The REDIH experience: an emerging design to develop an effective training program for graduate students in reproductive science
Notice bibliographique
Résumé
BACKGROUND: A training program in Reproduction, Early Development, and the Impact on Health (REDIH) was initiated in 2009 by researchers specializing in biomedical, clinical, population health, and ethics research from seven collaborating universities in Quebec and Ontario, and Health Canada. This paper reports the findings from the first three years of the 6-year program. OBJECTIVES: The objective of the REDIH program is to provide increased opportunities for excellent training in reproduction and early development for graduate students and fellows, in order to build research, clinical, regulatory, decision-making, and industry capacity in Canada. METHODS: A mixed methods approach was used to evaluate the REDIH training program, so as to combine the strengths of both qualitative and quantitative studies. A total of four focus groups (two with mentors and two with trainees) were run during the June 2012 REDIH meeting. Surveys were administered directly after each training module. The W(e)Learn framework was used as a guide to design and evaluate the program and answer the research questions. RESULTS: The data from the analysis of the focus group interviews, in corroboration with the survey data, suggested trainees enjoyed and benefited from the REDIH experience. Trainees provided several examples of new knowledge and skills they had acquired from REDIH sessions, regarding reproductive and early developmental biology, and health. A few trainees who had been in the program for over a year provided examples of knowledge and skills acquired during the REDIH session that they were using in their place of work. Next steps will include following up on REDIH graduates to see if the program has had any impact on trainees' employment opportunities and career development. CONCLUSION: Trainees and mentors concluded that the curricular design, which focuses on modules in 2-day learning sessions over a 6-year period, with opportunities for application in the workplace, enabled the sessions to be tailored to the outcomes of the formative evaluation. By sharing our experiences with REDIH, we hope that others can benefit from this unique emerging design, which focuses on the flexibility and receptivity of the mentors, and results in a program that lends itself to curriculum modification and tailoring as learners' needs are solicited and addressed.
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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 | 0,023 | 0,012 |
| 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 | 0,003 | 0,003 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,003 | 0,007 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».