Modeling Systematicity and Individuality in Nonlinear Second Language Development: The Case of English Grammatical Morphemes. Issue 4 (17th February 2016)

• Record Type: Journal Article
• Authors: Murakami, Akira
• Is Part Of: Language learning. Volume 66:Issue 4(2016)
• Page Start: 834
• Page End: 871
• Publication Date: 2016-02-17
• Subjects: statistical modeling -- mixed‐effects model -- generalized additive mixed model -- learner corpus -- individual variation -- grammatical morphemes; Language and languages -- Periodicals; Language and languages -- Study and teaching -- Periodicals; Linguistics; 407
• DOI: 10.1111/lang.12166
• Languages: English
• ISSNs: 0023-8333

Abstract

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. Open Practices: This article has been awarded an Open Data badge. All data are publicly accessible via the Open Science Framework athttps://osf.io/dbuh4 . Learn more about the Open Practices badges from the Center for Open Science:https://osf.io/tvyxz/wiki .