Competition Between Object Topology and Surface Features in Children’s Extension of Novel Nouns

Bibliographic Data

ID22157696
AuthorsPraveen Kenderla (0000-0001-7908-1146, Boston University), Sung-Ho Kim (0000-0002-2808-2293, Ewha Womans University), Melissa M Kibbe (0000-0002-9088-2523, Boston University)
Year2023
Volume7
Pages93-110
Publication date2023-04-05
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueOpen MIND (JOURNAL)
Journal identifiersISSN: 2470-2986 • E-ISSN: 2470-2986
PublisherMIT Press (PUBLISHER • US)
DOI10.1162/opmi_a_00073
PMID37416072
OpenAlexW4327908850
LanguageEN
Citations received4
References cited55

Objects’ topological properties play a central role in object perception, superseding objects’ surface features in object representation and tracking from early in development. We asked about the role of objects’ topological properties in children’s generalization of novel labels to objects. We adapted the classic name generalization task of Landau et al. (1988, 1992). In three experiments, we showed children (n = 151; 3–8-year-olds) a novel object (the standard) and gave the object a novel label. We then showed children three potential target objects and asked children which of the objects shared the same label as the standard. In Experiment 1, the standard object either did or did not contain a hole, and we asked whether children would extend the standard’s label to a target object that shared either metric shape or topology with the standard. Experiment 2 served as a control condition for Experiment 1. In Experiment 3, we pitted topology against another surface feature, color. We found that objects’ topology competed with objects’ surface features (both shape and color) in children’s extension of labels to novel objects. We discuss possible implications for our understanding of the inductive potential of objects’ topologies for making inferences about objects’ categories across early development

Biology · Combinatorics · Noun · Categorization, perception, and language · Child and Animal Learning Development · Computer Science · Hearing Impairment and Communication · Mathematics · Psychology · Artificial Intelligence · Ecology

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