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Notice bibliographique
Résumé
Over the last decades, there has been more and more interest in various modes of networked learning, knowledge creation, communities or practice (CoPs) but there is not yet a clear identification of the conditions to succeed in such initiatives. This interest for CoPs stems from the fact that organizations expect substantial gains from knowledge development and networked learning. Communities of practice are seen in many organizations as a source of networked learning, and ultimately of competitiveness and innovation. The interest for communities of practice arises from this objective of learning and innovation, but it is viewed as a specific form of learning and sharing, in principle more centred on the individuals and their exchanges than on “management” by the firm, although the firm does seem to have a role to play in fostering such initiatives. Thus, the use of communities of practice has emerged as a way to develop collective skills and organizational learning, in order to foster innovation and success for organizations. In this paper, we identify the conditions of success or failure of communities of practice as a mode of networked learning, knowledge management and knowledge sharing, as these conditions have not yet been established. We first define this new form of learning and knowledge sharing through communities of practice. We then present some of the results concerning success, or more precisely attainment of objectives, as success can be defined in various ways. We do this on the basis of 7 case studies of communities of practice implemented in firms. The empirical results are based on a questionnaire survey administered to the participants of these communities of practice, but also on qualitative interviews and regular work and exchanges with some of the animators and participants in these communities of practice. We highlight some interesting differences observed according to age and gender, as well as some limits and challenges that were observed in the learning and sharing process, which are often underestimated. We mainly highlight the factors which explain success, defined as attainment of objectives, and these are : commitment and motivation of participants for the attainment of objectives, as well as the presence of a leader, animator or steward.
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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 | 0,004 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 découle