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Linking Rule Acquisition in Novel Phrasal Constructions

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Title: Linking Rule Acquisition in Novel Phrasal Constructions
Language: English
Authors: Boyd, Jeremy K., Gottschalk, Erin A., Goldberg, Adele E.
Source: Language Learning. Dec 2009 59:64-89.
Availability: Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA/
Peer Reviewed: Y
Physical Description: PDF
Page Count: 26
Publication Date: 2009
Document Type: Journal Articles
Reports - Research
Descriptors: Phrase Structure, Task Analysis, Linguistic Input, Language Acquisition, Syntax, Language Usage, Comprehension, Adults, Children
DOI: 10.1111/j.1467-9922.2009.00536.x
ISSN: 0023-8333
Abstract: All natural languages rely on sentence-level form-meaning associations (i.e., linking rules) to encode propositional content about who did what to whom. Although these associations are recognized as foundational in many different theoretical frameworks (Goldberg, 1995, 2006; Lidz, Gleitman, & Gleitman, 2003; Pinker, 1984, 1989) and are--at least in principle--learnable (Allen, 1997; Morris, Cottrell, & Elman, 2000), very little empirical work has been done to establish that human participants are able to acquire them from the input. In the present work, we provided adult participants with 3 min worth of exposure to a novel syntactic construction and then tested to see what was learned. Experiment 1 established that participants are able to accurately deploy newly acquired linking rules in a forced-choice comprehension task, and that constructional knowledge largely persists over a 1-week period. In Experiment 2, participants were exposed to the linking rules immanent in one of two novel constructions and were asked to describe novel events using their exposure construction. The data indicate that participants were successful in using their exposure construction's linking rules in production, and that performance was equally good regardless of the specifics of the target linking pattern. These results indicate that linking rules can be learned relatively easily by adults, which, in turn, suggests that children may also be capable of learning them directly from the input.
Abstractor: As Provided
Number of References: 42
Entry Date: 2009
Accession Number: EJ864019
Database: ERIC
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  Data: Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA/
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  Data: 10.1111/j.1467-9922.2009.00536.x
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  Data: All natural languages rely on sentence-level form-meaning associations (i.e., linking rules) to encode propositional content about who did what to whom. Although these associations are recognized as foundational in many different theoretical frameworks (Goldberg, 1995, 2006; Lidz, Gleitman, & Gleitman, 2003; Pinker, 1984, 1989) and are--at least in principle--learnable (Allen, 1997; Morris, Cottrell, & Elman, 2000), very little empirical work has been done to establish that human participants are able to acquire them from the input. In the present work, we provided adult participants with 3 min worth of exposure to a novel syntactic construction and then tested to see what was learned. Experiment 1 established that participants are able to accurately deploy newly acquired linking rules in a forced-choice comprehension task, and that constructional knowledge largely persists over a 1-week period. In Experiment 2, participants were exposed to the linking rules immanent in one of two novel constructions and were asked to describe novel events using their exposure construction. The data indicate that participants were successful in using their exposure construction's linking rules in production, and that performance was equally good regardless of the specifics of the target linking pattern. These results indicate that linking rules can be learned relatively easily by adults, which, in turn, suggests that children may also be capable of learning them directly from the input.
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