Two experiments tested whether 4-year-old children extract and use geometric information in simple maps without task instruction or feedback. Children saw maps depicting an arrangement of three containers and were asked to place an object into a container designated on the map. In Experiment 1, one of the three locations on the map and the array was distinct and therefore served as a landmark; in Experiment 2, only angle, distance and sense information specified the target container. Children in both experiments used information for distance and angle, but not sense, showing signature error patterns found in adults. Children thus show early, spontaneously developing abilities to detect geometric correspondences between three-dimensional layouts and two-dimensional maps, and they use these correspondences to guide navigation. These findings begin to chart the nature and limits of the use of core geometry in a uniquely human, symbolic task.

For many centuries, philosophers and scientists have pondered the origins and nature of human intuitions about the properties of points, lines, and figures on the Euclidean plane, with most hypothesizing that a system of Euclidean concepts either is innate or is assembled by general learning processes. Recent research from cognitive and developmental psychology, cognitive anthropology, animal cognition, and cognitive neuroscience suggests a different view. Knowledge of geometry may be founded on at least two distinct, evolutionarily ancient, core cognitive systems for representing the shapes of large-scale, navigable surface layouts and of small-scale, movable forms and objects. Each of these systems applies to some but not all perceptible arrays and captures some but not all of the three fundamental Euclidean relationships of distance (or length), angle, and direction (or sense). Like natural number (Carey, 2009), Euclidean geometry may be constructed through the productive combination of representations from these core systems, through the use of uniquely human symbolic systems.

We present a qualitative, hierarchical approach for representing 2D space. Inspired by research on human vision, our approach supports computational models of visual problem-solving. A key idea is that hierarchical representations of space are constructed bottom-up; i.e., low-level representations support the construction of high-level representations. However, during problem-solving, representations are attended to top-down; the highest-level, most abstract representation contains the least detail, and thus is an ideal starting point for understanding the problem. We show how our representation scheme has been implemented in several successful models of visual problem-solving. 1

SUMMARY—Amid ongoing public speculation about the reasons for sex differences in careers in science and mathematics, we present a consensus statement that is based on the best available scientific evidence. Sex differences in science and math achievement and ability are smaller for the mid-range of the abilities distribution than they are for those with the highest levels of achievement and ability. Males are more variable on most measures of quantitative and visuospatial ability, which necessarily results in more males at both high- and low-ability extremes; the reasons why males are often more variable remain elusive. Successful careers in math and science require many types of cognitive abilities. Females tend to excel in verbal abilities, with large differences between females and males found when assessments include writing

Abstract. Cognitive simulation offers a means of more closely examining the reasons for behavior found in psychological studies. This paper describes a computational model of the visual oddity task, in which individuals are shown six images and asked to pick the one that doesn’t belong. We show that the model can match performance by participants from two cultures: Americans and the Mundurukú. We use ablation experiments on the model to provide evidence as to what factors might help explain differences in performance by the members of the two cultures.

Abstract: Research on human infants, adult nonhuman primates, and children and adults in diverse cultures provides converging evidence for four systems at the foundations of human knowledge. These systems are domain specific and serve to represent both entities in the perceptible world (inanimate manipulable objects and animate agents) and entities that are more abstract (numbers and geometrical forms). Human cognition may be based, as well, on a fifth system for representing social partners and for categorizing the social world into groups. Research on infants and children may contribute both to understanding of these systems and to attempts to overcome misconceptions that they may foster.

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Understanding how high-level visual properties are computed is a central problem in perception. Oddity tasks, where participants must identify a stimulus that is distinct in some way from others in an array, provide a method for determining what features are being computed. We describe a computational model of oddity detection that models data by Dehaene et al. (2006) on perception of simple geometric shapes. It starts with virtually the same input stimuli as given to human subjects, and automatically constructs representations. Oddity detection is accomplished by analogical processing, using SME and SEQL. The simulation is able to perform the task, and moreover, provides some insight as to what makes one problem harder than another.

Santiz and family, CELALI and the Casa de Cultura, Tenejapa, Chiapas. This research

Key w o r d s: cognitive development, geometry, visual shape, perception Vol. 23- n.3 (213-248)- 2009 Development of Sensitivity to Geometry