Several canonical experimental paradigms (e.g., serial reaction time task, discrete sequence production task,m×ntask) have been proposed to study the typical behavioral phenomenon and the nature of learning in sequential keypress tasks. A characteristic feature of most paradigms is that they are representative ofexternally-specifiedsequencing—motor tasks where the environment or task paradigm extrinsically provides the sequence of stimuli, i.e., the responses are stimulus-driven. Previous studies utilizing such canonical paradigms have largely overlooked the learning behaviors in a more realistic class of motor tasks (...) that involveinternally-guidedsequencing—where the sequence of motor actions is self-generated or internally-specified. In this work, we use the grid-navigation task as an instance of internally-guided sequencing to investigate the nature of learning in such paradigms. The participants performed Grid-Sailing Task (GST), which required navigating (by executing sequential keypresses) a 5 × 5 grid from start to goal (SG) position while using a particular key-mapping (KM) among the three cursor-movement directions and the three keyboard buttons. The participants performed two behavioral experiments—Single-SG and Mixed-SG condition. The Single-SG condition required performing GST on a single SG position repeatedly, whereas the Mixed-SG condition involved performing GST using the same KM on two novel SG positions presented in a random, inter-mixed manner. In the Single-SG condition, we show that motor learning contributes to the sequence-specific learning in GST with the repeated execution of the same trajectories. In the Mixed-SG condition, since the participants utilize the previously learned KM, we anticipate a transfer of learning from the Single-SG condition. The acquisition and transfer of a KM-specific internal model facilitates efficient trajectory planning on novel SG conditions. The acquisition of such a KM-specific internal model amounts to trajectory-independent cognitive learning in GST. We show that cognitive learning contributes to the learning in GST by showing transfer-related performance improvements in the Mixed-SG condition. In sum, we show the role of cognitive and motor learning processes in internally-guided sequencing and further make a case for using GST-like grid-navigation paradigms in investigating internally guided skill learning. (shrink)

This article first analyzes the research background of the design elements of cognitive psychology and neural networks at home and abroad, roughly understands the research status and research background of these two courses at home and abroad, and discusses the application of cognitive psychology to neural networks. The design method has not yet formed a systematic theoretical system. Then, a systematic theoretical analysis of the research in this article is carried out to analyze the relationship between the various (...) characteristics of cognitive psychology and the design elements of the neural network, and it uses these relationships to guide the design practice. Second, it analyzes the relationship between the influence and interaction of cognitive psychology on neural network design and connects cognitive psychology with neural network design. Finally, according to the theoretical analysis and research of the system, the application of cognitive psychology in neural network design, design practice, and the relationship between the two are systematically reviewed. Through the exploratory research on cognitive psychology in neural network design, we can see that the combination of neural network design and psychology, art aesthetics, and other cross-disciplinary and multidisciplinary research is necessary, which can promote the scientific and technological progress of neural network design in the context of the information age and the improvement of public mental health. Under the background of the era in which the neural network design becomes the link between people's emotions and culture, we must fully understand the essential role of each element in neural network design and build a design concept based on cognitive psychology and emotional experience. It is hoped that the content of this topic can provide a certain reference value for the future development of neural network design and cognitive psychology and clarify the new development direction. (shrink)

In this new volume in the Oxford Psychology Series, the author presents a highly readable account of the cognitive unconscious, focusing in particular on the problem of implicit learning. Implicit learning is defined as the acquisition of knowledge that takes place independently of the conscious attempts to learn and largely in the absence of explicit knowledge about what was acquired. One of the core assumptions of this argument is that implicit learning is a fundamental, "root" process, one that lies (...) at the very heart of the adaptive behavioral repertoire of every complex organism. The author's goals are to outline the essential features of implicit learning that have emerged from the many studies that have been carried out in a variety of experimental laboratories over the past several decades; to present the various alternative perspectives on this issue that have been proposed by other researchers and to try to accommodate these views with his own; to structure the literature so that it can be seen in the context of standard heuristics of evolutionary biology; to present the material within a functionalist approach and to try to show why the experimental data should be seen as entailing particular epistemological perspectives; and to present implicit processing as encompassing a general and ubiquitous set of operations that have wide currency and several possible applications. Chapter 1 begins with the core problem under consideration in this book, a characterization of "implicit learning" as it has come to be used in the literature. Reber puts this seemingly specialized topic into a general framework and suggests a theoretical model based on standard heuristics of evolutionary biology. In his account, Reber weaves a capsule history of interest in and work on the cognitive unconscious. Chapter 2 turns to a detailed overview of the experimental work on the acquisition of implicit knowledge, which currently is of great interest. Chapter 3 develops the evolutionary model within which one can see learning and cognition as richly intertwining issues and not as two distinct fields with one dominating the other. Finally, Chapter 4 explores a variety of entailments and speculations concerning implicit cognitive processes and their general role in the larger scope of human performance. (shrink)

We extend recent information-theoretic phase transition approaches to evolutionary and cognitive process via the Rate Distortion and Joint Asymptotic Equipartition Theorems, in the circumstance of interaction with a highly structured environment. This suggests that learning plateaus in cognitive systems and punctuated equilibria in evolutionary process are formally analogous, even though evolution is not cognitive. Extending arguments by Adami et al. (2000), we argue that 'adaptation' is the process by which a distorted genetic image of a coherently structured (...) environment is imposed upon a species. (shrink)

In recent years, the family of algorithms collected under the term ``deep learning'' has revolutionized artificial intelligence, enabling machines to reach human-like performances in many complex cognitive tasks. Although deep learning models are grounded in the connectionist paradigm, their recent advances were basically developed with engineering goals in mind. Despite of their applied focus, deep learning models eventually seem fruitful for cognitive purposes. This can be thought as a kind of biological exaptation, where a physiological structure becomes applicable (...) for a function different from that for which it was selected. In this paper, it will be argued that it is time for cognitive science to seriously come to terms with deep learning, and we try to spell out the reasons why this is the case. First, the path of the evolution of deep learning from the connectionist project is traced, demonstrating the remarkable continuity, and the differences as well. Then, it will be considered how deep learning models can be useful for many cognitive topics, especially those where it has achieved performance comparable to humans, from perception to language. It will be maintained that deep learning poses questions that cognitive sciences should try to answer. One of such questions is the reasons why deep convolutional models that are disembodied, inactive, unaware of context, and static, are by far the closest to the patterns of activation in the brain visual system. (shrink)

Cognitive penetration of perception, broadly understood, is the influence that the cognitive system has on a perceptual system. The paper shows a form of cognitive penetration in the visual system which I call ‘architectural’. Architectural cognitive penetration is the process whereby the behaviour or the structure of the perceptual system is influenced by the cognitive system, which consequently may have an impact on the content of the perceptual experience. I scrutinize a study in perceptual learning (...) that provides empirical evidence that cognitive influences in the visual system produce neural reorganization in the primary visual cortex. The type of cognitive penetration can be synchronic and diachronic. (shrink)

Why do children learn language more easily than adults do? This puzzle has fascinated cognitive and language scientists for decades. In the present letter, we approach the language learning puzzle from a cognitive perspective that is inspired by evidence from the perceptual and motor learning literature. Neuroscientific studies show that two memory systems in the brain are involved in human learning: an early implicit procedural memory system and a late-developing cognitive or declarative memory system. We argue that (...) higher cognitive development constrains implicit statistical learning processes that are essential for learning patterns and regularities in languages, that is, the adult cognitive architecture has a cost. This is supported by experimental evidence showing that acquisition of implicit linguistic knowledge is enhanced under cognitive depletion in adults. More research is needed to test the cognitive cost hypothesis as it could partly solve the language learning puzzle. (shrink)

The cognitive penetrability of perceptual experiences has been a long-standing topic of disagreement among philosophers and psychologists. Although the notion of cognitive penetrability itself has also been under dispute, the debate has mainly focused on the cases in which cognitive states allegedly penetrate perceptual experiences. This paper concerns the plausibility of two prominent cases. The first one originates from Susanna Siegel’s claim that perceptual experiences can represent natural kind properties. If this is true, then the concepts we (...) possess change the way things appear to us. The second candidate for cognitive penetration is Fiona Macpherson’s claim that, in addition to concepts, our beliefs can penetrate perceptual experiences. It is argued that neither candidate is a case of cognitive penetration. In doing so, I provide an explanation to both that is based on perceptual learning, a non-cognitive phenomenon where relatively slow and long-lasting modifications to an organism’s perceptual system bring about changes in perception. This explanation is theoretically more plausible and remains closer to the empirical data than the explanations based on cognitive penetration. (shrink)

In this new volume in the Oxford Psychology Series, the author presents a highly readable account of the cognitive unconscious, focusing in particular on the problem of implicit learning. Implicit learning is defined as the acquisition of knowledge that takes place independently of the conscious attempts to learn and largely in the absence of explicit knowledge about what was acquired. One of the core assumptions of this argument is that implicit learning is a fundamental, "root" process, one that lies (...) at the very heart of the adaptive behavioral repertoire of every complex organism. The author's goals are to outline the essential features of implicit learning that have emerged from the many studies that have been carried out in a variety of experimental laboratories over the past several decades; to present the various alternative perspectives on this issue that have been proposed by other researchers and to try to accommodate these views with his own; to structure the literature so that it can be seen in the context of standard heuristics of evolutionary biology; to present the material within a functionalist approach and to try to show why the experimental data should be seen as entailing particular epistemological perspectives; and to present implicit processing as encompassing a general and ubiquitous set of operations that have wide currency and several possible applications. Chapter 1 begins with the core problem under consideration in this book, a characterization of "implicit learning" as it has come to be used in the literature. Reber puts this seemingly specialized topic into a general framework and suggests a theoretical model based on standard heuristics of evolutionary biology. In his account, Reber weaves a capsule history of interest in and work on the cognitive unconscious. Chapter 2 turns to a detailed overview of the experimental work on the acquisition of implicit knowledge, which currently is of great interest. Chapter 3 develops the evolutionary model within which one can see learning and cognition as richly intertwining issues and not as two distinct fields with one dominating the other. Finally, Chapter 4 explores a variety of entailments and speculations concerning implicit cognitive processes and their general role in the larger scope of human performance. (shrink)

Pothos & Busemeyer's (P&B's) query about whether quantum probability can provide a foundation for the cognitive modeling embodies so many underlying implications that the subject is far from exhausted. In this brief commentary, however, I suggest that the conceptual thresholds of the meaningful learning give rise to a typical Boltzmann's weighting measure, which indicates astatistical verisimilitudeof quantum behavior in the human cognitive ensemble.

The function and legitimacy of values in decision making is a critically important issue in the contemporary analysis of science. It is particularly relevant for some of the more application-oriented areas of science, specifically decision-oriented science in the field of regulation of technological risks. Our main objective in this paper is to assess the diversity of roles that non-cognitive values related to decision making can adopt in the kinds of scientific activity that underlie risk regulation. We start out, first, (...) by analyzing the issue of values with the help of a framework taken from the wider philosophical debate on science and values. Second, we study the principal conceptualizations used by scholars who have applied them to numerous case studies. Third, we appraise the links between those conceptualizations and learning processes in decision-oriented science. In this, we recur to the concept of methodological learning, i.e., learning about the best methodologies for generating knowledge that is useful for science-based regulatory decisions. The main result of our analysis is that non-cognitive values can contribute to methodological improvements in science in three principal ways: as basis for critical analysis, for contextualizing methodologies, and for establishing the burden of proof. (shrink)

Learning to write in a foreign language is a complex cognitive process. The process-genre approach is a common instructional practice adopted by language teachers to develop learners’ writing abilities. However, the interacting elements of procedural knowledge, linguistic knowledge, and generic knowledge in this approach may exceed the capacity of an individual learner’s working memory, thus actually hindering the acquisition of writing skills. According to the collective working memory effect, it was hypothesized that teaching writing skills of English as a (...) foreign language by adopting a process-genre approach in collaborative conditions could lead to better writing performance, lower cognitive load, and higher instructional efficiency. The reported experiment compared learning writing skills of English as a foreign language in individual and collaborative instructional conditions from a cognitive load perspective, a rarely adopted approach in this field. The results indicated that the collaborative instructional condition was more effective and efficient than the individual instructional condition in improving the quality of written products as well as in optimizing the cognitive (working memory) load experienced by the learners. Measures of cognitive load were used to support the cognitive load theory’s interpretation of the results, which is the unique contribution of this research study to the field. (shrink)

De nombreuses études sur l'apprentissage des langues étrangères montrent que l'apprenant est incapable d'atteindre le niveau d'un locuteur natif. Des phénomènes de fossilisation et de nativisation demeurent, même à un niveau très avancé (Selinker & Lamendella, 1980 ; Selinker & Lakshamanan, 1992 ; Andersen, 1983 ; Narcy-Combes, 2005). Cet article met en évidence le rôle limitatif des représentations cognitives chez l'apprenant dans un contexte où il est possible d'isoler chronologiquement la construction des représentations cognitives et celle d'une première langue. Ce (...) contexte est celui de la surdité profonde prélinguistique, et plus spécifiquement celui de l'oralisme : l’acquisition de la langue y est différée de quelques mois ou années sans qu'il n'y ait de système linguistique préalable puisque les oralistes sont tenus à l'écart des langues signées. Les jeunes sourds développent des représentations cognitives dans leurs premières années de vie, préalablement à l'accès à une première langue. Or, des études expérimentales (ex. Vinter, 2000) montrent que les sujets sourds ont une approche inhabituelle du spatial et du temporel, approche pouvant être mise en rapport avec l'absence de perception auditive. Du fait des liens entre perception sensorielle et conception (ex. Talmy, 1988 & 2000), les représentations cognitives des sujets sourds relativement à l'espace et au temps seraient donc spécifiques. La langue orale produite par ces sujets à l'adolescence présente quant à elle des caractéristiques inhabituelles dans les domaines de la langue qui sont liés à l'espace et au temps, et ce, aussi bien chez les anglophones que chez les francophones dont les productions orales ont été analysées (ex. Vincent-Durroux, 2009 & 2008). Les représentations cognitives influent donc sur l'appropriation de la langue par les sourds. La discussion porte sur le fait que, dans le contexte de l'apprentissage de langues étrangères par des entendants, les représentations cognitives sous-jacentes à la langue maternelle pourraient avoir un rôle limitatif et ainsi expliquer la persistance des phénomènes de fossilisation et de nativisation. (shrink)

Purpose: The aim of this research was to test whether Hong Kong science students would prefer a learning environment based on critical constructivism and whether a closer preferred-actual fit to such an environment would be associated with better learning outcomes. Method: The participants were 149 Hong Kong secondary school Chemistry students aged 16--19 years. They completed actual and preferred forms of a Chinese version of the Constructivist Learning Environment Survey and measures of self-efficacy and intrinsic value of their Chemistry course. (...) Their Chemistry examination scores were also obtained at the end of the course. Findings: Analysis showed that these students would prefer their Chemistry classrooms to be more personally relevant, to allow students more say and to share more control, and to encourage more negotiation with their teacher. Regression surface analysis showed that congruence of person environment fit did not influence examination results but was associated with greater valuing of the course and higher student self-efficacy. Research implications: Further research with a wider sampling from Hong Kong and elsewhere and focusing on other subject areas will be necessary to assess the generalizability of these findings. Practical implications: It seems that educational reforms based on critical constructivist principles may be of value in non-Western contexts. Original value: Educational reforms in Hong Kong and elsewhere currently are based on traditional constructivist principles. But this is the first research to support a more radical approach in what is usually regarded as a relatively conservative Asian educational context. (shrink)

The fields of machine learning (ML) and cognitive science have developed complementary approaches to computationally modeling human behavior. ML's primary concern is maximizing prediction accuracy; cognitive science's primary concern is explaining the underlying mechanisms. Cross-talk between these disciplines is limited, likely because the tasks and goals usually differ. The domain of e-learning and knowledge acquisition constitutes a fruitful intersection for the two fields’ methodologies to be integrated because accurately tracking learning and forgetting over time and predicting future performance (...) based on learning histories are central to developing effective, personalized learning tools. Here, we show how a state-of-the-art ML model can be enhanced by incorporating insights from a cognitive model of human memory. This was done by exploiting the predictive performance equation's (PPE) narrow but highly specialized domain knowledge with regard to the temporal dynamics of learning and forgetting. Specifically, the PPE was used to engineer timing-related input features for a gradient-boosted decision trees (GBDT) model. The resulting PPE-enhanced GBDT outperformed the default GBDT, especially under conditions in which limited data were available for training. Results suggest that integrating cognitive and ML models could be particularly productive if the available data are too high-dimensional to be explained by a cognitive model but not sufficiently large to effectively train a modern ML algorithm. Here, the cognitive model's insights pertaining to only one aspect of the data were enough to jump-start the ML model's ability to make predictions—a finding that holds promise for future explorations. (shrink)

Considerable evidence indicates that domain specific knowledge in the form of schemas is the primary factor distinguishing experts from novices in problem‐solving skill. Evidence that conventional problem‐solving activity is not effective in schema acquisition is also accumulating. It is suggested that a major reason for the ineffectiveness of problem solving as a learning device, is that the cognitive processes required by the two activities overlap insufficiently, and that conventional problem solving in the form of means‐ends analysis requires a relatively (...) large amount of cognitive processing capacity which is consequently unavailable for schema acquisition. A computational model and experimental evidence provide support for this contention. Theoretical and practical implications are discussed. (shrink)

The ability to anticipate team members' actions enables joint action towards a common goal. Task knowledge and mental simulation allow for anticipating other agents' actions and for making inferences about their underlying mental representations. In human–AI teams, providing AI agents with anticipatory mechanisms can facilitate collaboration and successful execution of joint action. This paper presents a computational cognitive model demonstrating mental simulation of operators' mental models of a situation and anticipation of their behavior. The work proposes two successive steps: (...) (1) A hierarchical cluster algorithm is applied to recognize patterns of behavior among pilots. These behavioral clusters are used to derive commonalities in situation models from empirical data (N = 13 pilots). (2) An ACT-R (adaptive control of thought - rational) cognitive model is implemented to mentally simulate different possible outcomes of action decisions and timing of a pilot. model tracing of ACT-R allows following up on operators' individual actions. Two models are implemented using the symbolic representations of ACT-R: one simulating normative behavior and the other by simulating individual differences and using subsymbolic learning. Model performance is analyzed by a comparison of both models. Results indicate the improved performance of the individual differences over the normative model and are discussed regarding implications for cognitive assistance capable of anticipating operator behavior. (shrink)

Extended and distributed cognition theories argue that human cognitive systems sometimes include non-biological objects. On these views, the physical supervenience base of cognitive systems is thus not the biological brain or even the embodied organism, but an organism-plus-artifacts. In this paper, we provide a novel account of the implications of these views for learning, education, and assessment. We start by conceptualising how we learn to assemble extended cognitive systems by internalising cultural norms and practices. Having a better (...) grip on how extended cognitive systems are assembled, we focus on the question: If our cognition extends, how should we educate and assess such extended cognitive systems? We suggest various ways to minimize possible negative effects of extending one’s cognition and to efficiently find and organise (online) information by adopting a virtue epistemology approach. Educational and assessment implications are foregrounded, particularly in the case of Danish students’ use of the Internet during exams. (shrink)

Mental representations remain the central posits of psychology after many decades of scrutiny. However, there is no consensus about the representational format(s) of biological cognition. This paper provides a survey of evidence from computational cognitive psychology, perceptual psychology, developmental psychology, comparative psychology, and social psychology, and concludes that one type of format that routinely crops up is the language-of-thought (LoT). We outline six core properties of LoTs: (i) discrete constituents; (ii) role-filler independence; (iii) predicate–argument structure; (iv) logical operators; (v) (...) inferential promiscuity; and (vi) abstract content. These properties cluster together throughout cognitive science. Bayesian computational modeling, compositional features of object perception, complex infant and animal reasoning, and automatic, intuitive cognition in adults all implicate LoT-like structures. Instead of regarding LoT as a relic of the previous century, researchers in cognitive science and philosophy-of-mind must take seriously the explanatory breadth of LoT-based architectures. We grant that the mind may harbor many formats and architectures, including iconic and associative structures as well as deep-neural-network-like architectures. However, as computational/representational approaches to the mind continue to advance, classical compositional symbolic structures – that is, LoTs – only prove more flexible and well-supported over time. (shrink)

In this article, I review recent findings in cognitive neuroscience in learning, particularly in the learning of mathematics and of reading. I argue that while cognitive neuroscience is in its infancy as a field, theories of learning will need to incorporate and account for this growing body of empirical data.

Invited to give the 2000 Rick Turner Memorial Lecture, I pondered the following question: What explains the fact that the sincere thought of a brilliant and heroic person such as Turner can appear preposterous to me, if bad faith or scholarly ignorance on one side or the other are ruled out, as they should be in this case? I address this question by considering what ‘ideologies' are from the perspective of cognitive learning theory. I describe the dynamics by which (...) pressures for social coordination cause brains to implement alternative natural softwares for performing inferences in complex domains of association and inference. I conclude by noting that this need not imply normative relativism, since the relative justifications for conclusions produced by different softwares can still be debated. My aim is thus not to contest Turner's ideology or political views, but to partially explain how learning produces differences that transcend factual disagreements and even ethical ones. S. Afr. J. Philos. Vol.22(2) 2003: 139–156. (shrink)

Recently, an associative learning account of cognitive control has been suggested (Verguts & Notebaert, 2009). In this so-called adaptation by binding theory, Hebbian learning of stimulus–stimulus and stimulus–response associations is assumed to drive the adaptation of human behavior. In this study, we evaluated the validity of the adaptation-by-binding account for the case of implicit learning of regularities within a stimulus set (i.e., the frequency of specific unit digit combinations in a two-digit number magnitude comparison task) and their association with (...) a particular response. Our data indicated that participants indeed learned these regularities and adapted their behavior accordingly. In particular, influences of cognitive control were even able to override the numerical distance effect—one of the most robust effects in numerical cognition research. Thus, the general cognitive processes involved in two-digit number magnitude comparison seem much more complex than previously assumed. Multi-digit number magnitude comparison may not be automatic and inflexible but influenced by processes of cognitive control being highly adaptive to stimulus set properties and task demands on multiple levels. (shrink)

Most biologists and some cognitive scientists have independently reached the conclusion that there is no such thing as learning in the traditional “instructive‘ sense. This is, admittedly, a somewhat extreme thesis, but I defend it herein the light of data and theories jointly extracted from biology, especially from evolutionary theory and immunology, and from modern generative grammar. I also point out that the general demise of learning is uncontroversial in the biological sciences, while a similar consensus has not yet (...) been reached in psychology and in linguistics at large. Since many arguments presently offered in defense of learning and in defense of “general intelligence‘ are often based on a distorted picture of human biological evolution, I devote some sections of this paper to a critique of “adaptationism,‘ providing also a sketch of a better evolutionary theory. Moreover, since certain standard arguments presented today as “knock-down‘ in psychology, in linguistics and in artificial intelligence are a perfect replica of those once voiced by biologists in favor of instruction and against selection, I capitalize on these errors of the past to draw some lessons for the present and for the future. (shrink)

Machine learning and statistical methods have yielded impressive results in a wide variety of natural language processing tasks. These advances have generally been regarded as engineering achievements. In fact it is possible to argue that the success of machine learning methods is significant for our understanding of the cognitive basis of language acquisition and processing. Recent work in unsupervised grammar induction is particularly relevant to this issue. It suggests that knowledge of language can be achieved through general learning procedures, (...) and that a richly articulated language faculty is not required to explain its acquisition. (shrink)

The past 50 years have seen an accumulation of evidence suggesting that associative learning depends on high-level cognitive processes that give rise to propositional knowledge. Yet, many learning theorists maintain a belief in a learning mechanism in which links between mental representations are formed automatically. We characterize and highlight the differences between the propositional and link approaches, and review the relevant empirical evidence. We conclude that learning is the consequence of propositional reasoning processes that cooperate with the unconscious processes (...) involved in memory retrieval and perception. We argue that this new conceptual framework allows many of the important recent advances in associative learning research to be retained, but recast in a model that provides a firmer foundation for both immediate application and future research. (shrink)

Language learning in preschool children tends to be likened to school-like learning, using verbal explanations more than actions when new words are learned during storytelling. Based on previous results that showed that sensorimotor elements help language learning at this age this study aimed to investigate whether positive emotions also act like essential elements for language learning. Fifty-five 4 to 5 year olds listened to a modified version of the Town Musicians of Bremen story. There were four conditions: one that included (...) emotions and sensorimotor elements during storytelling, one that had only emotions, one that had only sensorimotor elements, and one that had neither emotions nor sensorimotor elements. Results show no advantage of positive emotions by themselves, and a clear advantage of sensorimotor elements. Implications are discussed with regard to inducing emotions versus naturally arising emotional states, and also to the embodied learning perspective. (shrink)

The psycholinguistic literature has identified two syntactic adaptation effects in language production: rapidly decaying short-term priming and long-lasting adaptation. To explain both effects, we present an ACT-R model of syntactic priming based on a wide-coverage, lexicalized syntactic theory that explains priming as facilitation of lexical access. In this model, two well-established ACT-R mechanisms, base-level learning and spreading activation, account for long-term adaptation and short-term priming, respectively. Our model simulates incremental language production and in a series of modeling studies, we show (...) that it accounts for (a) the inverse frequency interaction; (b) the absence of a decay in long-term priming; and (c) the cumulativity of long-term adaptation. The model also explains the lexical boost effect and the fact that it only applies to short-term priming. We also present corpus data that verify a prediction of the model, that is, that the lexical boost affects all lexical material, rather than just heads. (shrink)

In recent years there has been renewed philosophical interest in the thesis that perceptual experience is cognitively penetrable, i.e., roughly, the view that the contents and/or character of a subject's perceptual experience can be modified by what a subject believes and desires. As has been widely noted, it is plausible that cognitive penetration has implications for perception's epistemic role. On the one hand, penetration could make agents insensitive to the world in a way which epistemically 'downgrades' their experience. On (...) the other hand, cognitive penetration may sometimes be epistemically beneficial by making agents more sensitive to the way the world is, i.e., by enabling them to see things that others cannot. For example, penetration could ground a 'high-level' view of perceptual content, according to which agents can have experiences as of 'complex' properties, e.g., natural kind and aesthetic properties. Relatedly, it could elucidate the view that agents can gain perceptual expertise by learning. A type of sophisticated perception which has hitherto received little attention in relation to cognitive penetration is ethical perception. In this paper I examine the significance of cognitive penetration for 'Perceptualist' views in ethics which appeal to a notion of 'ethical perception'. Although cognitive penetration could ground a literalist model of Ethical Perception according to which agents can have perceptual experiences of the instantiation of ethical properties, the results are otherwise somewhat mixed: cognitive penetrability does not support Perceptual Intuitionism, although it may provide some limited support for Virtue Ethics and Cornell Realism. However, as I stress, the significance of cognitive penetration for Perceptualism should not be overstated. (shrink)

Objective: Mindfulness-based intervention has been proposed to alleviate loneliness and improve social connectedness. Several randomized controlled trials have been conducted to evaluate the effectiveness of MBI. This study aimed to critically evaluate and determine the effectiveness and safety of MBI in alleviating the feeling of loneliness.Methods: We searched Medline, Embase, PsycInfo, Cochrane CENTRAL, and AMED for publications from inception to May 2020. We included RCTs with human subjects who were enrolled in MBI with loneliness as an outcome. The quality of (...) evidence was assessed using Cochrane's Risk of Bias tool and Grading of Recommendations Assessment, Development, and Evaluation. A random-effects model was used for meta-analysis.Results: Out of 92 articles identified, eight studies involving 815 participants were included in this study. Most trials conducted a minimum of 8 weeks of MBI. Most of the trials used UCLA-Loneliness Scale. A pooled analysis combining three trials and compared with wait-list showed significant improvement in loneliness score reduction using the UCLA-R scale with MD of −6.33 [95% confidence interval : −9.39, −3.26]. Subgroup analysis with only two Cognitively-Based Compassion Training trials also showed similar MD of −6.05. The overall quality of evidence was low.Conclusions: Mindfulness intervention with an average length of 8-week duration significantly improved the population's loneliness level with no mental health issue. However, this evidence had a low GRADE level. (shrink)

Recent studies have shown that self‐explanation is an effective metacognitive strategy, but how can it be leveraged to improve students' learning in actual classrooms? How do instructional treatments that emphasizes self‐explanation affect students' learning, as compared to other instructional treatments? We investigated whether self‐explanation can be scaffolded effectively in a classroom environment using a Cognitive Tutor, which is intelligent instructional software that supports guided learning by doing. In two classroom experiments, we found that students who explained their steps during (...) problem‐solving practice with a Cognitive Tutor learned with greater understanding compared to students who did not explain steps. The explainers better explained their solutions steps and were more successful on transfer problems. We interpret these results as follows: By engaging in explanation, students acquired better‐integrated visual and verbal declarative knowledge and acquired less shallow procedural knowledge. The research demonstrates that the benefits of self‐explanation can be achieved in a relatively simple computer‐based approach that scales well for classroom use. (shrink)

We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or “Bayes nets”. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old (...) children construct new causal maps and that their learning is consistent with the Bayes net formalism. (shrink)

Cognitive gadgets are distinctively human cognitive mechanisms – such as imitation, mind reading, and language – that have been shaped by cultural rather than genetic evolution. New gadgets emerge, not by genetic mutation, but by innovations in cognitive development; they are specialised cognitive mechanisms built by general cognitive mechanisms using information from the sociocultural environment. Innovations are passed on to subsequent generations, not by DNA replication, but through social learning: People with new cognitive mechanisms (...) pass them on to others through social interaction. Some of the new mechanisms, like literacy, have spread through human populations, while others have died out, because the holders had more students, not just more babies. The cognitive gadgets hypothesis is developed through four case studies, drawing on evidence from comparative and developmental psychology, experimental psychology, and cognitive neuroscience. The framework employed – cultural evolutionary psychology, a descendant of evolutionary psychology and cultural evolutionary theory – addresses parallel issues across the cognitive and behavioural sciences. In common with evolutionary developmental biology and the extended evolutionary synthesis, cultural evolutionary psychology underlines the importance of developmental processes and environmental factors in the emergence of human cognition. In common with computational approaches, it emphasises the power of general-purpose mechanisms of learning. Cultural evolutionary psychology, however, also challenges use of the behavioural gambit in economics and behavioural ecology, and rejects the view that human minds are composed of “innate modules” or “cognitive instincts.”. (shrink)

Meta-learning offers a promising framework to make sense of some parts of decision-making that have eluded satisfactory explanation. Here, we connect this research to work in animal behaviour and cognition in order to shed light on how and whether meta-learning could help us to understand the evolution of cognition.

Episodic representations can be entertained either as “remembered” or “imagined”—as outcomes of experience or as simulations of such experience. Here, we argue that this feature is the product of a dedicated cognitive function: the metacognitive capacity to determine the mnemicity of mental event simulations. We argue that mnemicity attribution should be distinguished from other metacognitive operations (such as reality monitoring) and propose that this attribution is a “cognitive gadget”—a distinctively human ability made possible by cultural learning. Cultural learning (...) is a type of social learning in which traits are inherited through social interaction. In the case of mnemicity, one culturally learns to discriminate metacognitive “feelings of remembering” from other perceptual, emotional, action-related, and metacognitive feelings; to interpret feelings of remembering as indicators of memory rather than imagination; and to broadcast the interpreted feelings in culture- and context-specific ways, such as “I was there” or “I witnessed it myself.” We review evidence from the literature on memory development and scaffolding, metacognitive learning and teaching, as well as cross-cultural psychology in support of this view before pointing out various open questions about the nature and development of mnemicity highlighted by our account. (shrink)

The human primate is a deeply cultural species, our cognition being shaped by culture, and cultural transmission amounting to an “epidemic of mental representations” (Sperber, 1996). The architecture of this aspect of human cognition has been shaped by our evolutionary past in ways that we can now begin to discern through comparative studies of other primates. Processes of social learning (learning from others) are important for cognitive science to understand because they are cognitively complex and take many interrelated forms; (...) they shape traditions, cultures and nonsocial aspects of cognition; and in turn they may be shaped by their cultural context. The study of primate social learning and culture has in recent years enjoyed a renaissance, providing a wealth of new findings, key aspects of which are reviewed. The focus is on cognitive issues, including learning about the consequences, sequential structure and hierarchical organization of actions; relating stored knowledge to the assimilation of new social knowledge; feedback guiding the construction of imitations; conceptual grasp of imitation; and the reciprocal relationship between social learning and culture. (shrink)

The goal of the present study was to investigate whether children’s cognitive strengths can compensate the accompanied weaknesses related to their specific learning difficulties. A Bayesian multigroup mediation SEM analysis in 281 fourth-grade children identified a cognitive compensatory mechanism in children with mathematical learning difficulties (n= 36): Children with weak number sense, but strong rapid naming performed slightly better on mathematics compared to peers with weak rapid naming. In contrast, a compensatory mechanism was not identified for children with (...) a comorbid mathematical and reading difficulty (n= 16). One explanation for the latter finding could relate to the lack of ability to compensate, because of the difficulties these children experience in both academic domains. These findings lead to a new direction in research on learning difficulties in mathematics and/or reading by suggesting that children with a learning disability each have a unique profile of interrelated cognitive strengths and weaknesses. Children might compensate with these strengths for their weaknesses, which could lead to (small) learning gains in the affected domain. (shrink)

With the wide application of computers and digital technologies, online information searching is being integrated into students’ learning process. Improving students’ creative question generation through online information searching is an emerging research topic in the creativity and pedagogy field. Online information searching brings diversified information, but it also leads to cognitive load brought by a large amount of online information. Using online information searching to generate creative questions depends on students’ cognitive properties. However, the existing literature ignores the (...) joint influence of students’ online information searching strategies and cognitive properties on their creative question generation. This study puts forward three hypotheses: first, the two strategies of students’ online information searching will increase their creative question generation; second, the impact of “keywords” is negatively moderated by students’ need for cognitive closure ; third, the impact of “Web page exploration” is positively moderated by NFCC. The main reason is that high NFCC prevents students from obtaining diversified perspectives by using different keywords, but it helps to avoid distractions caused by a large amount of online information and promote the persistency of their reading information. Based on the data of quasi-experimental tasks completed by 90 students in Grade 7 and Grade 8, the results support the above hypothesis. The contributions of creative question generation theory and NFCC theory, as well as important issues of future study, are discussed. (shrink)

Education has recently been shaped by the cognitive science of memory. In turn, the science of memory has been infused by revolutionary ideas found in Wittgenstein’s works. However, the memory science presently applied to education draws mainly on traditional models that are quickly becoming outmoded; Wittgenstein’s insights have yet to be fruitfully applied, though they have helped to develop the science of memory. In this chapter, I examine three Wittgensteinian reforms in memory science as they pertain to education . (...) First, Wittgenstein has inspired a particular strain of enactive models of memory and cognition, with important implications for theories of situated learning in education. Second, researchers have begun modeling memory as public practice , which deeply informs, inter alia, fraught theoretical discussions of assessment. Third, a number of memory researchers have rejected models based on a stored trace, a fundamental, Wittgensteinian revision with broad implications for characterizations of learning. (shrink)

Emotion has a substantial influence on the cognitive processes in humans, including perception, attention, learning, memory, reasoning, and problem solving. Emotion has a particularly strong influence on attention, especially modulating the selectivity of attention as well as motivating action and behavior. This attentional and executive control is intimately linked to learning processes, as intrinsically limited attentional capacities are better focused on relevant information. Emotion also facilitates encoding and helps retrieval of information efficiently. However, the effects of emotion on learning (...) and memory are not always univalent, as studies have reported that emotion either enhances or impairs learning and long-term memory retention, depending on a range of factors. Recent neuroimaging findings have indicated that the amygdala and prefrontal cortex cooperate with the medial temporal lobe in an integrated manner that affords (i) the amygdala modulating memory consolidation; (ii) the prefrontal cortex mediating memory encoding and formation; and (iii) the hippocampus for successful learning and long-term memory retention. We also review the nested hierarchies of circular emotional control and cognitive regulation (bottom-up and top-down influences) within the brain to achieve optimal integration of emotional and cognitive processing. This review highlights a basic evolutionary approach to emotion to understand the effects of emotion on learning and memory and the functional roles played by various brain regions and their mutual interactions in relation to emotional processing. We also summarize the current state of knowledge on the impact of emotion on memory and map implications for educational settings. In addition to elucidating the memory-enhancing effects of emotion, neuroimaging findings extend our understanding of emotional influences on learning and memory processes; this knowledge may be useful for the design of effective educational curricula to provide a conducive learning environment for both traditional “live” learning in classrooms and “virtual” learning through online-based educational technologies. (shrink)

The purpose of cognitive models is to make predictive simulations of human behaviour, but this is often done at the aggregate level. Cranford, Gonzalez, Aggarwal, Cooney, Tambe, and Lebiere show that they can automatically customize a model to a particular individual on‐the‐fly, and use it to make specific predictions about their next actions, in the context of a particular cybersecurity game.

Human language is a salient example of a neurocognitive system that is specialized to process complex dependencies between sensory events distributed in time, yet how this system evolved and specialized remains unclear. Artificial Grammar Learning (AGL) studies have generated a wealth of insights into how human adults and infants process different types of sequencing dependencies of varying complexity. The AGL paradigm has also been adopted to examine the sequence processing abilities of nonhuman animals. We critically evaluate this growing literature in (...) species ranging from mammals (primates and rats) to birds (pigeons, songbirds, and parrots) considering also cross‐species comparisons. The findings are contrasted with seminal studies in human infants that motivated the work in nonhuman animals. This synopsis identifies advances in knowledge and where uncertainty remains regarding the various strategies that nonhuman animals can adopt for processing sequencing dependencies. The paucity of evidence in the few species studied to date and the need for follow‐up experiments indicate that we do not yet understand the limits of animal sequence processing capacities and thereby the evolutionary pattern. This vibrant, yet still budding, field of research carries substantial promise for advancing knowledge on animal abilities, cognitive substrates, and language evolution. (shrink)