Gender perspectives: Artificial intelligence in academic practice

Abstract

The rapid integration of artificial intelligence (AI) into higher education is reshaping teaching and research practices, raising questions about digital literacy, ethics, and institutional readiness. Drawing on gender socialization theory, the Technology Acceptance Model (TAM), and the ethics of care perspective, this study examines whether gender influences AI-related knowledge, use, and perceptions among academic staff. The guiding research question is whether gender differences reflect competence gaps or differences in value orientations and professional contexts. A quantitative, cross-sectional survey was conducted using a convenience sample of 312 university teachers at public and private higher education institutions in Serbia (56.1% female; 43.9% male). A structured questionnaire with five-point Likert-scale items measured self-reported AI knowledge, frequency of ChatGPT use, perceptions of AI as a research support tool, perceived efficiency gains in teaching-related tasks, and attitudes toward adopting new educational concepts. The instrument demonstrated satisfactory internal consistency (Cronbach's α>0.70). Data were analyzed using descriptive statistics and chi-square tests of independence, with Cramer's V indicating effect size. Results show no statistically significant gender differences in self-reported AI knowledge. However, men report more frequent ChatGPT use and stronger perceptions of productivity benefits, whereas women more often evaluate AI through pedagogical and ethical lenses and report greater openness to using AI to support academic topic exploration. Overall, gender differences appear driven by disciplinary context and value frameworks rather than technical competence, underscoring the need for gender-sensitive training and institutional support to promote inclusive and responsible AI use in higher education.

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