Enhancing Neuroanatomy Learning with 3D Visualization: A Study on 3D Module Efficacy Using a Newly Created RRR Survey

Background: Neuroanatomy is challenging given the voluminous content, limited access to cadaver-based learning, and the reduction of curriculum hours. Digital 3D visualization software can be promising alternatives to traditional 2D resources, especially in regard to the spatial structures of the brain. However, their effect on student motivation, confidence, and academic performance remains ambiguous. Objective: This study aimed to evaluate the effectiveness of a newly developed 3D neuroanatomy module using a novel Reaction-Relevance-Results (RRR) survey and a Confidence in Topics scale. It further tested student performance, comparing differences based on gender and prior neuroanatomy exposure. Methods: A prospective within-subject pre-post study design was implemented among 35 students at the University of Louisville School of Medicine. Participants first studied from traditional 2D resources, followed by engagement with an interactive 3D neuroanatomy module. Surveys and tests were administered before and after the 3D intervention. Statistical analyses included Wilcoxon signed-rank tests, Mann-Whitney U tests, factor analysis, and effect size estimation. Qualitative feedback was also thematically analyzed. Results: Post-intervention, significant improvements were observed in RRR scores (Reaction: p = .002; Relevance: p < .001; Results: p < .001; Overall: p < .001), confidence ratings across superficial and deep structures (Overall: p < .001), and performance on anatomy tests (Overall: p < .001). Students with no prior neuroanatomy experience reported greater perceived gains, though actual performance did not differ significantly. Gender-related differences in software usability and perceived difficulty of deep structures were noted, but both sexes showed similar improvements in test scores. The 3D module particularly enhanced understanding of deep brain structures, reducing the performance gap between superficial and deep regions. Conclusion: 3D neuroanatomy software can enhance student motivation, confidence, and learning outcomes when compared to 2D resources, especially for complex internal brain structures. While some gender and experience-based spatial ability differences exist, 3D software appears to be able to lessen these gaps. Suggestions for future research include optimizing these tools for a diverse population and testing long-term retention outcomes.