Work

Statistical Word Learning is a Continuous Process: Evidence from the Human Simulation Paradigm.

Year: 2015

Type: conference-paper

Abstract: In the word-learning domain, both adults and young children are able to find the correct referent of a word from highly ambiguous contexts that involve many words and objects by computing distributional statistics across the co-occurrences of words and referents at multiple naming moments (Yu & Smith, 2007; Smith & Yu, 2008). However, there is still debate regarding how learners accumulate distributional information to learn object labels in natural learning environments, and what underlying learning mechanism learners are most likely to adopt. Using the Human Simulation Paradigm (Gillette, Gleitman, Gleitman & Lederer, 1999), we found that participants' learning performance gradually improved and that their ability to remember and carry over partial knowledge from past learning instances facilitated subsequent learning. These results support the statistical learning model that word learning is a continuous process.

Source: PubMed

Authors: Yayun Zhang, Daniel Yurovsky, Chen Yu

Institutions: Indiana University Bloomington, Indiana University, Stanford University

Language: English

Topic: Language Development and Disorders

Subfield: Developmental and Educational Psychology

Field: Psychology

Domain: Social Sciences

SDG: Quality education

Open Access status: green

Funder: Eunice Kennedy Shriver National Institute of Child Health and Human Development

Award: Sensorimotor Dynamics of Parent-Child Interactions Build Word Learning Skills