Assessing Gender Differences in Technological Readiness and AI Adoption Intentions among Pre-Service Teachers
Background: Artificial Intelligence (AI) is increasingly transforming instructional processes across educational settings, creating a need to understand the factors associated with its adoption among future educators, particularly across gender groups. Purpose: This study examined the relationships among technological readiness, attitude toward AI, and behavioural intention to adopt AI among pre-service teachers, and investigated whether gender moderates these relationships. Specifically, the study aimed to investigate the extent to which technological readiness is related to attitudes toward AI and behavioural intention to adopt AI, and whether these relationships vary between male and female pre-service teachers. Method: A quantitative cross-sectional survey design was employed, and data were collected from 378 undergraduate pre-service teachers enrolled in teacher education programmes at public universities in southwestern Nigeria using a structured online questionnaire administered through Google Forms. Data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) with SmartPLS 4, including multigroup analysis to examine gender differences. Results: The findings indicate that technological readiness was not significantly associated with behavioural intention to adopt AI (β = .092, t = 1.945, p = .052), and no significant gender differences were found in this relationship (t = 0.479, p = .630). However, technological readiness showed a significant positive association with attitude toward AI (β = .075, t = 2.330, p < .05), with significant gender differences in the strength and direction of this relationship (t = 3.991, p < .05). The relationship was positive among female pre-service teachers but negative among male pre-service teachers. Conclusion: These findings highlight the importance of strengthening technological confidence and promoting equitable AI integration initiatives in teacher education programmes. The study further highlights the need for teacher educators, informatics educators, and policymakers to create inclusive learning environments that support positive attitudes and engagement with AI technologies among future educators.