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Analogy and Abstraction
Author(s) -
Gentner Dedre,
Hoyos Christian
Publication year - 2017
Publication title -
topics in cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.191
H-Index - 56
eISSN - 1756-8765
pISSN - 1756-8757
DOI - 10.1111/tops.12278
Subject(s) - generalization , analogy , abstraction , analogical reasoning , computer science , concept learning , cognitive science , artificial intelligence , cognitive psychology , transfer of learning , domain (mathematical analysis) , psychology , machine learning , theoretical computer science , epistemology , mathematics , mathematical analysis , philosophy
A central question in human development is how young children gain knowledge so fast. We propose that analogical generalization drives much of this early learning and allows children to generate new abstractions from experience. In this paper, we review evidence for analogical generalization in both children and adults. We discuss how analogical processes interact with the child's changing knowledge base to predict the course of learning, from conservative to domain‐general understanding. This line of research leads to challenges to existing assumptions about learning. It shows that (a) it is not enough to consider the distribution of examples given to learners; one must consider the processes learners are applying; (b) contrary to the general assumption, maximizing variability is not always the best route for maximizing generalization and transfer.