A Guide to the Anatomy of the Anterior Abdominal Wall: Examining the Impact of Virtual Dissection on the Learner's Experience
Notice bibliographique
Résumé
Introduction As technology continuously improves, there is an increasing demand for higher quality educational resources. The internet has decreased barriers of accessing quality educational resources for students of all backgrounds. In medical education, the costs of obtaining and maintaining cadavers for the understanding of the human body can be a major expense. Furthermore, due to the effects of the COVID‐19 pandemic in minimizing in‐person learning, the demand for quality anatomy resources is at an all‐time high. Objectives This project aimed to create a quality and informative dissection of the anterior abdominal wall for learners, and to investigate the impact of virtual learning as a supplementary resource. Methods A complete and skilled dissection of the anterior abdominal wall was recorded. In addition, specific anatomical features were explained during the recording. The footage was then edited via Camtasia, a video editing software, where visual features, audio features, a comprehensive quiz, and the video's introductory and outgoing effects were prepared. The final production was uploaded to YouTube and prepared for medical students at the University of British Columbia, as well as the online community. A survey was linked at the end of the video, which was open for anyone who watched the production. Results People from across the world watched and provided feedback on this dissection. While a majority of feedback received came from respondents in North America, some comments were received from viewers in Brazil, India and China. 94.7% of respondents were actively completing or had completed an MD Degree and 5.3% of participants were actively completing or had completed an MBBS program. 84.2% of participants used this resource to prepare for their anatomy labs and dissections, 63.2% used this video to prepare for their anatomy lectures, and 68.4% of people used this to prepare for their examinations. Overall, 21.1% of respondents agreed and 78.9% of respondents strongly agreed that this online resource assisted them in fulfilling their purposes of watching this video. Conclusion Responses from the online survey indicate that using gross anatomy dissection videos helped improve the learning experience of anatomy and more resources should be created to fill this demand. Video Link: https://youtu.be/_Cl1djsxQlY
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 | 0,001 | 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 | 0,001 | 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 ».