Reimagining dissection lab preparation ‐ the role of digital media in anatomy education
Notice bibliographique
Résumé
Introduction Learning materials provided to students prior to anatomy dissection labs have classically been in the form of written instructions and images from prosections. However, these materials can be difficult to interpret, especially for beginner students. With the advancement of technology, educational curricula are exploring the integration of digital platforms to supplement more traditional teaching methods. Goal To investigate the utility of a video‐based guide for approaching dissection. Methods A video dissection guide was created demonstrating the dissection of the superficial back. The video outlines the anatomy, technique, procedure, and includes review questions. The video was made available online through YouTube, along with a feedback survey. A secondary video dissection guide highlighting the dissection of the deep back was subsequently produced and made available in the same avenue. Results After two months, the superficial back dissection video has received more than 1,400 views. Feedback was received from 68 respondents; a majority of whom were female (63.2%), aged 20–24 (60.3%), and had a current education level of a postgraduate degree or professional degree (54.4%). The majority of respondents agree or strongly agree that the video presented the anatomy in a clear and organized fashion (95.6%), enhanced their learning of the anatomy (100%), familiarized them with dissection tools and how to use them (89.7%), familiarized them with methods and techniques for dissection (92.6%), was more effective than a dissection guide (97.1%), and was more effective for learning anatomy than a textbook (88.2%). A poll of 54 respondents found that most agree or strongly agree that the video is a valuable resource for review/test preparation (88.9%). Preliminary survey results for the deep back dissection video indicates that, of 15 respondents, the majority agree or strongly agree that the video presented the anatomy in a clear and organized fashion (100%), enhanced their learning of the anatomy (93.3%), was more effective than a dissection guide (93.3%), and is a valuable resource for initial learning of dissection/anatomy (100%) and review/test preparation (86.7%). Conclusion In summary, digital media in the form of video‐based dissection guides may be a useful tool to incorporate into educational curricula for teaching gross anatomy of both superficial and deep structures. Future goals include the incorporation of clinically relevant information to dissected anatomical structures.
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 | 0,000 | 0,000 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».