A Study of Gender-Specific Learning Patterns in Online Medical Education

This study explores gender-specific learning patterns among medical students using an online educational tool utilized at the national level in France. Despite increasing numbers of women in medical school admissions, persistent disparities in professional medical careers raise concerns that such inequalities may already be present during university training. In this study, we analyze data from all fourth-year medical students in France for the academic years 2022-2023 and 2023-2024. We employ a Subgroup Discovery algorithm to identify patterns in online engagement and performance within these two national cohorts, focusing on gender as the key demographic variable. Our analysis revealed significant gender differences, with a proportion of male students displaying higher levels of engagement and academic performance. In contrast, female students were more likely to disengage from interactive components of the platform or to perform poorly or averagely in some medical specialties. We hypothesize that these differences may be attributed to the nature of the evaluations, which are predominantly in multiple-choice question format, potentially favoring male students. Additionally, stress and psychological distress, which are known to affect female students, may further exacerbate these performance disparities. These findings underscore the need for targeted interventions in medical education to address early gender disparities, promoting a more equitable learning environment for all students.