The neural basis of cognitive development: a constructivist manifesto

How do minds emerge from developing brains? According to "neural constructivism," the representational features of cortex are built from the dynamic interaction between neural growth mechanisms and environmentally derived neural activity. Contrary to popular selectionist models that emphasize regressive mechanisms, the neurobiological evidence suggests that this growth is a progressive increase in the representational properties of cortex. The interaction between the environment and neural growth results in a flexible type of learning: "constructive learning" minimizes the need for prespecification in accordance with recent neurobiological evidence that the developing cerebral cortex is largely free of domain-specific structure. Instead, the representational properties of cortex are built by the nature of the problem domain confronting it. This uniquely powerful and general learning strategy undermines the central assumption of classical learnability theory, that the learning properties of a system can be deduced from a fixed computational architecture. Neural constructivism suggests that the evolutionary emergence of neocortex in mammals is a progression toward more flexible representational structures, in contrast to the popular view of cortical evolution as an increase in innate, specialized circuits. Human cortical postnatal development is also more extensive and protracted than generally supposed, suggesting that cortex has evolved so as to maximize the capacity of environmental structure to shape its structure and function through constructive learning.     

Generative connectionist networks and constructivist cognitive development

This article presents a novel computational framework for modeling cognitive development. The new modeling paradigm provides a language with which to compare and contrast radically different facets of children's knowledge. Concepts from the study of machine learning are used to explore the power of connectionist networks that construct their own architectures during learning. These so-called generative algorithms are shown to escape from Fodor's (1980) critique of Constructivist development. We describe one generative connectionist algorithm (cascade-correlation) in detail. We report on the successful use of the algorithm to model cognitive development on balance scale phenomena; seriation; the integration of velocity, time, and distance cues; prediction of effect sizes from magnitudes of causal potencies and effect resistances; and the acquisition of English personal pronouns. The article demonstrates that computer models are invaluable for illuminating otherwise obscure discussions.     

Family patterns leading to learning disability: A cognitive approach

Traditional treatment of the learning disabled child seeks to offer an individualized remediation. The authors offer as an alternative the innovative use of the family therapy modality for treatment of the learning dysfunction. This approaches the source of the learning dysfunction embedded in the faulty communication patterns within the family. The child has the opportunity to experience and more accurately comprehend the communication patterns, become more adept at interpretation of implicit meanings, and to transfer these developing skills to the formal learning situation.     

The internal morality of medicine: a constructivist approach

Synthese - Physicians frequently ask whether they should give patients what they want, usually when there are considerations pointing against doing so, such as medicine’s values and...     

A constructivist approach to supervision: Some preliminary thoughts

Supervision from a constructivist point of view is explored. Supervision processes with three different therapists are presented to exemplify this constructivist stance. In this approach the relation between supervisor and therapist is seen as similar to that between therapist and client. Thus, a “therapist-centered” approach for supervision is outlined, the main points of which are as follows: The main focus of a constructivist supervision is the therapist, supervision should be centered on the therapist's complaint, supervision should generate a learning context, the therapist and supervisor have different types of expertise, the supervising context should generate alternative views about the problem, and the supervision context should be reflexive.     

A new approach to the formulation and testing of learning models

It is argued that current attempts to model human learning behavior commonly fail on one of two counts: either the model assumptions are artificially restricted so as to permit the application of mathematical techniques in deriving their consequences, or else the required complex assumptions are imbedded in computer programs whose technical details obscure the theoretical content of the model. The first failing is characteristic of so-called mathematical models of learning, while the second is characteristic of computer simulation models. An approach to model building which avoids both these failings is presented under the title of a black-box theory of learning. This method permits the statement of assumptions of any desired complexity in a language which clearly exhibits their theoretical content.Section II of the paper is devoted to the problem of testing and comparing alternative learning theories. The policy advocated is to abandon attempts at hypothesis testing. It is argued that, in general, we not only lack sufficient data and sufficiently powerful techniques to test hypotheses, but that the truth of a model is not really the issue of basic interest. A given model may be true in the sense that on the basis of available evidence we cannot statistically reject it, but not interesting in the sense that it provides little information about the processes underlying behavior. Rather, we should accept or reject models on the basis of how much information they provide about the way in which subjects respond to environmental structure. This attitude toward model testing is made precise by introducing a formal measure of the information content of a model. Finally, it is argued that the statistical concept of degrees-of-freedom is misleading when used in the context of model testing and should be replaced by a measure of the information absorbed from the data in estimating parameters.I would like to express my indebtedness to Ernest W. Adams and Julian Feldman for their guidance and encouragement of the research reported here.Much of the research reported here was conducted at the University of California, Berkeley, and incorporated in a Ph.D. dissertation in Logic and the Methodology of Science [15]. The research was supported in part by the Computer Institute for Social Science Research, Michigan State University.     

A category theory approach to cognitive development

The category theory concept of a commutative diagram is used to construct a model of the way in which symbolic processes are applied to problem solving. The model provides for a relationship between symbolic processes and the problem which depends on structural isomorphism and consistency, but is independent of similarity between symbol elements and problem elements. It is then shown that several different levels of thought can be distinguished within the basic model. More information is needed to assign symbolic processes to a problem in a consistent way with higher-level thought processes than with lower-level processes. These information-processing requirements permit the approximate age of mastery of each level to be predicted, thereby offering an alternate theory of cognitive developmental stages. Two experiments designed to test the theory are reported.     

Motivation towards closure and cognitive processes: An individual differences approach

Two studies (N = 212) examined the relationships between elementary cognitive processes and individual differences in the need for cognitive closure. The results indicated that the need for closure is linked with certain cognitive deficits, specifically a restricted pool of cognitive resources allocated to a current activity. It was also found that these cognitive limitations tend to be compensated for by a particularly efficient process of information-selection from the environment. However, the selection process is costly, thus in a situation of drainage of cognitive resources its effectiveness also drops and the selection advantage of high (vs. low) need for closure individuals is eliminated.     

Differential impact of preschool models on development and early learning of inner-city children: a three-cohort study

Three different preschool models operating in an urban school district were identified through cluster analysis of teacher responses to the Pre-K Survey of Beliefs and Practices. The language, self-help, social, motor, and adaptive development, along with mastery of basic skills, of 721 4-year-olds randomly selected from these models were compared. Children in the child-initiated model demonstrated greater mastery of basic skills than did children in programs in which academics were emphasized and skills were taught. Children in the combination model did significantly poorer on all measures except self-help and development of social coping skills compared with children in either the child-initiated or academically directed models. Girls outperformed boys in all areas except gross motor development and play and leisure skills. Implications for educational policymakers are discussed.     

A response-time approach to comparing generalized rational and take-the-best models of decision making

The authors develop and test generalized versions of take-the-best (TTB) and rational (RAT) models of multiattribute paired-comparison inference. The generalized models make allowances for subjective attribute weighting, probabilistic orders of attribute inspection, and noisy decision making. A key new test involves a response-time (RT) approach. TTB predicts that RT is determined solely by the expected time required to locate the 1st discriminating attribute, whereas RAT predicts that RT is determined by the difference in summed evidence between the 2 alternatives. Critical test pairs are used that partially decouple these 2 factors. Under conditions in which ideal observer TTB and RAT strategies yield equivalent decisions, both the RT results and the estimated attribute weights suggest that the vast majority of subjects adopted the generalized TTB strategy. The RT approach is also validated in an experimental condition in which use of a RAT strategy is essentially forced upon subjects.     

A tutorial introduction to Bayesian models of cognitive development

We present an introduction to Bayesian inference as it is used in probabilistic models of cognitive development. Our goal is to provide an intuitive and accessible guide to the what, the how, and the why of the Bayesian approach: what sorts of problems and data the framework is most relevant for, and how and why it may be useful for developmentalists. We emphasize a qualitative understanding of Bayesian inference, but also include information about additional resources for those interested in the cognitive science applications, mathematical foundations, or machine learning details in more depth. In addition, we discuss some important interpretation issues that often arise when evaluating Bayesian models in cognitive science.     

Cumulative risk and early cognitive development: a comparison of statistical risk models

Although it is generally accepted that social risk factors predict delays in early cognitive and language development, there is less agreement about how to represent such associations statistically. Using data collected prospectively on 87 African American children during their first 4 years, this study examined 3 analytic methods for describing a child's level of social risk: (a) individual risk variables, (b) factor scores derived from those risk variables, and (c) a risk index computed by tallying the number of risk conditions present. Comparisons indicated that the individual-risk-variables approach provides better overall prediction of developmental outcomes at a particular age but is less useful in predicting developmental patterns. The risk-factor approach provides good prediction of developmental trajectories when sample sizes are moderate to large. Finally, the risk-index approach is useful for relating social risk to developmental patterns when a large number of risk variables are assessed with a small sample or when other constructs are of primary interest.     

Inducing cognitive development and learning: A review of short-term training experiments I. The organismic developmental approach

The author reviewed and interpreted the literature of experimental studies whose purposes were to determine rules of generation that transform a child's cognitive organization at one stage of development into that of the next, more advanced stage. The categories of the research methodology were consistent with the organismic-developmental approach, and the findings of the studies tended to support most of the hypotheses generated from this approach. Some unresolved theoretical and methodological issues were presented, and research strategies to shed light on these issues were proposed.     

A cognitive behaviorist approach to the study of animal behavior

Traditional psychological approaches to animal learning and behavior have involved either the atheoretical behaviorist approach proposed by B. F. Skinner (1938), in which input-output relations are described in response to environmental manipulations, or the theoretical behaviorist approach offered by C. L Hull (1943), in which associations mediated by several hypothetical constructs and intervening variables are formed between stimuli and responses. Recently, the application of a cognitive behaviorist approach to animal learning and behavior has been found to have considerable value as a research tool. This perspective has grown out of E. C. Tolman's cognitive approach to learning in which behavior is mediated by mechanisms that are not directly observable but can be inferred from the results of critical experiments. In the present article, the author presents several examples of the successful application of the cognitive behaviorist approach. In each case, the experiments have been designed to distinguish between more traditional mechanisms and those mediated by hypothesized internal representations. These examples were selected because the evidence suggests that some form of active cognitive organization is needed to account for the behavioral results.     

Probabilistic mental models: a Brunswikian theory of confidence

Research on people's confidence in their general knowledge has to date produced two fairly stable effects, many inconsistent results, and no comprehensive theory. We propose such a comprehensive framework, the theory of probabilistic mental models (PMM theory). The theory (a) explains both the overconfidence effect (mean confidence is higher than percentage of answers correct) and the hard-easy effect (overconfidence increases with item difficulty) reported in the literature and (b) predicts conditions under which both effects appear, disappear, or invert. In addition, (c) it predicts a new phenomenon, the confidence-frequency effect, a systematic difference between a judgment of confidence in a single event (i.e., that any given answer is correct) and a judgment of the frequency of correct answers in the long run. Two experiments are reported that support PMM theory by confirming these predictions, and several apparent anomalies reported in the literature are explained and integrated into the present framework.