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Record W4226402501 · doi:10.32038/ltrq.2021.25.02

Teachers’ Beliefs and Practice about Written Corrective Feedback: A Case Study in a French as a Foreign Language Program

2021· article· en· W4226402501 on OpenAlexaff
María-Lourdes Lira-Gonzales, Antonella Valeo, Khaled Barkaoui

Bibliographic record

VenueLanguage Teaching Research Quarterly · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsYork UniversityUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsCorrective feedbackSituatedForeign languageEnglish as a foreign languagePsychologyClass (philosophy)PedagogyPeer feedbackSecond language writingMathematics educationMedical educationSecond languageComputer scienceMedicineLinguistics

Abstract

fetched live from OpenAlex

Despite ample research examining second (L2) and foreign language (FL) teacher feedback, research situated in French as a foreign language (FFL) contexts is scarce, in particular studies that examine the beliefs and practices of corrective written feedback (WCF) among FFL teachers. The present study seeks to address this gap by investigating the WCF beliefs and practices of FFL teachers in an undergraduate program in Costa Rica. The participants in this study were five teachers teaching in an FFL program in the Modern Languages School at a large university in Costa Rica. Data were gathered using an online questionnaire, a semi-structured interview, and samples of students’ writing with teacher feedback. The findings revealed that the participants held common beliefs concerning writing, teaching writing, feedback provision in an FL, and the interdependent relationship among teaching, learning, and feedback in an FFL writing class. The results also showed that participants’ beliefs and practices regarding various aspects of written corrective feedback (CF) tended to be aligned, specifically in terms of the use of comprehensive indirect error-coded WCF and the use of evaluation grids. Implications and future research avenues are discussed.

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.

How this classification was reachedexpand

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)0.012
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.048
GPT teacher head0.475
Teacher spread0.427 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueLanguage Teaching Research QuarterlySame topicStudent Assessment and FeedbackFrench-language works237,207