domains as rareiied as a cardiologistRi7;s knowledge of arrhythmia to those as commonplace as everyday folk psychology. Domains can vary from the highly concrete causally rich relations in a naive mechanics of physical objects to the highly abstract noncausal relations of mathematics or natural language syntax. Lumping together all of these different sorts of domains so as to have similar effects on cognitive development is likely to be misleading and un· informative. In this chapter, I consider some distinctions and their (...) implications.. (shrink)
y arguments about the intrinsically interactional nature of development (e.g. Johnston, 1988; Lehrman, 1953; Lemeri983O te learning takes place and an environment to be learned. The use of the term Cngnz`rii*e Psyc/10/0g_v.· An Inrerrzational Review. Edited by Michael W. Eysenck @1990 by John Wiley & Sons Ld..
We investigate how people use causal knowledge to design interventions to affect the outcomes of causal systems. We propose that in addition to using content or mechanism knowledge to evaluate the effectiveness of interventions, people are also influenced by the abstract structural properties of a causal system. In particular, we investigated two factors that influence whether people tend to intervene proximally (on the immediate cause of an outcome of interest) or distally (on the root cause of a chain leading to (...) the outcome). We presented people with causal chains describing a variety of real-world and artificial causal systems and asked them where they would intervene to affect the outcome. In Experiment 1, participants who were asked to choose the best long-term intervention intervened more distally than participants asked to choose the best short-term intervention. In Experiment 2, participants presented with a branching structure in which there were two distinct causal pathways from the root cause to the outcome were more likely to intervene on the root cause than participants presented with only one of the pathways. Our findings demonstrate two ways in which people integrate content knowledge and knowledge of a system’s causal structure to design effective interventions. (shrink)
The present studies investigated children’s and adults’ intuitive beliefs about the physical nature of essences. Adults and children (ranging in age from 6 to 10 years old) were asked to reason about two different ways of determining an unknown object’s category: taking a tiny internal sample from any part of the object (distributed view of essence), or taking a sample from one specific region (localized view of essence). Results from three studies indicated that adults strongly endorsed the distributed view, and (...) children showed a developmental shift from a localized to distributed view with increasing age. These results suggest that even children go beyond mere placeholder notions of essence, committing to conceptual frameworks of how essences might be physically instantiated. (shrink)
The ability to learn the direction of causal relations is critical for understanding and acting in the world. We investigated how children learn causal directionality in situations in which the states of variables are temporally dependent (i.e., autocorrelated). In Experiment 1, children learned about causal direction by comparing the states of one variable before versus after an intervention on another variable. In Experiment 2, children reliably inferred causal directionality merely from observing how two variables change over time; they interpreted Y (...) changing without a change in X as evidence that Y does not influence X. Both of these strategies make sense if one believes the variables to be temporally dependent. We discuss the implications of these results for interpreting previous findings. More broadly, given that many real-world environments are characterized by temporal dependency, these results suggest strategies that children may use to learn the causal structure of their environments. (shrink)
If folk science means individuals having well worked out mechanistic theories of the workings of the world, then it is not feasible. Laypeople’s explanatory understandings are remarkably coarse, full of gaps, and often full of inconsistencies. Even worse, most people overestimate their own understandings. Yet recent views suggest that formal scientists may not be so different. In spite of these limitations, science somehow works and its success offers hope for the feasibility of folk science as well. The success of science (...) arises from the ways in which scientists learn to leverage understandings in other minds and to outsource explanatory work through sophisticated methods of deference and simplification of complex systems. Three studies ask whether analogous processes might be present not only in laypeople but also in young children and thereby form a foundation for supplementing explanatory understandings almost from the start of our first attempts to make sense of the world. (shrink)
The article examines the question of how learning multiple tasks interacts with neural architectures and the flow of information through those architectures. It approaches the question by using the idealization of an artificial neural network where it is possible to ask more precise questions about the effects of modular versus nonmodular architectures as well as the effects of sequential versus simultaneous learning of tasks. A prior work has demonstrated a clear advantage of modular architectures when the two tasks must be (...) learned at the same time from the start, but this advantage may disappear when one task is first learned to a criterion before the second task is undertaken. Indeed, in some cases of sequential learning, nonmodular networks achieve success levels comparable to those of modular networks. In particular, if a nonmodular network is to learn two tasks of different difficulty and the more difficult task is presented first and learned to a criterion, then the network will learn the second, easier one without permanent degradation of the first one. In contrast, if the easier task is learned first, a nonmodular task may perform significantly less well than a modular one. It seems that the reason for this difference has to do with the fact that the sequential presentation of the more difficult task first minimizes interference between the two tasks. More broadly, the studies summarized in this article seem to imply that no single learning architecture is optimal for all situations. (shrink)
The more carefully we look, the more impressive the repertoire of infant concepts seems to be. Across a wide range of tasks, infants seem to be using concepts corresponding to surprisingly high-level and abstract categories and relations. It is tempting to try to explain these abilities in terms of a core capacity in spatial cognition that emerges very early in development and then gets extended beyond reasoning about direct spatial arrays and events. Although such a spatial cognitive capacity may indeed (...) form one valuable basis for later cognitive growth, it seems unlikely that it can be the sole or even primary explanation for either the impressive conceptual capacities of infants or the ways in which concepts develop. (shrink)
Rogers & McClelland's (R&M's) précis represents an important effort to address key issues in concepts and categorization, but few of the simulations deliver what is promised. We argue that the models are seriously underconstrained, importantly incomplete, and psychologically implausible; more broadly, R&M dwell too heavily on the apparent successes without comparable concern for limitations already noted in the literature.
What would it be like to have never learned English, but instead only to know Hopi, Mandarin Chinese, or American Sign Language? Would that change the way you think? Imagine entirely losing your language, as the result of stroke or trauma. You are aphasic, unable to speak or listen, read or write. What would your thoughts now be like? As the most extreme case, imagine having been raised without any language at all, as a wild child. What—if anything—would it be (...) like to be such a person? Could you be smart; could you reminisce about the past, plan the future? (shrink)
Bloom makes a strong case that word meaning acquisition does not require a dedicated word learning system. This conclusion, however, does not argue against a dedicated language acquisition system for syntax, morphology, and aspects of semantics. Critical questions are raised as to why word meaning should be so different from other aspects of language in the course of acquisition.
We introduce two notions–the shadows and the shallows of explanation–in opening up explanation to broader, interdisciplinary investigation. The shadows of explanation refer to past philosophical efforts to provide either a conceptual analysis of explanation or in some other way to pinpoint the essence of explanation. The shallows of explanation refer to the phenomenon of having surprisingly limited everyday, individual cognitive abilities when it comes to explanation. Explanations are ubiquitous, but they typically are not accompanied by the depth that we might, (...) prima facie, expect. We explain the existence of the shadows and shallows of explanation in terms of there being a theoretical abyss between explanation and richer, theoretical structures that are often attributed to people. We offer an account of the shallows, in particular, both in terms of shorn-down, internal, mental machinery, and in terms of an enriched, public symbolic environment, relative to the currently dominant ways of thinking about cognition and the world. (shrink)