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Record W3183823286 · doi:10.18162/fp.2021.629

Innovation pédagogique à distance pendant la pandémie de COVID-19 : l’exemple d’une séquence pédagogique de e-coopération induite par simulation en formation professionnelle

2021· article· fr· W3183823286 on OpenAlexvenueno aff
Delphine Guyet

Bibliographic record

VenueFormation et profession · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesCoronavirus disease 2019 (COVID-19)Political sciencePhilosophyMedicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Cet article traite d'une recherche pdagogique propos d'une squence de e-coopration induite par une simulation en formation professionnelle (conception, conduite et valuation de cette innovation pdagogique), impose par le premier confinement li la pandmie de la COVID-19 en France. Ce sminaire vise l'acquisition du raisonnement clinique en formation initiale de kinsithrapie. Par une recherche-action collaborative, en s'appuyant sur la simulation, l'apprentissage coopratif, la mdiation distance, cette construction pdagogique a confr une valeur ajoute aux apprentissages, releve la fois par les apprenants et par l' quipe pdagogique, transformant la contrainte de la distance en opportunit.

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)0.005
metaresearch head score (Gemma)0.009
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: none
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.007
Scholarly communication0.0050.004
Open science0.0010.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0150.002

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 head0.139
GPT teacher head0.468
Teacher spread0.329 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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