Seeing in Stereo: Exploring the Relationship between 3D Anatomical Resources and Spatial Ability
Notice bibliographique
Résumé
Three‐dimensional (3D) digital anatomical models have been shown to promote student engagement and satisfaction, while demonstrating complex spatial anatomical relationships. However, there is limited research to suggest that 3D digital anatomy models are more effective in improving spatial anatomy performance over traditional resources, particularly for students with varying spatial visualization ability (Vz). The present study aims to investigate the educational effectiveness of a digital 3D stereoscopic anatomy model compared to a 2D visualization and cadaveric specimen of the human pelvis. This study also aims to examine the relationship between Vz and learning from a 3D stereoscopic anatomy model of the human pelvis. We hypothesized that participants learning from the 3D stereoscopic model of the pelvis would improve performance overall on an anatomy knowledge post‐test more than participants learning from a 2D visualization or cadaveric specimen, and that low Vz participants would benefit more from the use of the 3D stereoscopic model compared to their high Vz counterparts. Participants were recruited from the Post‐Baccalaureate, Medical Year 1, and Medical Year 2 classes at Lake Erie College of Osteopathic Medicine (n=64). All participants completed a demographic survey and Mental Rotations Test (MRT) pretest to determine initial Vz. Participants were then sorted into three groups, normalized for MRT score, sex, and education level. Each group was invited to a brief learning session using a 3D stereoscopic model (n=21), 2D visualization (n=21), or cadaveric specimen of the pelvis (n=22) respectively. The 3D model, developed using Amira ® software, was projected stereoscopically using a dual projection system. All participants completed a pre‐ and post‐test in each session, consisting of 10 spatially‐oriented multiple choice questions pertaining to pelvis anatomy. Results show no significant difference in improvement from pre‐test to post‐test between the three groups. A linear regression analysis showed no significant correlations between MRT score and anatomy test improvement; however, Post‐Baccalaureate (novice) participants with high Vz tended to improve more after learning with the 3D model than Post‐Baccalaureate participants with low Vz. Participants with high Vz, irrespective of education level, improved more on a spatial anatomy test after learning with the 3D model compared to either of the other resources. Contrary to current literature, participants with low Vz appeared to benefit most from the 2D visualizations. Results of this study can be used to inform resource selection and curriculum design for health professional students, with special attention to the impact of Vz on learning. Support or Funding Information Funded by a LECOMT Research Support Grant. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0,000 | 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 ».