Infants have shown variable success in quantity comparison tasks, with infants of a given age sometimes successfully discriminating numerical differences at a 2:3 ratio but requiring 1:2 and even 1:4 ratios of change at other times. The current explanations for these variable results include the two-systems proposal--a theoretical framework that…

Recent studies show that both adults and young children possess powerful statistical learning capabilities to solve the word-to-world mapping problem. However, the underlying mechanisms that make statistical learning possible and powerful are not yet known. With the goal of providing new insights into this issue, the research reported in this…

Development in any domain is often characterized by increasingly abstract representations. Recent evidence in the domain of shape recognition provides one example; between 18 and 24 months children appear to build increasingly abstract representations of object shape [Smith, L. B. (2003). Learning to recognize objects. "Psychological…

This book presents a comprehensive and detailed theory of early human development based on the principles of dynamic systems theory. It raises fundamental questions about prevailing assumptions in the field and proposes a new theory of the development of cognition and action, unifying recent advances in dynamic systems theory with current research…

Used a modification of Akhtar, Carpenter, and Tomasello's (1996) task involving interpretation of novel nouns to test whether 18- to 28-month-olds' smart word learning derived from general attention and memory processes rather than knowledge about the communicative intents of others. Findings similar to those of Akhtar and colleagues suggest that…

Proposes an alternative account of the child's learning of nouns and adjectives that relies on properties of the semantic categories to be learned and of the word-learning task itself. In five experiments, a simple connectionist network was trained to label input objects in particular contexts; the network learned categories resembling nouns…