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Record W2593743313 · doi:10.7202/1039088ar

Interagir pour apprendre en gestion de classe au secondaire : analyse du discours des futurs enseignants dans un espace collaboratif

2017· article· fr· W2593743313 on OpenAlexaff
Pier-Ann Boutin, Christine Hamel, Josée-Anne Gouin

Bibliographic record

VenuePhronesis · 2017
Typearticle
Languagefr
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Afin de soutenir le développement professionnel des futurs enseignants au secondaire lors de leur formation initiale universitaire, et ce, en lien avec le concept de praticien réflexif dans une approche par compétence, un design pédagogique novateur fut mis en place dans un cours dédié à la gestion de classe. En effet, ce design, inspiré des principes de la communauté d’apprentissage (Brown, 1994), a amené les étudiants-stagiaires à développer un discours collectif sur leur pratique professionnelle à travers les enjeux propre à la gestion de classe au secondaire et à leurs préoccupations lors d’un stage de cinq semaines. Nous faisons la prémisse que la participation à l’élaboration d’un discours collectif sur les pratiques professionnelles permet aux étudiants de, non seulement, réfléchir sur leur pratique, mais de faire des apprentissages professionnels durables. Ainsi, notre étude s’attarde à l’engagement des étudiants dans l’élaboration du discours collectif et aux actions leur permettant de faire avancer celui-ci.

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)0.009
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0140.008
Scholarly communication0.0120.006
Open science0.0020.008
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0120.002

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 head0.038
GPT teacher head0.363
Teacher spread0.325 · 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 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
Published2017
Admission routes1
Has abstractyes

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