undergraduate thesis: Artificial language rule learning in school children

TitleArtificial language rule learning in school children
Authors
Issue Date2013
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Ng, L. [吳麗欣]. (2013). Artificial language rule learning in school children. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.
AbstractThe study investigated the utilization of rule learning to acquire non-adjacent dependencies in artificial languages, and the relationship between rule learning ability and Cantonese grammar ability, in Cantonese-speaking school children in Hong Kong. Fifty-nine children, aged 9;00 to 13;00 (mean age 10;04), in P4 to P5 were recruited from two primary schools and a local educational centre. The participants’ performance in rule learning test and their receptive and expressive Cantonese grammar ability were measured. The results showed a marginal significance in the children’s ability to differentiate the correctness of dependencies. This suggested the school children could abstract non-adjacent dependency rules in artificial languages which simulated Cantonese. Meanwhile, the results revealed no correlation between rule learning ability and Cantonese grammar ability. It was hypothesized that the above findings were resulted from inadequate exposure to the artificial languages in the experiment, thus longer and repeated exposure might yield better discrimination of rules as well as more salient correlation between rule learning ability and Cantonese grammar ability. This hypothesis and the school children’s ability to learn non-adjacent dependencies via rule learning were discussed.
DegreeBachelor of Science in Speech and Hearing Sciences
SubjectLearning ability
Dept/ProgramSpeech and Hearing Sciences
Persistent Identifierhttp://hdl.handle.net/10722/238525
HKU Library Item IDb5806054

 

DC FieldValueLanguage
dc.contributor.authorNg, Lai-yan-
dc.contributor.author吳麗欣-
dc.date.accessioned2017-02-15T13:04:36Z-
dc.date.available2017-02-15T13:04:36Z-
dc.date.issued2013-
dc.identifier.citationNg, L. [吳麗欣]. (2013). Artificial language rule learning in school children. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.-
dc.identifier.urihttp://hdl.handle.net/10722/238525-
dc.description.abstractThe study investigated the utilization of rule learning to acquire non-adjacent dependencies in artificial languages, and the relationship between rule learning ability and Cantonese grammar ability, in Cantonese-speaking school children in Hong Kong. Fifty-nine children, aged 9;00 to 13;00 (mean age 10;04), in P4 to P5 were recruited from two primary schools and a local educational centre. The participants’ performance in rule learning test and their receptive and expressive Cantonese grammar ability were measured. The results showed a marginal significance in the children’s ability to differentiate the correctness of dependencies. This suggested the school children could abstract non-adjacent dependency rules in artificial languages which simulated Cantonese. Meanwhile, the results revealed no correlation between rule learning ability and Cantonese grammar ability. It was hypothesized that the above findings were resulted from inadequate exposure to the artificial languages in the experiment, thus longer and repeated exposure might yield better discrimination of rules as well as more salient correlation between rule learning ability and Cantonese grammar ability. This hypothesis and the school children’s ability to learn non-adjacent dependencies via rule learning were discussed.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.subject.lcshLearning ability-
dc.titleArtificial language rule learning in school children-
dc.typeUG_Thesis-
dc.identifier.hkulb5806054-
dc.description.thesisnameBachelor of Science in Speech and Hearing Sciences-
dc.description.thesislevelBachelor-
dc.description.thesisdisciplineSpeech and Hearing Sciences-
dc.description.naturepublished_or_final_version-

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