Development of a novel anatomy education tool for teaching dermatomes, cutaneous nerve maps and surface anatomy concepts: The Dry‐Erase Anatomy Mannequin (DrEAM)
Notice bibliographique
Résumé
Dermatomes are areas of skin whose sensory innervation can be traced back to a single spinal nerve. Knowledge of dermatome patterns is fundamental to the study of human surface anatomy and is diagnostically useful for a range of neurologic pathologies and injuries. Dermatomes and other surface anatomy concepts are often visually depicted in lectures and textbooks through illustrations. Such visual depictions are two‐dimensional and typically only show the anterior and posterior surface maps of the body side‐by‐side. However, dermatomes and other surface projections, such as cutaneous nerve maps, are 3D shapes that often pass continuously from anterior to posterior. Thus, learning these concepts from such limited visual depictions can provide perceptual challenges to anatomy students who must eventually apply 2D mental schema onto their 3D patients. Additionally, there is a relative lack of emphasis placed on teaching surface anatomy, both within textbooks and as part of formal anatomy curricula. Various instructional methods and low‐fidelity models have been developed by others attempting to convey surface anatomy concepts including body painting exercises and drawing on cloth‐covered anatomy models, to name a few. Here, we report the development of a new educational tool: The Dry‐Erase Anatomy Mannequin (DrEAM). Our novel low‐fidelity learning tool consists of common retail clothing mannequins coated in a commercially available dry‐erase finish and allows students to mark, erase and remark 3D surface anatomy shapes and contours, such as dermatomes, using dry‐erase markers. We also document our recent deployment of the tool as part of our “Dermatome Day” ‐ an informal, interactive extracurricular anatomy teaching session for undergraduate medical students. Other potential use‐cases for the DrEAM in teaching surface anatomy concepts within a range of health professions curricula are further proposed. Lastly, we discuss the formal evaluation of the DrEAM to determine its efficacy in improving student learning outcomes related to surface anatomy concepts as compared to other traditionally used methods. We hypothesize that its use will promote increased understanding of surface anatomy concepts amongst medical students and lead to their improved performance on related test questions when compared to more traditional teaching methods. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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 | 0,001 | 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 ».