Clinical neuroanatomy teaching at Peking University Health Science Center: Evolution, current practice, and future...

Area of Science:

• Medical Education
• Neuroscience
• Educational Technology

Background:

• Neuroanatomy is a challenging medical subject, often causing "neurophobia" and deterring students from neurology.
• Traditional neuroanatomy curricula face challenges in engaging students and fostering deep understanding.

Purpose of the Study:

• To evaluate a technology-enhanced, integrated neuroanatomy curriculum at PKUHSC.
• To assess the impact of innovations like virtual reality, diffusion tensor imaging, and AI on student learning and confidence.

Main Methods:

• Implemented a blended learning model: lectures, labs, team-based learning (TBL), and case-based learning (CBL).
• Integrated technologies: virtual reality (VR), diffusion tensor imaging (DTI), 3D real-specimen scanning, knowledge graphs, and AI-powered formative assessments.
• Conducted student surveys and analyzed test performance data.

Main Results:

• 100% of students found 3D models helpful for understanding spatial relationships; >95% reported increased learning confidence.
• Smart course platform use positively correlated with anatomy understanding and test performance (β=1.24, p<0.001).
• Students using adaptive practice sessions achieved significantly higher scores (9.12±0.98) vs. non-users (7.12±2.41, p<0.001), with high scorers increasing from 24.0% to 83.1%.

Conclusions:

• A theoretically grounded, technology-enhanced, and clinically integrated curriculum significantly improves neuroanatomy learning outcomes.
• Hybrid models complementing traditional dissection and data-driven formative assessments are key transferable lessons.
• This approach offers a reproducible model for modernizing neuroanatomy education globally.