Facilitating Reflection-in-Action During High-Fidelity Simulation
Notice bibliographique
Résumé
Background: High-fidelity simulation has become common practice in undergraduate nursing education and highly skilled educators are needed to facilitate these complex learning opportunities. Reflective practice is considered an essential step to learning in simulation, starting with reflection-before-action through prebriefing, and ending with reflection-on-action, through debriefing. However, reflection-in-action may be the hallmark of artistry or mastery of a subject. Therefore, undergraduate nursing simulation facilitators need to develop skills to identify and support learners to reflect-in-action. Methods: I conducted a concept analysis to develop an understanding of the phenomena of reflection-in-action during high-fidelity simulation. I then conducted a descriptive phenomenology study with 11 undergraduate nursing simulation facilitators from eight colleges and universities across Alberta. Participants underwent a semi-structured interview, and Colazzi’s seven step process for analysis was utilized to understand the phenomenon of reflection-in-action as experienced by undergraduate nursing simulation facilitators during high-fidelity simulation. Results: Through the concept analysis, I identified four defining attributes of reflection-in-action: (a) reflection-in-action occurs during simulation scenarios; (b) a critical learning juncture occurs and is identified by the learners; (c) a pause in student action occurs; and (d) knowledge sharing through discussion. The experiences of the participants aligned with the findings from the concept analysis. Participants in the study were experienced simulation facilitators. Despite this, they had little formal training regarding reflection-in-action. Participants were able to identify reflection-in-action during high-fidelity simulation when students paused, collaborated, shared their thinking aloud, and changed their course of action. Barriers to reflection-in-action included learner fear and anxiety, poor simulation design, and inadequate preparation. Participants supported reflection-in-action through prebriefing, remaining curious, and providing cues, prompts, or facilitated paused. The benefits of reflection-in-action include collaborative learning, building confidence, critical thinking, and embedding reflection into practice. Conclusions: Phenomenological exploration of experiences of participants was able to add insights to enhance understanding of a poorly defined subject. The insights from this work may enhance simulation facilitator’s ability to effectively support reflection-in-action within high-fidelity simulation. These findings may contribute to theory development, checklists, and decision trees to support the facilitation of reflection-in-action during high-fidelity simulation. Keywords: nursing, education, simulation, reflection, reflection-in-action
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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 | 0,020 | 0,062 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,008 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».