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Record W2063201340 · doi:10.1017/s0272263115000194

THE EFFECTS OF CORRECTIVE FEEDBACK ON INSTRUCTED L2 SPEECH PERCEPTION

2015· article· en· W2063201340 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueStudies in Second Language Acquisition · 2015
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of CanadaMcGill University
KeywordsCorrective feedbackPerceptionPsychologySpeech perceptionContrast (vision)Cognitive psychologyMathematics educationAudiologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

To what extent do second language (L2) learners benefit from instruction that includes corrective feedback (CF) on L2 speech perception? This article addresses this question by reporting the results of a classroom-based experimental study conducted with 32 young adult Korean learners of English. An instruction-only group and an instruction + CF group were exposed to five 1-hr form-focused lessons that drew learners’ attention to the nonnative phonemic contrast /i/-/ɪ/, but only the instruction + CF group was given relevant feedback. Forced-choice identification tasks were completed by participants in a pretest, an immediate posttest, and a delayed posttest. The two groups showed similar accuracy on the pretest; however, the instruction + CF group outperformed the instruction-only group on the immediate and delayed posttests as well as on unfamiliar words. The significant predictors for these differences turned out to be perceptual accuracy vis-à-vis /ɪ/-natural and /ɪ/-synthesized sounds. These findings are discussed in terms of the pivotal role played by CF in developing accuracy in L2 speech perception.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.381
Teacher spread0.348 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it