Young children’s language experiences and language outcomes are highly variable. Research in recent decades has focused on understanding the extent to which family socioeconomic status (SES) relates to parents’ language input to their children and, subsequently, children’s language learning. Here, we first review research demonstrating differences in the quantity and quality of language that children hear across low-, mid-, and high-SES groups, but also—and perhaps more importantly—research showing that differences in input and learning also exist within SES groups. Second, in order to better understand the defining features of ‘high-quality’ input, we highlight findings from laboratory studies examining specific characteristics of the sounds, words, sentences, and social contexts of child-directed speech (CDS) that influence children’s learning. Finally, after narrowing in on these particular features of CDS, we broaden our discussion by considering family and community factors that may constrain parents’ ability to participate in high-quality interactions with their young children. A unification of research on SES and CDS will facilitate a more complete understanding of the specific means by which input shapes learning, as well as generate ideas for crafting policies and programs designed to promote children’s language outcomes.
Young children who hear more child-directed speech (CDS) tend to have larger vocabularies later in childhood, but the specific characteristics of CDS underlying this link are currently underspecified. The present study sought to elucidate how the structure of language input boosts learning by investigating whether repetition of object labels in successive sentences – a common feature of natural CDS – promotes young children’s efficiency in learning new words. Using a looking-while-listening paradigm, two-year-old children were taught the names of novel objects, with exposures either repeated across successive sentences or distributed throughout labeling episodes. Results showed successful learning only when label/object pairs had been repeated in blocks of successive sentences, suggesting that immediate opportunities to detect recurring structure facilitate young children’s learning. These findings offer insight into how the information flow within child-directed speech might influence vocabulary development, and we consider the findings alongside research showing the benefits of distributing information across time.
Children tend to regularize their productions when exposed to artificial languages, an advantageous response to unpredictable variation. But generalizations in natural languages are typically conditioned by factors that children ultimately learn. In two experiments, adult and six-year-old learners witnessed two novel classifiers, probabilistically conditioned by semantics. Whereas adults displayed high accuracy in their productions - applying the semantic criteria to familiar and novel items - children were oblivious to the semantic conditioning. Instead, children regularized their productions, over-relying on only one classifier. However, in a two-alternative forced-choice task, children's performance revealed greater respect for the system's complexity: they selected both classifiers equally, without bias toward one or the other, and displayed better accuracy on familiar items. Given that natural languages are conditioned by multiple factors that children successfully learn, we suggest that their tendency to simplify in production stems from retrieval difficulty when a complex system has not yet been fully learned.
Differences in vocabulary size among children can be explained in part by differences in parents' language input, but features of caregivers' input can be more or less beneficial depending on children's language abilities. The current study focused on a specific feature of infant-directed speech: parents' repetition of words across utterances. Although previous work with infants showed a positive relation between repetition and children's vocabulary, we predicted that this would not be the case later in development. Instead, parents may use less repetition as their children become increasingly proficient language learners. In the current study, we examined the extent to which low-income fathers of 24-month-olds (N=41) repeat words to their children using three indices: type-token ratio, automated repetition index, and partial repetition of open-class words. The same finding emerged across all measures of repetition: Fathers whose children had larger vocabularies at 24months repeated wordslessoften, suggesting a developmental coupling of fathers' input and children's language proficiency.
Language learners must place unfamiliar words into categories, often with few explicit indicators about when and how that word can be used grammatically. Reeder, Newport, and Aslin (2013) showed that college students can learn grammatical form classes from an artificial language by relying solely on distributional information (i.e., contextual cues in the input). Here, two experiments revealed that healthy older adults also show such statistical learning, though they are poorer than young at distinguishing grammatical from ungrammatical strings. This finding expands knowledge of which aspects of learning vary with aging, with potential implications for second language learning in late adulthood.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.