How Computer-Assisted Learning Influences Medical Students' Performance in Anatomy Courses

Anat Sci Educ. 2020 Jun 21. doi: 10.1002/ase.1997. Online ahead of print.

Abstract

Anatomy is an essential subject of the medical curriculum. Despite its relevance, the curricular time and logistical resources devoted to teaching anatomy are in decline, favoring the introduction of new pedagogical approaches based on computer-assisted learning (CAL). This new pedagogical approach provides an insight into students' learning profiles and features, which are correlated with knowledge acquisition. The aim of this study was to understand how training with CAL platforms can influence medical students' anatomy performance. A total of 611 medical students attending Musculoskeletal Anatomy (MA) and Cardiovascular Anatomy (CA) courses were allocated to one of three groups (MA Group, CA Group, MA + CA Group). An association between the performance in these anatomy courses and the number of CAL training sessions was detected. In MA Group (r = 0.761, P < 0.001) and MA+CA Group (r = 0.786, P < 0.001), a large positive correlation was observed between musculoskeletal anatomy performance and the number of CAL training sessions. Similarly, in the CA Group (r = 0.670, P < 0.001) and the MA + CA Group (r = 0.772, P < 0.001), a large positive correlation was observed between cardiovascular anatomy performance and the number of CAL training sessions. Multiple linear regression models were performed, considering either musculoskeletal or cardiovascular anatomy performance as the dependent variable. The results suggest that using CAL platforms to study has a positive dose-dependent effect on anatomy performance. Understanding students' individual features and academic background may contribute to the optimization of the learning process.

Keywords: anatomy academic performance; computer-assisted learning; computer-assisted training; gross anatomy education; learning analytics; learning profiles; medical education; undergraduate education.