La formation continue à distance : conditions propices pour répondre aux besoins des enseignantes et des enseignants. Étude de portée et perspective pour des formations à l’éducation à visée inclusive
Bibliographic record
Abstract
Résumé : Les évolutions constantes dans le milieu éducatif, notamment dans le champ de l’école à visée inclusive, modifient les offres de formations continues présentées aux enseignant·e·s. Si les formations à distance (FAD) répondent à divers enjeux sociaux tels que la conciliation famille-travail-étude, la dispersion géographique des professionnel·le·s ou encore des enjeux d’ordre économiques liés aux coûts des formations, dans le contexte suisse romand, celles-ci restent minoritaires. La littérature souligne l’importance de penser les modalités et les contenus des FAD en adéquation aux besoins des utilisateur·trice·s. Cet article propose donc un état des lieux, dans le contexte francophone, des divers besoins exprimés par les enseignant·e·s face à ces formations à distance. Une étude de portée sur des travaux publiés entre 2012 et 2021 a été effectuée. Trois catégories de facteurs, la motivation en tant qu’élément clef dans l’engagement, les modalités et les outils de collaboration sont discutés afin de souligner des perspectives pour la création de FAD dans le contexte vaudois à visée inclusive. Mots clés : formation continue, formation à distance (FAD), formation autoportante, développement professionnel, motivation, travail collaboratif Distance Learning Education: Conditions to Meet Teachers’ Needs. A Scoping Review and Perspective on Inclusive Education Training. Abstract: Ongoing developments in the education sector, particularly in the field of inclusive schools, are changing the range of continuing training courses available to teachers. While distance learning (DL) responds to a number of social challenges, such as the need to reconcile family, work and study, the geographical dispersion of professionals and economic issues linked to training costs, it remains a minority option in French-speaking Switzerland. The literature underscores the importance of designing DL modalities and content in line with users’ needs. This article provides an overview, in the French-speaking context, of the various needs expressed by teachers according to distance learning. A scoping study of works published between 2012 and 2021 was carried out. Three categories of factors – motivation as a key element in engagement, collaboration modalities and tools – are discussed in order to highlight perspectives for the creation of inclusive FADs in the Vaud context. Keywords: distance learning, self-paced training, professional development, motivation, collaborative work
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".