The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.
Construction Learning as a Function of Frequency, Frequency Distribution, and Function
Open accessAbstract
This article considers effects of construction frequency, form, function, and prototypicality on second language acquisition (SLA). It investigates these relationships by focusing on naturalistic SLA in the European Science Foundation corpus (Perdue, 1993) of the English verb–argument constructions (VACs): verb locative (VL), verb object locative (VOL), and ditransitive (VOO). Goldberg (2006) argued that Zipfian type/token frequency distributions (Zipf, 1935) in natural language constructions might optimize learning by providing one very high‐frequency exemplar that is also prototypical in meaning. This article tests and confirms this proposal for naturalistic English as a second language. We show that VAC type/token distribution in the input is Zipfian and that learners first use the most frequent, prototypical, and generic exemplar (e.g., put in the VOL VAC, give in the VOO ditransitive, etc.). Learning is driven by the frequency and frequency distribution of exemplars within constructions and by the match of their meaning to the construction prototype.
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Cited by
Alternative Approaches to Second Language Acquisition
(2011) · Routledge eBooks · doi:10.4324/9780203830932 · Cited by 1,079
Argument Structure in Usage-Based Construction Grammar: Experimental and corpus-based perspectives
Perek, F. (2015) · Constructional Approaches to Language · doi:10.1075/cal.17 · Cited by 417
The semiotic ecology and linguistic complexity of an online game world
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Metadata
- Authors
- ELLIS, N. C., & FERREIRA–JUNIOR, F.
- Venue
- The Modern Language Journal
- Publisher
- Wiley
- Published
- 2009-08-03
- Volume
- 93
- Issue
- 3
- Pages
- 370-385
- ISSN
- 0026-7902 (ISSN-L)
- 1540-4781
- OpenAlex
- W2043270946
- Cited by
- 351
- References
- 65
- FWCI
- 14.42
- Type
- journal article
- Language
- en
- Open access
- bronze
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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