Notice bibliographique
Résumé
This qualitative research examines the perceptions of e-learning stakeholders within the Canadian Department of Defence and makes strategy recommendations that may support e-learning adoption.A review of the literature describes the diffusion of educational technology as a slow and evolutionary process that may take twenty-five years or more to be realized in educational settings.Adoption is more successful if the technologies are easily integrated, not too complex and offer obvious advantage over existing practices.A review of distance education systems suggests a return to the basics.Large distance education systems thrive using print as the media of choice to support learning.Leading theories of distance education inform the reader of the essential requirements to support learning at a distance including the requirement for interaction and communication.The Canadian Forces (CF) are aligned with the Advanced Distributed Learning (ADL) and the Shareable Content Object Reference Model (SCORM).As one of only two ADL colabs located outside the United States, learning objects, contrary perspectives to the learning object paradigm, and notions about the SCORM standard are explored.Moreover, many complex notions embedded in the learning object concept have led some to ask where is the learning in learning objects and complex standards.Two related themes that have recently gained momentum are the convergence of knowledge management with e-learning and the rapid development of e-learning.These notions seem to support a shift from course-based learning to just-in-time and informal learning constructs.Elements of a strategic plan including the requirement for vision and leadership are examined as critical components to adoption.There is no shortage of educational technology.However, vision, leadership, and pedagogical practices have not kept pace with technological development.Hence, strategy and vision must be able to withstand the constant barrage and challenge of implementing new technologies.The v Chapter Four, "findings," provides a rich description of the challenges of implementing advanced technology applications, in the words of the candidates who were interviewed.The Chapter Five, "conclusion," provides strategic recommendations that may be considered for implementation.vi Chapter II -Review of Related LiteratureThe introduction of new technology can be both exciting and alienating.It may create or destroy jobs, and it can both enhance the quality of our lives and seriously undermine it.It poses challenges for all aspects of our society, including the ways in which we teach and learn (Paul, 1995, p. 127).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».