Besoins perçus et adaptation des démarches d’enseignement: le cas de l’enseignement des sciences et technologies au secondaire
Bibliographic record
Abstract
Cet article traite de l’adaptation des démarches d’enseignement en cours d’action, adoptées par les enseignants des sciences et technologies de l’école secondaire. Il vise à comprendre les processus dynamiques de l’adaptation de l’enseignement. Il s’appuie sur des données qui ont été obtenues grâce à un protocole de recherche qualitative axé sur des techniques de groupes de réflexion. Les résultats de la recherche mettent en évidence l’hétérogénéité des parcours d’adaptation des enseignants. Ils soulignent la nécessité du professionnalisme de l’enseignant des sciences et technologies. Ils suggèrent de prendre en considération la complexité des besoins d’adaptation. Ceux-ci commandent en définitive la compatibilité entre les démarches de l’enseignant et les besoins de ses élèves. Le processus d’adaptation est aussi guidé par le plaisir de la reconnaissance, les rapports de l’enseignant aux savoirs, de même que par la défense des valeurs collectives.Mots clé: adaptation de l’enseignement, perception des besoins, enseignement des sciences et technologies This article deals with the adjustment of teaching approaches made by high school science and technology teachers while teaching. It aims at achieving a better understanding of the dynamic processes of teaching adjustment. It relies on a qualitative methodology using focus groups. Data analysis shows the multiplicity of ways that teachers use to adjust their teaching. It stresses out the importance of science and technology teachers’ professionalism and suggests taking into account the complexity of teacher and student needs in the equation of teaching adjustment. Those needs call for an increased compatibility between teaching approaches and students’ needs. The adjustment of teaching approaches is also related to the quest for recognition, the teacher relationship with knowledge and the collective values in place. Keywords: Teaching adjustment, students and teachers needs, science and technology teaching
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".