Global Secrets of Early Language Learning
A new study, involving an extensive international sample of 1,001 children across 43 languages, offers groundbreaking insights into how infants and toddlers learn language.
The research utilized day-long audio recordings and machine learning analysis. Key findings indicate that age, clinical factors, and the amount of adult speech children hear are the primary drivers of language development, challenging previous beliefs about the influence of gender, multilingualism, and socioeconomic.
This comprehensive study provides a more nuanced understanding of language acquisition in early childhood.
Key Facts:
- The study analyzed language development in children from 12 countries, speaking 43 languages.
- Major predictors of language development include age, clinical factors, and exposure to adult speech, not gender or socioeconomic status.
- For every 100 adult vocalizations heard per hour, children produced 27 more vocalizations, with this effect increasing with age.
Elika Bergelson, associate professor of psychology at Harvard University, studies how infants and toddlers learn language from the world around them. The developmental psychologist specifically strives to parse the various theories that account for the onset and eventual mastery of language comprehension and production.
Bergelson’s latest paper, published this month in the Proceedings of the National Academy of Sciences, represents a more global approach to developing and testing such theories.
Written with Alejandrina Cristia at the École normale supérieure, PSL University and 11 others, the paper is based on an extremely large sample of two- to 48-month olds. Day-long audio recordings captured the babbling and baby talk of 1,001 children representing 12 countries and 43 languages. Analysis was completed with the help of machine learning.
Results show that the main predictors of language development are age, clinical factors such as prematurity or dyslexia, and how much speech children receive from the world around them. In contrast to previous research, no effects were found related to gender, multilingualism, or socioeconomics.
The study was able to simultaneously consider many variables that are usually looked at separately while also considering how big their effects were.
“Notably, it wasn’t just child factors like age or risk for language delay that mattered, but a key environmental factor too: how much speech children heard from adults,” Bergelson said.
“For every 100 adult vocalizations children heard per hour, they produced 27 more vocalizations themselves, and this effect grew with age.”
The work also touches on well-worn critiques of low-income parents and caregivers.
“There’s been much debate and discussion in the literature in recent years about how socioeconomic status does or doesn’t link to language input and language output,” noted Bergelson.
“We looked in many, many, many different ways … In no form did we ever find evidence that moms with more education had kids who produced more speech in these tens of thousands of hours of recordings from daily life.”
Funding: Financial support for the study was provided by the National Science Foundation, National Institutes of Health, and the National Endowment for the Humanities, among others.
Abstract
Everyday language input and production in 1,001 children from six continents
Language is a universal human ability, acquired readily by young children, who otherwise struggle with many basics of survival. And yet, language ability is variable across individuals. Naturalistic and experimental observations suggest that children’s linguistic skills vary with factors like socioeconomic status and children’s gender.
But which factors really influence children’s day-to-day language use?
Here, we leverage speech technology in a big-data approach to report on a unique cross-cultural and diverse data set: >2,500 d-long, child-centered audio-recordings of 1,001 2- to 48-mo-olds from 12 countries spanning six continents across urban, farmer-forager, and subsistence-farming contexts.
As expected, age and language-relevant clinical risks and diagnoses predicted how much speech (and speech-like vocalization) children produced. Critically, so too did adult talk in children’s environments: Children who heard more talk from adults produced more speech.
In contrast to previous conclusions based on more limited sampling methods and a different set of language proxies, socioeconomic status (operationalized as maternal education) was not significantly associated with children’s productions over the first 4 y of life, and neither were gender or multilingualism.
These findings from large-scale naturalistic data advance our understanding of which factors are robust predictors of variability in the speech behaviors of young learners in a wide range of everyday contexts.
