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Record W2979862318

Apprendre à communiquer et communiquer pour apprendre en mathématiques dans le programme d'immersion française

2019· dissertation· fr· W2979862318 on OpenAlexaboutno aff
Marie-Josée Morneau

Bibliographic record

VenueMspace (University of Manitoba) · 2019
Typedissertation
Languagefr
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesSociologyArt
DOInot available

Abstract

fetched live from OpenAlex

Les élèves en immersion française (IF) éprouvent des besoins au niveau du vocabulaire expressif et de la structure syntaxique dans leur deuxième langue (L2), le français, limitant ainsi la communication du raisonnement mathématique. Une approche littératiée fondée sur la langue d’apprentissage comme véhicule cognitif peut soutenir la L2 des élèves en IF. Or, l’approche n’a jamais été examinée en mathématiques en IF. L’objectif était d’évaluer les effets d’une approche littératiée sur la compréhension mathématique, le niveau global de communication oral et la précision langagière dans la L2. Deux groupes d’élèves de classes combinées 7e et 8e année en IF au Manitoba furent comparés : un groupe expérimental qui a reçu un enseignement littératié pendant six semaines et un autre contrôle. Les résultats ont démontré un effet positif sur la structure syntaxique, ce qui suggère que l’approche littératiée joue un rôle clé dans la facilitation du raisonnement mathématique en contexte IF.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.267
Teacher spread0.246 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

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