Can virtual dissection be effectively performed remotely? Pilot study from a second‐year neuroanatomy laboratory at a large distributed medical school
Notice bibliographique
Résumé
Background Virtual dissection is an emerging area in undergraduate medical anatomy teaching as it incorporates clinical radiology into students' dissection experience. Virtual dissection is performed on near life‐size anatomy visualization tables (AVTs), which are very similar to hospital radiology workstations. Patient CT scans are loaded into these tables and through powerful software interactions students work together to manipulate the data and perform their dissection. Recent technology developments have allowed for some of the virtual dissection functionality to be accessed remotely on hand‐held devices (e.g. tablets). While this makes the virtual dissection experience feasible in a distributed program, it is unclear whether this “lighter” version of the software provides students with the same learning opportunities as virtual dissection performed on an AVT. Methods During a second‐year cadaveric neuroanatomy laboratory, 288 medical students were invited to use an online application to access content from an AVT remotely. Students accessed and examined three clinical radiology cases on their device at both the main teaching campus as well as at the distributed campuses. Following the laboratory session, students completed an anonymous online survey to assess their experience. All students had performed virtual dissection on an AVT during their first year of medical school allowing them to compare their experiences. Results The survey response rate was 7.9% across four separate campuses. 52.2% of students were located on the main campus and 47.8% were from one of the distributed campus. Most students (74.0%) “agreed” or “strongly agreed” that virtual dissection enhanced their understanding of the cadaveric content presented in the laboratory and their understanding of radiology anatomy. In addition, most students 74.0%) “agreed” or “strongly agreed” that virtual dissection enhanced their awareness of the clinical applications of the anatomy. Students reported that they would have liked to have more ability to virtually dissect the cases and more time to study them. Conclusions Virtual dissection is a valuable addition to a second‐year medical undergraduate neuroanatomy cadaveric laboratory. However, students reported that performing the dissection on their tablets was not as effective as performing it on the AVT. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».