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COMBINED DEPLOYABLE KEYSTROKE LOGGING AND EYETRACKING FOR INVESTIGATING L2 WRITING FLUENCY

Published online by Cambridge University Press:  02 August 2019

Evgeny Chukharev-Hudilainen ,
Aysel Saricaoglu Open the ORCID record for Aysel Saricaoglu [Opens in a new window] ,
Mark Torrance  and
Hui-Hsien Feng
Evgeny Chukharev-Hudilainen*
Affiliation:
Department of English, Iowa State University
Aysel Saricaoglu
Affiliation:
Department of English Language and Literature, Social Sciences University of Ankara
Mark Torrance
Affiliation:
Department of Psychology, Nottingham Trent University
Hui-Hsien Feng
Affiliation:
Department of English, National Kaohsiung University of Science and Technology
*
*Correspondence concerning this article should be addressed to Evgeny Chukharev-Hudilainen, 203 Ross Hall, Ames, Iowa 50011, USA. E-mail: evgeny@iastate.edu
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Abstract

Although fluency is an important subconstruct of language proficiency, it has not received as much attention in L2 writing research as complexity and accuracy have, in part due to the lack of methodological approaches for the analysis of large datasets of writing-process data. This article presents a method of time-aligned keystroke logging and eye-tracking and reports an empirical study investigating L2 writing fluency through this method. Twenty-four undergraduate students at a private university in Turkey performed two writing tasks delivered through a web text editor with embedded keystroke logging and eye-tracking capabilities. Linear mixed-effects models were fit to predict indices of pausing and reading behaviors based on language status (L1 vs. L2) and linguistic context factors. Findings revealed differences between pausing and eye-fixation behavior in L1 and L2 writing processes. The article concludes by discussing the affordances of the proposed method from the theoretical and practical standpoints.

Type
Research Article
Information
Studies in Second Language Acquisition , Volume 41 , Special Issue 3: Methodological Advances in Investigating L2 Writing Processes , July 2019 , pp. 583 - 604
Copyright
Copyright © Cambridge University Press 2019 

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Footnotes

This material is based upon work supported by the National Science Foundation under Grant No. 1550122. The authors are grateful to the anonymous reviewers and the special issue editors, Dr. Andrea Révész and Dr. Marije Michel, for the valuable feedback on the early versions of this manuscript.

References

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