Across socioeconomic status (SES), parental input varies in quantity and quality, and this impacts children's early language abilities and later academic performance. While these relationships are firmly established, their mechanisms are not well understood. Aggregated measures of input (e.g., total words) and outcomes (e.g., vocabulary size) track the consequences of multiple years of learning, but this ignores how children acquire language knowledge through iterative encounters with sentences. To observe this process directly, the present project combines high-density input recordings, eye-tracking methods, and computational modeling to isolate the cues that children use to interpret sentences and how strategies vary with input differences. At a scientific level, this research provides a framework for comparing systematic variation across social groups. While existing models of acquisition assume that the convenience sample (i.e., higher-SES children) offers a suitable proxy of learning in all children, this project tests an alternative hypothesis that SES-related differences in input affect what information children attend to when listening to sentences. Isolating between-child differences in comprehension will reveal strategies that learners must acquire to interpret new sentences. At a societal level, learning and communication depend on accurately interpreting sentences. Describing children's comprehension strategies enables better predictions of future outcomes and offers methods for targeting multiple pathways by which early language can affect academic performance. This framework will benefit other populations whose input differs from mainstream peers, e.g., dual language learners, cochlear implant users.
To understand the sentence-level processes that mediate between parental input and language outcomes, the present project examines how language experience influences comprehension strategies in 5- and 6-year-olds from varying SES backgrounds. This project tests the hypothesis that input properties regulate what cues are informative for interpreting sentence meanings. For higher-SES groups, greater input quantity supports learning of fine-grained word properties, and increased word diversity enhances the need to access detailed patterns when interpreting sentences. For lower-SES groups, however, decreased quantity and diversity make coarse-grained patterns more useful, both because they require less input to learn and imply similar meanings when words occur in canonical sentence frames. This project measures word-specific and sentence-frame patterns in parental input using high-density recordings of utterances, and distinguishes children's sentence interpretations using eye-tracking experiments. Computational models combine these data to derive child-specific estimates of reliance on fine-grained word knowledge versus coarse-grained frame knowledge during comprehension.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
