Teachers in the Trenches: Exploring Canadian-Certified Early-Career Teachers' Experiences of Turnover and Retention in International Schools in China
Notice bibliographique
Résumé
Teacher turnover, often referred to as teacher attrition or migration, has been a growing worldwide concern for many years, particularly for teachers within their first five years of the teaching profession. Multiple studies have been conducted that identify the causes of teacher turnover and the possible teacher retention strategies within schools that can reduce the impact of this problem. Despite having knowledge of the factors that cause teacher turnover and the potential solutions for teacher retention, much of the research available on teacher turnover is both US-based and quantitative in nature, and as a result the unique and descriptive accounts of the human voices that experience the issue are often underrepresented from outside North America. \nInspired by my own experiences while working in an international school, this phenomenological study was conducted with the purpose of discovering and exploring the unique experiences of Canadian-certified early-career teachers surrounding the challenges, barriers and supports connected to teacher turnover and retention decisions in international secondary schools that use a Canadian curriculum in China. In order to carry out this study, a combination of a survey and individual interviews was used. Surveys were analyzed descriptively while interview data were audio recorded, transcribed verbatim and analyzed using a general inductive approach. \nThe findings of this study suggest that turnover and retention decisions in China are highly individualistic in nature and depend on a multitude of different contextual and individual factors. However, five main themes emerged from participants’ accounts which were influential in turnover and retention decisions. They included: participants motivations for working in China; barriers that influence turnover decisions; existing supports to overcome turnover challenges; supports teachers feel would be beneficial to enhance retention decisions; and, advice from teachers to teachers. By exploring these themes, a more comprehensive understanding of beginning teachers’ perceptions and experiences surrounding the phenomenon of turnover and retention decisions in international schools in China emerged. Moreover, the importance of supporting early-career teachers both individually and professionally during the transition period into the teaching profession was highlighted throughout this study.
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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 | 0,000 | 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 | 0,000 | 0,000 |
| 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 ».