Mentor or evaluator? Assisting and assessing newcomers to the professions
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Notice bibliographique
Résumé
Purpose A four‐year longitudinal study was conducted on the school‐to‐work transition in four professions traditionally called “helping professions,” namely education, social work, occupational therapy, and physiotherapy. One goal of the study was to understand the nature and process of the mentoring relationships that develop and sustain newcomers in their professional life, especially the possible tension between the roles of mentor and evaluator. It was expected that this would help us in our jobs of preparing student practitioners and supporting their mentors and would offer models of practice suitable for other occupations. Design/methodology/approach Teams of researchers visited university students involved in professional training and engaged in a practicum during their final year at university. The students and their supervisors were interviewed separately according to a semi‐structured protocol, and each interview, lasting between 40 and 60 minutes, was audiotaped and transcribed. Findings An inherent contradiction between supervision‐as‐mentoring as the literature defines it and supervision‐as‐evaluation – as the universities and professions demand was observed. Evaluation as it is practiced often includes intangibles, even though the intended evaluation seems well‐defined. Practical implications Although this study was focused on practice in four particular professions, it is believed that the findings may be extrapolated to any enterprise where experienced practitioners are placed in a supervisory role with newcomers and are expected to perform the potentially conflicting role of mentor and evaluator. If the same person must mentor and evaluate the newcomer, they must be trained in these roles, evaluation guidelines must be clearly defined, and dialogue is of prime importance. Originality/value The paper focuses on the role of the universities in the preparation of new entrants to the “helping professions” and offers some suggestions for their support – which are generalizable to any workplace where beginners are trained, mentored and evaluated.
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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 | 0,006 | 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 | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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