Necessary conditions to implement innovation in remote networked schools: The stakeholders’ perceptions
Bibliographic record
Abstract
Remote Networked Schools (RNS) is an initiative by the Quebec Ministry of Education, Leisure and Sports (MELS) to investigate solutions that the use of information and communication technologies (ICT) can offer for the preservation of small rural schools in Quebec, Canada. The implementation of RNS mobilized then – as it still does now – the local capacity for innovation of all the stakeholders involved in this networking effort to improve learning. Building on Donald P. Ely’s work (1990; 1999), this paper presents the results of an investigation of the RNS educational stakeholders’ perceptions of the importance of the conditions that facilitate the implementation of educational technology innovations for the success of RNS in their locations. Les conditions nécessaires à l’implantation de l’innovation de l'École éloignée en réseau: la perception des intervenants Résumé: L’École éloignée en réseau est une initiative du Ministère de l’Éducation, du Loisir et du Sport du Québec (MELS), qui a comme objectif d’explorer ce que l’usage des technologies de l’information et de la communication (TIC) peut offrir pour la sauvegarde des petites écoles rurales au Québec, Canada. L'implantation de l’École éloignée en réseau a mobilisé (et continue aujourd’hui) la capacité locale, pour l’innovation, de tous les intervenants impliqués dans cet effort de mise en réseau pour améliorer l’apprentissage. Partant des recherches de Donald P. Ely (1990; 1999), ce texte présente les résultats d’une étude sur la perception des intervenants impliqués dans l’École éloignée en réseau, quant à l’importance des conditions facilitant l’implantation d’innovations technologiques afin que cela soit un succès dans leur communauté.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".