What’s new? Children prefer novelty in referent selection
نویسندگان
چکیده
منابع مشابه
Rapid Survey of Wasting and Stunting in Children: Whats New, Whats Old and Whats the Buzz?
Nationwide Rapid Survey on Children (RSoC), conducted by the Ministry of Women and Child Development and UNICEF in 2013-14 showed a marked improvement in the status of the child malnutrition over the third National Family Health Survey (NFHS-3) that was conducted in 2005-06. Despite some impressive gains in the anthropometric indicators of malnutrition, the absolute levels remain high, and of c...
متن کاملThe role of vocabulary knowledge and novelty biases in word learning: Exploring referent selection and retention in 18- to 24- month-old children and associative models
Approved: ____________________________________ Thesis Supervisor ____________________________________ Title and Department ____________________________________ Date
متن کاملChildren’s referent selection and word learning
It is well-established that toddlers can correctly select a novel referent from an ambiguous array in response to a novel label. There is also a growing consensus that robust word learning requires repeated label-object encounters. However, the effect of the context in which a novel object is encountered is less wellunderstood. We present two embodied neural network replications of recent empir...
متن کاملDo children prefer mentalistic descriptions?
Against a long tradition of childhood realism (Piaget, 1929), A. S. Lillard and J. H. Flavell (1990) found that 3-year-olds prefer to characterize people by their mental states (beliefs, desires, emotions) than by their visible behaviors. In this exploratory study, we extend this finding to a new cohort of 3-year-olds, examine how these preferences change from 3-4 years, and explore relationshi...
متن کاملFeature Selection and Novelty in Computational Aesthetics
An approach for exploring novelty in expression-based evolutionary art systems is presented. The framework is composed of a feature extractor, a classifier, an evolutionary engine and a supervisor. The evolutionary engine exploits shortcomings of the classifier, generating misclassified instances. These instances update the training set and the classifier is re-trained. This iterative process f...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Cognition
سال: 2011
ISSN: 0010-0277
DOI: 10.1016/j.cognition.2010.10.015