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Record W4399376798 · doi:10.7202/1111722ar

L’enseignement aspectuel des temps du passé selon une approche basée sur les concepts

2024· article· fr· W4399376798 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

Venue˜La œRevue de l'AQEFLS/Revue de l'AQEFLS · 2024
Typearticle
Languagefr
FieldArts and Humanities
TopicClassical Studies and Philology
Canadian institutionsMcGill UniversityUniversité de Montréal
Fundersnot available
KeywordsPhilosophy

Abstract

fetched live from OpenAlex

La présente étude vise à déterminer la mesure dans laquelle un enseignement basé sur les concepts permet à des apprenants de français langue seconde (FLS) de s’approprier le concept d’aspect verbal pour comprendre la distinction entre le passé composé et l’imparfait. En tout, 16 apprenants adultes de FLS provenant de trois niveaux différents (A2, n = 8; B1, n = 6; B2, n = 4) ont participé à deux séances de 1 h 30 au cours desquelles la différence aspectuelle entre le passé composé et l’imparfait a été enseignée au moyen d’une séquence d’enseignement basé sur les concepts. Des verbalisations écrites et orales ont été recueillies chez les participants au début et à la fin de l’étude, et ceux-ci ont également rempli un texte à trous faisant office de prétest et de posttest. Les résultats montrent que les apprenants de tous les niveaux ont saisi la notion d’aspect, mais que les apprenants de niveau plus avancé étaient en mesure de mieux appliquer le concept en contexte d’utilisation.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.798
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.073
GPT teacher head0.248
Teacher spread0.176 · 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