Children learn their first language simply by listening to the linguistic utterances
provided by their caregivers and other speakers around them. In order to
extract meaning and grammatical rules from these utterances, children must track
regularities in the input, which are omnipresent in language. The ability to discover
and adapt to these statistical regularities in the input is termed statistical
learning and has been suggested to be one of the key mechanisms underlying language
acquisition. In this thesis, I investigated a special case of statistical learning,
non-adjacent dependency (NAD) learning. NADs are grammatical dependencies
between distant elements in an utterance, such as is and -ing in the sentence Mary is
walking. I examined which factors play a role in the development of NAD learning
by illuminating this process from different stand points: the first study compares
NAD learning in the linguistic and the non-linguistic domain during the earliest
stages of development, at 4 months of age. This study suggests that at this age,
NAD learning seems to be domain-specific to language. The second study puts a
spotlight on the development of NAD learning in the linguistic domain and proposes
that there may be a sensitive period for linguistic NAD learning during early
childhood. Finally, the third study shows that children can not only recall newly
learned NADs in a test immediately following familiarization, but also recall them
after a retention period, which is critical to show more long-term learning. Overall,
the findings in this thesis further illuminate how NADs, as a spotlight into
language acquisition, are learned, stored in memory, and recalled.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:78993 |
Date | 29 April 2022 |
Creators | Paul, Mariella |
Contributors | Universität Leipzig |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
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