Longitudinal data collection to follow social network and language development dynamics at preschool
Sicheng Dai1,2, Hélène Bouchet3,4, Márton Karsai5
1Univ. Lyon, ENS de Lyon, Inria, CNRS, UCB Lyon 1, LIP UMR 5668, IXXI, F-69342, Lyon, France.
This study tracked 200 children in preschool for three years, observing how social interactions influence oral language development. The DyLNet dataset offers insights into child socialization and early language learning.
Area of Science:
- Developmental Psychology
- Linguistics
- Sociology
Background:
- Understanding the interplay between social environments and language acquisition in early childhood is crucial.
- Existing research often lacks detailed, real-world interaction data.
- Longitudinal studies are needed to capture developmental trajectories.
Purpose of the Study:
- To investigate the relationship between child socialization and oral language learning in a preschool setting.
- To provide a comprehensive dataset for analyzing social interaction patterns and language development.
- To facilitate research on the co-development of social and linguistic skills.
Main Methods:
- A large-scale, three-year longitudinal study at a French preschool.
- Utilized Radio Frequency Identification Wireless Proximity Sensors to record proximity interactions (child-adult, inter/intra-class).
- Collected parallel survey data on socio-demographics and linguistic skills.
Main Results:
- Collected ten weeks of cleaned, pre-processed interaction data over one school year.
- Acquired socio-demographic and language development data at the beginning and end of the period.
- Inferred real social interactions and differentiated between settings.
Conclusions:
- The DyLNet dataset offers a unique resource for studying the simultaneous development of language and social interactions in children.
- This data can advance research in developmental psychology, linguistics, and educational sciences.
- The findings can inform early childhood education strategies.
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