Enseigner avec l’Approche neurolinguistique. Quel apport pour l’apprentissage des langues ?
Bibliographic record
Abstract
L’objectif de ce numéro de Lidil est de présenter les dernières recherches sur l’Approche neurolinguistique (ANL) pour l’enseignement des langues étrangères et secondes, notamment en situant cette approche dans le champ de la didactique des langues étrangères et secondes, et en délimitant les différents contextes dans lesquels elle prend vie à travers le monde en vue d’en identifier les gains potentiels. Trois axes thématiques ont été retenus. Le premier permet d’esquisser les contours de l’ANL. L’article de Cartier présente un travail historique sur sa genèse. Dans l’article suivant, Ling réfléchit à des passerelles possibles entre ANL et approche actionnelle dans le cadre de programmes inscrit dans le CECRL. Le deuxième axe interroge la pertinence de l’ANL vis-à-vis de différents publics, ce que fait Gettliffe, dans une étude de cas avec des étudiants, et Dat & Starkey-Perret, dans le cadre de l’enseignement de l’anglais dans le secondaire. Le dernier axe porte sur des dispositifs didactiques et pédagogiques s’appuyant sur l’ANL en France. Les articles de Guedat-Bittighoffer et de Nocus & Maksud rendent compte d’une évaluation à la fois qualitative et quantitative d’une expérimentation de l’ANL auprès d’élèves allophones en contexte scolaire. Le numéro se clôt par un entretien avec Joan Netten et David Macfarlane qui replacent l’ANL dans son contexte d’origine, le Canada. REMERCIEMENTS Ont été sollicités pour évaluer les articles de ce numéro (dossier thématique) : Jose Aguilar Río, Charlotte Alazard, Nathalie Auger, Violaine Bigot, Jacques Crinon, Jean-Marc Dewaele, Catherine Felce, Roxane Gagnon, Cyrille Granget, Marie-Cécile Guernier, Françoise Hapel, Maria Kihlstedt, Grégory Miras, Marie-Françoise Narcy-Combes, Jérôme Riou, Évelyne Rosen-Reinhardt, Jeremi Sauvage, Nathalie Spanghero, Pascale Trevisiol, Kossi-Seto Yibokou. This issue of Lidil aims to present the latest research on the Neurolinguistic Approach (NLA) for Learning and Teaching Foreign Languages, in particular by situating this approach within the field of second language education research and by delineating the various contexts in which it is implemented worldwide in order to identify its potential benefits. This issue is divided in three thematic axes. The first of these offers an outline of the NLA. The article by Cartier provides a historical overview of its development. In the following article, Ling reflects on possible bridges between NLA and the Action-oriented approach in the context of CEFR programmes. The second axis questions the relevance of NLA for different audiences, which is explored by Gettliffe (a case study of university students) and by Dat & Starkey-Perret (teaching English as a foreign language at secondary level). The third section examines a number of programs that apply the NLA in France. The articles by Guedat-Bittighoffer on one hand, and by Nocus & Maksud on the other, report on a qualitative and quantitative evaluation of an NLA experiment with allophone pupils in a school context. The issue concludes with an interview with Joan Netten and David Macfarlane, who speak about the NLA in its original context, Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".