The role of central conceptual structures in the development of children's thought Article

Case, R, Okamoto, Y, Griffin, S et al. (1996). The role of central conceptual structures in the development of children's thought . MONOGRAPHS OF THE SOCIETY FOR RESEARCH IN CHILD DEVELOPMENT, 61(1-2), 10.2307/1166077

cited authors

  • Case, R; Okamoto, Y; Griffin, S; McKeough, A; Bleiker, C; Henderson, B; Stephenson, KM

abstract

  • In this Monograph, we present a new theory of children's conceptual development and the empirical research on which that theory is based. The main construct in the theory is the notion of a central conceptual structure. These structures are denned as networks of semantic nodes and relations that represent children's core knowledge in a domain and that can be applied to the full range of tasks that the domain entails. Major transformations are hypothesized to take place in these structures as children enter each new stage of their development. Once formed, the new structures are hypothesized to exert a powerful influence on all subsequent knowledge acquisition. The process by which they exert this effect is believed to be a dynamic one, in which general conceptual insights and more specific task understandings become reciprocally coupled, each exerting a bootstrapping effect on the other. In the first chapter, the general theoretical framework that underlies this conception is spelled out in broad strokes and compared to other contemporary views of conceptual development. In subsequent chapters, more detailed models of children's central conceptual structures are presented for three different domains: number, space, and social interaction. These models are then tested using a mixture of new and previously designed cognitive tasks, which are administered to children from four different age groups (4, 6, 8, and 10 years), three different social classes (high, medium, and low), and four different countries (the United States, Canada, Japan, and China). The results of a 6-year program of instructional research are also summarized and used to clarify and refine the theory. Analytic tools that are employed include computer simulation, item analysis, and linked growth curve analysis. Statistical techniques include latent structure analysis, factor analysis, and Guttman scaling. Problems with previous versions of the theory and implications of the present version are discussed in the final chapter.

publication date

  • January 1, 1996

Digital Object Identifier (DOI)

volume

  • 61

issue

  • 1-2