Virtual Reality Instructional Design in Orthopedic Physical Therapy Education: A Randomized Controlled Trial
Notice bibliographique
Résumé
Introduction. Effective clinical decision-making (CDM) skills are essential for physical therapist practice. The purpose of this study was to compare the effects of virtual reality (VR) patient simulation with those of a traditional standardized patient simulation on the CDM of student physical therapists (SPTs). Review of Literature. Authentic experiential learning opportunities are needed to promote CDM. The effects of VR simulation on the CDM of SPTs are unknown. Subjects. Fifty-nine first-year SPTs participated in this study. Methods. A randomized controlled trial compared the effects of VR with those of standardized patient simulation on several aspects of CDM in 59 first-year students after an upper extremity orthopedic unit. Perceived CDM abilities and metacognitive awareness were assessed before and after allocated instruction. Diagnostic accuracy and diagnostic efficiency were measured during instruction. Student engagement was assessed immediately after instruction and psychomotor skill was assessed 1 week later. Results. Statistically significant within-group differences in CDM were noted after both VR and standardized patient instruction, but no between-group differences were found. Although effect sizes were considered large with either learning experience, the observed experimental effect was greater after a VR experience. No between-group differences were found between metacognitive awareness, diagnostic accuracy, or psychomotor skill assessment. Diagnostic efficiency was statistically significantly greater in the standardized patient condition, while engagement was significantly greater in the VR condition. Discussion and Conclusion. Measures of perceived CDM improved regardless of instructional method; however, the effect size was greater after VR. These findings reveal 2 effective experiential learning options to promote CDM. These results exemplify the normative trajectory of CDM development and recommendations for differentiated curricular instruction. Although resource intensive initially, VR technology appears capable of advancing CDM skills in an efficient manner that may minimize future cost and the faculty facilitation associated with standardized patient instruction.
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 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 | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 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 | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».