Effectiveness of Different Teaching Modalities in Human Gross Anatomy Education

With increasing cost and time constraints, anatomy education has shifted away from classic dissection in favor of more effective teaching modalities. Here we investigated different teaching modalities on test performance and student satisfaction in the human gross anatomy laboratory at the New York Institute of Technology College of Osteopathic Medicine (NYITCOM). The anatomy laboratory for first-year osteopathic students at NYITCOM was divided into stations including radiology, case-based learning, prosection, and dissection. Content covered at those stations was tested via anatomy laboratory examinations, comprised of computer-based identification and multiple-choice questions. Our data encompassed 459 first-year medical students taking anatomy in 2022 at both NYITCOM campus sites (Arkansas and New York). We coded 355 exam questions by teaching modality used in the anatomy laboratory. Questions covered in multiple modalities were classified as 'mixed'. Performance among modalities was analyzed using a three-way ANOVA. Prosection-based questions (mean = 75.6) performed significantly worse than dissection (mean = 83.4, p < 0.01) and mixed-modality (mean = 80.7, p < 0.01). There was no significant difference in performance on material taught through dissection, radiology, case-based activity and mixed modalities. In addition, we investigated the effect of an instructor at the case-based activity station using repeated measures ANOVA. Our results indicate that case-based activity stations performed better without an instructor present (mean = 77.4 v. 72.7; p < 0.05). This study showed that teaching via prosection results in poorer performance than other teaching modalities and that dissection or hybrid models appear more effective in knowledge retention. Contrary to actual performance, students rated prosection as the most effective teaching modality. These results come at a critical time when COVID-19 has accelerated the shift away from dissection in favor of virtual methods.