Anatomy Students: The Difference between their Opinions and their Practice in Studying Anatomy
Notice bibliographique
Résumé
Postsecondary institutions are choosing to use digital resources to teach the anatomical sciences, however, studies remain divided about whether these digital resources benefit students over traditional methods such as cadaveric dissection and textbooks/atlases. Recent trends in a systematic human anatomy course at the University of Western Ontario show more students registering in the online section of the course than the traditional face to face (F2F) section. As more students register for online courses, it is important to understand which resources traditional F2F students rely upon to ensure that they do not become disadvantaged should a future anatomy course change to completely online. Students in this systematic human anatomy course (n=127) were surveyed about the usefulness of several anatomy resources, including cadaveric dissection, textbooks/atlases and e‐learning tools, as well as which resources they used while studying. Students were also asked about their preference for digital and printed resources as well as the perceived value of lectures and laboratories. In this undergraduate anatomy course, F2F students attend a weekly 1‐hour cadaveric laboratory where they viewed and manipulated prosections as they interacted with teaching assistants. We hypothesized that F2F students would favor traditional study methods such as printed materials and dissection over the use of digital resources. Furthermore, because of the hand‐on experience of the prosection laboratory, we hypothesized students would value the lab experience over the anatomy lectures. Results showed that students' opinions of resource usefulness did not reflect the resources they chose to study with. When asked about the usefulness of dissection, textbook/atlases, and e‐learning tools students reported all resources as equally useful. However, despite their positive perceptions, they used lecture slides (92%) significantly more than the PowerPoint lab slides (66%), textbooks/atlases (62%), and e‐learning tools (29%; p<0.01). The overwhelming preference for lecture slides may be due to the professor's narrative that accompanies the slides. Student experience suggests that theory assessments are most often based on the material delivered in the slides. When students were surveyed about using traditional printed or digital resources, results showed that students do not follow a consistent style. Chi Square analysis indicated that printed textbooks and atlases were used significantly more often by students than electronic versions of these resources (p<0.01). Conversely, digital PowerPoint lecture and lab slides were used significantly more than their hardcopy counterparts (p<0.01). These results suggest that students prefer to use the resources supplied or suggested to them by their educators. Furthermore, students valued lectures significantly more than laboratories (p<0.001), possible because they perceived that the simple identification style of the laboratory assessment would not reflect the higher order material taught in the lab. Our results suggest that F2F students are more likely to depend on lectures and abstain from using novel methods such as e‐learning tools and thus may be disadvantaged if this course is taught in a fully online fashion using e‐learning tools.
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 | 0,004 | 0,022 |
| 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 | 0,002 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».