Two standard epistemological accounts are conflated in Dienes & Perner's account of knowledge, and this conflation requires the rejection of their four conditions of knowledge. Because their four metarepresentations applied to the explicit-implicit distinction are paired with these conditions, it follows by modus tollens that if the latter are inadequate, then so are the former. Quite simply, their account misses the link between true reasoning and knowledge.

Il rapporto tra lo spazio e la formazione del pensiero sollecita riflessioni pedagogiche in dialogo con il mondo dell'architettura. Nelle scienze umane è oggi sentita una "svolta spaziale" che induce la ricerca a riconsiderare il rapporto tra spazio e pedagogia. Una delle possibili declinazioni di tale rapporto riguarda la progettazione di scuole come ambienti di apprendimento.

May implicit and explicit collaboration influence text comprehension and spatial recognition interaction? Visuospatial representation implies implicit, visual and spatial processing of actions and concepts at different levels of awareness. Implicit learning is linked to unaware, nonverbal and prototypical processing, especially in the early stages of development when it is prevailing. Spatial processing is studied as knowledge prototypes , conceptual and mind maps . According to the hypothesis that text comprehension and spatial recognition connecting processes may also be implicit, this paper (...) analyzes the possibility to identify and to define implicit non verbal criteria for organizing concepts into spatial representation. The focus of the research question is if prototypical processing (mainly implicit, but also explicit) criteria of conceptual organization may be model based. According to Thinking Prototypes Theory , explicit knowledge could be supported by implicit models of basic processing. On implicit side, conceptual development could be the resultant of the increasing complexity of prototypical implicit models interaction during individual lifespan, as in conceptual change research explicit conceptual development may be dependent on correlation . Unlike Theory Theory in Thinking Prototypes Theory implicit processing may collaborate with explicit knowledge without transforming itself from implicit to explicit. Prototypical implicit processing is considered as an entanglement of basic functions operating synergically in a complex way. Prototypical implicit processing units may be classified as far as they concern different basic thinking operations ( add , chain , each , compare , focus and link ). The experimental design was developed with primary school students in Naples. (shrink)

This paper presents a computational model of the way humans inductively identify and aggregate concepts from the low-level stimuli they are exposed to. Based on the idea that humans tend to select the simplest structures, it implements a dynamic hierarchical chunking mechanism in which the decision whether to create a new chunk is based on an information-theoretic criterion, the Minimum Description Length (MDL) principle. We present theoretical justifications for this approach together with results of an experiment in which participants, exposed (...) to meaningless symbols, have been implicitly encouraged to create high-level concepts by grouping them. Results show that the designed model, called hereafter MDLChunker, makes precise quantitative predictions both on the kind of chunks created by the participants and also on the moment at which these creations occur. They suggest that the simplicity principle used to design MDLChunker is particularly efficient to model chunking mechanisms. The main interest of this model over existing ones is that it does not require any adjustable parameter. (shrink)

The distinction between rules and similarity is central to our understanding of much of cognitive psychology. Two aspects of existing research have motivated the present work. First, in different cognitive psychology areas we typically see different conceptions of rules and similarity; for example, rules in language appear to be of a different kind compared to rules in categorization. Second, rules processes are typically modeled as separate from similarity ones; for example, in a learning experiment, rules and similarity influences would be (...) described on the basis of separate models. In the present article, I assume that the rules versus similarity distinction can be understood in the same way in learning, reasoning, categorization, and language, and that a unified model for rules and similarity is appropriate. A rules process is considered to be a similarity one where only a single or a small subset of an object's properties are involved. Hence, rules and overall similarity operations are extremes in a single continuum of similarity operations. It is argued that this viewpoint allows adequate coverage of theory and empirical findings in learning, reasoning, categorization, and language, and also a reassessment of the objectives in research on rules versus similarity. Key Words: categorization; cognitive explanation; language; learning; reasoning; rules; similarity. (shrink)

The financial crash of 2008 following the selling of fictitious derivatives was a crisis of both rationality and values whose aftermath has thrown the legitimation of deregulated markets, and governments, into question. This paper critiques the Becker metaphor of human capital and submits that human value is central to and the fulcrum of both economic and social values. It illustrates that Hume and Adam Smith directly countered the Hobbesian hypothesis that human nature is based only on self-interest, distinguishes market values (...) from social values, explicit from implicit values and parallels Sen in adopting an ordinal ranking of what people value rather than a search for cardinality. It draws on cognitive psychology, neural research, revealed preference theory and a principle of implicit verification. It also outlines implications for what Adam Smith centrally valued as concern for the welfare of the whole of society. (shrink)

The connectionist vehicle theory of phenomenal experience in the target article identifies consciousness with the brain’s explicit representation of information in the form of stable patterns of neural activity. Commentators raise concerns about both the conceptual and empirical adequacy of this proposal. On the former front they worry about our reliance on vehicles, on representation, on stable patterns of activity, and on our identity claim. On the latter front their concerns range from the general plausibility of a vehicle theory to (...) our specific attempts to deal with the dissociation studies. We address these concerns, and then finish by considering whether the vehicle theory we have defended has a coherent story to tell about the active, unified subject to whom conscious experiences belong. (shrink)

People are unable to report how they decide whether to move backwards or forwards to catch a ball. When asked to imagine how their angle of elevation of gaze would change when they caught a ball, most people are unable to describe what happens although their interception strategy is based on controlling changes in this angle. Just after catching a ball, many people are unable to recognise a description of how their angle of gaze changed during the catch. Some people (...) confidently choose incorrect descriptions that would guarantee failure of interception demonstrating unconscious knowledge co-existing with systematically different conscious beliefs. Where simple solutions to important evolutionary problems exist, unconscious perception needs to be impervious to conscious beliefs. (shrink)

O'Brien & Opie do not address the question of the psychotherapeutic role of unconscious representational states such as beliefs. A dilemma is proposed: if they accept the legitimacy of such states then they should modify what they say about dissociation, and if they do not, they owe us an account of why.

This paper presents a skill learning model CLARION. Different from existing models of mostly high-level skill learning that use a top-down approach (that is, turning declarative knowledge into procedural knowledge through practice), we adopt a bottom-up approach toward low-level skill learning, where procedural knowledge develops first and declarative knowledge develops later. Our model is formed by integrating connectionist, reinforcement, and symbolic learning methods to perform on-line reactive learning. It adopts a two-level dual-representation framework (Sun, 1995), with a combination of localist (...) and distributed representation. We compare the model with human data in a minefield navigation task, demonstrating some match between the model and human data in several respects. (shrink)

O'Brien & Opie's (O&O's) theory demands a view of unconscious processing that is incompatible with virtually all current PDP models of neural activity. Relative to the alternatives, the theory is closer to an AI than a parallel distributed processing (PDP) perspective, and its treatment of phenomenology is ad hoc. It raises at least one important question: Could features of network relaxation be the “switch” that turns an unconscious into a conscious network?

We used several cue–target SOAs and three different degrees of cue predictability , to investigate the role of awareness of cue–target predictability on cueing effects. A group of participants received instructions about the informative value of the cue, while another group did not receive such instructions. Participants were able to extract the predictive value of a spatially peripheral cue and use it to orient attention, whether or not specific instructions about the predictive value of the cue were given, and no (...) matter their ability to correctly report it in a post-test questionnaire. In the non-predictive block, bad estimators who received no instructions showed regular cueing effects, while good estimators exhibited smaller and non-significant facilitatory effects at the short SOA and an absence of significant IOR at longer SOAs. However, for the instructions group, the pattern of results reversed. (shrink)

Philosophers and scientists have across the ages been amazed about the fact that development and learning often lead to not just a merely incremental and gradual change in the learner but sometimes to a result that is strikingly different from the learner’s original situation: amazed, but at times also worried. Both philosophical and cognitive neuroscientific insights suggest that experts appear to perform ‘different’ tasks compared to beginners who behave in a similar way. These philosophical and empirical perspectives give some insight (...) into what happens when a novice is transitioning to a stage of expertise. Generally, this implies that increased skill and expertise support better results and a more flexible performance, in part because these allow an agent to withdraw part of her attention and other cognitive resources from the tasks involved, enabling her to devote those resources to supporting, or completely different, tasks. As positive as these developments appear, these changes have also raised concerns. The main concern is whether gaining expertise is like raising a ‘cognitive monster’ which escapes the individual’s conscious control and influences her actions with undesirable automatisms. If so, we should ask ourselves whether experts are capable of taming this monster. The answer appears initially not to be positive. Indeed, it has been noted that since it is difficult for experts to withhold automatic responses this can lead to inflexibility or performance that is only optimal under certain conditions, because it is limited to a specific domain, often context-dependent, biased and inflexible. In what follows, I will consider this challenge of protecting expertise and harnessing this brittleness from philosophical and cognitive neuroscientific perspectives. Taking into account that action is in general determined by a multitude of factors, with learning and development affecting how these factors exert their influence, a philosophical question is how this complex and dynamic process can be explained and subsequently, how controlling it might be understood. First, though, I will present the issue at hand more closely: should we appreciate expertise if it is similar to growing a ‘cognitive monster’? Second, I will introduce the framework of a “Sculpted Space of Actions” (Keestra, 2014), which I developed in order to explain how the challenge of selecting an adequate option for action is facilitated by expertise as it helps to constrain the space of potential action options. Subsequently, the question is raised of how such a Sculpted Space of Actions influences an expert’s engagement with specific situations, like teaching students in a classroom setting. It will be argued that a well prepared expert—teacher or otherwise— is not only able to rely upon her routines but will at the same time be more perceptive and attentive to unforeseen events and actions, according to the recent cognitive neuroscientific theory of Predictive Processing. Integrating the theory of Predictive Processing with the Sculpted Space of Actions framework, I conclude that expertise contributes to adaptive and flexible responses to specific contexts, yet only if it is associated with explicit planning and articulation of situation specific intentions—the latter effectively putting the cognitive monster at rest for a while. (shrink)

The previous papers raise a number of issues. How should we develop task typologies both to separate judgement from related cognitive tasks and to classify tasks within the judgement domain? Are there grounds for selecting between models of judgement when empirical tests fail to do so? What techniques can be used to find out more about the cognitive processes underlying judgement behaviour? I discuss these issues and give a brief assessment of the current state of play in this rapidly changing (...) area. (shrink)

This paper investigates the conscious status of both the knowledge that an item is legal and the knowledge of why it is legal in sequence learning. We compared ability to control use of knowledge with stated awareness of the knowledge as measures of the conscious status of knowledge. Experiment 1 showed that when people could control use of judgment knowledge they were indeed conscious of having that knowledge according to their own statements. Yet Experiment 2 showed that people could exert (...) such control over the use of judgment knowledge when claiming they had no structural knowledge: i.e. conscious judgment knowledge could be based on unconscious structural knowledge. Further implicit learning research should be clear over whether judgment or structural knowledge is claimed to be unconscious as the two dissociate in sequence learning. (shrink)

The implicit-explicit distinction is applied to knowledge representations. Knowledge is taken to be an attitude towards a proposition which is true. The proposition itself predicates a property to some entity. A number of ways in which knowledge can be implicit or explicit emerge. If a higher aspect is known explicitly then each lower one must also be known explicitly. This partial hierarchy reduces the number of ways in which knowledge can be explicit. In the most important type of implicit knowledge, (...) representations merely reflect the property of objects or events without predicating them of any particular entity The dearest cases of explicit knowledge of a fact are representations of one's own attitude of knowing that fact. These distinctions are discussed in their relationship to similar distinctions such as procedural-declarative, conscious unconscious, verbalizable-nonverbalizable, direct-indirect tests, and automatic voluntary control. This is followed by an outline of how these distinctions can be used to integrate and relate the often divergent uses of the implicit-explicit distinction in different research areas. We illustrate this for visual perception, memory, cognitive development, and artificial grammar learning. (shrink)

Evidence from aphasia is considered that leads to a distinction between abstract and concrete thought processes and hence for a distinction between rules and similarity. It is argued that perceptual classification is inherently a rule-following procedure and these rules are unable to be followed when a patient has difficulty with name comprehension and retrieval.

The constructivist notion that features are purely functional is incompatible with the classical computational metaphor of mind. I suggest that the discontent expressed by Schyns, Goldstone and Thibaut about fixed-features theories of categorization reflects the growing impact of connectionism, and show how their perspective is similar to recent research on implicit learning, consciousness, and development. A hard problem remains, however: How to bridge the gap between subsymbolic and symbolic cognition.

Electronic Mail: [email protected] Abstract Stability of activation, while it may be necessary for information to become available to consciousness, is not sufficient to produce phenomenal experience. We suggest that consciousness involves access to information and that access makes information symbolic. From this perspective, implicit representations exist, and are best thought of as sub-symbolic. Crucially, such representations can be causally efficacious in the absence of consciousness.

Consciousness remains a mystery—“a phenomenon that people do not know how to think about—yet” (Dennett, , p. 21). Here, I consider how the connectionist perspective on information processing may help us progress toward the goal of understanding the computational principles through which conscious and unconscious processing differ. I begin by delineating the conceptual challenges associated with classical approaches to cognition insofar as understanding unconscious information processing is concerned, and to highlight several contrasting computational principles that are constitutive of the connectionist (...) approach. This leads me to suggest that conscious and unconscious processing are fundamentally connected, that is, rooted in the very same computational principles. I further develop a perspective according to which the brain continuously and unconsciously learns to redescribe its own activity itself based on constant interaction with itself, with the world, and with other minds. The outcome of such interactions is the emergence of internal models that are metacognitive in nature and that function so as to make it possible for an agent to develop a (limited, implicit, practical) understanding of itself. In this light, plasticity and learning are constitutive of what makes us conscious, for it is in virtue of our own experiences with ourselves and with other people that our mental life acquires its subjective character. The connectionist framework continues to be uniquely positioned in the Cognitive Sciences to address the challenge of identifying what one could call the “computational correlates of consciousness” (Mathis & Mozer, ) because it makes it possible to focus on the mechanisms through which information processing takes place. (shrink)

Several forms of dietary learning have been identified in humans. These include flavor–flavor learning, flavor–postingestive learning , and learned satiety. Generally, learning is thought to occur in the absence of contingency or demand awareness. However, a review of the literature suggests that this conclusion may be premature because measures of awareness lack the rigor that is found in studies of other kinds of human learning. If associations do configure outside awareness then this should be regarded as a rare instance of (...) automatic learning. Conversely, if awareness is important, then successful learning may be governed by an individual’s beliefs and predilection to attend to stimulus relationships. For researchers of dietary learning this could be critical because it might explain why learning paradigms have a reputation for being unreliable. Since most food preferences are learned, asking questions about awareness can also tell us something fundamental about everyday dietary control. (shrink)

Contemporary studies in unconscious cognition are essentially founded on dissociation, i.e., on how it dissociates with respect to conscious mental processes and representations. This is claimed to be in so many and diverse ways that one is often lost in dissociation. In order to reduce this state of confusion we here carry out two major tasks: based on the central distinction between cognitive processes and representations, we identify and isolate the main dissociation paradigms; we then critically analyze their key tenets (...) and reported findings. (shrink)

The concept of tacit knowledge is widely used in social sciences to refer to all those knowledge that cannot be codified and have to be transferred by personal contacts. All this literature has been affected by two kind of biases : (1) the interest has been focused more on the result (tacit knowledge) than on the process (implicit learning); (2) tacit knowledge has been somehow reduced to physical skills or know-how; other possible forms of tacit knowledge have been neglected. These (...) two biases seem interconnected one with each other. A greater consideration of the role and relevance of implicit learning allows us to consider tacit knowledge as something more than pure physical skills or know how. This is the first step in order to develop more detailed categorisation of the different forms that tacit knowledge can assume. (shrink)

This paper describes how meta-cognitive processes (i.e., the self monitoring and regulating of cognitive processes) may be captured within a cognitive architecture Clarion. Some currently popular cognitive architectures lack sufficiently complex built-in meta-cognitive mechanisms. However, a sufficiently complex meta-cognitive mechanism is important, in that it is an essential part of cognition and without it, human cognition may not function properly. We contend that such a meta-cognitive mechanism should be an integral part of a cognitive architecture. Thus such a mechanism has (...) been developed within the Clarion cognitive architecture. The paper demonstrates how human data of two meta-cognitive experiments are simulated using Clarion. The simulations show that the meta-cognitive processes represented by the experimental data (and beyond) can be adequately captured within the Clarion framework. (shrink)

The models used in social simulation to date have mostly been very simplistic cognitively, with little attention paid to the details of individual cognition. This work proposes a more cognitively realistic approach to social simulation. It begins with a model created by Gilbert (1997) for capturing the growth of academic science. Gilbert’s model, which was equation-based, is replaced here by an agent-based model, with the cognitive architecture CLARION providing greater cognitive realism. Using this cognitive agent model, results comparable to previous (...) simulations and to human data are obtained. It is found that while different cognitive settings may affect the aggregate number of scientific articles produced, they do not generally lead to different distributions of number of articles per author. The paper concludes with a discussion of the correspondence between our model and the constructivist view of academic science. It is argued that using more cognitively realistic models in simulations may lead to novel insights. (shrink)

While the study of implicit learning is nothing new, the field as a whole has come to embody — over the last decade or so — ongoing questioning about three of the most fundamental debates in the cognitive sciences: The nature of consciousness, the nature of mental representation (in particular the difficult issue of abstraction), and the role of experience in shaping the cognitive system. Our main goal in this chapter is to offer a framework that attempts to integrate current (...) thinking about these three issues in a way that specifically links consciousness with adaptation and learning. Our assumptions about this relationship are rooted in further assumptions about the nature of processing and of representation in cognitive systems. When considered together, we believe that these assumptions offer a new perspective on the relationships between conscious and unconscious processing and on the function of consciousness in cognitive systems. (shrink)

This paper traces missing links in the history of economic thought. In outlining Hume's concept of 'the reflexive mind' it shows that this opened frontiers between philosophy and psychology which Bertrand Russell denied and which logical positivism in philosophy and positive economics displaced. It relates this to Hume's influence not only on Smith, but also on Schopenhauer and the later Wittgenstein, with parallels in Gestalt psychology and recent findings from neural research and cognitive psychology. It critiques Kant's reaction to Hume's (...) claim that one may assume but cannot prove cause and effect and how Samuelson's Foundations of Economic Analysis has been Kantian but wrong in claims for axioms that are universal truths. It illustrates how Samuelson's presumption that language and mathematics are 'identical' was as mistaken as the logical atomism of Russell and the early Wittgenstein, relates this to Kleinian splitting, denial and projective identification and suggests that recovery of greater realism in economics needs to regain links with such philosophy and psychology. (shrink)

How can we explain the intentional nature of an expert’s actions, performed without immediate and conscious control, relying instead on automatic cognitive processes? How can we account for the differences and similarities with a novice’s performance of the same actions? Can a naturalist explanation of intentional expert action be in line with a philosophical concept of intentional action? Answering these and related questions in a positive sense, this dissertation develops a three-step argument. Part I considers different methods of explanations in (...) cognitive neuroscience (Bennett & Hacker’s philosophical, conceptual analysis; Marr’s three levels of explanation; Neural Correlates of Consciousness research; mechanistic explanation), defending ‘mechanistic explanation’ as a method that provides the necessary tools for integrating interdisciplinary insights into human action. Furthermore, a dynamic, explanatory mechanism allows the assessment of the impact of learning and development on expert action in a valuable way that other methods don’t. Part II continues by scrutinizing several cognitive neuroscientific theories of learning and development (neuroconstructivism; dual-processing theories; simulation theory; extended mind/cognition hypothesis), arguing for the complex interactions between different types of processing and different action representations involved in expert action performances. Moreover, according to our discussion of a particular ‘simulation theory’ these interactions can be influenced in several ways with the use of language, allowing an agent to configure a specific action representation for performance at a later stage. The results of Parts I and II are then applied in Part III to a parallel discussion of philosophical analyses of intentional action (discussing i.a. Frankfurt, Bratman, Pacherie and Ricoeur) and cognitive neuroscientific insights in it. Both approaches are found to converge in emphasizing the importance for an expert to develop stable patterns of actions that comply maximally not only with his intentions, but also with his motor expertise and with situational conditions. Consequently, his actions – automatic, or not – rely on this ‘sculpted space of actions’. (shrink)

In: E. Vargios (ed.), Educational Psychology Research Focus, pp.1-26. Nova Science Publishers, Hauppauge, NY. 2007.