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Record W1574372962 · doi:10.18806/tesl.v30i1.1129

The Pedagogy of Error Correction: Surviving the Written Corrective Feedback Challenge

2013· article· en· W1574372962 on OpenAlex
Danielle Guénette

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTESL Canada Journal · 2013
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsCorrective feedbackPedagogyPsychologyMathematics education

Abstract

fetched live from OpenAlex

Should we correct our students’ language errors? Most ESL teachers would an- swer this question with a resounding Yes while at the same time wondering how to meet the challenge. The collaborative project reported below was designed to provide ESL teacher trainees with an opportunity to experience the ups and downs of providing corrective feedback on writing and develop their awareness in this regard. To this end, the teacher trainees acted as corrective-feedback tutors to high school learners during one school semester. During the course of the proj- ect, they kept journals documenting their reflections in regard to this demanding pedagogical practice. Time constraints, motivation, and fear of making mistakes themselves or of not providing adequate guidance to the learners were among the major hurdles encountered by the tutors. In interviews conducted at the end of the project, the tutors offered suggestions for overcoming these difficulties and surviving the corrective-feedback trials and tribulations. The survival tips pre- sented were drawn from the tutors’ recommendations as well as from insights from corrective-feedback research.Devrait-on corriger les erreurs de langue de nos étudiants? La plupart des en- seignants d’ALS répondraient à cette question par un oui catégorique tout en se demandant comment relever ce défi. Le projet collaboratif décrit ci-dessous a été conçu pour fournir aux stagiaires en ALS une occasion de vivre les hauts et les bas liés au fait de présenter de la rétroaction corrective aux travaux écrits, et de se conscientiser à cet égard. À cette fin, les stagiaires ont joué le rôle de tuteurs fournissant de la rétroaction corrective à des élèves du secondaire pendant un se- mestre. Au cours de projet, ils ont tenu un journal pour noter leurs réflexions relatives à cette pratique pédagogique exigeante. Parmi les obstacles les plus im- portants auxquels les tuteurs ont fait face, notons les contraintes de temps, la motivation et la peur de se tromper eux-mêmes ou de ne pas fournir des conseils adéquats aux élèves. Lors d’entrevues qui ont eu lieu à la fin du projet, les tuteurs ont offert des suggestions pour surmonter ces difficultés et survivre aux vicissi- tudes de la rétroaction corrective. Les conseils de survie présentés sont tirés des recommandations des tuteurs et des perspectives découlant de la recherche sur la rétroaction corrective.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.794
Threshold uncertainty score0.955

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0460.000

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 head0.050
GPT teacher head0.364
Teacher spread0.313 · 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