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

Area of Science:

• Medical Education
• Anatomy Pedagogy
• Educational Technology

Background:

• Anatomy education faces declining resources, prompting exploration of new teaching methods.
• Computer-assisted learning (CAL) offers a promising alternative for anatomy instruction.
• Understanding the impact of CAL on student learning profiles is crucial.

Purpose of the Study:

• To investigate the influence of computer-assisted learning (CAL) platforms on medical students' anatomy performance.
• To determine the correlation between the extent of CAL training and anatomy course outcomes.

Main Methods:

• 611 medical students were divided into Musculoskeletal Anatomy (MA), Cardiovascular Anatomy (CA), and combined (MA + CA) groups.
• The number of CAL training sessions was recorded for each student.
• Statistical analyses, including correlation and multiple linear regression, were used to assess the relationship between CAL usage and anatomy performance.

Main Results:

• A significant positive correlation was found between the number of CAL sessions and performance in both Musculoskeletal Anatomy (MA) and Cardiovascular Anatomy (CA).
• Performance in MA showed strong correlations with CAL sessions in the MA Group (r=0.761) and MA + CA Group (r=0.786).
• Performance in CA showed strong correlations with CAL sessions in the CA Group (r=0.670) and MA + CA Group (r=0.772).

Conclusions:

• Computer-assisted learning (CAL) demonstrates a positive, dose-dependent effect on medical students' anatomy performance.
• Increased engagement with CAL platforms is associated with improved academic outcomes in anatomy.
• Personalized learning approaches considering student profiles can optimize anatomy education.