive model. Originality/value: The significance and originality of this paper lies in the fact that it proposes causal investigations of the real bases for rational decision making as a central human feature which runs counter to conventional wisdom and has far reaching implications for education, to name just one discipline; it demonstrates the importance and necessity of interdisciplinary research; and it outlines an exciting new research agenda that promises to be more productive in terms of understanding and hence planning for, the way in which humans make decisions.

The authors attempt to refute criticism by scholar Jordan Paper of their scholarly methodology concerning an article they wore on ancient Chinese texts. The authors argue that Paper read too much into the text of the original article, particularly concerning Paper's assertion that the authors assumed a Hebrew Bible deity at the center of early Chinese religion. The authors argue that they do not cite scholars such as David Keightly and Robert Eno in their original article, and that they do not employ circular logic in reading their own concepts of Christian divinity into ancient texts. The authors state that they are not alone in utilizing the concept of the cognitive science of religion (CSR) in their research.

Among those living systems, which are cognizers? Among the behaviours of, and causes of behaviour in, living systems, which are cognitive? Such questions sit at the heart of a sophisticated, ongoing debate, of which the recent papers by Corcoran et al. (2020) and Sims and Kiverstein (2021) serve as excellent examples. I argue that despite their virtues, both papers suffer from flawed conceptions of the point of the debate. This leaves their proposals ill-motivated—good answers to the wrong question. Additionally, their proposals are unfit to serve the legitimate roles for characterizations of cognition. [ABSTRACT FROM AUTHOR]

It is often argued that neuroscience can be expected to provide insights of significance for education. Advocates of this view are sometimes committed to "brainism", the view (a) that an individual's mental life is constituted by states, events and processes in her brain, and (b) that psychological attributes may legitimately be ascribed to the brain. This paper considers the case for rejecting brainism in favour of "personalism", the view that psychological attributes are appropriately ascribed only to persons and that mental phenomena do not occur "inside" the person but are aspects of her mode of engagement with the world. The paper explores arguments for personalism from Russian philosopher Evald Ilyenkov and a number of contemporary Western thinkers, including Peter Hacker and John McDowell. It is argued that, since plausible forms of personalism do not deny that brain functioning is a causal precondition of our mental lives, personalism is consistent with the claim that neuroscience is relevant to education, and not just to the explanation of learning disorders. Nevertheless, it is important that fascination with scientific innovation and technological possibility should not distort our conception of what education is or ought to be, leading us to portray education not as a communicative endeavour, but as an exercise in engineering.

Little of 150 years of research in Cognitive Neurosciences, Human Factors, and the mathematics of Production Management have found their way into educational policy and certainly not into the classroom or in the production of educational materials in any meaningful or practical fashion. Whilst more mundane concepts of timing, sequencing, spatial organisation, and Gestalt principles of perception are well known and applied, the nature of Receiver Operating Characteristics (ROC) and the responsibility of the sender in that regard, as well as the maintenance of simplistic notions of developmental brain organization and hemisphericity for language rather than the neurophysiology of embodied language as an example, still inform pre-K-3 curriculum. The paper intends to overview the science of human physiologic efficiencies in engineering terms in an attempt to develop novel approaches and thinking to classroom-based practice and subsequently leadership and policy informed by current neuroscientific realities and by production management and optimization principles now applied to schools, and their consumers. (Contains 7 figures.)

As we rapidly approach the 50th year of the much-celebrated "cognitive revolution", it is worth reflecting on its widespread impact on individual disciplines and areas of multidisciplinary endeavour. Of specific concern in this paper is the example of the influence of cognitivism's equation of mind and computer in education. Within education, this paper focuses on a particular area of concern to which both mind and computer are simultaneously central: educational technology. It examines the profound and lasting effect of cognitive science on our understandings of the educational potential of information and communication technologies, and further argues that recent and multiple "signs of discontent", "crises" and even "failures" in cognitive science and psychology should result in changes in these understandings. It concludes by suggesting new directions that educational technology research might take in the light of this crisis of cognitivism.

There is no more central issue to education than thinking and reasoning. Certainly, such an emphasis chimes with the rationalist and cognitive deep structure of the Western educational tradition. The contemporary tendency reinforced by cognitive science is to treat thinking ahistorically and aculturally as though physiology, brain structure and human evolution are all there is to say about thinking that is worthwhile or educationally significant. The movement of critical thinking also tends to treat thinking ahistorically, focusing on universal processes of logic and reasoning. Against this trend and against the scientific spirit of the age this paper presents a historical and philosophical picture of thinking. By contrast with dominant cognitive and logical models the paper emphasizes kinds of thinking and styles of reasoning. The paper grows out of interests primarily in the work of Nietzsche, Heidegger and Wittgenstein, and in the extension and development of their work in Critical Theory and French poststructuralist philosophy. The paper draws directly on some of this work to argue for the recognition of different kinds of thinking, which are explored by reference to Heidegger, and also the significance of styles of reasoning, which are explored by reference to Wittgenstein and to Ian Hacking.

This paper examines the characteristics of the thinking skill we call "melioration" i.e., the competence to borrow a concept from a field of knowledge supposedly far removed from his or her domain, and adapt it to a pressing challenge in an area of personal knowledge or interest. The skill has its source in conscious personal meaning-making, not in the process of deduction. In the unplanned operation of connection and association, one creates a new concept generating a new insight into a phenomenon, which hitherto had not been described in such a way. This paper relates melioration to existing theories of intelligence, taking the position that human cognitive/intellectual functioning is in part the ability to learn or think in the framework of familiar systemic concepts, and in part the ability to learn or think with new systemic concepts that are then available for future application.

Knauff and Gazzo Castañeda (2022) object to using the term "new paradigm" to describe recent developments in the psychology of reasoning. This paper concedes that the Kuhnian term "paradigm" may be queried. What cannot is that the work subsumed under this heading is part of a new, progressive movement that spans the brain and cognitive sciences: Bayesian cognitive science. Sampling algorithms and Bayes nets used to explain biases in JDM can implement the Bayesian new paradigm approach belying any advantages of mental models theory (MMT) at the algorithmic level. Moreover, this paper argues that new versions of MMT lack a computational level theory and questions the grounds for MMTs much-vaunted generality. The paper then examines common ground on the importance of small-scale models/simulations of the world and the importance of argumentation in the social domain rather than individual reasoning. Finally, the paper concludes that although there may be prospects for moving reasoning research forward in a more collective, collaborative manner, many disagreements remain to be resolved. [ABSTRACT FROM AUTHOR]

Copyright of Studies about Language / Kalbu Studijos is the property of Studies about Language / Kalbu Studijos 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 paper explores the potential of neuroscience for improving educational practice by describing the perspective of educational psychology as a linking science; providing historical context showing educational psychology's 100-year search for an educationally relevant neuroscience; offering a conceptual framework for the connections among neuroscience, cognitive science, educational psychology, and educational practice; and laying out a research agenda for the emerging field of educational neuroscience.

The paper deals with the aspects of professional training of specialists in computational linguistics by the example of the University of Stuttgart. First of all, we have attempted to define the essence of the terms "applied linguistics" and "computational linguistics" based on the views of Ukrainian and foreign scholars. We have found out that there is an obvious inconsistency in using these terms as Ukrainian scholars view it as a science related to practical application of linguistic achievements with the use of the latest technologies, whereas abroad they believe that computational linguistics is aimed at developing strategies for researches on natural languages. However, applied linguistics is related to language teaching methodology. We have concluded that German scholars view computational linguistics as a cognitive science that attempts to most successfully apply the achievements of linguistics in practice. Based on the view, German universities develop curricula that encompass theoretical and practical aspects of computational linguistics to prepare modern specialists able to comprehend the complexity of the field and be willing to adapt to challenges of a globalized world. Consequently, we have described the peculiarities of the programmes of a Bachelor of Science in Machine Language Programming and a Master of Science in Computational Linguistics. We have defined that duration of the programmes is traditional--three and two years respectively. Their structure comprises obligatory and elective courses, including Computer Science, Mathematics and Linguistics. In addition, future specialists may develop key professional competences attending seminars and colloquiums, participating in research projects, etc. It has been indicated that the list of electives involves those subjects aimed at enhancing future specialists' skills in linguistics as well as computer science, yet they are entitled to suggest what they are interested in even if such courses are not included. We have also suggested that rather perspective are further studies on the essence of the terms "applied linguistics" and "computational linguistics" based on the research findings of scholars all over the world.

This paper examines the intersection between creativity, problem solving, cognitive psychology and neuroscience in a discussion surrounding the genesis of new ideas and innovative science. Three creative activities are considered. These are (a) the interaction between visual-spatial and analytical or verbal reasoning, (b) attending to feeling in listening to the "self", and (c) the interaction between conscious and non-conscious reasoning. Evidence for the importance of each of these activities to the creative process is drawn from (a) historical and introspective accounts of novel problem solving by noted scientists and mathematicians; (b) cognitive psychology and neuroscience; and (c) a recent empirical study of novel mathematics problem solving. An explanation of these activities is given in terms of cognitive neuroscience. A conceptual framework connecting each of these activities is presented and the implications for learning and teaching considered. (Contains 3 figures.)

To what extent does playing a musical instrument contribute to an individual’s construction of knowledge? This paper aims to address this question by examining music performance from an embodied perspective and offering a narrative-style review of the main literature on the topic. Drawing from both older theoretical frameworks on motor learning and more recent theories on sensorimotor coupling and integration, this paper seeks to challenge and juxtapose established ideas with contemporary views inspired by recent work on embodied cognitive science. By doing so we advocate a centripetal approach to music performance, contrasting the prevalent centrifugal perspective: the sounds produced during performance not only originate from bodily action (centrifugal), but also cyclically return to it (centripetal). This perspective suggests that playing music involves a dynamic integration of both external and internal factors, transcending mere output-oriented actions and revealing music performance as a form of knowledge acquisition based on real-time sensorimotor experience. [ABSTRACT FROM AUTHOR]

In this paper, I argue that the fields of artificial intelligence (AI) and education have been deeply intertwined since the early days of AI. Specifically, I show that many of the early pioneers of AI were cognitive scientists who also made pioneering and impactful contributions to the field of education. These researchers saw AI as a tool for thinking about human learning and used their understanding of how people learn to further AI. Furthermore, I trace two distinct approaches to thinking about cognition and learning that pervade the early histories of AI and education. Despite their differences, researchers from both strands were united in their quest to simultaneously understand and improve human and machine cognition. Today, this perspective is neither prevalent in AI nor the learning sciences. I conclude with some thoughts on how the artificial intelligence in education and learning sciences communities might reinvigorate this lost perspective. [ABSTRACT FROM AUTHOR]

The past 20 years have seen research on language acquisition in the cognitive sciences grow immensely. The current paper offers a fairly extensive review of this literature, arguing that new cognitive theories and empirical data are perfectly consistent with core predictions a behavior analytic approach makes about language development. The review focuses on important examples of productive linguistic behavior: word learning and early grammatical behavior. Language experience, through social and other contingencies, influences language development directly. Through these contingencies, the structure of language behavior exhibits a gradual emergence.

This study uses several bibliometric indices to explore the temporal course of publication trends regarding the bilingual advantage in executive control over a ten-year window. These indices include the number of published papers, numbers of citations, and the journal impact factor. According to the information available in their abstracts, studies were classified into one of four categories: supporting, ambiguous towards, not mentioning, or challenging the bilingual advantage. Results show that the number of papers challenging the bilingual advantage increased notably in 2014 and 2015. Both the average impact factor and the accumulated citations as of June 2016 were equivalent between categories. However, of the studies published in 2014, those that challenge the bilingual advantage accumulated more citations in June 2016 than those supporting it. Our findings offer evidence-based bibliometric information about the current state of the literature and suggest a change in publication trends regarding the literature on the bilingual advantage. [ABSTRACT FROM AUTHOR]

The growing integration of renewable energy sources into grid-connected microgrids has created new challenges in power generation forecasting and energy management. This paper explores the use of advanced machine learning algorithms, specifically Support Vector Regression (SVR), to enhance the efficiency and reliability of these systems. The proposed SVR algorithm leverages comprehensive historical energy production data, detailed weather patterns, and dynamic grid conditions to accurately forecast power generation. Our model demonstrated significantly lower error metrics compared to traditional linear regression models, achieving a Mean Squared Error of 2.002 for solar PV and 3.059 for wind power forecasting. The Mean Absolute Error was reduced to 0.547 for solar PV and 0.825 for wind scenarios, and the Root Mean Squared Error (RMSE) was 1.415 for solar PV and 1.749 for wind power, showcasing the model's superior accuracy. Enhanced predictive accuracy directly contributes to optimized resource allocation, enabling more precise control of energy generation schedules and reducing the reliance on external power sources. The application of our SVR model resulted in an 8.4% reduction in overall operating costs, highlighting its effectiveness in improving energy management efficiency. Furthermore, the system's ability to predict fluctuations in energy output allowed for adaptive real-time energy management, reducing grid stress and enhancing system stability. This approach led to a 10% improvement in the balance between supply and demand, a 15% reduction in peak load demand, and a 12% increase in the utilization of renewable energy sources. Our approach enhances grid stability by better balancing supply and demand, mitigating the variability and intermittency of renewable energy sources. These advancements promote a more sustainable integration of renewable energy into the microgrid, contributing to a cleaner, more resilient, and efficient energy infrastructure. The findings of this research provide valuable insights into the development of intelligent energy systems capable of adapting to changing conditions, paving the way for future innovations in energy management. Additionally, this work underscores the potential of machine learning to revolutionize energy management practices by providing more accurate, reliable, and cost-effective solutions for integrating renewable energy into existing grid infrastructures. [ABSTRACT FROM AUTHOR]

Artificial neural network models are able to achieve great performance at numerous computationally challenging tasks like face recognition. It is of significant importance to explore the difference between neural network models and human brains in terms of computational mechanism. This issue has become an experimental focus for some researchers in recent studies, and it is believed that using human behavior to understand neural network models can address this issue. This paper compares the neural network model performance with human performance on a classic yet important task: judging the ethnicity of a given face. This study uses Caucasian and East Asian faces to train 4 neural networks including AlexNet, VGG11, VGG13, and VGG16. Then, the ethnicity judgments of the neural networks are compared with human data using classical psychophysical methods by fitting psychometric curves. The results suggest that VGG11, followed by VGG16, shows a similar response pattern as humans, while simpler AlexNet and more complex VGG13 do not resemble human performance. Thus, this paper explores a new paradigm to compare neural networks and human brains. • Neural networks are able to provide cognitive approaches from face perception. • Human perception is used as a benchmark to evaluate the performance of neural networks. • Neural networks utilizing eye regions are confirmed to be better to perceive faces. • Attentional region analysis would unveil the processing details of a neural network. [ABSTRACT FROM AUTHOR]

This paper proposes epistemic environmentalism as a novel framework for accounting for the contribution of the environment – broadly construed – to epistemic standings and which can be used to improve or protect epistemic environments. The contribution of the environment to epistemic standings is explained through recent developments in epistemology and cognitive science, including embodied cognition, embedded cognition, extended cognition and distributed cognition. The paper examines how these developments support epistemic environmentalism, as well as contributes theoretical resources to make epistemic assessments of dynamic environments. The epistemic environmentalist procedure from the assessment of an individual environment to changes made to that environment based on promoting the attainment of epistemic goods is also discussed. [ABSTRACT FROM AUTHOR]

This study utilizes mathematical formalism and Figure-Ground argument mapping to categorize stative locative events in Vietnamese as surjective or bijective. Bijective events exhibit a one-to-one mapping of Figures and Grounds, while surjectives allow a single Figure to map onto multiple Grounds. Through analysis of Vietnamese sentences, the paper demonstrates how bijective and surjective locatives encode deterministic and ambiguous spatial relations between Figures and Grounds, respectively. This novel distinction aids in enhancing the understanding of locative event typologies and provides an explanatory model for cross-linguistic analysis. The proposed integrated formal framework combines predicate logic, set theory, and lexical semantics to account for complex locative meanings, with significant applications in computational and theoretical linguistics, as well as cognitive science. [ABSTRACT FROM AUTHOR]

While research evidence has the potential to improve classroom practice, research–practice gaps continue to persist not least owing to the limited relevance of research findings for practice. A common approach in healthcare to address the research–practice gap is to form research priority setting partnerships (PSPs) in which stakeholders identify questions they would like research to answer. This paper presents the results from such a PSP in education with a focus on cognitive science research, which has received increased attention in the past few years owing to its potential to explain memory and learning processes and inform classroom practice. Over 400 questions from teachers were collected using an online survey. The final 15 research priorities highlight the need for research on a wider range of subjects, settings and phases as well as research designs that take the complexity of classrooms into consideration and aim to answer how different teaching strategies interact with each other as well as student motivation and agency at the micro‐ and macro‐level. The role of teacher expertise vs. fidelity to original research designs should also be investigated further. Overall, this paper highlights the importance of taking teacher voice into account to ensure that new research in the field is both academically rigorous and practically relevant. [ABSTRACT FROM AUTHOR]

Ignorance, or the lack of knowledge, appears to be steadily spreading, despite the increasing availability of information. The notion of informed ignorance herein proposed to describe the widespread position of being exposed to an abundance of information yet lacking relevant knowledge, which is tied to the exponential growth in misinformation driven by technological developments and social media. Linked to many of societies' most looming catastrophes, from political polarization to the climate crisis, practices related to knowledge and information are deemed some of the most imminent and daunting modern threats, evidenced by the latest report of the World Economic Forum, which has named misinformation the most severe short-term global risk. This paper's epistemic perspective links the properties of today's information culture and the ways in which it interacts with individual capacities and limitations in current technological and socio-political contexts. Such a position is analyzed through the lens of epistemic principles as a contemporary epistemic phenotype that emerges from an environment of ill-adapted and excessive information inputs and leads to a distinctive type of social injustice that is primarily epistemic in nature. While equity and accessibility are widely discussed as important contributing factors to epistemic discrepancies, other overlooked but fundamental issues underlying epistemic injustices are considered, such as information manipulation, cognitive limitations, and epistemic degradation. To effectively face this elusive threat, we propose an inclusive viewpoint that harnesses knowledge from cognitive science, science and technology studies, and social epistemology to inform a unifying theory of its main impacts and driving forces. By adjusting a modern epistemic framework to the described phenomena, we intend to contextually outline its trajectory and possible means of containment based on a shared responsibility to maintain ethical epistemic standards. In a time of international unrest and mounting civil acts of violence, it is pertinent to emphasize the ethical principles of knowledge systems and authorities and suggest policy adaptations to maintain a social contract based on the shared values of truth and freedom. [ABSTRACT FROM AUTHOR]

As such, the workshop has always been located in Italy, with the workshop Steering Committee constantly committed to involve every major Italian research group working on agents and multi-agent systems. The first Workshop "From Objects to Agents" (WOA) was held in Parma in May 2000. The topics discussed in the papers covered some of the most debated subjects in the research on agents and multi-agent systems, and were not limited to the theme of the workshop, which was suggested in the call for papers as I multi-agent systems in the machine learning era i . [Extracted from the article]