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Enregistrement W2900864799 · doi:10.1017/cts.2018.225

2494 Selectives: Implementing self-directed collaborative selectives as part of a curriculum for pre-health care professional students

2018· article· en· W2900864799 sur OpenAlexaff
Leonor Corsino, Stephanie A. Freel, Melanie J. Bonner, Joan Wilson, Christie McCray, Maureen D. Cullins, Linda Lee, Kathryn M. Andolsek

Notice bibliographique

RevueJournal of Clinical and Translational Science · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueHealth and Medical Research Impacts
Établissements canadiensProcess Research Ortech (Canada)
Organismes subventionnairesnon disponible
Mots-clésPracticumCurriculumMedical educationHealth careMedicinePopulationPopulation healthPsychologyNursingPolitical sciencePedagogyPublic health

Résumé

récupéré en direct d'OpenAlex

OBJECTIVES/SPECIFIC AIMS: To provide students an opportunity to select health care-oriented course work that reflects both their interests and the increasingly diverse spectrum of health professions education and health care careers. To increase the opportunity for students to enter professional schools and health care professions with enhanced engagement and experience. METHODS/STUDY POPULATION: The 4-credit elective (Selective) curriculum is a component of the 38 credit Duke School of Medicine Master of Science in Biomedical Sciences (MBS) program which is completed over 10.5 months. Students work closely with their advisors to choose activities that reflect their interests. Selectives are offered by an array of schools, institutes, and programs within Duke University, including: the School of Medicine, School of Law, Global Health Institute, Bioethics and Science Policy Master Program, Clinical Research Training Program, Center for Documentary Studies, and Medical Informatics. Students may also pursue directed studies in areas such as health policy, or an inter-professional trip to Honduras. In addition to the course-based Selectives, three research practicum options are offered: Community Engagement, Clinical Research (Duke Office of Clinical Research), and a self-selected mentored research experience. Finally, the MBS program offers 2 in-house specific Selectives: Fundamentals of Learning: Theory and Practice, and Planning for Health Professions Education. RESULTS/ANTICIPATED RESULTS: The MBS program accepted its first cohort of students in June 2015. Two cohorts have graduated and the third has begun (n=30, 2016; n=42, 2017; n=43 enrolled, 2018). Our students come from diverse background with a third from populations historically underrepresented in STEM due to race/ethnicity, and another third underrepresented due to other factors such as low socioeconomic status, first generation to college, LGBQT, and those from rural and immigrant communities. Thus far, Selective distribution has been: Clinical research practicum (7, 2016; 14, 2017; 9, 2018); Mentored research practicum (2, 2016; 1, 2017); Community engagement practicum (7, 2016; 4, 2017; 5, 2018); Planning for health professions educations (14, 2016; 32, 2017; 33, 2018), Fundamentals of learning: Theory and Practice (7, 2016; 17, 2017; 18, 2018); documentary film (1, 2016); inter-professional trip to Honduras (2, 2016, 2, 2017). Since the implementation of the curriculum, at least 53 of 70 students who have applied (76%) were admitted to health professions or other graduate schools despite having lower initial MCAT and undergraduate GPAs in aggregate than the average of students who matriculate to allopathic medical school programs: 41 to medical schools, 3 to dental school, 2 each to osteopathic and physician assistant schools and 1 each to physical therapy, business school and law school. Eighteen of the 2016 graduates, and 21 of the 2017 graduates work in research for their gap year following graduation, the majority being employed in our institution’s research programs providing a pipeline of trained research assistants and coordinators. DISCUSSION/SIGNIFICANCE OF IMPACT: Lessons learned by implementing our curriculum include the following: (1) students are eager to explore different areas of health care; (2) collaboration across schools, centers, departments, institutes, and offices increases our ability to identify common areas of interest; (3) implementing a diverse curriculum can be challenging due to the need for significant organization and planning; (4) the diversity of courses can be a source of confusion when there is a lack of standardization in learner expectations; (5) continued collaboration across, schools, centers, institutes programs, health professions and sections requires a significant amount of time and expertise. However, our programs demonstrate significant positive impacts both on students and at the institutional level. Our program shows that a diverse curriculum leads to a high number of students engaged in pursuing and successfully continuing a health profession education. Institutional benefits include a robust pipeline for a diverse research workforce.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,014
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,146
Score d'incertitude au seuil0,994

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0070,014
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,099
Tête enseignante GPT0,591
Écart entre enseignants0,492 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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