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Domain‐Specific Principles Affect Learning and Transfer in Children
Author(s) -
Brown Ann L.
Publication year - 1990
Publication title -
cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
DOI - 10.1207/s15516709cog1401_6
Subject(s) - generalization , transfer of learning , cognitive science , context (archaeology) , cognitive psychology , psychology , object (grammar) , perception , affect (linguistics) , analogy , transfer of training , concept learning , causality (physics) , computer science , artificial intelligence , developmental psychology , epistemology , communication , neuroscience , paleontology , philosophy , physics , quantum mechanics , biology
In this paper I discuss the curious lack of contact between developmental psychologists studying the principles of early learning and those concentrating an later learning in children, where predispositions to learn certain types of concepts are less readily discussed. Instead, there is tacit agreement that learning and transfer mechanisms are content‐independent and age‐dependent. I argue here that one cannot study learning and transfer in a vacuum and that children's ability to learn is intimately dependent on what they are required to learn and the context in which they must learn it. Specifically, I argue that children learn and transfer readily, even in traditional laboratory settings, if they are required to extend their knowledge about causal mechanisms that they already understand. This point is illustrated in a series of studies with children from 1 to 3 years of age learning about simple mechanisms of physical causality (pushing‐pulling, wetting, cutting, etc.). In addition, I document children's difficulty learning about causally impossible events, such as pulling with strings that do not appear to make contact with the object they are pulling. Even young children transfer on the basis of deep structural principles rather than perceptual features when they have access to the requisite domain‐specific knowledge. I argue that a search for causal explanations is the basis of broad understanding, of wide patterns of generalization, and of flexible transfer and creative inferential projections—in sum, the essential elements of meaningful learning.

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