How supervision and educational supports impact medical students’ preparation for future learning of endotracheal intubation skills: a non-inferiority experimental trial
Notice bibliographique
Résumé
BACKGROUND: Professional education cannot keep pace with the rapid advancements of knowledge in today's society. But it can develop professionals who can. 'Preparation for future learning' (PFL) has been conceptualized as a form of transfer whereby learners use their previous knowledge to learn about and adaptively solve new problems. Improved PFL outcomes have been linked to instructional approaches targeting learning mechanisms similar to those associated with successful self-regulated learning (SRL). We expected training that includes evidence-based SRL-supports would be non-inferior to training with direct supervision using the outcomes of a 'near transfer' test, and a PFL assessment of simulated endotracheal intubation skills. METHOD: This study took place at the University of Toronto from October 2014 to August 2015. We randomized medical students and residents (n = 54) into three groups: Unsupervised, Supported; Supervised, Supported; and Unsupervised, Unsupported. Two raters scored participants' test performances using a Global Rating Scale with strong validity evidence. We analyzed participants' near transfer and PFL outcomes using two separate mixed effects ANCOVAs. RESULTS: For the Unsupervised, Supported group versus the Supervised, Supported group, we found that the difference in mean scores was 0.20, with a 95% Confidence Interval (CI) of - 0.17 to 0.57, on the near transfer test, and was 0.09, with a 95% CI of - 0.28 to 0.46, on the PFL assessment. Neither mean score nor their 95% CIs exceeded the non-inferiority margin of 0.60 units. Compared to the two Supported groups, the Unsupervised, Unsupported group was non-inferior on the near transfer test (differences in mean scores were 0.02 and - 0.22). On the PFL assessment, however, the differences in mean scores were 0.38 and 0.29, and both 95% CIs crossed the non-inferiority margin. CONCLUSIONS: Training with SRL-supports was non-inferior to training with a supervisor. Both interventions appeared to impact PFL assessment outcomes positively, yet inconclusively when compared to the Unsupervised and Unsupported group, By contrast, the Unsupervised, Supported group did not score well on the near transfer test. Based on the observed sensitivity of the PFL assessment, we recommend researchers continue to study how such assessments may measure learners' SRL outcomes during structured learning experiences.
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Comment cette classification a été obtenuedéplier
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 | 0,002 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».