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Integrating plastinate-derived three-dimensional scans into computer-based anatomy practical examinations
Rosaysela Santos1, Jordan Moberg Parker1, Frank H Thai1
1Department of Biomedical Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, USA.
None:
Anatomy instruction increasingly incorporates three-dimensional (3D) digital resources; however, the assessment of practical anatomy knowledge often relies on two-dimensional (2D) images. This misalignment may limit the authenticity of computer-based anatomy practical examinations (APEs). We implemented 3D scans of plastinated human specimens in APEs and examined student usage patterns and perceptions. High-resolution 3D scans of plastinated specimens were embedded into APE items. Fifteen anatomy practical questions were analyzed across three consecutive cohorts of first-year medical students. Usage analytics captured the frequency of 3D scan views during exams and were compared with item difficulty. Student perceptions of 2D and 3D resources were assessed via a post-exam questionnaire. Quantitative data were analyzed using nonparametric statistics, and qualitative responses were analyzed thematically. Students consistently accessed 3D scans during APEs, with significantly higher usage for more difficult exam items. A direct correlation was observed between item difficulty and 3D scan views (r2 = 0.43, p < 0.01). Usage varied by anatomical unit, with lower engagement for nervous system items relative to cardiovascular/pulmonary and musculoskeletal items. Students rated both 2D images and 3D scans as helpful, with a nonsignificant trend favoring 3D scans. Qualitative responses highlighted improved spatial orientation and contextualization with 3D scans, alongside concerns regarding load time and navigation, while 2D images were valued for efficiency. Plastinate-derived 3D scans serve a complementary role in computer-based anatomy practical assessment. Integrating optimized 3D resources may enhance the authenticity of APEs, particularly for spatially complex anatomy, while maintaining efficiency in high-stakes testing environments.

