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Record W2150037669 · doi:10.1017/s0261444812000365

Oral corrective feedback in second language classrooms

2012· article· en· W2150037669 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.

Bibliographic record

VenueLanguage Teaching · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsMcGill University
Fundersnot available
KeywordsCorrective feedbackPsychologyFocus on formSecond-language acquisitionSecond languageMathematics educationFocus (optics)PedagogyLinguisticsGrammar

Abstract

fetched live from OpenAlex

This article reviews research on oral corrective feedback (CF) in second language (L2) classrooms. Various types of oral CF are first identified, and the results of research revealing CF frequency across instructional contexts are presented. Research on CF preferences is then reviewed, revealing a tendency for learners to prefer receiving CF more than teachers feel they should provide it. Next, theoretical perspectives in support of CF are presented and some contentious issues addressed related to the role of learner uptake, the role of instruction, and the overall purpose of CF: to initiate the acquisition of new knowledge or to consolidate already acquired knowledge. A brief review of laboratory studies assessing the effects of recasts is then presented before we focus on classroom studies assessing the effects of different types of CF. Many variables mediate CF effectiveness: of these, we discuss linguistic targets and learners' age in terms of both previous and prospective research. Finally, CF provided by learners and the potential benefits of strategy training for strengthening the role of CF during peer interaction are highlighted.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.020
GPT teacher head0.272
Teacher spread0.252 · 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