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Record W4220728478 · doi:10.37571/2022.0102

Amenagements flexibles et cooperation entre eleves

2022· article· fr· W4220728478 on OpenAlexvenueno aff
Sylvain Connac, Catherine Hueber, Laurent Lanneau

Bibliographic record

VenueDidactique · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicInformation Technology and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Les pratiques pédagogiques actuelles accordent une importance forte aux aménagements flexibles de l’espace. Les élèves sont autorisés et encouragés à se déplacer en classe et à y choisir des assises différentes pour travailler et apprendre. Le principe de cet article est l’étude d’une conséquence de cette flexibilité : la coopération entre les élèves. Nous avons suivi et observé méthodologiquement une classe d’élèves de 8 à 10 ans, en France, qui ont l’habitude de travailler selon ces modalités. Nous avons réalisé des captations vidéos tout au long de l’année scolaire puis mené des entretiens d’autoconfrontation avec plusieurs élèves. De l’analyse de ce matériau, nous en avons déduit que les organisations flexibles conduisent effectivement les élèves à coopérer, mais que les libertés permises nécessitent plusieurs précautions : former les élèves à la coopération pour éviter les malentendus, introduire un dispositif de limitation des libertés pour favoriser l’autorégulation et penser les différentes postures possibles des enseignants pour articuler apprentissage et enseignement.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.003
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.002

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 head0.018
GPT teacher head0.316
Teacher spread0.298 · 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
Published2022
Admission routes1
Has abstractyes

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