Generative AI Usage and Academic Performance among Healthcare Management Students: A Comparative Study of Undergraduate and Postgraduate Learners

Background: Generative artificial intelligence (GenAI) tools have rapidly permeated higher education, yet empirical evidence on their differential impact across student cohorts in healthcare management programmes remains limited.

Objectives: This study examined GenAI usage patterns and their associations with academic performance among undergraduate (UG) and postgraduate (PG) healthcare management students, and compared outcomes across both cohorts.

Methods: A cross-sectional survey design was employed with a purposive sample of 300 students (150 UG; 150 PG) from three accredited Indian institutions. Validated instruments assessed GenAI literacy, usage frequency, purpose of use, and academic self-efficacy. Academic performance was operationalised through cumulative GPA, faculty-rated critical thinking, research output scores, and assignment quality. Data were analysed using independent samples t-tests, chi-square tests, one-way ANOVA, and hierarchical multiple regression.

Results: PG students demonstrated significantly higher GenAI usage frequency (4.1 vs 3.2 days/week; p<.001), AI literacy (3.87 vs 3.21; p<.001), and critical-use orientation than UG counterparts. High GenAI users outperformed low users on all academic metrics in both groups (all p<.001), with stronger associations observed in PG students (CGPA: 7.89 vs 7.11; R²=0.47). Regression analyses identified AI literacy (β=.341), critical-use orientation (β=.318), and usage frequency (β=.302) as the strongest predictors of PG performance, while AI literacy (β=.287) and critical use (β=.214) predominated in the UG model.

Conclusions: GenAI use confers significant academic benefits in healthcare management education when applied critically and purposefully. Programmes should integrate structured AI literacy curricula tailored to UG and PG learning contexts to optimise these benefits and mitigate dependency risks.