Visual-spatial Intelligence and Learning Modality Preference for Neuroanatomy Comprehension Among Medical Students.

Autor: Ilyas, Muhana Fawwazy, Nanang Wiyono, Ghozali, Dhoni Akbar, Hastami, Yunia, Handayani, Selfi, Munawaroh, Siti, Muthmainah, Muthmainah, Triniputri, Winastari Yarhanim, Dwi Widodo, Dhito Putranto, Khoirumuna, Khonsa
Zdroj: Education in Medicine Journal; 2024, Vol. 16 Issue 1, p149-164, 16p
Abstrakt: Neuroanatomy comprehension, an essential aspect of medical education, is important for understanding and diagnosing neurological cases. However, neuroanatomy is perceived as one of the most difficult subjects, thus contributing to the prevalence of neurophobia among medical students worldwide. This cross-sectional observational analytic study aimed to investigate the association of visual-spatial intelligence (VSI) levels and learning modality preferences with neuroanatomical comprehension levels among 229 freshman medical students of Universitas Sebelas Maret (UNS), Indonesia. VSI level was measured using the Revised Purdue Spatial Visualization Test: Visualization of Rotations (PSVT:R); learning modality preference using the VAK or visual (V), auditory (A), and kinaesthetic (K) learning styles survey; and neuroanatomical comprehension level using neuroanatomy final examination. The results show a significant correlation between VSI and comprehension of neuroanatomy (r = 0.229; p < 0.0001), with notable differences in learning modality preferences. Students with visual preferences (V, VA, VK, and VAK) exhibited higher neuroanatomical comprehension compared to those without visual preferences (A, K, and AK). Visual learning modality preference was a significant predictor of VSI (β = 0.206; p = 0.006) and neuroanatomy comprehension (β = 0.161; p = 0.033), and VSI was a significant predictor of neuroanatomy comprehension (β = 0.305; p < 0.0001). This study highlights the importance of considering VSI and learning modality preference in the context of neuroanatomy comprehension among medical students. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index