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Record W4297494249 · doi:10.1522/rhe.v6i1.1230

L' apprentissage en profondeur : une voie prometteuse pour développer les compétences du 21e siècle à l'école St-Vincent

2022· article· fr· W4297494249 on OpenAlexaffvenue
Danny Brochu, Érika Villemure

Bibliographic record

VenueRevue hybride de l éducation · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsAssociation Québécoise des Enseignantes et des Enseignants du PrimaireCommission Scolaire des Hautes Rivières
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophyArt

Abstract

fetched live from OpenAlex

Depuis maintenant deux ans, l’école primaire St-Vincent vise à développer les compétences du 21e siècle auprès des élèves. À titre de conseiller pédagogique et d’enseignante, nous vous proposons d’expliquer ce projet du point de vue des praticiens. Pour ce faire, nous présenterons brièvement le cadre de référence utilisé, puis nous nous attarderons aux défis que représente ce type de projet au regard des pratiques enseignantes. Nous vous présenterons également les modalités d’accompagnement du personnel scolaire mis en place et l’exemple d’un projet réalisé.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.186
GPT teacher head0.410
Teacher spread0.223 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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