Anatomy in a New Curriculum: Using Digital Media to Facilitate the Learning of Anatomy in the Medical Curriculum
Notice bibliographique
Résumé
Introduction The advances in technology have allowed teachers to develop new ways to teach their course materials to their students. This has ranged from using educational videos to developing online learning modules that students may complete at their pace and time. Although these advances in enhancing student knowledge have been made in many subjects, there are limited resources available to students for the purposes of learning anatomy. One area that needs to be expanded is one of educational anatomy video tutorials/lessons. Objectives This project was designed to create an educational video tutorial/lesson that provides a step by step tutorial that the students can follow to complete their anatomy lab. The video is designed to complement the lab component rather than replace it as we have realized that there is no substitute to viewing the material first hand. The video would allow students to prepare for the lab and upon its completion, they may refer back to the video and use it as a study tool. Methods To begin the cadaver was dissected and prepared so that the anatomical structures that needed to be identified were properly exposed for the filming. The filming was done in a stepwise manner, where the anatomical structures were identified and commented on throughout the video. During the editing, process animations were added to tag key anatomical structures and a quiz was added towards the end to allow students to test their knowledge of the materials in the video. Results To gather the efficacy of the videos and receive feedback we gave the students a survey to conduct prior to and after their lab. The results showed that more than 95% of students felt that the video helped them prepare for the upcoming lab dissection. While 98.9% of students felt that they would like to have a similar lab video for labs in the future. Also, 93% of the students stated that they would like to use the videos to study for their exams. Conclusion Due to the positive responses received it can be concluded that the use of video tutorials in teaching anatomy is an effective tool that can be implemented alongside the lecture material and cadaver dissections to enhance the learning of students. 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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,018 | 0,003 |
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 source (Gemma direct ou Codex distillé), 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 ».