What predicts how quickly children learn language?

Join us for our next LuCiD seminar, featuring an in-person talk on Tuesday, 7th May 2024 (11 am UK time - in-person & via Zoom). Prof. Caroline Rowland (Max Planck Institute, Nijmegen) will talk about What predicts how quickly children learn language?

Abstract: There are large individual differences in the speed with which children acquire language in the early years. A popular approach is to attribute this variance to differences in the quality and quantity of the child's interactions and input; for example, to the amount of child directed speech or the number of conversational turns that adults and children use in interaction. However, even the strongest findings report only small to moderate effect sizes of linguistic input. In recent years we've been applying a constructivist approach to explaining individual variation to see how far it can take us. In this approach, language development is conceptualized as emerging from rich pre-linguistic communicative and cognitive abilities, with individual learning trajectories being shaped by interactions between environmental input, the child’s current knowledge, and the child’s learning and processing mechanisms. In this talk I illustrate some of our findings from this approach, using data from the longitudinal Language 0-5 Project, in which we followed 90 children from 6 months to 4 and a half years old, and assessed the impact of a range of socio-cognitive, cognitive, and environmental factors on individual differences in language growth.

How to join the seminar: This seminar will take place in person at the University of Manchester, but we will provide a blended approach for anyone who is unable to attend in person. As always the seminar is free to attend & booking isn't required, just get in touch to request the zoom link and don't forget to join the seminar mailing list

Where to find us on the day: The seminar will be held at the University of Manchester in A101 Samuel Alexander Building, which is marked as number 67 on the campus map.

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