A study of gender-specific differences in online platform in medical education

Abstract Background This study explores gender-specific learning patterns among medical students using a national online educational platform in France. Although the proportion of women admitted to medical schools has steadily increased, persistent gender disparities remain in medical career progression. These inequalities may already emerge during university training, influencing learning behaviors. Understanding when and how these differences appear is crucial to designing targeted interventions that promote equity in medical education. Methods We analyzed anonymized data from all sixth-year medical students in France during the 2022–2023 and 2023–2024 academic years. This dataset covers the entire national cohort using the online platform to prepare for mandatory medical examinations. We applied a Subgroup Discovery algorithm using gender as the target variable to identify interpretable patterns associated with online engagement, learning activity and academic performance that characterize male and female students. Analyses considered platform use, participation in interactive activities, and performance across assessment formats and medical specialties. Results Our analysis revealed marked gender differences in both engagement and academic performance. Male students were more likely to belong to subgroups characterized by high engagement with the platform or higher academic performance, particularly in Progressive Case assessments and several medical specialties. Female students were more frequently associated with lower participation in the platform’s interactive features and with response patterns suggesting a greater tendency to omit correct answer choices. Together with the existing literature, these findings generated several hypotheses regarding the mechanisms underlying these disparities, including assessment design, response strategies under uncertainty, examination context, and psychological factors. Conclusions Gender disparities in performance are already observable during medical training, before students enter professional practice. These findings highlight the importance of evaluating how assessment design, online learning environments, and educational support influence gender equity in medical education. This study also illustrates the value of data-driven approaches such as Subgroup Discovery for generating testable hypotheses that can inform future educational research and interventions.