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A META-ANALYSIS OF SENSITIVITY TO GRAMMATICAL INFORMATION DURING SELF-PACED READING: TOWARDS A FRAMEWORK OF REFERENCE FOR READING TIME EFFECT SIZES

Published online by Cambridge University Press:  07 May 2019

Nick Avery  and
Emma Marsden
Nick Avery*
Affiliation:
University of York
Emma Marsden
Affiliation:
University of York
*
*Correspondence concerning this article should be addressed to Nicholas Avery, Department of Education, University of York, Heslington, York, United Kingdom, YO10 5DD. E-mail: nicholas.avery@york.ac.uk
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Abstract

Despite extensive theoretical and empirical research, we do not have estimations of the magnitude of sensitivity to grammatical information during L2 online processing. This is largely due to reliance on null hypothesis significance testing (Plonsky, 2015). The current meta-analysis draws on data from one elicitation technique, self-paced reading, across 57 studies (N = 3,052), to estimate sensitivity to L2 morphosyntax and how far L1 background moderates this. Overall, we found a reliable sensitivity to L2 morphosyntax at advanced proficiencies (d = .20, 95% CIs .15, .25), with some evidence that this was reliably lower than for native speakers (NSs). These patterns were not generally moderated by linguistic feature or sentence region. However, effects for anomaly detection were larger among NSs than L2 learners and the effects among L2 learners appeared to show a trend toward L1 influence. Finding smaller effects than in other subdomains, we provide an initial framework of reference for L2 reading time effect sizes.

Type
Research Article
Information
Studies in Second Language Acquisition , Volume 41 , Issue 5 , December 2019 , pp. 1055 - 1087
Open Practices
Open materials Open data
Copyright
Copyright © Cambridge University Press 2019 

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Footnotes

Aspects of this article were presented at the 2017 Second Language Research Forum, Ohio State University, and at the 2nd Biennial Conference of the French Second Language Acquisition Network: Research Methodology in the Field of Second Language Acquisition and Learning, Université Paul-Valéry, Montpellier 3, 2018. We are grateful to the editors and three anonymous SSLA reviewers for their valuable comments. We thank Luke Plonsky for useful statistical advice and the authors who shared their data with us: Filiz Çele, Masahiro Hara, Alan Juffs (NSF grant SBR-9709152), Sehoon Jung, and Natasha Tokowicz.

The experiment in this article earned an Open Data badge for transparent practices. The materials are available at https://www.iris-database.org/iris/app/home/detail?id=york%3a936220&ref=search/.

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