The Development of Early Phonological Networks: An Analysis of Individual Longitudinal Vocabulary Growth

While much work has emphasized the role of the environment in language learning, research equally reports consistent effects of the child's knowledge, in particular, the words known to individual children, in steering further lexical development. Much of this work is based on cross-sectional data, assuming that the words typically known to children at n months predict the words typically known to children at n+x months. Given acknowledged variability in the number of words known to individual children at different ages, a more conclusive analysis of this issue requires examination of individual differences in the words learned by individual children across development, that is, using longitudinal data. In the current study, using longitudinal vocabulary data from children learning Norwegian, we ask whether the phonological connectivity of a word to words that the child already knows or words in the child's environment predicts the likelihood of the child learning that word across development. The results suggest that the early vocabulary grows predominantly in a rich-get-richer manner, where word learning is predicted by the connectivity of a word to already known words. However, word learning is, to a lesser extent, also influenced by the connectivity of a word to words in the child's linguistic environment. Our results highlight the promise of using longitudinal data to better understand the factors that influence vocabulary development.

Authors

Institutions

Publication Details

Journal
Cognitive Science
Published
2025-09-01
DOI
https://doi.org/10.1111/cogs.70109
Citations
3
Primary Topic
Language Development and Disorders
Type
article
Field-Weighted Citation Impact
10.33

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Development of Early Phonological Networks: An Analysis of Individual Longitudinal Vocabulary Growth

Michaela Vystrčilová, Laura Hansel, Alexander S. Ecker, Judith Kalinowski et al.
3 citations
Cognitive Science
Language Development and Disorders
10.33
article

The Development of Early Phonological Networks: An Analysis of Individual Longitudinal Vocabulary Growth

Michaela Vystrčilová, Laura Hansel, Alexander S. Ecker, Judith Kalinowski, Nivedita Mani
article en
3 citations

Abstract

While much work has emphasized the role of the environment in language learning, research equally reports consistent effects of the child's knowledge, in particular, the words known to individual children, in steering further lexical development. Much of this work is based on cross-sectional data, assuming that the words typically known to children at n months predict the words typically known to children at n+x months. Given acknowledged variability in the number of words known to individual children at different ages, a more conclusive analysis of this issue requires examination of individual differences in the words learned by individual children across development, that is, using longitudinal data. In the current study, using longitudinal vocabulary data from children learning Norwegian, we ask whether the phonological connectivity of a word to words that the child already knows or words in the child's environment predicts the likelihood of the child learning that word across development. The results suggest that the early vocabulary grows predominantly in a rich-get-richer manner, where word learning is predicted by the connectivity of a word to already known words. However, word learning is, to a lesser extent, also influenced by the connectivity of a word to words in the child's linguistic environment. Our results highlight the promise of using longitudinal data to better understand the factors that influence vocabulary development.

Cognitive ScienceVol. 49(9)
Max Planck Institute for Dynamics and Self-Organization (DE), Universitätsmedizin Göttingen (DE), Leibniz ScienceCampus Primate Cognition (DE), University of Göttingen (DE)
Deutsche Forschungsgemeinschaft, Leibniz-Gemeinschaft
Openalex Percentile: Top 2%
Language Development and Disorders
10.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.