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Record W2130372131 · doi:10.1017/s0272263109990520

ORAL FEEDBACK IN CLASSROOM SLA

2010· article· en· W2130372131 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

VenueStudies in Second Language Acquisition · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsMcGill University
Fundersnot available
KeywordsCorrective feedbackPsychologyForeign languageMathematics educationSecond languageSecond-language acquisitionDevelopmental psychologyLinguistics

Abstract

fetched live from OpenAlex

To investigate the pedagogical effectiveness of oral corrective feedback (CF) on target language development, we conducted a meta-analysis that focused exclusively on 15 classroom-based studies ( N = 827). The analysis was designed to investigate whether CF was effective in classroom settings and, if so, whether its effectiveness varied according to (a) types of CF, (b) types and timing of outcome measures, (c) instructional setting (second vs. foreign language classroom), (d) treatment length, and (e) learners’ age. Results revealed that CF had significant and durable effects on target language development. The effects were larger for prompts than recasts and most apparent in measures that elicit free constructed responses. Whereas instructional setting was not identified as a contributing factor to CF effectiveness, effects of long treatments were larger than those of short-to-medium treatments but not distinguishable from those of brief treatments. A simple regression analysis revealed effects for age, with younger learners benefiting from CF more than older learners.

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 score0.223
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 communication0.0000.000
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 head0.031
GPT teacher head0.312
Teacher spread0.281 · 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