Modeling systematicity and individuality in nonlinear second language development: The case of English grammatical morphemes

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Modeling systematicity and individuality in nonlinear second language development : The case of English grammatical morphemes. / Murakami, Akira.

In: Language Learning, Vol. 66, No. 4, 12.2016, p. 834-871.

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@article{00d348c4adaf4b328fb225656e079609,
title = "Modeling systematicity and individuality in nonlinear second language development: The case of English grammatical morphemes",
abstract = "This article introduces two sophisticated statistical modeling techniques that allow researchers to analyze systematicity, individual variation, and nonlinearity in second language (L2) development. Generalized linear mixed-effects models can be used to quantify individual variation and examine systematic effects simultaneously, and generalized additive mixed models allow for the examination of systematicity, individuality, and nonlinearity within a single model. Based on a longitudinal learner corpus, this article illustrates the usefulness of these models in the context of L2 accuracy development of English grammatical morphemes. I discuss the strengths of each technique and the ways in which these techniques can benefit L2 acquisition research, further highlighting the importance of accounting for individual variation in modeling L2 development.",
keywords = "statistical modeling, mixed-effects model, generalized additive mixed model, learner corpus, individual variation, grammatical morphemes",
author = "Akira Murakami",
year = "2016",
month = dec,
doi = "10.1111/lang.12166",
language = "English",
volume = "66",
pages = "834--871",
journal = "Language Learning",
issn = "0023-8333",
publisher = "Wiley",
number = "4",

}

RIS

TY - JOUR

T1 - Modeling systematicity and individuality in nonlinear second language development

T2 - The case of English grammatical morphemes

AU - Murakami, Akira

PY - 2016/12

Y1 - 2016/12

N2 - This article introduces two sophisticated statistical modeling techniques that allow researchers to analyze systematicity, individual variation, and nonlinearity in second language (L2) development. Generalized linear mixed-effects models can be used to quantify individual variation and examine systematic effects simultaneously, and generalized additive mixed models allow for the examination of systematicity, individuality, and nonlinearity within a single model. Based on a longitudinal learner corpus, this article illustrates the usefulness of these models in the context of L2 accuracy development of English grammatical morphemes. I discuss the strengths of each technique and the ways in which these techniques can benefit L2 acquisition research, further highlighting the importance of accounting for individual variation in modeling L2 development.

AB - This article introduces two sophisticated statistical modeling techniques that allow researchers to analyze systematicity, individual variation, and nonlinearity in second language (L2) development. Generalized linear mixed-effects models can be used to quantify individual variation and examine systematic effects simultaneously, and generalized additive mixed models allow for the examination of systematicity, individuality, and nonlinearity within a single model. Based on a longitudinal learner corpus, this article illustrates the usefulness of these models in the context of L2 accuracy development of English grammatical morphemes. I discuss the strengths of each technique and the ways in which these techniques can benefit L2 acquisition research, further highlighting the importance of accounting for individual variation in modeling L2 development.

KW - statistical modeling

KW - mixed-effects model

KW - generalized additive mixed model

KW - learner corpus

KW - individual variation

KW - grammatical morphemes

U2 - 10.1111/lang.12166

DO - 10.1111/lang.12166

M3 - Article

VL - 66

SP - 834

EP - 871

JO - Language Learning

JF - Language Learning

SN - 0023-8333

IS - 4

ER -