Faculty development: What do we know about barriers, enablers, and satisfaction levels among African oncology faculty?
Notice bibliographique
Résumé
11023 Background: Faculty development (FD) programs and initiatives have been shown to improve teaching, learning, and overall satisfaction levels of academic faculty. However, these benefits are not fully realized in resource constrained settings like those found in some Sub-Saharan African academic institutions, that often face many FD challenges. Improving FD activities in the region may enhance the capacity of oncology faculty to address these challenges. We sought to examine African oncology faculty’s satisfaction and the perceived enablers and barriers with current FD opportunities. Methods: We randomly surveyed oncology faculty ( n = 21) through the African Organization for Research and Training in Cancer (AORTIC) listserv and conducted semi-structured interviews with nine ( n = 9) faculty involved in African oncology training programs to ascertain their perspectives on faculty development activities including curriculum development, teaching, and learning. All survey respondents and interview participants are current members of the AORTIC. Descriptive and inferential statistical techniques, and thematic analysis were used to analyze the survey and interview data respectively. Results: Interim survey results revealed that 64% of academic oncology faculty believe that there are barriers to their FD at their current academic institutions. Barriers cited for FD from the interviews include the competitive nature of FD courses and programs, limited online learning opportunities, poor internet access, time constraints, language barriers, and high costs associated with FD activities. A significant minority of the survey respondents (43%) were dissatisfied with their overall FD. Access to curriculum development opportunities (χ2 = 10.97, p = 0.001) and longer duration of practice (χ2 = 7.9, p = 0.019) were significantly associated with an increased overall satisfaction with FD of oncology faculty. Themes emerging from the interviews also revealed that participants believe that addressing issues relating to access to local institutional support and opportunities including funding, reduced fees for individuals from low- and middle-income countries, getting time off work from local institution, and availability of online FD education will enable them to increase their participation in FD activities. Conclusions: A considerable number of African oncologists face many FD challenges and are therefore dissatisfied with the current state of their FD. Incorporating the recommendations offered by participants into faculty development planning activities may improve faculty satisfaction levels, remove barriers, and improve outcomes for learners. Also, the finding that access to curriculum development opportunities leads to increased levels of satisfaction with FD could guide FD for faculty in African oncology training programs.
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 | 0,007 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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; 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 ».