Notice bibliographique
Résumé
The role of trust in traditional face-to-face mentoring has already been investigated in several research studies. However, to our knowledge, very few studies have examined how trust is established in electronic-mentoring relationships. The purpose of the current study is to examine by means of the Mayer et al. (1995) model how e-mentees perceive a prospective e-mentor's trustworthiness and how these perceptions influence the decision to be mentored by a particular e-mentor. A sample comprised of 253 undergraduate and graduate students from the Telfer School of Management at the University of Ottawa participated as potential mentees by completing a survey after having reviewed the selected e-mentor’s profile. The survey employed quantitative and qualitative measurements to assess the mentee's perception of the prospective e-mentor’s level of trustworthiness. In the quantitative section, both the Behavioural Trust Inventory (Gillespie, 2003) and the Factors of Perceived Trustworthiness (Mayer et al., 1999) were measured. The Behavioural Trust Inventory was designed to measure the extent to which a mentee is willing to be vulnerable in e-mentoring relationships. The Factors of Perceived Trustworthiness (ability, benevolence and integrity) were designed to measure these three attributes’ contributions to the extent to which the mentees perceived the e-mentor as being trustworthy. The factorial structure (confirmatory factor analysis) and internal consistency (Cronbach’s alpha) of the constructs were examined. Structural equation modeling was conducted to test the fit of the models (Behavioural Trust Inventory and Mayer et al.) to an e-mentoring context. In the qualitative section, the indicators of trustworthiness were collected by means of an open-ended question and were analyzed by means of content analysis. The results of the quantitative analysis revealed that the models (the Behavioural Trust Inventory and the Factors of Perceived Trustworthiness) have an adequate fit with the e-mentoring model after accounting for some correlated error terms. The results of the qualitative analysis identified some other attributes (apart from ability, benevolence and integrity groups) have an influence on the extent to which the mentees perceived the e-mentor as being trustworthy. The main finding is that the Mayer et al. (1995) model appears to be a suitable device for the measurement of trust in e-mentoring relationships at the initiation phase.
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 | 0,002 | 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».