This article offers a plausible domain-general explanation for why some concepts of processes are resistant to instructional remediation although other, apparently similar concepts are more easily understood. The explanation assumes that processes may differ in ontological ways: that some processes (such as the apparent flow in diffusion of dye in water) are emergent and other processes (such as the flow of blood in human circulation) are direct. Although precise definition of the two kinds of processes are probably impossible, attributes of direct and emergent processes are described that distinguish them in a domain-general way. Circulation and diffusion, which are used as examples of direct and emergent processes, are associated with different kinds of misconceptions. The claim is that stu-Do Not Copy dents ’ misconceptions for direct kinds of processes, such as blood circulation, are of the same ontological kind as the correct conception, suggesting that misconceptions of direct processes may be nonrobust. However, students ’ misconceptions of emergent processes are robust because they misinterpret emergent processes as a kind of commonsense direct processes. To correct such a misconception requires a re-representation or a conceptual shift across ontological kinds. Therefore, misconceptions of emergent processes are robust because such a shift requires that students know about the emergent kind and can overcome their (perhaps even innate) predisposition to conceive of all processes as a direct kind. Such a domain-general explanation suggests that teaching students the causal structure underlying emergent processes may enable them to recognize and understand a variety of emergent processes for which they have robust misconceptions, such as concepts of electricity, heat and temperature, and evolution. Correspondence and requests for reprints should be sent to Michelene T. H. Chi, Learning Research

To whom correspondence should be addressed. The study reported here tests a prediction that autism should occur more often in families of individuals whose occupation requires advanced folk physics but with no requirement of good folk psychology. Physics, engineering, and mathematics are paradigm examples of such occupations. Students in Cambridge University, studying one of these 3 subjects, were screened for cases of autism in their families. Relative to a control group of students studying literature, autism occurred significantly more often in families of students in the fields of physics, engineering, and mathematics. 2 Autism is considered to be the most severe of the childhood psychiatric disorders. It is strongly heritable (Bailey et al., 1995) and is diagnosed on the basis of abnormalities in social development, communication, and imagination (APA, 1994). First-degree relatives of children with autism are at raised risk not only of autism itself, but also of a lesser variant (or broader phenotype) of autism (Baron-Cohen & Hammer, 1997; Bolton et al., 1994). One model proposes that the broader phenotype might be characterised as involving deficits in ‘folk psychology ’ (social understanding) in the presence of intact or superior abilities in ‘folk physics ’ (understanding inanimate objects) (Baron-Cohen, in press). This study builds on the notion that cognition has a domain-specific structure (Barkow,

for assistance, and Nora Newcombe and Elliott Blass for advice and comments on the manuscript. Above all, I am grateful to Ariel Grace and Kristin Shutts for their unending support and after-hours labor on this project. Draft, 4/20/05. This paper has not yet been peer reviewed. Please do not copy or cite without author's permission. This report considers three prominent claims that boys and men have greater natural aptitude for high-level careers in mathematics and science. According to the first claim, males are more focused on objects and mechanical systems from the beginning of life. According to the second claim, males have a profile of spatial and numerical abilities that predisposes them to greater aptitude in mathematics. According to the third claim, males show greater variability in mathematical aptitude, yielding a preponderance of males at the upper end of the distribution of mathematical talent. Research on cognitive development in human infants and preschool children, and research on cognitive performance by students at all levels, provides evidence against these claims. Mathematical and scientific reasoning develop from a set of biologically based capacities that males and females share. From these capacities, men and women appear to develop equal talent for mathematics and science.

Explanation of why things happen is one of humans ’ most important cognitive operations. In everyday life, people are continually generating explanations of why other people behave the way they do, why they get sick, why computers or cars are not working properly, and of many other puzzling occurrences. More systematically, scientists develop theories to provide general explanations of physical phenomena such as why objects fall to earth, chemical phenomena such as why elements combine, biological phenomena such as why species evolve, medical phenomena such as why organisms develop diseases, and psychological phenomena such as why people sometimes make mental errors. This chapter reviews computational models of the cognitive processes that underlie these kinds of explanations of why events happen. It is not concerned with another sense of explanation that just means clarification, as when someone explains the U. S. constitution. The focus will be on scientific explanations, but more mundane examples will occasionally be used, on the grounds that the cognitive processes for explaining why events happen are much the same in everyday life and in science, although scientific explanations tend tobe more systematic and rigorous than everyday ones. In addition to providing a concise review of previous computational models of explanation, this chapter describes a new neural network model that shows how explanations can be performed by multimodal distributed representations.

Infants' developing causal expectations for the outcome of a simple tool-use event from ages 8 to 12 months were investigated. Causal expectations were studied by comparing infants' developing tool-use actions (i.e., as tool-use agents) with their developing perceptual reactions (i.e., as tool-use observers) to possible and impossible tool-use events. In Experiment 1, tool-use actions were studied by presenting infants, ages 8 and 12 months, with tool-use object-retrieval problems. In Experiment 2, a second age-matched sample of infants watched a comparable series of possible and impossible tool-use events in which a tool was used to retrieve a goalobject. Two core related findings were made. First, infants' causal action and causal perception develop in parallel. In both action and perception, supporting tool-use develops before surrounding tool-use. Second, infants' tool-use action develops before their causal perception of comparable tool-use events. The findings support the constru...

The concordance between performance and judgements of the causal effectiveness of an instrumental action suggests that such actions are mediated by causal knowledge. Although causal learning exhibits many associative phenomena—blocking, inhibitory or preventative learning, and super-learning—judgements of the causal status of a cue can be changed retrospectively as a result of learning episodes that do not directly involve the cue. In order to explain retrospective revaluation, a modi®ed associative theory is described in which the learning processes for retrieved cue representations are the opposite to those for presented cues, and this theory is evaluated by studies of the role of within-compound associations in retrospective revaluation and blocking. However, this modi®ed theory only applies when the within-compound association represents a contiguous rather than a causal cue relationship. Causal learning and representation is a fundamental form of cognition, if not the fundamental form. Without the capacity to learn about and represent the causal relationships between our actions and their consequences, the mind would be radically disconnected from the world. However detailed and rich our knowledge, however sophisticated and complex our inferences and planning, cognition would be impotent if our thoughts could not be

In this chapter, I outline and defend a version of concept empiricism. The theory has

Acknowledgements: SBC, JH, and RG were supported by the MRC during the period of this work. SW was supported by the McDonnell-Pew Trust. JL was supported by the Isaac Newton Trust. We are also grateful for support from the Shirley Foundation. Parts

Before the age of 4 months, infants make inductive inferences about the motions of physical objects. Developmental psychologists have provided verbal accounts of the knowledge that supports these inferences, but often these accounts focus on categorical rather than probabilistic principles. We propose that infant object perception is guided in part by probabilistic principles like persistence: things tend to remain the same, and when they change they do so gradually. To illustrate this idea we develop an ideal observer model that incorporates probabilistic principles of rigidity and inertia. Like previous researchers, we suggest that rigid motions are expected from an early age, but we challenge the previous claim that the inertia principle is relatively slow to develop [1]. We support these arguments by modeling several experiments from the developmental literature. Over the past few decades, ingenious experiments [1, 2] have suggested that infants rely on systematic expectations about physical objects when interpreting visual scenes. Looking time studies suggest, for example, that infants expect objects to follow continuous trajectories through time and

Abstract not found