Virtual Dissection: An Interactive Anatomy Learning Tool

• Published in: Anatomical sciences education Vol. 14; no. 6; pp. 788 - 798
• Main Authors: Wainman, Bruce, Aggarwal, Akanksha, Birk, Sapriya K., Gill, Jaskaran S., Hass, Katrina S., Fenesi, Barbara
• Format: Journal Article
• Language: English
• Published: United States Wiley 01.11.2021; Wiley Subscription Services, Inc
• Subjects: Ability Grouping; Anatomy; Anatomy - education; Computer Simulation; Cross-Over Studies; Dissection; dissector model; Electronic Learning; fabric model; Familiarity; familiarization; female pelvis; gross anatomy education; health professions education; Humans; Instructional Effectiveness; Laboratory Procedures; medical education; Science Instruction; Simulation Training; Spatial Ability; Student Characteristics; Undergraduate Students; Virtual Reality; visuospatial ability; female pelvis; virtual reality; medical education; health professions education; fabric model; gross anatomy education; familiarization; dissector model; visuospatial ability
• ISSN: 1935-9772; 1935-9780; 1935-9780
• DOI: 10.1002/ase.2035

The novelty of three‐dimensional visualization technology (3DVT), such as virtual reality (VR), has captured the interest of many educational institutions. This study’s objectives were to (1) assess how VR and physical models impact anatomy learning, (2) determine the effect of visuospatial ability on anatomy learning from VR and physical models, and (3) evaluate the impact of a VR familiarization phase on learning. This within‐subjects, crossover study recruited 78 undergraduate students who studied anatomical structures at both physical and VR models and were tested on their knowledge immediately and 48 hours after learning. There were no significant differences in test scores between the two modalities on both testing days. After grouping participants on visuospatial ability, low visuospatial ability learners performed significantly worse on anatomy knowledge tests compared to their high visuospatial ability counterparts when learning from VR immediately (P = 0.001, d = 1.515) and over the long‐term (P = 0.003, d = 1.279). In contrast, both low and high visuospatial ability groups performed similarly well when learning from the physical model and tested immediately after learning (P = 0.067) and over the long‐term (P = 0.107). These results differ from current literature which indicates that learners with low visuospatial ability are aided by 3DVT. Familiarizing participants with VR before the learning phase had no impact on learning (P = 0.967). This study demonstrated that VR may be detrimental to low visuospatial ability students, whereas physical models may allow all students, regardless of their visuospatial abilities, to learn similarly well.