The PhD Experience: A Review of the Factors Influencing Doctoral Students’ Completion, Achievement, and Well-Being
Notice bibliographique
Résumé
Aim/Purpose: Research on students in higher education contexts to date has focused primarily on the experiences undergraduates, largely overlooking topics relevant to doctoral students’ mental, physiological, motivational, and social experiences. Existing research on doctoral students has consistently found mental and physical health concerns and high attrition rates among these students, but a comprehensive understanding of these students’ experiences is still lacking. Background: The present review paper aims to offer deep insight into the issues affecting doctoral students by reviewing and critically analyzing recent literature on the doctoral experience. An extensive review of recent literature uncovered factors that can be readily categorized as external and internal to the doctoral student; external factors include supervision, personal/social lives, the department and socialization, and financial support opportunities, while internal factors motivation, writing skills, self-regulatory strategies, and academic identity. Methodology: 163 empirical articles on the topic of doctoral education are reviewed and analyzed in the present paper. Contribution: The present paper represents a comprehensive review of the factors found to influence the experiences (e.g., success, satisfaction, well-being) of doctoral students in their programs. It represents a unique contribution to the field of doctoral education as it attempt to bring together all the factors found to date to shape the lived experiences of doctoral students, as well as evidence-based ways to facilitate students’ success and well-being through these factors. More specifically, the present paper aims to inform students, faculty, and practitioners (e.g., student support staff) of the optimal practices and structures uncovered to date, as most beneficial to doctoral students in terms of both academic success and well-being. Impact on Society: Decreases to doctoral students’ well-being as they progress in their programs, financial struggles, and the notable difficulty in maintaining a social life/family responsibilities have been widely discussed in popular culture. The present paper aims to highlight these, and other, issues affecting the doctoral experience in an attempt to contribute to the conversation with comprehensive empirical evidence. By facilitating discussions on the issues that play a role in the attribution and dissatisfaction of existing doctoral students, and perhaps deter potential doctoral students from ever entering doctoral education system, we hope to contribute to a student-cantered focus in which departments are concerned with the academic success of doctoral students, but also equally concerned with maximizing students’ well-being in the process of attaining a doctoral degree. This, we hope, will enhance the societal perception of doctoral education as a challenging, yet worthwhile and rewarding process. Future Research: Future research in which the confluence of the factors discussed in this review, particularly with respect to the cross-cutting impact of socialization variables, is recommended to provide a sufficiently in-depth examination of the salient predictors of doctoral student development and persistence. Future research efforts that steer away from single-factor foci to explore interactive or redundant relationships between factors are thus recommended, as are analyses of the potential effects that changes to one aspect of the doctoral experience (e.g., motivational interventions) can have on other factors. Finally, studies employing various alternative methodologies and analytical methods (e.g., observational, questionnaire, experimental, experience sampling) are similarly expected to yield valuable knowledge as to the nature and extent of the afore-mentioned and novel contributing factors, as well as the utility of student intervention programs aimed at improving both the personal and professional lives of doctoral students internationally
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».