3-004 - Rethinking the recipe for language growth: where quantity meets quality of input

Session Type: Paper Symposium

Integrative Statement

Children learn language in a sea of data -- words, referents, and pragmatic cues. Recent research has focused on understanding the statistical structure of children’s language learning environments. Methodological innovations – including sensory devices, data analysis and mining techniques, reaction time methods, and tracking of real-time changes to language and gestural inputs - offer new opportunities to study both quantity and quality of early language experience in finer detail. The capacity to collect and analyze large-scale and high-density data yields fresh insights into the structure of the input, its variability across learners, its relevance to learning outcomes, and most critically its relation to underlying learning mechanisms.

The central theme in this symposium is that the statistical structure of free-flowing interaction between children and parents in everyday activities influence individual learning outcomes, and links from input to outcome reveal new insights into language learning mechanisms. The first paper explores the real-time dynamics of language input at multiple timescales based on data from naturalistic daily routines. The second paper shows how micro-level sensory-motor behaviors in child-parent free-play predict later language outcomes. The third talk investigates experimentally how elaboration in child-directed speech promotes vocabulary learning. The fourth paper shows the fluency of social interactions between parents and children in relation to language growth.

Overall, this symposium will focus on linking both quantity and quality of language learning input to children’s learning outcomes in the real world, providing deeper insights into developmental processes in general and mechanisms of language learning in particular.

Sub Unit

• Language, Communication

Chair

• Chen Yu, Indiana University

Individual Presentations

• Temporal Features of Infants’ Real-Time Language Experiences in the Home Setting - Presenting Author: Catherine S Tamis-Lemonda, New York University; Yana Kuchirko, New York University; Rufan Luo, New York University; Huining Liu, New York University; Kelly Escobar, New York University; Jonna Knudsen, New York University

• Sensory-motor behaviors during child-parent toy play predict word learning - Presenting Author: Chen Yu, Indiana University; Linda B Smith, Indiana University; Sumarga H Suanda, Indiana University; Seth Foster, Indiana University; Kaitlin Fondren, Indiana University

• How ‘quality’ features of child-directed speech lead to faster understanding and facilitate children’s early word learning - Presenting Author: Anne Fernald, Stanford Univ; Adriana Weisleder, New York University

• Keeping the conversation going: The importance of fluency and connectedness for language learning - Presenting Author: Jessa Michele Reed, Temple University; Kathryn A Hirsh-Pasek, Temple University; Lauren B Adamson, Georgia State University; Roberta M Golinkoff, University of Delaware; Roger Bakeman, Georgia State University; Margaret Tresch Owen, Univ of Texas at Dallas