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Record W1528280139 · doi:10.4000/apliut.5129

Comment aider des étudiants en situation d’échec en anglais : le cas d’un dispositif de remédiation pour des étudiants de première année d’IUT Informatique

2015· article· fr· W1528280139 on OpenAlexaff
Josée Vaquiéri

Bibliographic record

VenueRecherche et pratiques pédagogiques en langues de spécialité · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsService de Recherche et d'EXpertise en Transformation des Produits Forestiers
Fundersnot available
KeywordsHumanitiesArtPsychology

Abstract

fetched live from OpenAlex

Dans cette fiche pédagogique, nous décrivons un travail mené avec des étudiants en situation d’échec en anglais. Le dispositif hybride mis en place vise à faire d'eux des acteurs de leur progression dans un cadre adapté mêlant individualisation, autonomie et suivi rigoureux. Pour lever les freins à la réussite et développer chez les étudiants un « sentiment d'efficacité personnelle » (Bandura 2003), nous encourageons une réflexion métacognitive dans un environnement sécurisant. La réussite se mesure à l'amélioration de l'aptitude des étudiants à mobiliser efficacement leurs ressources linguistiques.

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)0.039
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.511
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0390.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.004
Open science0.0010.000
Research integrity0.0030.003
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 head0.137
GPT teacher head0.424
Teacher spread0.287 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2015
Admission routes1
Has abstractyes

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