The paper examines constraints and preferences employed by people in learning decision rules from preclassified examples. Results from four experiments with human subjects were analyzed and compared with artificial intelligence (AI) inductive learning programs. The results showed the people's rule inductions tended to emphasize category validity (probability of some property, given a category) more than cue validity (probability that an entity is a member of a category given that it has some property) to a greater extent than did the AI (...) programs. Although the relative proportions of different rule types (e.g., conjunctive vs. disjunctive) changed across experiments, a single process model provided a good account of the data from each study. These observations are used to argue for describing constraints in terms of processes embodied in models rather than in terms of products or outputs. Thus AI induction programs become candidate psychological process models and results from inductive learning experiments can suggest new algorithms. More generally, the results show that human inductive generalizations tend toward greater specificity than would be expected if conceptual simplicity were the key constraint on inductions. This bias toward specificity may be due to the fact that this criterion both maximizes inferences that may be drawn from category membership and protects rule induction systems from developing over‐generalizations. (shrink)

The present paper analyzes the self‐generated explanations (from talk‐aloud protocols) that “Good” and “Poor” students produce while studying worked‐out examples of mechanics problems, and their subsequent reliance on examples during problem solving. We find that “Good” students learn with understanding: They generate many explanations which refine and expand the conditions for the action parts of the example solutions, and relate these actions to principles in the text. These self‐explanations are guided by accurate monitoring of their own understanding and misunderstanding. Such (...) learning results in example‐independent knowledge and in a better understanding of the principles presented in the text. “Poor” students do not generate sufficient self‐explanations, monitor their learning inaccurately, and subsequently rely heavily on examples. We then discuss the role of self‐explanations in facilitating problem solving, as well as the adequacy of current AI models of explanation‐based learning to account for these psychological findings. (shrink)

This first volume contains discussions of the brain, methods for analyzing behavior, thought, consciousness, attention, association, time, and memory.

Reviews evidence which suggests that there may be little or no direct introspective access to higher order cognitive processes. Ss are sometimes unaware of the existence of a stimulus that importantly influenced a response, unaware of the existence of the response, and unaware that the stimulus has affected the response. It is proposed that when people attempt to report on their cognitive processes, that is, on the processes mediating the effects of a stimulus on a response, they do not do (...) so on the basis of any true introspection. Instead, their reports are based on a priori, implicit causal theories, or judgments about the extent to which a particular stimulus is a plausible cause of a given response. This suggests that though people may not be able to observe directly their cognitive processes, they will sometimes be able to report accurately about them. Accurate reports will occur when influential stimuli are salient and are plausible causes of the responses they produce, and will not occur when stimuli are not salient or are not plausible causes. (shrink)

We are reviewing and summarizing evidence for the processes of acquisition of information outside of conscious awareness (processing information about covariations, nonconscious indirect and interactive inferences, self-perpetuation of procedural knowledge). A considerable amount of data indicates that as compared to consciously controlled cognition, the nonconscious information-acquisition processes are not only much faster but also structurally more sophisticated in the sense that they are capable of efficient processing of multidimensional and interactive relations between variables. Those mechanisms of nonconscious acquisition of information (...) provide a major channel for the development of procedural knowledge which is indispensable for such important aspects of cognitive functioning as encoding and interpretation of stimuli and the triggering emotional reactions. (shrink)

Tested the 2-process theory of detection, search, and attention presented by the current authors in a series of experiments. The studies demonstrate the qualitative difference between 2 modes of information processing: automatic detection and controlled search; trace the course of the learning of automatic detection, of categories, and of automatic-attention responses; and show the dependence of automatic detection on attending responses and demonstrate how such responses interrupt controlled processing and interfere with the focusing of attention. The learning of categories is (...) shown to improve controlled search performance. A general framework for human information processing is proposed. The framework emphasizes the roles of automatic and controlled processing. The theory is compared to and contrasted with extant models of search and attention. (shrink)

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models. (shrink)

Linking the process of rational decision making to emotions, an award-winning scientist who has done extensive research with brain-damaged patients notes the dependence of thought processes on feelings and the body's survival-oriented regulators. 50,000 first printing.

In Concepts, Kinds, and Cognitive Development, Frank C. Keil provides a coherent account of how concepts and word meanings develop in children, adding to our understanding of the representational nature of concepts and word meanings at all ages. Keil argues that it is impossible to adequately understand the nature of conceptual representation without also considering the issue of learning. Weaving together issues in cognitive development, philosophy, and cognitive psychology, he reconciles numerous theories, backed by empirical evidence from nominal kinds studies, (...) natural-kinds studies, and studies of fundamental categorical distinctions. He shows that all this evidence, when put together, leads to a better understanding of semantic and conceptual development. The book opens with an analysis of the problems of modeling qualitative changes in conceptual development, investigating how concepts of natural kinds, nominal kinds, and artifacts evolve. The studies on nominal kinds document a powerful and unambiguous developmental pattern indicating a shift from a reliance on global tabulations of characteristic features to what appears to be a small set of defining ones. The studies on natural kinds document an analogous shift toward a core theory instead of simple definition. Both sets of studies are strongly supported by cross cultural data. While these patterns seem to suggest that the young child organizes concepts according to characteristic features, Keil argues that there is a framework of conceptual categories and causal beliefs that enables even very young children to understand kinds at a deeper, theoretically guided, level. This account suggests a new way of understanding qualitative change and carries strong implications for how concepts are represented at any point in development. A Bradford Book. (shrink)

Subjects exposed to strings of letters generated by a finite state grammar can later classify grammatical and nongrammatical test strings, even though they cannot adequately say what the rules of the grammar are (e.g., Reber, 1989). The MINERVA 2 (Hintzman, 1986) and Medin and Schaffer (1978) memory‐array models and a number of connectionist outoassociator models are tested against experimental data by deriving mainly parameter‐free predictions from the models of the rank order of classification difficulty of test strings. The importance of (...) different assumptions regarding the coding of features (How should the absence of a feature be coded? Should single letters or digrams be coded?), the learning rule used (Hebb rule vs. delta rule), and the connectivity (Should features be predicted only by previous features in the string, or by all features simultaneously?) is investigated by determining the performance of the models with and without each assumption. Only one class of connectionist model (the simultaneous delta rule) passes all the tests. It is shown that this class of model can be regarded by abstracting a set of representative but incomplete rules of the grammar. (shrink)

A number of ways of taxonomizing human learning have been proposed. We examine the evidence for one such proposal, namely, that there exist independent explicit and implicit learning systems. This combines two further distinctions, (1) between learning that takes place with versus without concurrent awareness, and (2) between learning that involves the encoding of instances (or fragments) versus the induction of abstract rules or hypotheses. Implicit learning is assumed to involve unconscious rule learning. We examine the evidence for implicit learning (...) derived from subliminal learning, conditioning, artificial grammar learning, instrumental learning, and reaction times in sequence learning. We conclude that unconscious learning has not been satisfactorily established in any of these areas. The assumption that learning in some of these tasks (e.g., artificial grammar learning) is predominantly based on rule abstraction is questionable. When subjects cannot report the rules that govern stimulus selection, this is often because their knowledge consists of instances or fragments of the training stimuli rather than rules. In contrast to the distinction between conscious and unconscious learning, the distinction between instance and rule learning is a sound and meaningful way of taxonomizing human learning. We discuss various computational models of these two forms of learning. (shrink)

Complete URL to this document: http://srsc.ulb.ac.be/axcWWW/93-Principles.html.

I examine the phenomenon of implicit learning, the process by which knowledge about the rule-governed complexities of the stimulus environment is acquired independently of conscious attempts to do so. Our research with the two seemingly disparate experimental paradigms of synthetic grammar learning and probability learning, is reviewed and integrated with other approaches to the general problem of unconscious cognition. The conclusions reached are as follows: Implicit learning produces a tacit knowledge base that is abstract and representative of the structure of (...) the environment; such knowledge is optimally acquired independently of conscious efforts to learn; and it can be used implicitly to solve problems and make accurate decisions about novel stimulus circumstances. Various epistemological issues and related problems such as intuition, neuroclinical disorders of learning and memory, and the relationship of evolutionary processes to cognitive science are also discussed. (shrink)

A number of ways of taxonomizing human learning have been proposed. We examine the evidence for one such proposal, namely, that there exist independent explicit and implicit learning systems. This combines two further distinctions, between learning that takes place with versus without concurrent awareness, and between learning that involves the encoding of instances versus the induction of abstract rules or hypotheses. Implicit learning is assumed to involve unconscious rule learning. We examine the evidence for implicit learning derived from subliminal learning, (...) conditioning, artificial grammar learning, instrumental learning, and reaction times in sequence learning. We conclude that unconscious learning has not been satisfactorily established in any of these areas. The assumption that learning in some of these tasks is predominantly based on rule abstraction is questionable. When subjects cannot report the “implicitly learned” rules that govern stimulus selection, this is often because their knowledge consists of instances or fragments of the training stimuli rather than rules. In contrast to the distinction between conscious and unconscious learning, the distinction between instance and rule learning is a sound and meaningful way of taxonomizing human learning. We discuss various computational models of these two forms of learning. (shrink)

This article examines the anatomy and circuitry of skills that, like reading, calculating, recognizing, or remembering, are common abilities of humans. While the anatomical areas active are unique to each skill there are features common to all tasks. For example, all skills produce activation of a small number of widely separated neural areas that appear necessary to perform the task. These neural areas relate to internal codes that may not be observed by any external behavior nor be reportable by the (...) performer. There is considerable plasticity to the performance of skills. Task components can be given priority through attention, which serves to increase activation of the relevant brain areas. Attention can also cause reactivation of sensory areas driven by input, but usually only after a delay. The threshold for activation for any area may be temporarily reduced by prior activation . Skill components requiring attention tend to cause interference resulting in the dual tasks effects and unified focus of attention described in many cognitive studies. Practice may change the size or number of brain areas involved and alter the pathways used by the skill. By combining cognitive and anatomical analyses, a more general picture of the nature of skill emerges. (shrink)

Je lui ai associÉ un court extrait d'une revue de questions portant sur le même thème. Implicit memory is revealed when previous experiences facilitate perf on a task that does not require conscious or intentional recollection of those expces. Explicit memory is revealed when perf on a task requires conscious recolelction of previous expces. Il s'agit de defs descriptives qui n'impliquent pas l'existence de deux systs de mÉmo sÉparÉs. Historiquement Descartes est le premier ˆ faire mention de phÉnomènes de mÉmo (...) implicites, Leibniz, Maine de Biran, Bergson en ont Également parlÉ. Korsakoff (1889) avec ses travaux sur les amnÉsiques montre qu'ils sont capables d'utiliser de l'info qu'ils ont acquises dans des Épisodes rÉcents sans pour autant manifester le moindre souvenir de l'Épisode. L'interprÉtation de ces phÉnomènes Était alors que ça renvoyait ˆ des traces en mÉmoire trop tÉnues pour accèder jusqu'au champ de la conscience. Cette interprÉtation va pouvoir être ÉcartÉe par les travaux rÉcents. Thorndike a Également conduit un nbre important de travaux sur MI. Les trauvaux un peu plus rÉcents ont montrÉ qu'un apprentissage antÉrieur pouvait faciliter une perfce sans qu'il y ait ref explicite à l'Épisode d'apprentissage. On a montrÉ aussi l'effet de stimuli subliminaux, qui en tant que tels ne peuvent pas être rappelÉs consciemment, mais qui influencent la conduite ou les jugts ultÉrieurs. Par ex, la prÉsentation de formes sur des temps très courts qui excluent la possibilitÉ d'une perception consciente influence significativement lechoix de formes dans une pÉreuve ultÉrieure de choix forcÉs où les sjts doivent indiquer la forme qu'il prÉfère entre deux. Ils choisissent prÉfÉrentiellement celles qui leur ont ÉtÉ prÉsentÉes de manière subliminale. De même Bargh et al. ont montrÉ que des sjts soumis de manière subliminale ˆ des mots hostiles portent ultÉrieurement des jugts plus nÉgatifs sur une personne target. Il ya Également eu des travaux sur l'apprsge ou le condt without awareness en particulier apprsge implicite de règles de grammaire (ie le sjt peut construire de nouvelles phrases conformes ˆ la syntaxe de celles qui lui ont ÉtÉ prÉsentÉes sans pour autant petre capables d'noncer les règles de grammaire qu'il utilise) Rem: N'est ce pas un pbe de typemÉtacognition??? Enfin, tous les travaux sur le priming sont des elts en faveur de MI: Facilitation in the processing of a stimulus as a function of a recent encounter with the same stimulus. Type de perfce sur lesquels les effets de priming ont ÉtÉ dÉmontrÉs: -T‰ches de dÉcision lexicale: Le sjt doit dire si la cha"ne de caractères qu'on lui prÉsente est un mot ou pas: Le temps de latence est beaucoup plus court si la cha"ne a dÉjˆ ÉtÉ prÉsentÉe une première fois. -Mesures de temps d'identification de mots en rpÉsentation tachitoscopiques -ComplÉmentation de mots: les sjts ont tendance ˆ complÉter pour crÉer les mots qui leur ont ÉtÉ prÉsentÉs antÉrieurement. L'intÉrêt pour le paradigme de priming se retouve chez les gens qui s'intÉressent ˆ: -reconnaissance de mots et organisation lexicale. les effets de priming permettent de faire des hyps sur l'accès lexical et la reprÉsentation. -M. Épisodique: travux sur les amnÉsiques qui ne se souviennent pas qu'on vient de leur prÉsenter des mots mais qui manifestent une mÉmoire implicite lorsqu'on leur fait faire de la complÉmentation de mots. DISSOCIATION ENTRE M.I. ET M EXPLICITE 1-Si de nombreux travaux montrent que la M explicite est influencÉe par le travail d'Élaboration (profondeur de traitement) en jeu pendant la première phase d'Étude des stimuli, il semble que la MI ne le soit pas. 2-Le changt de modalitÉ (par ex auditif -> visuel) entre la phase d'Étude et la phase de test provoque une attÉnuation importante de l'effet de priming si le test est un test de MI mais pas si c'est un test de ME. 3-Les effets de primings persistent assez largement sur plusieurs jours ce qui n'est pas le cas des perfces ˆ une Épreuve de reconnaissance. 4-Les perfces sur des tests de MI ne semblent pas influencÉes par des manipulations d'interfÉrences proactives ou rÉtroactives dont on sait qu'elles influencent les perfces en ME. 5-Absce de corrÉlation entre perfces ˆ des tests de reconnaissance et perfces ˆ une Épreuve de complÉmentation de mots. SIMILARITES ENTRE PRIMING ET REMEMBERING 1- A certaines conditions les durÉes de rÉtention on des effets parallèles sur les effets de priming et les mesures de ME (REm: en partie contradictoire avec 3 ci dessus) 2-La manipulation du contexte de la liste lors de la phase d'Étude affecte ˆ la fois les perfces en reconnaissance et en identification de mots. 3- ME et MI sont influencÉes par des associations nouvellement acquises entre des paires de mots non reliÉes (Rem: contradictoires avec 4 ci dessus ??) 4- Rem: Le contraire de 1 du pt "dissociation" !!!! dans une manip particulière 5-Johnston et al. ont montrÉ que des mots identifÉs plus rapidement Étaient plus svt jugÉs comme 'old' dans une t‰che de reconnaissance que les mots identifiÉs plus lentement. Il n'est pas exclu que les phÉnomènes que l'on interprètent comme relevant de MI soient parfois de la ME involontaire cad des cas o les cues fournis dans le test conduisent ˆ un souvenir involontaire mais totalement conscient. LES INTERPRETATIONS THEORIQUES DE MI 1-Les effets de priming sur des test de MI sont attribuables ˆ l'activation temporaires de reprÉsentations ou structures de K prÉ-existantes . Cette activation est supposÉe avoir lieu de manière automatique, indÉpendamment des processus d'Élaboration nÉcessaires pour Établir de nouvelles traces Épisodiques. 2- les difÉrences entre ME et MI sont dues ˆ la nature et aux relations entre les processus d'encodage et de rÉcupÉration. Une version de cette approche est celle qui s'appuie sur la distinction entre processus dirigÉs par les donnÉes et processus dirigÉs par les concepts. Ces derniers reflètent des activitÉs initiÉes par le sjt comme l'Élaboration, l'organisation et la reconstruction, c'est sur ce type de processus que reposerait la ME alors que la MI reposerait sur des processus data-driven. 3-ME et MI renvoient ˆ des systs sous jacents diffÉrents. Pour Cohen & Squire (1984), la ME est supportÉe par une M DECLARATIVE , syst qui est en jeu dans la formation de nouvelles reprÉsentations. La MI repose sur un syst PROCEDURAL dans lequel la M se manifeste par des modifications on line de procÉdures ou opÉrations de traitement. Le syst de M Épisodique est vu comme la base pour le souvenir explicite d'evts rÉcents tandis que la M sÉmantique est responsable des perfces sur des tests de MI. Chacune de ces approches est conforme ˆ certaines des donnÉes recueillies mais pas ˆ d'autres. (shrink)

Implicit and explicit memory tasks are interpreted within a traditional memory theory that distinguishes associations between different classes of memory units . Associations from specific sensory features to logogens are strengthened by perceptual experiences, leading to specific perceptual priming. Associations among concepts are strengthened by use, leading to specific conceptual priming. Activating associations from concepts to logogens leads to semantic and associative priming. Item presentation also establishes a new association from it to a representation of the personal context, comprising an (...) “episodic memory.” Such contextual associations play a major role in explicit memory tasks such as recall or recognition. A critical assumption of the theory is that presentation of a given item strengthens its sensory and contextual associations independently; this permits the theory to explain various dissociations of implicit and explicit memory measures. Furthermore, by assuming that brain-injured patients with global amnesia have a selective deficit in establishing novel associations to the context, the theory can explain their deficits in explicit memory along side their intact implicit memory. (shrink)

_role, especially in learning, and through devising hybrid neural network models that (in a qualitative manner) approxi-_ _mate characteristics of human consciousness. In doing so, the paper examines explicit and implicit learning in a variety_ _of psychological experiments and delineates the conscious/unconscious distinction in terms of the two types of learning_ _and their respective products. The distinctions are captured in a two-level action-based model C_larion_. Some funda-_ _mental theoretical issues are also clari?ed with the help of the model. Comparisons with (...) existing models of conscious-_. (shrink)

We investigated the impact of attention during encoding on later retrieval. During study, participants read some words aloud and named the print color of other words aloud . Then one of two memory tests was administered. The explicit test—recognition—required conscious recollection of whether a word was studied. Previously read words were recognized more accurately than were previously color named words. This contrasted sharply with performance on the implicit test—repetition priming in lexical decision. Here, words that were color named during study (...) showed priming equivalent to words that were read during study; both were responded to faster than unstudied words. Thus, an attentional manipulation during study had a strong effect on an explicit test of memory, but almost no effect on an implicit test. Focal attention during study is crucial for remembering consciously but not necessarily for remembering without awareness. (shrink)

Research on expert‐novice differences has mainly focused on how experts solve familiar problems. We know far less about the skills and knowledge used by experts when they are confronted with novel problems within their area of expertise. This article discusses a study in which verbal protocols were taken from subjects of various expertise designing an experiment in an area with which they were unfamiliar. The results showed that even when domain knowledge is lacking, experts solve a novel problem within their (...) area of expertise by dividing the problem into a number of subproblems that are solved in a specified order. The lack of domain knowledge is compensated for by using abstract knowledge structures and domain‐specific heuristic strategies. However, the quality of their solutions is considerably lower than the quality attained by experts who were familiar with the type of problem to be solved. The results suggest that when experts are confronted with novel problems as compared with familiar problems, their form of reasoning remains intact, but the content of their reasoning suffers due to lack of domain knowledge. (shrink)

Made-Up Minds addresses fundamental questions of learning and concept invention by means of an innovative computer program that is based on the cognitive ...