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Record W2945064565 · doi:10.7202/1059174ar

Perceptions par les élèves du climat de soutien en mathématiques : validation d’échelles et étude des différences selon le genre en 5e secondaire

2019· article· fr· W2945064565 on OpenAlexvenueno aff
Doriane Jaegers, Dominique Lafontaine

Bibliographic record

VenueMesure et évaluation en éducation · 2019
Typearticle
Languagefr
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPsychologyArt

Abstract

fetched live from OpenAlex

Cette étude vise à valider des échelles en langue française destinées à mesurer les perceptions qu’ont les élèves de 5e secondaire (16 ans) du climat de soutien dans leur classe de mathématiques. Se basant sur la théorie de l’autodétermination (Deci et Ryan, 2000a, 2000b) et, plus spécifiquement, sur la satisfaction des trois besoins fondamentaux, les échelles utilisées étayent le troisième pilier du modèle tridimensionnel d’un enseignement de qualité de Klieme et ses collaborateurs (2006). Les résultats d’analyses factorielles exploratoires et confirmatoires ont abouti à quatre échelles dont les qualités psychométriques sont satisfaisantes. La présente recherche examine également les différences de perceptions du climat de soutien en mathématiques en fonction du genre. Si aucune différence n’est trouvée pour trois échelles, les analyses indiquent que, de manière significative, les filles perçoivent davantage l’implication de leur enseignant que les garçons, et ce, même sous contrôle du niveau socioéconomique et des performances en mathématiques.

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)0.010
metaresearch head score (Gemma)0.025
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.037
GPT teacher head0.351
Teacher spread0.314 · 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
Published2019
Admission routes1
Has abstractyes

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