SRCD 2019: language input and prediction

Here are my slides for SRCD 2019.

A large body of research indicates that environmental factors like SES play a role in children’s language development (for review see Fernald & Weisleder, 2011). These findings reveal that children’s day-to-day language experiences vary tremendously, as do their developmental trajectories. Factors like SES, language input, and language processing abilities interact to shape children’s emerging linguistic abilities (e.g., Weisleder & Fernald, 2013).

At the same time, a related body of work has investigated whether a particular aspect of language processing – prediction – supports development, and a number of findings are in line with this view (e.g., Reuter et al., under revision). However, the origins of individual differences in prediction are unknown. Given prior findings linking language input and processing efficiency, it seems likely that language input also supports predictive language processing. Importantly, evaluating the link between input and prediction is essential for evaluating prediction-based theories of learning: These theories claim that accurate predictions are the result of accumulated language processing experiences. Children who receive more input have more processing experiences and therefore should be able to generate more accurate predictions during language processing (e.g., Dell & Chang, 2014).

We therefore hypothesized that home language input supports children’s emerging language processing abilities, including predictive language processing. Using a combination of eye-tracking tasks, LENA recordings, and vocabulary measures (PPVT), we find that:  High-SES toddlers receive marginally more language input from caregivers. High-input toddlers have larger vocabularies, and, importantly, high-input toddlers generate more robust predictions during language processing. These findings add to a body of literature linking SES-based disparities in input and processing (e.g., Weisleder & Fernald, 2013) and provide further support for prediction-based theories of language development (e.g., Dell & Chang, 2014).

We thank all participant families and we’re grateful to all Princeton Baby Lab research assistants for their help with data collection. We also thank Monica Ellwood-Lowe and Mahesh Srinivasan for organizing our SRCD 2019 symposium on SES-based disparities in language development.