A Focused Ethnography of Tenure-Track PhD-Prepared Nursing Faculty Members’ Teaching Experiences
Notice bibliographique
Résumé
Introduction: New faculty’s experiences in a tenure track position have been reported to be stressful and retention of new faculty can be difficult in the competitive academic climate. However, research literature on this topic is predominantly American based. A focused ethnography was undertaken to understand the experience of new PhD-prepared nursing faculty in Canada more fully. Purpose: The purpose of this article is to present findings about the teaching experiences from a research study examining the experiences of 17 new PhD-prepared, tenure-track nursing faculty in their role from nine Canadian universities representing various provinces and regions. Method: A focused ethnography method was used to examine these experiences. Semi-structured virtual interviews of participants were conducted between March 2021 and April 2022. Recruitment stopped when no new information was being found or data saturation was reached. Lincoln and Guba’s (1985) criteria for rigour in qualitative methods underpinned this work. Qualitative methods such as constant comparison of data, memoing, and triangulation of data were integral to enhancing rigor. Roper and Shapiro’s (2000) steps for thematic analysis were followed and Quirkos qualitative software was used to store interviews, memos, and theme development in one secure format. Results: The central themes elucidated from participants’ responses in this study were mentoring, joys and challenges of teaching, institutional supports and processes, and managing a heavy workload. Even if experienced with teaching in the academic setting, participants wanted a mentor to aid with socialization to the institution. Many new faculty reported that time management and heavy workloads were significant challenges during the initial period, but they were developing strategies to aid with balancing the multiple academic demands and personal life demands. Participants expressed joy with the act of teaching and sharing of knowledge even if some participants experienced incivility or bullying from students. Experience with teaching graduate classes varied from institution to institution although most participants had begun to supervise graduate students or even have their student graduate, which was very fulfilling. The impact of the COVID-19 pandemic on these new tenure-track faculty’s teaching experiences was also explored. Conclusion: Implications for practice and potential faculty supports are proposed based upon the findings of this research, in addition to key future research directions.
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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 | 0,003 | 0,001 |
| 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 | 0,001 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 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 ».