2026 ASEE Annual Conference & Exposition

As artificial intelligence (AI) becomes increasingly embedded in higher education, understanding how diverse student populations engage with AI tools is essential for advancing inclusive engineering education. Student veterans represent a growing yet underexamined population in engineering programs. Although they often bring valuable strengths such as discipline, teamwork, leadership, and applied problem-solving from military service, they also face significant challenges when transitioning from structured military environments to the self-directed and culturally unfamiliar context of academic learning. While prior research has examined veterans’ pathways and transition experiences in engineering, limited empirical work has explored how AI tools shape these experiences. This work-in-progress study explores how student veterans in undergraduate and graduate engineering programs engage with or experience AI tools both in their academic learning and in navigating the broader transition from military to college life. Guided by Schlossberg’s 4S Transition Theory (situation, self, support, and strategies), the study conceptualizes AI as a potential transition factor that may influence how veterans interpret challenges, mobilize strengths, access support networks, and implement coping strategies during the transition process. Using a basic qualitative research design, the study employed purposive and snowball sampling to recruit student veterans across diverse service backgrounds, ranks, and engineering sub-disciplines. Data was collected through semi-structured interviews conducted via secure video conferencing platforms and transcribed verbatim. Twenty participants completed the interview. Data analysis proceeded in two phases: (1) inductive thematic analysis to identify emergent patterns grounded in participants’ narratives, followed by (2) deductive mapping of themes to the 4S framework to examine how AI interacts with key transition dimensions. Findings are expected to inform more equitable AI integration in engineering education by identifying ways AI tools may support veterans’ learning, reduce transition barriers, and enhance belonging and persistence. This study contributes to emerging discussions on leveraging AI as a learning technology and a structured support mechanism for military-connected learners in engineering pathways.