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Exploring the potential relationship between eye gaze and English L2 speakers’ responses to recasts

Bibliographic Data

ID11655777
AuthorsKim Mcdonough (0000-0003-3165-9687, Concordia University, corresponding author), Dustin Crowther (0000-0002-4399-0169, Michigan State University), Paula Kielstra (Chenelière Éducation, Canada), Pavel Trofimovich (0000-0001-6696-2411, Concordia University)
Year2015
Volume31
Issue4
Pages563-575
Publication date2015-06-03
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSecond language Research (JOURNAL)
Journal identifiersISSN: 0267-6583 • E-ISSN: 1477-0326
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.1177/0267658315589656
OpenAlexW2400694300
LanguageEN
Citations received8
References cited34

This exploratory study investigated whether joint attention through eye gaze was predictive of second language (L2) speakers’ responses to recasts. L2 English learners ( N = 20) carried out communicative tasks with research assistants who provided feedback in response to non-targetlike (non-TL) forms. Their interaction was audio-recorded and their eye gaze behavior was tracked simultaneously using the faceLAB system. Transcripts were coded for characteristics of the feedback episodes (linguistic target, feedback type, intonation, prosody) and types of response (no opportunity, no reformulation, non-TL response, TL response). Eye gaze length for the researcher (when producing the feedback move) and the L2 speaker (when responding to feedback) were obtained in seconds using Captiv software. Following data pruning to reduce the data set to clausal recasts in response to grammatical errors, a logistic regression model revealed that both L2 speaker and mutual eye gaze were predictive of TL responses. Methodological issues for eye-tracking research during L2 interaction are provided, and suggestions for future research are discussed

Cognitive psychology · Eye tracking · Fluency · Gaze · Intonation (linguistics · Linguistics · Mathematics education · Prosody · Computer Science · Hearing Impairment and Communication · Language, Metaphor, and Cognition · Psychology · Speech and dialogue systems · Artificial Intelligence

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Unique citing works8
Citations per year1
Citation span2018 - 2023 (6)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 8

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