Learning with GenAI across campuses: student experiences of GenAI-enhanced cybersecurity education

Generative artificial intelligence (GenAI) is increasingly embedded in higher education, yet limited research has examined how GenAI-supported learning operates alongside geographically distributed peer collaboration. This qualitative study explores student experiences in an AI-enhanced cross-campus cybersecurity learning environment connecting university campuses in California, United States, and Ontario, Canada. Anonymous reflections were collected from 19 students (nine in California and ten in Ontario) about their experiences with GenAI-supported learning, cross-campus interaction, associated challenges, and recommendations for improving the learning experience. The findings indicate that students perceived GenAI as supporting concept clarification, greater perceived learning efficiency, idea development, and problem-solving, while also emphasizing the importance of critically evaluating GenAI-generated information. Cross-campus interaction was perceived as exposing students to diverse perspectives, experiences, and approaches to cybersecurity, which participants described as broadening their understanding of collaborative problem-solving across contexts. Students nevertheless identified challenges involving scheduling, technology, differences in experience, GenAI accuracy, and responsible use. They recommended more structured cross-campus projects, hands-on activities, clearer guidance on ethical GenAI use, and greater engagement with industry professionals. The study contributes to research on technology-enhanced learning in higher education by suggesting how GenAI-supported learning and geographically distributed peer interaction can provide complementary educational resources: GenAI offers immediate cognitive and informational support, while cross-campus interaction provides access to situated human perspectives. Together, these experiences highlight the importance of verification, contextual judgment, critical AI literacy, and intentional pedagogical design in GenAI-enhanced learning environments.