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Auditory statistical learning in children: Novel insights from an online measure

  • IMME LAMMERTINK (a1), MEREL VAN WITTELOOSTUIJN (a1), PAUL BOERSMA (a1), FRANK WIJNEN (a2) and JUDITH RISPENS (a3)...

Abstract

Nonadjacent dependency learning is thought to be a fundamental skill for syntax acquisition and often assessed via an offline grammaticality judgment measure. Asking judgments of children is problematic, and an offline task is suboptimal as it reflects only the outcome of the learning process, disregarding information on the learning trajectory. Therefore, and following up on recent methodological advancements in the online measurement of nonadjacent dependency learning in adults, the current study investigates if the recording of response times can be used to establish nonadjacent dependency learning in children. Forty-six children (mean age: 7.3 years) participated in a child-friendly adaptation of a nonadjacent dependency learning experiment (López-Barroso, Cucurell, Rodríguez-Fornells, & de Diego-Balaguer, 2016). They were exposed to an artificial language containing items with and without nonadjacent dependencies while their response times (online measure) were measured. After exposure, grammaticality judgments (offline measure) were collected. The results show that children are sensitive to nonadjacent dependencies, when using the online measure (the results of our offline measure did not provide evidence of learning). We therefore conclude that future studies can use online response time measures (perhaps in addition to the offline grammaticality judgments) to further investigate nonadjacent dependency learning in children.

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Copyright

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

Corresponding author

ADDRESS FOR CORRESPONDENCE Imme Lammertink, University of Amsterdam, Spuistraat 134, 1012 VB Amsterdam. E-mail: i.l.lammertink@uva.nl

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