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Record W4400041861 · doi:10.18162/fp.2024.807

Le travail collaboratif pour développer un dispositif de formation à la réflexivité : quels effets pour les formateurs ?

2024· article· fr· W4400041861 on OpenAlexvenueno aff
Anaïs Corfdir, Sandrine Biémar, Kathleen Degrove, Line Fischer, Valérie Henry, Jim Plumat, Sophie Pondeville, Philippe Snauwaert, Arnaud Vervoort, Evelyne Charlier

Bibliographic record

VenueFormation et profession · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArtPhilosophy

Abstract

fetched live from OpenAlex

Cet article présente une recherche menée avec des formateurs d’enseignants à l’université de Namur, impliqués dans un projet collaboratif visant à élaborer un dispositif de formation centré sur les compétences réflexives de leurs étudiants futurs enseignants. La recherche interroge les effets perçus du travail collaboratif par ces formateurs sur leur propre développement professionnel et leurs pratiques au cours de l’élaboration et de la mise en oeuvre de ce dispositif (six ans). Une collecte de données par entretiens semi-directifs a été réalisée auprès des formateurs impliqués. Le matériau a été traité par catégorisations thématiques. Des effets de changements identitaires et de développement de compétences ont notamment pu être relevés. En perspectives, nous dégageons des pistes pour soutenir le développement de l’innovation pédagogique en milieu universitaire.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.046
metaresearch head score (Gemma)0.098
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.243

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.098
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0100.009
Scholarly communication0.0160.013
Open science0.0030.012
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0140.003

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 head0.091
GPT teacher head0.427
Teacher spread0.336 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2024
Admission routes1
Has abstractyes

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