Gender Disparity in AI Usage for Learning Chemistry among Undergraduate Students in Zaria, Kaduna State, Nigeria

This study investigated gender disparities in Artificial Intelligence (AI) usage for learning chemistry among undergraduate students in Zaria, Kaduna State, Nigeria. A survey research design was employed using a researcher-validated 5-point Likert scale questionnaire to collect data from students across three categories: Faculty of Education (main campus), Faculty of Education (affiliated institution), and Faculty of Physical Sciences. The objectives were to compare patterns of AI usage 
for learning chemistry across faculties, examine gender differences in AI usage, and explore the interaction between gender and faculty. Data were analyzed using IBM SPSS statistic package. The research questions were answered using descriptive statistics (mean and standard deviation) while the hypotheses were tested at 0.05 level of confidence using a two-way Analysis of Variance (ANOVA). The findings revealed a significant main effect of faculty category on AI usage, F(2, 1354) = 8.85, p < .001, partial η² = .013, with students from the Faculty of Education (main campus) and affiliated institutions reporting significantly higher AI usage than those in the Faculty of Physical Sciences. The main effect of gender was not significant, F(1, 1354) = 2.58, p = .108, partial η² = .002, indicating no overall gender disparity in AI usage. However, the interaction between gender and 
faculty was significant, F(2, 1354) = 8.59, p < .001, partial η² = .013. Specifically, female students in the affiliated institution reported higher AI usage for learning chemistry than males, while the reverse was observed in the main campus, and no difference was found in Physical Sciences.