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Record W1917290384 · doi:10.5565/rev/jtl3.446

Les connaissances implicites et explicites en grammaire : quelle importance pour l’enseignement? Quelles conséquences?

2011· article· en· W1917290384 on OpenAlexaff
Marie Nadeau, Carole Fisher

Bibliographic record

VenueBellaterra Journal of Teaching & Learning Language & Literature · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsUniversité du Québec à ChicoutimiUniversité du Québec à Montréal
Fundersnot available
KeywordsDictationGrammarLinguisticsSentencePoint (geometry)PsychologyComputer scienceNatural language processingPhilosophy

Abstract

fetched live from OpenAlex

This paper presents a review of research in cognitive psychology on implicit and explicit knowledge and learning from the point of view of written French didactic, focusing on its silent morphology, in order to draw consequences for teaching. Standard grammar exercises are then examined for the type of knowledge they require: to what extent do they prepare the students to write and revise their texts ? We show that most exercises are not adequate to develop either explicit or implicit knowledge of grammar.. Finally, initial results of an experimentation of two types of activities developping explicit grammatical knowledge, no error dictation and sentence of the day, are presented. Results are positive: experiments in 21classes of primary and secondary education show a strong effect on the ability of students to achieve grammatical agreements in French.

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)0.014
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.060
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.014
Scholarly communication0.0090.014
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.035
GPT teacher head0.295
Teacher spread0.260 · 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 designTheoretical or conceptual
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

Citations34
Published2011
Admission routes1
Has abstractyes

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Same venueBellaterra Journal of Teaching & Learning Language & LiteratureSame topicLinguistics and Discourse AnalysisFrench-language works237,207