Raconter sa biographie langagière en la géolocalisant : le récit cartographique numérique comme outil de formation en didactique des langues secondes
Bibliographic record
Abstract
Cet article détaille une étude portant sur le récit cartographique numérique comme outil de formation en didactique des langues secondes permettant de raconter sa biographie langagière de manière dynamique et multimodale. Pour mener à bien cette étude, nous avons analysé un corpus de biographies langagières (N=10) produites avec le logiciel StoryMap par des étudiants bilingues en formation en didactique des langues secondes. Les résultats de notre analyse thématique font ressortir les caractéristiques de composition du récit biographique numérique et de l’expression des expériences langagières formelles et informelles d’apprentissage de ces étudiants qui se destinent à enseigner le français langue seconde. Ils mettent en évidence que ce type de tâche d’écriture médiatique leur a permis de matérialiser (par l’écriture, l’image, la géolocalisation) leur répertoire langagier, d’expliciter leurs rapports aux langues et de prendre du recul sur leur parcours de formation.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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.
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".