La planification stratégique de la formation à distance à l'ère de la téléinformatique
Bibliographic record
Abstract
Teleinformatics in distance education poses a great challenge to secondary and tertiary educational institutions. The speed at which this technology is evolving and the need for new and appropriate pedagogical strategies is reshaping distance education into a new system of knowledge transmission. The arrival of the electronic highway, the creation of a world-wide classroom, and-in the near future-a world-wide university and library are only a few of the manifestations of the accelerated evolution of teleinformatics in education (Knight, 1995; Rossman, 1992). The technology's capacity to meet expectations rapidly and in a flexible manner has brought about new demands for service from non-traditional users while at the same time broadening the array of choices for the traditional clientele. This flexibility in reacting to ever-changing and varied demands requires an organization that is capable of responding to the evolution of internal and external environments. Inclusion of technology in education and its use to support study programs has created a new paradigm : planning that is orderly and pro-active and that supports and preserves the establishment's mission while allowing the system to evolve in accord with the changes. To make it possible, we propose a model of strategic planning that is adapted to the particular needs of distance education in a pro-active and technological environment. L'avènement de la téléinformatique en formation à distance pose un défi de taille aux établissements d'enseignement secondaire et tertiaire qui utilisent ce réseau de communication. La rapidité avec laquelle évolue cette technologie et la nécessité de nouvelles stratégies pédagogiques appropriées sont en train de moduler la formation à distance en un système original de transmission de la connaissance. L'arrivée de l'autoroute électronique, de la salle de classe et, dans un avenir proche, d'une université et d'une bibliothèque mondialisées ne sont que quelques manifestations de cette évolution accélérée de la téléinformatique en éducation (Knight, 1995; Rossman, 1992). La capacité de ce système à répondre rapidement et de manière souple aux attentes a fait naître de nouvelles exigences de service de la part d'usagers non traditionnels, tout en élargissant l'éventail des choix pour la clientèle traditionnelle. Cette flexibilité de réaction du système aux demandes toujours changeantes et variées exige une organisation capable de réagir à l'évolution des environnements interne et externe. L'inclusion de la technologie en éducation et son utilisation à l'appui des programmes d'études fait naître un nouveau paradigme, celui d'une planification ordonnée et proactive qui puisse favoriser et préserver la mission de l'institution, tout en permettant au système d'évoluer en accord avec les changements. Pour ce faire, on propose un modèle de planification stratégique adapté aux particularités de la formation à distance dans un environnement techno-prévisionnel.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".