The Influence of Adult Input on Children's Early Word Learning:A Case Study of A Mandarin-Speaking Child

Children's early vocabulary development is not linear.At the outset,word learning is very slow.However,by approximately 19 months of age,children's vocabulary rapidly expands,entering the phase of the "word spurt". The phenomenon of breaking word learning's bottleneck can be interpreted by several theories,such as constraint theories which emphasize innate cognitive biases,socialpragmatic theories emphasizing the role of social and linguistic environments,and associationistic views involving computations of the co-occurrence between words and their referents in naturalistic speech.However,these theories cannot account by themselves for cross-linguistic differences or similarities across children,despite differences in input-didn't really understand this parenthesis.Although the updated theory of Emergentist Coalition Model(ECM) combines early use of attentional cues with later use of social inputs and linguistic cues,it cannot account for the consistent cross-linguistic differences appearing at the very beginning of children's vocabulary which correspond to linguistic features and social inputs.Such differences,particularly the composition of verbs and nouns in children's early vocabularies,challenge the theory of "Noun bias" supported by many researchers.Thus,whether children can use social and linguistic cues in the beginning of word development,noun and verb acquisition in particular,is of interest for this paper.Although there are many studies investigating the relationship between adult's speech input and children's early language development,they do not reveal the regularity and developmental changes both in caregivers' input and infants' word acquisition.Furthermore,none of these studies focused on Chinese,a language with vastly different linguistic properties from English.A longitudinal case method with a Chinese female infant was used.Tracking the infant from 6-to 20-months of age,the researcher visited the family monthly for one-hour recordings of naturalistic interaction.The naturalistic data on caregiver-to-child input were transcribed into CHAT format and analyzed with the CLAN program,counting the frequency of nouns and verbs and word position in caregivers' utterances.Then,the development of child's comprehension and production vocabulary was assessed by both observed data and the Putonghua version of the MacArthur Communicative Development Inventory(PCDI). Seven spontaneous speech samples(6,10,11,13,15,17 and 19 months) were analyzed.In addition,the study also focused on the roles of specific contexts of caregivers' input,selecting three contexts in the naturalistic data(booking reading,feeding and playing). The caregivers were found to produce more verb than noun in tokens and types in most samples,although the difference was significant only for tokens.The position in caregivers' utterances was favorable for verbs,but not nouns,with many verbs dropping subjects and objects.However,the ratio of verbs and nouns varied with specific context.The frequency of nouns was higher relative to verbs in the booking reading context,but verbs were more frequent in both the feeding and playing contexts.In addition,more verbs than nouns were found in the child's early vocabulary,regardless of how they were measured and this corresponded to the caregivers' speech input.Specifically,the child could both comprehend and produce higher ratios of verbs than nouns with the CDI measure,and produced a larger cumulative number of verbs than nouns up to the 15 month.Children can use linguistic input in their vocabulary acquisition even at the very beginning of language development.The dominance of verbs in Chinese adults' speech influences children's early word composition,with more verbs than nouns in both comprehension and production.This result again supports the view of cross-linguistic differences but not the "noun bias" in children's early vocabularies.In addition,the frequency of verbs and nouns varies with specific context.